TY - JOUR A1 - Walch, Daniela M. R. A1 - Singh, Rakesh K. A1 - Soreide, Janne E. A1 - Lantuit, Hugues A1 - Poste, Amanda T1 - Spatio-temporal variability of suspended particulate matter in a high-arctic estuary (Adventfjorden, Svalbard) using sentinel-2 time-series JF - Remote sensing N2 - Arctic coasts, which feature land-ocean transport of freshwater, sediments, and other terrestrial material, are impacted by climate change, including increased temperatures, melting glaciers, changes in precipitation and runoff. These trends are assumed to affect productivity in fjordic estuaries. However, the spatial extent and temporal variation of the freshwater-driven darkening of fjords remain unresolved. The present study illustrates the spatio-temporal variability of suspended particulate matter (SPM) in the Adventfjorden estuary, Svalbard, using in-situ field campaigns and ocean colour remote sensing (OCRS) via high-resolution Sentinel-2 imagery. To compute SPM concentration (C-SPMsat), a semi-analytical algorithm was regionally calibrated using local in-situ data, which improved the accuracy of satellite-derived SPM concentration by similar to 20% (MRD). Analysis of SPM concentration for two consecutive years (2019, 2020) revealed strong seasonality of SPM in Adventfjorden. Highest estimated SPM concentrations and river plume extent (% of fjord with C-SPMsat > 30 mg L-1) occurred during June, July, and August. Concurrently, we observed a strong relationship between river plume extent and average air temperature over the 24 h prior to the observation (R-2 = 0.69). Considering predicted changes to environmental conditions in the Arctic region, this study highlights the importance of the rapidly changing environmental parameters and the significance of remote sensing in analysing fluxes in light attenuating particles, especially in the coastal Arctic Ocean. KW - ocean colour KW - coastal darkening KW - SPM KW - sediment plumes KW - Arctic coast KW - remote sensing KW - regional tuning KW - coastal ecosystems; KW - land-ocean-interaction KW - riverine inputs Y1 - 2022 U6 - https://doi.org/10.3390/rs14133123 SN - 2072-4292 VL - 14 IS - 13 PB - MDPI CY - Basel ER - TY - JOUR A1 - Zappa, Luca A1 - Schlaffer, Stefan A1 - Brocca, Luca A1 - Vreugdenhil, Mariette A1 - Nendel, Claas A1 - Dorigo, Wouter T1 - How accurately can we retrieve irrigation timing and water amounts from (satellite) soil moisture? JF - International journal of applied earth observation and geoinformation N2 - While ensuring food security worldwide, irrigation is altering the water cycle and generating numerous environmental side effects. As detailed knowledge about the timing and the amounts of water used for irrigation over large areas is still lacking, remotely sensed soil moisture has proved potential to fill this gap. However, the spatial resolution and revisit time of current satellite products represent a major limitation to accurately estimating irrigation. This work aims to systematically quantify their impact on the retrieved irrigation information, hence assessing the value of satellite soil moisture for estimating irrigation timing and water amounts. In a real-world experiment, we modeled soil moisture using actual irrigation and meteorological data, obtained from farmers and weather stations, respectively. Modeled soil moisture was compared against various remotely sensed products differing in terms of spatio-temporal resolution to test the hypothesis that high-resolution observations can disclose the irrigation signal from individual fields while coarse-scale satellite products cannot. Then, in a synthetic experiment, we systematically investigated the effect of soil moisture spatial and temporal resolution on the accuracy of irrigation estimates. The analysis was further elaborated by considering different irrigation scenarios and by adding realistic amounts of random errors in the soil moisture time series. We show that coarse-scale remotely sensed soil moisture products achieve higher correlations with rainfed simulations, while high-resolution satellite observations agree significantly better with irrigated simulations, suggesting that high-resolution satellite soil moisture can inform on field-scale (similar to 40 ha) irrigation. A thorough analysis of the synthetic dataset showed that satisfactory results, both in terms of detection (F-score > 0.8) and quantification (Pearson's correlation > 0.8), are found for noise-free soil moisture observations either with a temporal sampling up to 3 days or if at least one-third of the pixel covers the irrigated field(s). However, irrigation water amounts are systematically underestimated for temporal samplings of more than one day, and decrease proportionally to the spatial resolution, i.e., coarsening the pixel size leads to larger irrigation underestimations. Although lower spatial and temporal resolutions decrease the detection and quantification accuracies (e.g., R between 0.6 and 1 depending on the irrigation rate and spatio-temporal resolution), random errors in the soil moisture time series have a stronger negative impact (Pearson R always smaller than 0.85). As expected, better performances are found for higher irrigation rates, i.e. when more water is supplied during an irrigation event. Despite the potentially large underestimations, our results suggest that high-resolution satellite soil moisture has the potential to track and quantify irrigation, especially over regions where large volumes of irrigation water are applied to the fields, and given that low errors affect the soil moisture observations. KW - remote sensing KW - soil moisture KW - irrigation KW - detection KW - quantification KW - sentinel-1 Y1 - 2022 U6 - https://doi.org/10.1016/j.jag.2022.102979 SN - 1569-8432 SN - 1872-826X VL - 113 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Barbosa, Luis Romero A. A1 - Coelho, Victor Hugo R. A1 - Gusmao, Ana Claudia V. L. F. A1 - Fernandes, Lucila A. E. A1 - da Silva, Bernardo B. A1 - Galvao, Carlos de O. A1 - Caicedo, Nelson O. L. A1 - da Paz, Adriano R. A1 - Xuan, Yunqing A1 - Bertrand, Guillaume F. A1 - Melo, Davi de C. D. A1 - Montenegro, Suzana M. G. L. A1 - Oswald, Sascha A1 - Almeida, Cristiano das N. T1 - A satellite-based approach to estimating spatially distributed groundwater recharge rates in a tropical wet sedimentary region despite cloudy conditions JF - Journal of hydrology N2 - Groundwater recharge (GWR) is one of the most challenging water fluxes to estimate, as it relies on observed data that are often limited in many developing countries. This study developed an innovative water budget method using satellite products for estimating the spatially distributed GWR at monthly and annual scales in tropical wet sedimentary regions despite cloudy conditions. The distinctive features proposed in this study include the capacity to address 1) evapotranspiration estimations in tropical wet regions frequently overlaid by substantial cloud cover; and 2) seasonal root-zone water storage estimations in sedimentary regions prone to monthly variations. The method also utilises satellite-based information of the precipitation and surface runoff. The GWR was estimated and validated for the hydrologically contrasting years 2016 and 2017 over a tropical wet sedimentary region located in North-eastern Brazil, which has substantial potential for groundwater abstraction. This study showed that applying a cloud-cleaning procedure based on monthly compositions of biophysical data enables the production of a reasonable proxy for evapotranspiration able to estimate groundwater by the water budget method. The resulting GWR rates were 219 (2016) and 302 (2017) mm yr(-1), showing good correlations (CC = 0.68 to 0.83) and slight underestimations (PBIAS =-13 to-9%) when compared with the referenced estimates obtained by the water table fluctuation method for 23 monitoring wells. Sensitivity analysis shows that water storage changes account for +19% to-22% of our monthly evaluation. The satellite-based approach consistently demonstrated that the consideration of cloud-cleaned evapotranspiration and root-zone soil water storage changes are essential for a proper estimation of spatially distributed GWR in tropical wet sedimentary regions because of their weather seasonality and cloudy conditions. KW - remote sensing KW - water balance KW - groundwater recharge KW - water table KW - fluctuation KW - tropical climate KW - sedimentary aquifer Y1 - 2022 U6 - https://doi.org/10.1016/j.jhydrol.2022.127503 SN - 0022-1694 SN - 1879-2707 VL - 607 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Fernandez-Palomino, Carlos Antonio A1 - Hattermann, Fred A1 - Krysanova, Valentina A1 - Vega-Jacome, Fiorella A1 - Bronstert, Axel T1 - Towards a more consistent eco-hydrological modelling through multi-objective calibration BT - a case study in the Andean Vilcanota River basin, Perú JF - Hydrological sciences journal = Journal des sciences hydrologiques N2 - 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. KW - Andes KW - eco-hydrology KW - SWAT KW - hydrological signatures KW - remote sensing KW - equifinality Y1 - 2020 U6 - https://doi.org/10.1080/02626667.2020.1846740 SN - 0262-6667 SN - 2150-3435 VL - 66 IS - 1 SP - 59 EP - 74 PB - Routledge, Taylor & Francis Group CY - Abingdon ER - TY - JOUR A1 - Göritz, Anna A1 - Berger, Stella A. A1 - Gege, Peter A1 - Grossart, Hans-Peter A1 - Nejstgaard, Jens C. A1 - Riedel, Sebastian A1 - Röttgers, Rüdiger A1 - Utschig, Christian T1 - Retrieval of water constituents from hyperspectral in-situ measurements under variable cloud cover BT - a case study at Lake Stechlin (Germany) JF - Remote sensing / Molecular Diversity Preservation International (MDPI) N2 - Remote sensing and field spectroscopy of natural waters is typically performed under clear skies, low wind speeds and low solar zenith angles. Such measurements can also be made, in principle, under clouds and mixed skies using airborne or in-situ measurements; however, variable illumination conditions pose a challenge to data analysis. In the present case study, we evaluated the inversion of hyperspectral in-situ measurements for water constituent retrieval acquired under variable cloud cover. First, we studied the retrieval of Chlorophyll-a (Chl-a) concentration and colored dissolved organic matter (CDOM) absorption from in-water irradiance measurements. Then, we evaluated the errors in the retrievals of the concentration of total suspended matter (TSM), Chl-a and the absorption coefficient of CDOM from above-water reflectance measurements due to highly variable reflections at the water surface. In order to approximate cloud reflections, we extended a recent three-component surface reflectance model for cloudless atmospheres by a constant offset and compared different surface reflectance correction procedures. Our findings suggest that in-water irradiance measurements may be used for the analysis of absorbing compounds even under highly variable weather conditions. The extended surface reflectance model proved to contribute to the analysis of above-water reflectance measurements with respect to Chl-a and TSM. Results indicate the potential of this approach for all-weather monitoring. KW - remote sensing KW - inland water KW - hyperspectral measurements KW - in-situ KW - cloud KW - surface reflection KW - inversion KW - bio-optical modeling Y1 - 2018 U6 - https://doi.org/10.3390/rs10020181 SN - 2072-4292 VL - 10 IS - 2 PB - MDPI CY - Basel ER - TY - JOUR A1 - Coesfeld, Jacqueline A1 - Kuester, Theres A1 - Kuechly, Helga U. A1 - Kyba, Christopher C. M. T1 - Reducing variability and removing natural light from nighttime satellite imagery: A case study using the VIIRS DNB JF - Sensors N2 - 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. KW - airglow KW - artificial light KW - calibration KW - VIIRS DNB KW - nightlights KW - remote sensing Y1 - 2020 VL - 20 PB - MDPI CY - Basel ER - TY - JOUR A1 - Pereira, Bruno A1 - Medeiros, Pedro Henrique Augusto A1 - Francke, Till A1 - Ramalho, Geraldo A1 - Förster, Saskia A1 - De Araujo, Jose Carlos T1 - Assessment of the geometry and volumes of small surface water reservoirs by remote sensing in a semi-arid region with high reservoir density JF - Hydrological sciences journal = Journal des sciences hydrologiques N2 - 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. KW - reservoir volume KW - high-density reservoir network KW - water height-area-volume curve KW - semi-arid KW - remote sensing Y1 - 2019 U6 - https://doi.org/10.1080/02626667.2019.1566727 SN - 0262-6667 SN - 2150-3435 VL - 64 IS - 1 SP - 66 EP - 79 PB - Routledge, Taylor & Francis Group CY - Abingdon ER - TY - JOUR A1 - Brieger, Frederic A1 - Herzschuh, Ulrike A1 - Pestryakova, Luidmila Agafyevna A1 - Bookhagen, Bodo A1 - Zakharov, Evgenii S. A1 - Kruse, Stefan T1 - Advances in the Derivation of Northeast Siberian Forest Metrics Using High-Resolution UAV-Based Photogrammetric Point Clouds JF - Remote sensing N2 - 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. KW - UAV KW - photogrammetry KW - remote sensing KW - structure from motion KW - tundra-taiga ecotone KW - point cloud KW - forest structure Y1 - 2019 U6 - https://doi.org/10.3390/rs11121447 SN - 2072-4292 VL - 11 IS - 12 PB - MDPI CY - Basel ER - TY - JOUR A1 - Loibl, David A1 - Bookhagen, Bodo A1 - Valade, Sebastien A1 - Schneider, Christoph T1 - OSARIS, the "Open Source SAR Investigation System" for Automatized Parallel InSAR Processing of Sentinel-1 Time Series Data With Special Emphasis on Cryosphere Applications JF - Frontiers in Earth Science N2 - 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. KW - remote sensing KW - InSAR KW - high mountain environments KW - rock glacier KW - sentinel-1 KW - time series analysis Y1 - 2019 U6 - https://doi.org/10.3389/feart.2019.00172 SN - 2296-6463 VL - 7 PB - Frontiers Media CY - Lausanne ER - TY - JOUR A1 - Moustakas, Aristides A1 - Günther, Matthias A1 - Wiegand, Kerstin A1 - Müller, Karl-Heinz A1 - Ward, David A1 - Meyer, Katrin M. A1 - Jeltsch, Florian T1 - Long-term mortality patterns of the deep-rooted Acacia erioloba BT - The middle class shall die! JF - Journal of vegetation science N2 - Question: Is there a relationship between size and death in the Iona-lived, deep-rooted tree, Acacia erioloba, in a semi-arid savanna? What is the size-class distribution of A. erioloba mortality? Does the mortality distribution differ from total tree size distribution? Does A. erioloba mortality distribution match the mortality distributions recorded thus far in other environments? Location: Dronfield Ranch, near Kimberley, Kalahari, South Africa. Methods: A combination of aerial photographs and a satellite image covering 61 year was used to provide long-term spatial data on mortality. We used aerial photographs of the study area from 1940, 1964, 1984, 1993 and a satellite image from 2001 to follow three plots covering 510 ha. We were able to identify and individually follow ca. 3000 individual trees from 1940 till 2001. Results: The total number of trees increased over time. No relationship between total number of trees and mean tree size was detected. There were no trends over time in total number of deaths per plot or in size distributions of dead trees. Kolmogorov-Smirnov tests showed no differences in size class distributions for living trees through time. The size distribution of dead trees was significantly different from the size distribution of all trees present on the plots. Overall, the number of dead trees was low in small size classes, reached a peak value when canopy area was 20 - 30 m(2), and declined in lamer size-classes. Mortality as a ratio of dead vs. total trees peaked at intermediate canopy sizes too. Conclusion: A. erioloba mortality was size-dependent, peaking at intermediate sizes. The mortality distribution differs from all other tree mortality distributions recorded thus far. We suggest that a possible mechanism for this unusual mortality distribution is intraspecific competition for water in this semi-arid environment. KW - competition KW - long-term data KW - remote sensing KW - savanna KW - size dependent mortality KW - size distribution KW - tree death Y1 - 2006 U6 - https://doi.org/10.1111/j.1654-1103.2006.tb02468.x SN - 1100-9233 VL - 17 SP - 473 EP - 480 PB - Blackwell CY - Malden ER - TY - JOUR A1 - Hoffmann, Bernd A1 - Feakins, Sarah J. A1 - Bookhagen, Bodo A1 - Olen, Stephanie M. A1 - Adhikari, Danda P. A1 - Mainali, Janardan A1 - Sachse, Dirk T1 - Climatic and geomorphic drivers of plant organic matter transport in the Arun River, E Nepal JF - Earth & planetary science letters KW - plant wax biomarker KW - leaf wax delta D KW - carbon cycle KW - remote sensing KW - erosion Y1 - 2016 U6 - https://doi.org/10.1016/j.epsl.2016.07.008 SN - 0012-821X SN - 1385-013X VL - 452 SP - 104 EP - 114 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Heine, Iris A1 - Francke, Till A1 - Rogass, Christian A1 - Medeiros, Pedro Henrique Augusto A1 - Bronstert, Axel A1 - Förster, Saskia T1 - Monitoring seasonal changes in the water surface areas of reservoirs using TerraSAR-X time series data in semiarid northeastern Brazil JF - IEEE journal of selected topics in applied earth observations and remote sensing N2 - 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. KW - Image classification KW - monitoring KW - radar imaging KW - remote sensing KW - synthetic aperture radar (SAR) Y1 - 2014 U6 - https://doi.org/10.1109/JSTARS.2014.2323819 SN - 1939-1404 SN - 2151-1535 VL - 7 IS - 8 SP - 3190 EP - 3199 PB - Inst. of Electr. and Electronics Engineers CY - Piscataway ER -