@article{BriegerHerzschuhPestryakovaetal.2019, author = {Brieger, Frederic and Herzschuh, Ulrike and Pestryakova, Luidmila Agafyevna and Bookhagen, Bodo and Zakharov, Evgenii S. and Kruse, Stefan}, title = {Advances in the Derivation of Northeast Siberian Forest Metrics Using High-Resolution UAV-Based Photogrammetric Point Clouds}, series = {Remote sensing}, volume = {11}, journal = {Remote sensing}, number = {12}, publisher = {MDPI}, address = {Basel}, issn = {2072-4292}, doi = {10.3390/rs11121447}, pages = {24}, year = {2019}, abstract = {Forest structure is a crucial component in the assessment of whether a forest is likely to act as a carbon sink under changing climate. Detailed 3D structural information about the tundra-taiga ecotone of Siberia is mostly missing and still underrepresented in current research due to the remoteness and restricted accessibility. Field based, high-resolution remote sensing can provide important knowledge for the understanding of vegetation properties and dynamics. In this study, we test the applicability of consumer-grade Unmanned Aerial Vehicles (UAVs) for rapid calculation of stand metrics in treeline forests. We reconstructed high-resolution photogrammetric point clouds and derived canopy height models for 10 study sites from NE Chukotka and SW Yakutia. Subsequently, we detected individual tree tops using a variable-window size local maximum filter and applied a marker-controlled watershed segmentation for the delineation of tree crowns. With this, we successfully detected 67.1\% of the validation individuals. Simple linear regressions of observed and detected metrics show a better correlation (R2) and lower relative root mean square percentage error (RMSE\%) for tree heights (mean R2 = 0.77, mean RMSE\% = 18.46\%) than for crown diameters (mean R2 = 0.46, mean RMSE\% = 24.9\%). The comparison between detected and observed tree height distributions revealed that our tree detection method was unable to representatively identify trees <2 m. Our results show that plot sizes for vegetation surveys in the tundra-taiga ecotone should be adapted to the forest structure and have a radius of >15-20 m to capture homogeneous and representative forest stands. Additionally, we identify sources of omission and commission errors and give recommendations for their mitigation. In summary, the efficiency of the used method depends on the complexity of the forest's stand structure.}, language = {en} } @misc{BriegerHerzschuhPestryakovaetal.2019, author = {Brieger, Frederic and Herzschuh, Ulrike and Pestryakova, Luidmila Agafyevna and Bookhagen, Bodo and Zakharov, Evgenii S. and Kruse, Stefan}, title = {Advances in the derivation of Northeast Siberian forest metrics using high-resolution UAV-based photogrammetric point clouds}, series = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, journal = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, number = {1337}, issn = {1866-8372}, doi = {10.25932/publishup-47331}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-473318}, pages = {24}, year = {2019}, abstract = {Forest structure is a crucial component in the assessment of whether a forest is likely to act as a carbon sink under changing climate. Detailed 3D structural information about the tundra-taiga ecotone of Siberia is mostly missing and still underrepresented in current research due to the remoteness and restricted accessibility. Field based, high-resolution remote sensing can provide important knowledge for the understanding of vegetation properties and dynamics. In this study, we test the applicability of consumer-grade Unmanned Aerial Vehicles (UAVs) for rapid calculation of stand metrics in treeline forests. We reconstructed high-resolution photogrammetric point clouds and derived canopy height models for 10 study sites from NE Chukotka and SW Yakutia. Subsequently, we detected individual tree tops using a variable-window size local maximum filter and applied a marker-controlled watershed segmentation for the delineation of tree crowns. With this, we successfully detected 67.1\% of the validation individuals. Simple linear regressions of observed and detected metrics show a better correlation (R2) and lower relative root mean square percentage error (RMSE\%) for tree heights (mean R2 = 0.77, mean RMSE\% = 18.46\%) than for crown diameters (mean R2 = 0.46, mean RMSE\% = 24.9\%). The comparison between detected and observed tree height distributions revealed that our tree detection method was unable to representatively identify trees <2 m. Our results show that plot sizes for vegetation surveys in the tundra-taiga ecotone should be adapted to the forest structure and have a radius of >15-20 m to capture homogeneous and representative forest stands. Additionally, we identify sources of omission and commission errors and give recommendations for their mitigation. In summary, the efficiency of the used method depends on the complexity of the forest's stand structure.}, language = {en} } @article{PereiraMedeirosFranckeetal.2019, author = {Pereira, Bruno and Medeiros, Pedro Henrique Augusto and Francke, Till and Ramalho, Geraldo and F{\"o}rster, Saskia and De Araujo, Jose Carlos}, title = {Assessment of the geometry and volumes of small surface water reservoirs by remote sensing in a semi-arid region with high reservoir density}, series = {Hydrological sciences journal = Journal des sciences hydrologiques}, volume = {64}, journal = {Hydrological sciences journal = Journal des sciences hydrologiques}, number = {1}, publisher = {Routledge, Taylor \& Francis Group}, address = {Abingdon}, issn = {0262-6667}, doi = {10.1080/02626667.2019.1566727}, pages = {66 -- 79}, year = {2019}, abstract = {Water fluxes in highly impounded regions are heavily dependent on reservoir properties. However, for large and remote areas, this information is often unavailable. In this study, the geometry and volume of small surface reservoirs in the semi-arid region of Brazil were estimated using terrain and shape attributes extracted by remote sensing. Regression models and data classification were used to predict the volumes, at different water stages, of 312 reservoirs for which topographic information is available. The power function used to describe the reservoir shapes tends to overestimate the volumes; therefore, a modified shape equation was proposed. Among the methods tested, four were recommended based on performance and simplicity, for which the mean absolute percentage errors varied from 24 to 39\%, in contrast to the 94\% error achieved with the traditional method. Despite the challenge of precisely deriving the flooded areas of reservoirs, water management in highly reservoir-dense environments should benefit from volume prediction based on remote sensing.}, language = {en} } @phdthesis{Conradt2013, author = {Conradt, Tobias}, title = {Challenges of regional hydrological modelling in the Elbe River basin : investigations about model fidelity on sub-catchment level}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-65245}, school = {Universit{\"a}t Potsdam}, year = {2013}, abstract = {Within a research project about future sustainable water management options in the Elbe River basin, quasi-natural discharge scenarios had to be provided. The semi-distributed eco-hydrological model SWIM was utilised for this task. According to scenario simulations driven by the stochastical climate model STAR, the region would get distinctly drier. However, this thesis focuses on the challenge of meeting the requirement of high model fidelity even for smaller sub-basins. Usually, the quality of the simulations is lower at inner points than at the outlet. Four research paper chapters and the discussion chapter deal with the reasons for local model deviations and the problem of optimal spatial calibration. Besides other assessments, the Markov Chain Monte Carlo method is applied to show whether evapotranspiration or precipitation should be corrected to minimise runoff deviations, principal component analysis is used in an unusual way to evaluate local precipitation alterations by land cover changes, and remotely sensed surface temperatures allow for an independent view on the evapotranspiration landscape. The overall insight is that spatially explicit hydrological modelling of such a large river basin requires a lot of local knowledge. It probably needs more time to obtain such knowledge as is usually provided for hydrological modelling studies.}, language = {en} } @article{HoffmannFeakinsBookhagenetal.2016, author = {Hoffmann, Bernd and Feakins, Sarah J. and Bookhagen, Bodo and Olen, Stephanie M. and Adhikari, Danda P. and Mainali, Janardan and Sachse, Dirk}, title = {Climatic and geomorphic drivers of plant organic matter transport in the Arun River, E Nepal}, series = {Earth \& planetary science letters}, volume = {452}, journal = {Earth \& planetary science letters}, publisher = {Elsevier}, address = {Amsterdam}, issn = {0012-821X}, doi = {10.1016/j.epsl.2016.07.008}, pages = {104 -- 114}, year = {2016}, language = {en} } @phdthesis{Smith2018, author = {Smith, Taylor}, title = {Decadal changes in the snow regime of High Mountain Asia, 1987-2016}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-407120}, school = {Universit{\"a}t Potsdam}, pages = {xiii, 142}, year = {2018}, abstract = {More than a billion people rely on water from rivers sourced in High Mountain Asia (HMA), a significant portion of which is derived from snow and glacier melt. Rural communities are heavily dependent on the consistency of runoff, and are highly vulnerable to shifts in their local environment brought on by climate change. Despite this dependence, the impacts of climate change in HMA remain poorly constrained due to poor process understanding, complex terrain, and insufficiently dense in-situ measurements. HMA's glaciers contain more frozen water than any region outside of the poles. Their extensive retreat is a highly visible and much studied marker of regional and global climate change. However, in many catchments, snow and snowmelt represent a much larger fraction of the yearly water budget than glacial meltwaters. Despite their importance, climate-related changes in HMA's snow resources have not been well studied. Changes in the volume and distribution of snowpack have complex and extensive impacts on both local and global climates. Eurasian snow cover has been shown to impact the strength and direction of the Indian Summer Monsoon -- which is responsible for much of the precipitation over the Indian Subcontinent -- by modulating earth-surface heating. Shifts in the timing of snowmelt have been shown to limit the productivity of major rangelands, reduce streamflow, modify sediment transport, and impact the spread of vector-borne diseases. However, a large-scale regional study of climate impacts on snow resources had yet to be undertaken. Passive Microwave (PM) remote sensing is a well-established empirical method of studying snow resources over large areas. Since 1987, there have been consistent daily global PM measurements which can be used to derive an estimate of snow depth, and hence snow-water equivalent (SWE) -- the amount of water stored in snowpack. The SWE estimation algorithms were originally developed for flat and even terrain -- such as the Russian and Canadian Arctic -- and have rarely been used in complex terrain such as HMA. This dissertation first examines factors present in HMA that could impact the reliability of SWE estimates. Forest cover, absolute snow depth, long-term average wind speeds, and hillslope angle were found to be the strongest controls on SWE measurement reliability. While forest density and snow depth are factors accounted for in modern SWE retrieval algorithms, wind speed and hillslope angle are not. Despite uncertainty in absolute SWE measurements and differences in the magnitude of SWE retrievals between sensors, single-instrument SWE time series were found to be internally consistent and suitable for trend analysis. Building on this finding, this dissertation tracks changes in SWE across HMA using a statistical decomposition technique. An aggregate decrease in SWE was found (10.6 mm/yr), despite large spatial and seasonal heterogeneities. Winter SWE increased in almost half of HMA, despite general negative trends throughout the rest of the year. The elevation distribution of these negative trends indicates that while changes in SWE have likely impacted glaciers in the region, climate change impacts on these two pieces of the cryosphere are somewhat distinct. Following the discussion of relative changes in SWE, this dissertation explores changes in the timing of the snowmelt season in HMA using a newly developed algorithm. The algorithm is shown to accurately track the onset and end of the snowmelt season (70\% within 5 days of a control dataset, 89\% within 10). Using a 29-year time series, changes in the onset, end, and duration of snowmelt are examined. While nearly the entirety of HMA has experienced an earlier end to the snowmelt season, large regions of HMA have seen a later start to the snowmelt season. Snowmelt periods have also decreased in almost all of HMA, indicating that the snowmelt season is generally shortening and ending earlier across HMA. By examining shifts in both the spatio-temporal distribution of SWE and the timing of the snowmelt season across HMA, we provide a detailed accounting of changes in HMA's snow resources. The overall trend in HMA is towards less SWE storage and a shorter snowmelt season. However, long-term and regional trends conceal distinct seasonal, temporal, and spatial heterogeneity, indicating that changes in snow resources are strongly controlled by local climate and topography, and that inter-annual variability plays a significant role in HMA's snow regime.}, language = {en} } @phdthesis{Boesche2015, author = {B{\"o}sche, Nina Kristine}, title = {Detection of rare earth elements and rare earth oxides with hyperspectral spectroscopy}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-85363}, school = {Universit{\"a}t Potsdam}, pages = {147}, year = {2015}, abstract = {The continuously increasing demand for rare earth elements in technical components of modern technologies, brings the detection of new deposits closer into the focus of global exploration. One promising method to globally map important deposits might be remote sensing, since it has been used for a wide range of mineral mapping in the past. This doctoral thesis investigates the capacity of hyperspectral remote sensing for the detection of rare earth element deposits. The definition and the realization of a fundamental database on the spectral characteristics of rare earth oxides, rare earth metals and rare earth element bearing materials formed the basis of this thesis. To investigate these characteristics in the field, hyperspectral images of four outcrops in Fen Complex, Norway, were collected in the near-field. A new methodology (named REEMAP) was developed to delineate rare earth element enriched zones. The main steps of REEMAP are: 1) multitemporal weighted averaging of multiple images covering the sample area; 2) sharpening the rare earth related signals using a Gaussian high pass deconvolution technique that is calibrated on the standard deviation of a Gaussian-bell shaped curve that represents by the full width of half maxima of the target absorption band; 3) mathematical modeling of the target absorption band and highlighting of rare earth elements. REEMAP was further adapted to different hyperspectral sensors (EO-1 Hyperion and EnMAP) and a new test site (Lofdal, Namibia). Additionally, the hyperspectral signatures of associated minerals were investigated to serve as proxy for the host rocks. Finally, the capacity and limitations of spectroscopic rare earth element detection approaches in general and of the REEMAP approach specifically were investigated and discussed. One result of this doctoral thesis is that eight rare earth oxides show robust absorption bands and, therefore, can be used for hyperspectral detection methods. Additionally, the spectral signatures of iron oxides, iron-bearing sulfates, calcite and kaolinite can be used to detect metasomatic alteration zones and highlight the ore zone. One of the key results of this doctoral work is the developed REEMAP approach, which can be applied from near-field to space. The REEMAP approach enables rare earth element mapping especially for noisy images. Limiting factors are a low signal to noise ratio, a reduced spectral resolution, overlaying materials, atmospheric absorption residuals and non-optimal illumination conditions. Another key result of this doctoral thesis is the finding that the future hyperspectral EnMAP satellite (with its currently published specifications, June 2015) will be theoretically capable to detect absorption bands of erbium, dysprosium, holmium, neodymium and europium, thulium and samarium. This thesis presents a new methodology REEMAP that enables a spatially wide and rapid hyperspectral detection of rare earth elements in order to meet the demand for fast, extensive and efficient rare earth exploration (from near-field to space).}, language = {en} } @phdthesis{Hahne2004, author = {Hahne, Kai}, title = {Detektion eines mesozoischen Gangschwarmes in NW Namibia und Rekonstruktion regionaler Spannungszust{\"a}nde w{\"a}hrend der S{\"u}datlantik{\"o}ffnung}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-0001687}, school = {Universit{\"a}t Potsdam}, year = {2004}, abstract = {Gangschw{\"a}rme nehmen eine bedeutende Stellung im Verst{\"a}ndnis zur kontinentalen Fragmentierung ein. Einerseits markieren sie das Pal{\"a}o-Spannungsfeld und helfen bei der Rekonstruktion der strukturellen Entwicklung der gedehnten Lithosph{\"a}re, andererseits gibt ihre petrologische Beschaffenheit Aufschluß {\"u}ber die Entstehung des Magmas, Aufstieg und Platznahme und schließlich erlaubt ihre Altersbestimmung die Rekonstruktion einer chronologischen Reihenfolge magmatischer und struktureller Ereignisse. Das Arbeitsgebiet im namibianischen Henties Bay-Outjo Dike swarm (HOD) war zur Zeit der Unterkreide einem Rifting mit intensiver Platznahme von {\"u}berwiegend mafischen G{\"a}ngen unterworfen. Geochemische Signaturen weisen die G{\"a}nge als erodierte F{\"o}rderkan{\"a}le der Etendeka Plateaubasalte aus. Durch den Einsatz von hochaufl{\"o}senden Aeromagnetik- und Satellitendaten war es m{\"o}glich, die Geometrie des Gangschwarmes erstmals detailliert synoptisch zu erfassen. Viele zu den Schichten des Grundgebirges foliationsparallel verlaufende magnetische Anomalien k{\"o}nnen unaufgeschlossenen kretazischen Intrusionen zugeordnet werden. Bei der nach Norden propagierenden S{\"u}datlantik{\"o}ffnung spielte die unterschiedliche strukturelle Vorzeichnung durch die neoproterozoischen Falteng{\"u}rtel sowie Lithologie und Spannungsfeld des Angola Kratons eine bedeutende Rolle. Im k{\"u}stennahen zentralen Bereich war dank der Vorzeichnung des Nordost streichenden Damara-Falteng{\"u}rtels ein Rifting in Nordwest-S{\"u}dost-Richtung dominierend, bis das Angola Kraton ein weiteres Fortscheiten nach Nordosten hemmte und die Vorzeichnung des Nordwest streichenden Kaoko-Falteng{\"u}rtels an der Westgrenze den weiteren Riftverlauf und die letztendlich erfolgreiche {\"O}ffnung des S{\"u}datlantiks bestimmte. Aus diesem Grund kann das Gebiet des HOD als ein failed rift betrachtet werden. Die Entwicklung des Spannungsfeldes im HOD kann folgendermaßen skizziert werden: 1. Platznahme von G{\"a}ngen bei gleichzeitig hoher Dehnungsrate und hohem Magmenfluß. 2. Platznahme von Zentralvulkanen entlang reaktivierter pal{\"a}ozoischer Lineamente bei Abnahme der Dehnungsrate und fortbestehendem hohen Magmenfluß. 3. Abnahme/Versiegen des Magmenflusses und neotektonische Bewegungen f{\"u}hren zur Bildung von Halbgr{\"a}ben.}, language = {de} } @phdthesis{Stettner2018, author = {Stettner, Samuel}, title = {Exploring the seasonality of rapid Arctic changes from space}, doi = {10.25932/publishup-42578}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-425783}, school = {Universit{\"a}t Potsdam}, pages = {XIII, 132}, year = {2018}, abstract = {Arctic warming has implications for the functioning of terrestrial Arctic ecosystems, global climate and socioeconomic systems of northern communities. A research gap exists in high spatial resolution monitoring and understanding of the seasonality of permafrost degradation, spring snowmelt and vegetation phenology. This thesis explores the diversity and utility of dense TerraSAR-X (TSX) X-Band time series for monitoring ice-rich riverbank erosion, snowmelt, and phenology of Arctic vegetation at long-term study sites in the central Lena Delta, Russia and on Qikiqtaruk (Herschel Island), Canada. In the thesis the following three research questions are addressed: • Is TSX time series capable of monitoring the dynamics of rapid permafrost degradation in ice-rich permafrost on an intra-seasonal scale and can these datasets in combination with climate data identify the climatic drivers of permafrost degradation? • Can multi-pass and multi-polarized TSX time series adequately monitor seasonal snow cover and snowmelt in small Arctic catchments and how does it perform compared to optical satellite data and field-based measurements? • Do TSX time series reflect the phenology of Arctic vegetation and how does the recorded signal compare to in-situ greenness data from RGB time-lapse camera data and vegetation height from field surveys? To answer the research questions three years of TSX backscatter data from 2013 to 2015 for the Lena Delta study site and from 2015 to 2017 for the Qikiqtaruk study site were used in quantitative and qualitative analysis complimentary with optical satellite data and in-situ time-lapse imagery. The dynamics of intra-seasonal ice-rich riverbank erosion in the central Lena Delta, Russia were quantified using TSX backscatter data at 2.4 m spatial resolution in HH polarization and validated with 0.5 m spatial resolution optical satellite data and field-based time-lapse camera data. Cliff top lines were automatically extracted from TSX intensity images using threshold-based segmentation and vectorization and combined in a geoinformation system with manually digitized cliff top lines from the optical satellite data and rates of erosion extracted from time-lapse cameras. The results suggest that the cliff top eroded at a constant rate throughout the entire erosional season. Linear mixed models confirmed that erosion was coupled with air temperature and precipitation at an annual scale, seasonal fluctuations did not influence 22-day erosion rates. The results highlight the potential of HH polarized X-Band backscatter data for high temporal resolution monitoring of rapid permafrost degradation. The distinct signature of wet snow in backscatter intensity images of TSX data was exploited to generate wet snow cover extent (SCE) maps on Qikiqtaruk at high temporal resolution. TSX SCE showed high similarity to Landsat 8-derived SCE when using cross-polarized VH data. Fractional snow cover (FSC) time series were extracted from TSX and optical SCE and compared to FSC estimations from in-situ time-lapse imagery. The TSX products showed strong agreement with the in-situ data and significantly improved the temporal resolution compared to the Landsat 8 time series. The final combined FSC time series revealed two topography-dependent snowmelt patterns that corresponded to in-situ measurements. Additionally TSX was able to detect snow patches longer in the season than Landsat 8, underlining the advantage of TSX for detection of old snow. The TSX-derived snow information provided valuable insights into snowmelt dynamics on Qikiqtaruk previously not available. The sensitivity of TSX to vegetation structure associated with phenological changes was explored on Qikiqtaruk. Backscatter and coherence time series were compared to greenness data extracted from in-situ digital time-lapse cameras and detailed vegetation parameters on 30 areas of interest. Supporting previous results, vegetation height corresponded to backscatter intensity in co-polarized HH/VV at an incidence angle of 31°. The dry, tall shrub dominated ecological class showed increasing backscatter with increasing greenness when using the cross polarized VH/HH channel at 32° incidence angle. This is likely driven by volume scattering of emerging and expanding leaves. Ecological classes with more prostrate vegetation and higher bare ground contributions showed decreasing backscatter trends over the growing season in the co-polarized VV/HH channels likely a result of surface drying instead of a vegetation structure signal. The results from shrub dominated areas are promising and provide a complementary data source for high temporal monitoring of vegetation phenology. Overall this thesis demonstrates that dense time series of TSX with optical remote sensing and in-situ time-lapse data are complementary and can be used to monitor rapid and seasonal processes in Arctic landscapes at high spatial and temporal resolution.}, language = {en} } @phdthesis{Antonoglou2024, author = {Antonoglou, Nikolaos}, title = {GNSS-based remote sensing: Innovative observation of key hydrological parameters in the Central Andes}, doi = {10.25932/publishup-62825}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-628256}, school = {Universit{\"a}t Potsdam}, pages = {xxii, 116}, year = {2024}, abstract = {The Central Andean region is characterized by diverse climate zones with sharp transitions between them. In this work, the area of interest is the South-Central Andes in northwestern Argentina that borders with Bolivia and Chile. The focus is the observation of soil moisture and water vapour with Global Navigation Satellite System (GNSS) remote-sensing methodologies. Because of the rapid temporal and spatial variations of water vapour and moisture circulations, monitoring this part of the hydrological cycle is crucial for understanding the mechanisms that control the local climate. Moreover, GNSS-based techniques have previously shown high potential and are appropriate for further investigation. This study includes both logistic-organization effort and data analysis. As for the prior, three GNSS ground stations were installed in remote locations in northwestern Argentina to acquire observations, where there was no availability of third-party data. The methodological development for the observation of the climate variables of soil moisture and water vapour is independent and relies on different approaches. The soil-moisture estimation with GNSS reflectometry is an approximation that has demonstrated promising results, but it has yet to be operationally employed. Thus, a more advanced algorithm that exploits more observations from multiple satellite constellations was developed using data from two pilot stations in Germany. Additionally, this algorithm was slightly modified and used in a sea-level measurement campaign. Although the objective of this application is not related to monitoring hydrological parameters, its methodology is based on the same principles and helps to evaluate the core algorithm. On the other hand, water-vapour monitoring with GNSS observations is a well-established technique that is utilized operationally. Hence, the scope of this study is conducting a meteorological analysis by examining the along-the-zenith air-moisture levels and introducing indices related to the azimuthal gradient. The results of the experiments indicate higher-quality soil moisture observations with the new algorithm. Furthermore, the analysis using the stations in northwestern Argentina illustrates the limits of this technology because of varying soil conditions and shows future research directions. The water-vapour analysis points out the strong influence of the topography on atmospheric moisture circulation and rainfall generation. Moreover, the GNSS time series allows for the identification of seasonal signatures, and the azimuthal-gradient indices permit the detection of main circulation pathways.}, language = {en} } @phdthesis{Buchhorn2013, author = {Buchhorn, Marcel}, title = {Ground-based hyperspectral and spectro-directional reflectance characterization of Arctic tundra vegetation communities : field spectroscopy and field spectro-goniometry of Siberian and Alaskan tundra in preparation of the EnMAP satellite mission}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-70189}, school = {Universit{\"a}t Potsdam}, year = {2013}, abstract = {The Arctic tundra, covering approx. 5.5 \% of the Earth's land surface, is one of the last ecosystems remaining closest to its untouched condition. Remote sensing is able to provide information at regular time intervals and large spatial scales on the structure and function of Arctic ecosystems. But almost all natural surfaces reveal individual anisotropic reflectance behaviors, which can be described by the bidirectional reflectance distribution function (BRDF). This effect can cause significant changes in the measured surface reflectance depending on solar illumination and sensor viewing geometries. The aim of this thesis is the hyperspectral and spectro-directional reflectance characterization of important Arctic tundra vegetation communities at representative Siberian and Alaskan tundra sites as basis for the extraction of vegetation parameters, and the normalization of BRDF effects in off-nadir and multi-temporal remote sensing data. Moreover, in preparation for the upcoming German EnMAP (Environmental Mapping and Analysis Program) satellite mission, the understanding of BRDF effects in Arctic tundra is essential for the retrieval of high quality, consistent and therefore comparable datasets. The research in this doctoral thesis is based on field spectroscopic and field spectro-goniometric investigations of representative Siberian and Alaskan measurement grids. The first objective of this thesis was the development of a lightweight, transportable, and easily managed field spectro-goniometer system which nevertheless provides reliable spectro-directional data. I developed the Manual Transportable Instrument platform for ground-based Spectro-directional observations (ManTIS). The outcome of the field spectro-radiometrical measurements at the Low Arctic study sites along important environmental gradients (regional climate, soil pH, toposequence, and soil moisture) show that the different plant communities can be distinguished by their nadir-view reflectance spectra. The results especially reveal separation possibilities between the different tundra vegetation communities in the visible (VIS) blue and red wavelength regions. Additionally, the near-infrared (NIR) shoulder and NIR reflectance plateau, despite their relatively low values due to the low structure of tundra vegetation, are still valuable information sources and can separate communities according to their biomass and vegetation structure. In general, all different tundra plant communities show: (i) low maximum NIR reflectance; (ii) a weakly or nonexistent visible green reflectance peak in the VIS spectrum; (iii) a narrow "red-edge" region between the red and NIR wavelength regions; and (iv) no distinct NIR reflectance plateau. These common nadir-view reflectance characteristics are essential for the understanding of the variability of BRDF effects in Arctic tundra. None of the analyzed tundra communities showed an even closely isotropic reflectance behavior. In general, tundra vegetation communities: (i) usually show the highest BRDF effects in the solar principal plane; (ii) usually show the reflectance maximum in the backward viewing directions, and the reflectance minimum in the nadir to forward viewing directions; (iii) usually have a higher degree of reflectance anisotropy in the VIS wavelength region than in the NIR wavelength region; and (iv) show a more bowl-shaped reflectance distribution in longer wavelength bands (>700 nm). The results of the analysis of the influence of high sun zenith angles on the reflectance anisotropy show that with increasing sun zenith angles, the reflectance anisotropy changes to azimuthally symmetrical, bowl-shaped reflectance distributions with the lowest reflectance values in the nadir view position. The spectro-directional analyses also show that remote sensing products such as the NDVI or relative absorption depth products are strongly influenced by BRDF effects, and that the anisotropic characteristics of the remote sensing products can significantly differ from the observed BRDF effects in the original reflectance data. But the results further show that the NDVI can minimize view angle effects relative to the contrary spectro-directional effects in the red and NIR bands. For the researched tundra plant communities, the overall difference of the off-nadir NDVI values compared to the nadir value increases with increasing sensor viewing angles, but on average never exceeds 10 \%. In conclusion, this study shows that changes in the illumination-target-viewing geometry directly lead to an altering of the reflectance spectra of Arctic tundra communities according to their object-specific BRDFs. Since the different tundra communities show only small, but nonetheless significant differences in the surface reflectance, it is important to include spectro-directional reflectance characteristics in the algorithm development for remote sensing products.}, language = {en} } @misc{OzturkPittoreBehlingetal.2020, author = {Ozturk, Ugur and Pittore, Massimiliano and Behling, Robert and R{\"o}ßner, Sigrid and Andreani, Louis and Korup, Oliver}, title = {How robust are landslide susceptibility estimates?}, series = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, journal = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, number = {2}, issn = {1866-8372}, doi = {10.25932/publishup-54198}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-541980}, pages = {17}, year = {2020}, abstract = {Much of contemporary landslide research is concerned with predicting and mapping susceptibility to slope failure. Many studies rely on generalised linear models with environmental predictors that are trained with data collected from within and outside of the margins of mapped landslides. Whether and how the performance of these models depends on sample size, location, or time remains largely untested. We address this question by exploring the sensitivity of a multivariate logistic regression-one of the most widely used susceptibility models-to data sampled from different portions of landslides in two independent inventories (i.e. a historic and a multi-temporal) covering parts of the eastern rim of the Fergana Basin, Kyrgyzstan. We find that considering only areas on lower parts of landslides, and hence most likely their deposits, can improve the model performance by >10\% over the reference case that uses the entire landslide areas, especially for landslides of intermediate size. Hence, using landslide toe areas may suffice for this particular model and come in useful where landslide scars are vague or hidden in this part of Central Asia. The model performance marginally varied after progressively updating and adding more landslides data through time. We conclude that landslide susceptibility estimates for the study area remain largely insensitive to changes in data over about a decade. Spatial or temporal stratified sampling contributes only minor variations to model performance. Our findings call for more extensive testing of the concept of dynamic susceptibility and its interpretation in data-driven models, especially within the broader framework of landslide risk assessment under environmental and land-use change.}, language = {en} } @misc{BoescheRogassLubitzetal.2017, author = {B{\"o}sche, Nina Kristine and Rogass, Christian and Lubitz, Christin and Brell, Maximilian and Herrmann, Sabrina and Mielke, Christian and Tonn, Sabine and Appelt, Oona and Altenberger, Uwe and Kaufmann, Hermann}, title = {Hyperspectral REE (Rare Earth Element) mapping of outcrops}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-400171}, pages = {27}, year = {2017}, abstract = {In this study, an in situ application for identifying neodymium (Nd) enriched surface materials that uses multitemporal hyperspectral images is presented (HySpex sensor). Because of the narrow shape and shallow absorption depth of the neodymium absorption feature, a method was developed for enhancing and extracting the necessary information for neodymium from image spectra, even under illumination conditions that are not optimal. For this purpose, the two following approaches were developed: (1) reducing noise and analyzing changing illumination conditions by averaging multitemporal image scenes and (2) enhancing the depth of the desired absorption band by deconvolving every image spectrum with a Gaussian curve while the rest of the spectrum remains unchanged (Richardson-Lucy deconvolution). To evaluate these findings, nine field samples from the Fen complex in Norway were analyzed using handheld X-ray fluorescence devices and by conducting detailed laboratory-based geochemical rare earth element determinations. The result is a qualitative outcrop map that highlights zones that are enriched in neodymium. To reduce the influences of non-optimal illumination, particularly at the studied site, a minimum of seven single acquisitions is required. Sharpening the neodymium absorption band allows for robust mapping, even at the outer zones of enrichment. From the geochemical investigations, we found that iron oxides decrease the applicability of the method. However, iron-related absorption bands can be used as secondary indicators for sulfidic ore zones that are mainly enriched with rare earth elements. In summary, we found that hyperspectral spectroscopy is a noninvasive, fast and cost-saving method for determining neodymium at outcrop surfaces}, language = {en} } @phdthesis{Nikolaeva2013, author = {Nikolaeva, Elena}, title = {Landslide kinematics and interactions studied in central Georgia by using synthetic aperture radar interferometry, optical imagery and inverse modeling}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-70406}, school = {Universit{\"a}t Potsdam}, year = {2013}, abstract = {Landslides are one of the biggest natural hazards in Georgia, a mountainous country in the Caucasus. So far, no systematic monitoring and analysis of the dynamics of landslides in Georgia has been made. Especially as landslides are triggered by extrinsic processes, the analysis of landslides together with precipitation and earthquakes is challenging. In this thesis I describe the advantages and limits of remote sensing to detect and better understand the nature of landslide in Georgia. The thesis is written in a cumulative form, composing a general introduction, three manuscripts and a summary and outlook chapter. In the present work, I measure the surface displacement due to active landslides with different interferometric synthetic aperture radar (InSAR) methods. The slow landslides (several cm per year) are well detectable with two-pass interferometry. In same time, the extremely slow landslides (several mm per year) could be detected only with time series InSAR techniques. I exemplify the success of InSAR techniques by showing hitherto unknown landslides, located in the central part of Georgia. Both, the landslide extent and displacement rate is quantified. Further, to determine a possible depth and position of potential sliding planes, inverse models were developed. Inverse modeling searches for parameters of source which can create observed displacement distribution. I also empirically estimate the volume of the investigated landslide using displacement distributions as derived from InSAR combined with morphology from an aerial photography. I adapted a volume formula for our case, and also combined available seismicity and precipitation data to analyze potential triggering factors. A governing question was: What causes landslide acceleration as observed in the InSAR data? The investigated area (central Georgia) is seismically highly active. As an additional product of the InSAR data analysis, a deformation area associated with the 7th September Mw=6.0 earthquake was found. Evidences of surface ruptures directly associated with the earthquake could not be found in the field, however, during and after the earthquake new landslides were observed. The thesis highlights that deformation from InSAR may help to map area prone landslides triggering by earthquake, potentially providing a technique that is of relevance for country wide landslide monitoring, especially as new satellite sensors will emerge in the coming years.}, language = {en} } @phdthesis{Mester2023, author = {Mester, Benedikt}, title = {Modeling flood-induced human displacement risk under global change}, doi = {10.25932/publishup-60929}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-609293}, school = {Universit{\"a}t Potsdam}, pages = {XVI, 143}, year = {2023}, abstract = {Extreme flooding displaces an average of 12 million people every year. Marginalized populations in low-income countries are in particular at high risk, but also industrialized countries are susceptible to displacement and its inherent societal impacts. The risk of being displaced results from a complex interaction of flood hazard, population exposed in the floodplains, and socio-economic vulnerability. Ongoing global warming changes the intensity, frequency, and duration of flood hazards, undermining existing protection measures. Meanwhile, settlements in attractive yet hazardous flood-prone areas have led to a higher degree of population exposure. Finally, the vulnerability to displacement is altered by demographic and social change, shifting economic power, urbanization, and technological development. These risk components have been investigated intensively in the context of loss of life and economic damage, however, only little is known about the risk of displacement under global change. This thesis aims to improve our understanding of flood-induced displacement risk under global climate change and socio-economic change. This objective is tackled by addressing the following three research questions. First, by focusing on the choice of input data, how well can a global flood modeling chain reproduce flood hazards of historic events that lead to displacement? Second, what are the socio-economic characteristics that shape the vulnerability to displacement? Finally, to what degree has climate change potentially contributed to recent flood-induced displacement events? To answer the first question, a global flood modeling chain is evaluated by comparing simulated flood extent with satellite-derived inundation information for eight major flood events. A focus is set on the sensitivity to different combinations of the underlying climate reanalysis datasets and global hydrological models which serve as an input for the global hydraulic model. An evaluation scheme of performance scores shows that simulated flood extent is mostly overestimated without the consideration of flood protection and only for a few events dependent on the choice of global hydrological models. Results are more sensitive to the underlying climate forcing, with two datasets differing substantially from a third one. In contrast, the incorporation of flood protection standards results in an underestimation of flood extent, pointing to potential deficiencies in the protection level estimates or the flood frequency distribution within the modeling chain. Following the analysis of a physical flood hazard model, the socio-economic drivers of vulnerability to displacement are investigated in the next step. For this purpose, a satellite- based, global collection of flood footprints is linked with two disaster inventories to match societal impacts with the corresponding flood hazard. For each event the number of affected population, assets, and critical infrastructure, as well as socio-economic indicators are computed. The resulting datasets are made publicly available and contain 335 displacement events and 695 mortality/damage events. Based on this new data product, event-specific displacement vulnerabilities are determined and multiple (national) dependencies with the socio-economic predictors are derived. The results suggest that economic prosperity only partially shapes vulnerability to displacement; urbanization, infant mortality rate, the share of elderly, population density and critical infrastructure exhibit a stronger functional relationship, suggesting that higher levels of development are generally associated with lower vulnerability. Besides examining the contextual drivers of vulnerability, the role of climate change in the context of human displacement is also being explored. An impact attribution approach is applied on the example of Cyclone Idai and associated extreme coastal flooding in Mozambique. A combination of coastal flood modeling and satellite imagery is used to construct factual and counterfactual flood events. This storyline-type attribution method allows investigating the isolated or combined effects of sea level rise and the intensification of cyclone wind speeds on coastal flooding. The results suggest that displacement risk has increased by 3.1 to 3.5\% due to the total effects of climate change on coastal flooding, with the effects of increasing wind speed being the dominant factor. In conclusion, this thesis highlights the potentials and challenges of modeling flood- induced displacement risk. While this work explores the sensitivity of global flood modeling to the choice of input data, new questions arise on how to effectively improve the reproduction of flood return periods and the representation of protection levels. It is also demonstrated that disentangling displacement vulnerabilities is feasible, with the results providing useful information for risk assessments, effective humanitarian aid, and disaster relief. The impact attribution study is a first step in assessing the effects of global warming on displacement risk, leading to new research challenges, e.g., coupling fluvial and coastal flood models or the attribution of other hazard types and displacement events. This thesis is one of the first to address flood-induced displacement risk from a global perspective. The findings motivate for further development of the global flood modeling chain to improve our understanding of displacement vulnerability and the effects of global warming.}, language = {en} } @article{HeineFranckeRogassetal.2014, author = {Heine, Iris and Francke, Till and Rogass, Christian and Medeiros, Pedro Henrique Augusto and Bronstert, Axel and F{\"o}rster, Saskia}, title = {Monitoring seasonal changes in the water surface areas of reservoirs using TerraSAR-X time series data in semiarid northeastern Brazil}, series = {IEEE journal of selected topics in applied earth observations and remote sensing}, volume = {7}, journal = {IEEE journal of selected topics in applied earth observations and remote sensing}, number = {8}, publisher = {Inst. of Electr. and Electronics Engineers}, address = {Piscataway}, issn = {1939-1404}, doi = {10.1109/JSTARS.2014.2323819}, pages = {3190 -- 3199}, year = {2014}, abstract = {The 933 km(2) Bengue catchment in northeastern Brazil is characterized by distinct rainy and dry seasons. Precipitation is stored in variously sized reservoirs, which is essential for the local population. In this study, we used TerraSAR-X SM(HH) data for an one-year monitoring of seasonal changes in the reservoir areas from July 2011 to July 2012. The monitoring was based on acquisitions in the ascending pass direction, complemented by occasional descending-pass images. To detect water surface areas, a histogram analysis followed by a global threshold classification was performed, and the results were validated using in situ GPS data. Distinguishing between small reservoirs and similar looking dark areas was difficult. Therefore, we tested several approaches for identifying misclassified areas. An analysis of the surface area dynamics of the reservoirs indicated high spatial and temporal heterogeneities and a large decrease in the total water surface area of the reservoirs in the catchment by approximately 30\% within one year.}, language = {en} } @article{LoiblBookhagenValadeetal.2019, author = {Loibl, David and Bookhagen, Bodo and Valade, Sebastien and Schneider, Christoph}, title = {OSARIS, the "Open Source SAR Investigation System" for Automatized Parallel InSAR Processing of Sentinel-1 Time Series Data With Special Emphasis on Cryosphere Applications}, series = {Frontiers in Earth Science}, volume = {7}, journal = {Frontiers in Earth Science}, publisher = {Frontiers Media}, address = {Lausanne}, issn = {2296-6463}, doi = {10.3389/feart.2019.00172}, pages = {20}, year = {2019}, abstract = {With the advent of the two Sentinel-1 (S1) satellites, Synthetic Aperture Radar (SAR) data with high temporal and spatial resolution are freely available. This provides a promising framework to facilitate detailed investigations of surface instabilities and movements on large scales with high temporal resolution, but also poses substantial processing challenges because of storage and computation requirements. Methods are needed to efficiently detect short term changes in dynamic environments. Approaches considering pair-wise processing of a series of consecutive scenes to retain maximum temporal resolution in conjunction with time series analyses are required. Here we present OSARIS, the "Open Source SAR Investigation System," as a framework to process large stacks of S1 data on high-performance computing clusters. Based on Generic Mapping Tools SAR, shell scripts, and the workload manager Slurm, OSARIS provides an open and modular framework combining parallelization of high-performance C programs, flexible processing schemes, convenient configuration, and generation of geocoded stacks of analysis-ready base data, including amplitude, phase, coherence, and unwrapped interferograms. Time series analyses can be conducted by applying automated modules to the data stacks. The capabilities of OSARIS are demonstrated in a case study from the northwestern Tien Shan, Central Asia. After merging of slices, a total of 80 scene pairs were processed from 174 total input scenes. The coherence time series exhibits pronounced seasonal variability, with relatively high coherence values prevailing during the summer months in the nival zone. As an example of a time series analysis module, we present OSARIS' "Unstable Coherence Metric" which identifies pixels affected by significant drops from high to low coherence values. Measurements of motion provided by LOSD measurements require careful evaluation because interferometric phase unwrapping is prone to errors. Here, OSARIS provides a series of modules to detect and mask unwrapping errors, correct for atmospheric disturbances, and remove large-scale trends. Wall clock processing time for the case study (area ~9,000 km2) was ~12 h 4 min on a machine with 400 cores and 2 TB RAM. In total, ~12 d 10 h 44 min (~96\%) were saved through parallelization. A comparison of selected OSARIS datasets to results from two state-of-the-art SAR processing suites, ISCE and SNAP, shows that OSARIS provides products of competitive quality despite its high level of automatization. OSARIS thus facilitates efficient S1-based region-wide investigations of surface movement events over multiple years.}, language = {en} } @phdthesis{Hoffmann2016, author = {Hoffmann, Bernd}, title = {Plant organic matter mobilization and export in fluvial systems}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-99336}, school = {Universit{\"a}t Potsdam}, pages = {xiii, 131}, year = {2016}, abstract = {The global carbon cycle is closely linked to Earth's climate. In the context of continuously unchecked anthropogenic CO₂ emissions, the importance of natural CO₂ bond and carbon storage is increasing. An important biogenic mechanism of natural atmospheric CO₂ drawdown is the photosynthetic carbon fixation in plants and the subsequent longterm deposition of plant detritus in sediments. The main objective of this thesis is to identify factors that control mobilization and transport of plant organic matter (pOM) through rivers towards sedimentation basins. I investigated this aspect in the eastern Nepalese Arun Valley. The trans-Himalayan Arun River is characterized by a strong elevation gradient (205 - 8848 m asl) that is accompanied by strong changes in ecology and climate ranging from wet tropical conditions in the Himalayan forelad to high alpine tundra on the Tibetan Plateau. Therefore, the Arun is an excellent natural laboratory, allowing the investigation of the effect of vegetation cover, climate, and topography on plant organic matter mobilization and export in tributaries along the gradient. Based on hydrogen isotope measurements of plant waxes sampled along the Arun River and its tributaries, I first developed a model that allows for an indirect quantification of pOM contributed to the mainsetm by the Arun's tributaries. In order to determine the role of climatic and topographic parameters of sampled tributary catchments, I looked for significant statistical relations between the amount of tributary pOM export and tributary characteristics (e.g. catchment size, plant cover, annual precipitation or runoff, topographic measures). On one hand, I demonstrated that pOMsourced from the Arun is not uniformly derived from its entire catchment area. On the other, I showed that dense vegetation is a necessary, but not sufficient, criterion for high tributary pOM export. Instead, I identified erosion and rainfall and runoff as key factors controlling pOM sourcing in the Arun Valley. This finding is supported by terrestrial cosmogenic nuclide concentrations measured on river sands along the Arun and its tributaries in order to quantify catchment wide denudation rates. Highest denudation rates corresponded well with maximum pOM mobilization and export also suggesting the link between erosion and pOM sourcing. The second part of this thesis focusses on the applicability of stable isotope records such as plant wax n-alkanes in sediment archives as qualitative and quantitative proxy for the variability of past Indian Summer Monsoon (ISM) strength. First, I determined how ISM strength affects the hydrogen and oxygen stable isotopic composition (reported as δD and δ18O values vs. Vienna Standard Mean Ocean Water) of precipitation in the Arun Valley and if this amount effect (Dansgaard, 1964) is strong enough to be recorded in potential paleo-ISM isotope proxies. Second, I investigated if potential isotope records across the Arun catchment reflect ISM strength dependent precipitation δD values only, or if the ISM isotope signal is superimposed by winter precipitation or glacial melt. Furthermore, I tested if δD values of plant waxes in fluvial deposits reflect δD values of environmental waters in the respective catchments. I showed that surface water δD values in the Arun Valley and precipitation δD from south of the Himalaya both changed similarly during two consecutive years (2011 \& 2012) with distinct ISM rainfall amounts (~20\% less in 2012). In order to evaluate the effect of other water sources (Winter-Westerly precipitation, glacial melt) and evapotranspiration in the Arun Valley, I analysed satellite remote sensing data of rainfall distribution (TRMM 3B42V7), snow cover (MODIS MOD10C1), glacial coverage (GLIMSdatabase, Global Land Ice Measurements from Space), and evapotranspiration (MODIS MOD16A2). In addition to the predominant ISM in the entire catchment I found through stable isotope analysis of surface waters indications for a considerable amount of glacial melt derived from high altitude tributaries and the Tibetan Plateau. Remotely sensed snow cover data revealed that the upper portion of the Arun also receives considerable winter precipitation, but the effect of snow melt on the Arun Valley hydrology could not be evaluated as it takes place in early summer, several months prior to our sampling campaigns. However, I infer that plant wax records and other potential stable isotope proxy archives below the snowline are well-suited for qualitative, and potentially quantitative, reconstructions of past changes of ISM strength.}, language = {en} } @article{CoesfeldKuesterKuechlyetal.2020, author = {Coesfeld, Jacqueline and Kuester, Theres and Kuechly, Helga U. and Kyba, Christopher C. M.}, title = {Reducing variability and removing natural light from nighttime satellite imagery: A case study using the VIIRS DNB}, series = {Sensors}, volume = {20}, journal = {Sensors}, publisher = {MDPI}, address = {Basel}, pages = {13}, year = {2020}, abstract = {Temporal variation of natural light sources such as airglow limits the ability of night light sensors to detect changes in small sources of artificial light (such as villages). This study presents a method for correcting for this effect globally, using the satellite radiance detected from regions without artificial light emissions. We developed a routine to define an approximate grid of locations worldwide that do not have regular light emission. We apply this method with a 5 degree equally spaced global grid (total of 2016 individual locations), using data from the Visible Infrared Imaging Radiometer Suite (VIIRS) Day-Night Band (DNB). This code could easily be adapted for other future global sensors. The correction reduces the standard deviation of data in the Earth Observation Group monthly DNB composites by almost a factor of two. The code and datasets presented here are available under an open license by GFZ Data Services, and are implemented in the Radiance Light Trends web application.}, language = {en} } @misc{CoesfeldKuesterKuechlyetal.2020, author = {Coesfeld, Jacqueline and Kuester, Theres and Kuechly, Helga U. and Kyba, Christopher C. M.}, title = {Reducing variability and removing natural light from nighttime satellite imagery: A case study using the VIIRS DNB}, series = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, journal = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, number = {11}, issn = {1866-8372}, doi = {10.25932/publishup-52439}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-524397}, pages = {15}, year = {2020}, abstract = {Temporal variation of natural light sources such as airglow limits the ability of night light sensors to detect changes in small sources of artificial light (such as villages). This study presents a method for correcting for this effect globally, using the satellite radiance detected from regions without artificial light emissions. We developed a routine to define an approximate grid of locations worldwide that do not have regular light emission. We apply this method with a 5 degree equally spaced global grid (total of 2016 individual locations), using data from the Visible Infrared Imaging Radiometer Suite (VIIRS) Day-Night Band (DNB). This code could easily be adapted for other future global sensors. The correction reduces the standard deviation of data in the Earth Observation Group monthly DNB composites by almost a factor of two. The code and datasets presented here are available under an open license by GFZ Data Services, and are implemented in the Radiance Light Trends web application.}, language = {en} } @phdthesis{Purinton2020, author = {Purinton, Benjamin}, title = {Remote sensing applications to earth surface processes in the Eastern Central Andes}, doi = {10.25932/publishup-44592}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-445926}, school = {Universit{\"a}t Potsdam}, pages = {xiii, 134}, year = {2020}, abstract = {Geomorphology seeks to characterize the forms, rates, and magnitudes of sediment and water transport that sculpt landscapes. This is generally referred to as earth surface processes, which incorporates the influence of biologic (e.g., vegetation), climatic (e.g., rainfall), and tectonic (e.g., mountain uplift) factors in dictating the transport of water and eroded material. In mountains, high relief and steep slopes combine with strong gradients in rainfall and vegetation to create dynamic expressions of earth surface processes. This same rugged topography presents challenges in data collection and process measurement, where traditional techniques involving detailed observations or physical sampling are difficult to apply at the scale of entire catchments. Herein lies the utility of remote sensing. Remote sensing is defined as any measurement that does not disturb the natural environment, typically via acquisition of images in the visible- to radio-wavelength range of the electromagnetic spectrum. Remote sensing is an especially attractive option for measuring earth surface processes, because large areal measurements can be acquired at much lower cost and effort than traditional methods. These measurements cover not only topographic form, but also climatic and environmental metrics, which are all intertwined in the study of earth surface processes. This dissertation uses remote sensing data ranging from handheld camera-based photo surveying to spaceborne satellite observations to measure the expressions, rates, and magnitudes of earth surface processes in high-mountain catchments of the Eastern Central Andes in Northwest Argentina. This work probes the limits and caveats of remote sensing data and techniques applied to geomorphic research questions, and presents important progress at this disciplinary intersection.}, language = {en} } @phdthesis{Jagdhuber2012, author = {Jagdhuber, Thomas}, title = {Soil parameter retrieval under vegetation cover using SAR polarimetry}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-60519}, school = {Universit{\"a}t Potsdam}, year = {2012}, abstract = {Soil conditions under vegetation cover and their spatial and temporal variations from point to catchment scale are crucial for understanding hydrological processes within the vadose zone, for managing irrigation and consequently maximizing yield by precision farming. Soil moisture and soil roughness are the key parameters that characterize the soil status. In order to monitor their spatial and temporal variability on large scales, remote sensing techniques are required. Therefore the determination of soil parameters under vegetation cover was approached in this thesis by means of (multi-angular) polarimetric SAR acquisitions at a longer wavelength (L-band, lambda=23cm). In this thesis, the penetration capabilities of L-band are combined with newly developed (multi-angular) polarimetric decomposition techniques to separate the different scattering contributions, which are occurring in vegetation and on ground. Subsequently the ground components are inverted to estimate the soil characteristics. The novel (multi-angular) polarimetric decomposition techniques for soil parameter retrieval are physically-based, computationally inexpensive and can be solved analytically without any a priori knowledge. Therefore they can be applied without test site calibration directly to agricultural areas. The developed algorithms are validated with fully polarimetric SAR data acquired by the airborne E-SAR sensor of the German Aerospace Center (DLR) for three different study areas in Germany. The achieved results reveal inversion rates up to 99\% for the soil moisture and soil roughness retrieval in agricultural areas. However, in forested areas the inversion rate drops significantly for most of the algorithms, because the inversion in forests is invalid for the applied scattering models at L-band. The validation against simultaneously acquired field measurements indicates an estimation accuracy (root mean square error) of 5-10vol.\% for the soil moisture (range of in situ values: 1-46vol.\%) and of 0.37-0.45cm for the soil roughness (range of in situ values: 0.5-4.0cm) within the catchment. Hence, a continuous monitoring of soil parameters with the obtained precision, excluding frozen and snow covered conditions, is possible. Especially future, fully polarimetric, space-borne, long wavelength SAR missions can profit distinctively from the developed polarimetric decomposition techniques for separation of ground and volume contributions as well as for soil parameter retrieval on large spatial scales.}, language = {en} } @phdthesis{Morgenstern2012, author = {Morgenstern, Anne}, title = {Thermokarst and thermal erosion : degradation of Siberian ice-rich permafrost}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-62079}, school = {Universit{\"a}t Potsdam}, year = {2012}, abstract = {Current climate warming is affecting arctic regions at a faster rate than the rest of the world. This has profound effects on permafrost that underlies most of the arctic land area. Permafrost thawing can lead to the liberation of considerable amounts of greenhouse gases as well as to significant changes in the geomorphology, hydrology, and ecology of the corresponding landscapes, which may in turn act as a positive feedback to the climate system. Vast areas of the east Siberian lowlands, which are underlain by permafrost of the Yedoma-type Ice Complex, are particularly sensitive to climate warming because of the high ice content of these permafrost deposits. Thermokarst and thermal erosion are two major types of permafrost degradation in periglacial landscapes. The associated landforms are prominent indicators of climate-induced environmental variations on the regional scale. Thermokarst lakes and basins (alasses) as well as thermo-erosional valleys are widely distributed in the coastal lowlands adjacent to the Laptev Sea. This thesis investigates the spatial distribution and morphometric properties of these degradational features to reconstruct their evolutionary conditions during the Holocene and to deduce information on the potential impact of future permafrost degradation under the projected climate warming. The methodological approach is a combination of remote sensing, geoinformation, and field investigations, which integrates analyses on local to regional spatial scales. Thermokarst and thermal erosion have affected the study region to a great extent. In the Ice Complex area of the Lena River Delta, thermokarst basins cover a much larger area than do present thermokarst lakes on Yedoma uplands (20.0 and 2.2 \%, respectively), which indicates that the conditions for large-area thermokarst development were more suitable in the past. This is supported by the reconstruction of the development of an individual alas in the Lena River Delta, which reveals a prolonged phase of high thermokarst activity since the Pleistocene/Holocene transition that created a large and deep basin. After the drainage of the primary thermokarst lake during the mid-Holocene, permafrost aggradation and degradation have occurred in parallel and in shorter alternating stages within the alas, resulting in a complex thermokarst landscape. Though more dynamic than during the first phase, late Holocene thermokarst activity in the alas was not capable of degrading large portions of Pleistocene Ice Complex deposits and substantially altering the Yedoma relief. Further thermokarst development in existing alasses is restricted to thin layers of Holocene ice-rich alas sediments, because the Ice Complex deposits underneath the large primary thermokarst lakes have thawed completely and the underlying deposits are ice-poor fluvial sands. Thermokarst processes on undisturbed Yedoma uplands have the highest impact on the alteration of Ice Complex deposits, but will be limited to smaller areal extents in the future because of the reduced availability of large undisturbed upland surfaces with poor drainage. On Kurungnakh Island in the central Lena River Delta, the area of Yedoma uplands available for future thermokarst development amounts to only 33.7 \%. The increasing proximity of newly developing thermokarst lakes on Yedoma uplands to existing degradational features and other topographic lows decreases the possibility for thermokarst lakes to reach large sizes before drainage occurs. Drainage of thermokarst lakes due to thermal erosion is common in the study region, but thermo-erosional valleys also provide water to thermokarst lakes and alasses. Besides these direct hydrological interactions between thermokarst and thermal erosion on the local scale, an interdependence between both processes exists on the regional scale. A regional analysis of extensive networks of thermo-erosional valleys in three lowland regions of the Laptev Sea with a total study area of 5,800 km² found that these features are more common in areas with higher slopes and relief gradients, whereas thermokarst development is more pronounced in flat lowlands with lower relief gradients. The combined results of this thesis highlight the need for comprehensive analyses of both, thermokarst and thermal erosion, in order to assess past and future impacts and feedbacks of the degradation of ice-rich permafrost on hydrology and climate of a certain region.}, language = {en} } @article{FernandezPalominoHattermannKrysanovaetal.2020, author = {Fernandez-Palomino, Carlos Antonio and Hattermann, Fred F. and Krysanova, Valentina and Vega-Jacome, Fiorella and Bronstert, Axel}, title = {Towards a more consistent eco-hydrological modelling through multi-objective calibration}, series = {Hydrological sciences journal = Journal des sciences hydrologiques}, volume = {66}, journal = {Hydrological sciences journal = Journal des sciences hydrologiques}, number = {1}, publisher = {Routledge, Taylor \& Francis Group}, address = {Abingdon}, issn = {0262-6667}, doi = {10.1080/02626667.2020.1846740}, pages = {59 -- 74}, year = {2020}, abstract = {Most hydrological studies rely on a model calibrated using discharge alone. However, judging the model reliability based on such calibration is problematic, as it does not guarantee the correct representation of internal hydrological processes. This study aims (a) to develop a comprehensive multi-objective calibration framework using remote sensing vegetation data and hydrological signatures (flow duration curve - FDC, and baseflow index) in addition to discharge, and (b) to apply this framework for calibration of the Soil and Water Assessment Tool (SWAT) in a typical Andean catchment. Overall, our calibration approach outperformed traditional discharge-based and FDC signature-based calibration strategies in terms of vegetation, streamflow, and flow partitioning simulation. New hydrological insights for the region are the following: baseflow is the main component of the streamflow sustaining the long dry-season flow, and pasture areas offer higher water yield and baseflow than other land-cover types. The proposed approach could be used in other data-scarce regions with complex topography.}, language = {en} } @misc{FernandezPalominoHattermannKrysanovaetal.2020, author = {Fernandez-Palomino, Carlos Antonio and Hattermann, Fred F. and Krysanova, Valentina and Vega-Jacome, Fiorella and Bronstert, Axel}, title = {Towards a more consistent eco-hydrological modelling through multi-objective calibration}, series = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, journal = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, number = {1}, issn = {1866-8372}, doi = {10.25932/publishup-56876}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-568766}, pages = {18}, year = {2020}, abstract = {Most hydrological studies rely on a model calibrated using discharge alone. However, judging the model reliability based on such calibration is problematic, as it does not guarantee the correct representation of internal hydrological processes. This study aims (a) to develop a comprehensive multi-objective calibration framework using remote sensing vegetation data and hydrological signatures (flow duration curve - FDC, and baseflow index) in addition to discharge, and (b) to apply this framework for calibration of the Soil and Water Assessment Tool (SWAT) in a typical Andean catchment. Overall, our calibration approach outperformed traditional discharge-based and FDC signature-based calibration strategies in terms of vegetation, streamflow, and flow partitioning simulation. New hydrological insights for the region are the following: baseflow is the main component of the streamflow sustaining the long dry-season flow, and pasture areas offer higher water yield and baseflow than other land-cover types. The proposed approach could be used in other data-scarce regions with complex topography.}, language = {en} }