@misc{CoesfeldAndersonBaughetal.2018, author = {Coesfeld, Jacqueline and Anderson, Sharolyn J. and Baugh, Kimberly and Elvidge, Christopher D. and Schernthanner, Harald and Kyba, Christopher C. M.}, title = {Variation of individual location radiance in VIIRS DNB monthly composite images}, series = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, journal = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, number = {1113}, issn = {1866-8372}, doi = {10.25932/publishup-47232}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-472326}, pages = {19}, year = {2018}, abstract = {With the growing size and use of night light time series from the Visible Infrared Imaging Radiometer Suite Day/Night Band (DNB), it is important to understand the stability of the dataset. All satellites observe differences in pixel values during repeat observations. In the case of night light data, these changes can be due to both environmental effects and changes in light emission. Here we examine the stability of individual locations of particular large scale light sources (e.g., airports and prisons) in the monthly composites of DNB data from April 2012 to September 2017. The radiances for individual pixels of most large light emitters are approximately normally distributed, with a standard deviation of typically 15-20\% of the mean. Greenhouses and flares, however, are not stable sources. We observe geospatial autocorrelation in the monthly variations for nearby sites, while the correlation for sites separated by large distances is small. This suggests that local factors contribute most to the variation in the pixel radiances and furthermore that averaging radiances over large areas will reduce the total variation. A better understanding of the causes of temporal variation would improve the sensitivity of DNB to lighting changes.}, language = {en} } @article{CoesfeldAndersonBaughetal.2018, author = {Coesfeld, Jacqueline and Anderson, Sharolyn J. and Baugh, Kimberly and Elvidge, Christopher D. and Schernthanner, Harald and Kyba, Christopher C. M.}, title = {Variation of Individual Location Radiance in VIIRS DNB Monthly Composite Images}, series = {Remote sensing}, volume = {10}, journal = {Remote sensing}, number = {12}, publisher = {MDPI}, address = {Basel}, issn = {2072-4292}, doi = {10.3390/rs10121964}, pages = {17}, year = {2018}, abstract = {With the growing size and use of night light time series from the Visible Infrared Imaging Radiometer Suite Day/Night Band (DNB), it is important to understand the stability of the dataset. All satellites observe differences in pixel values during repeat observations. In the case of night light data, these changes can be due to both environmental effects and changes in light emission. Here we examine the stability of individual locations of particular large scale light sources (e.g., airports and prisons) in the monthly composites of DNB data from April 2012 to September 2017. The radiances for individual pixels of most large light emitters are approximately normally distributed, with a standard deviation of typically 15-20\% of the mean. Greenhouses and flares, however, are not stable sources. We observe geospatial autocorrelation in the monthly variations for nearby sites, while the correlation for sites separated by large distances is small. This suggests that local factors contribute most to the variation in the pixel radiances and furthermore that averaging radiances over large areas will reduce the total variation. A better understanding of the causes of temporal variation would improve the sensitivity of DNB to lighting changes.}, language = {en} } @article{CardenasMolinerHontoriaetal.2018, author = {Cardenas, Aura and Moliner, Ana and Hontoria, Chiquinquira and Schernthanner, Harald}, title = {Analysis of land-use/land-cover changes in a livestock landscape dominated by traditional silvopastoral systems}, series = {International Journal of Remote Sensing}, volume = {39}, journal = {International Journal of Remote Sensing}, number = {14}, publisher = {Routledge, Taylor \& Francis Group}, address = {Abingdon}, issn = {0143-1161}, doi = {10.1080/01431161.2018.1463116}, pages = {4684 -- 4698}, year = {2018}, abstract = {Remote sensing, which is a common method to examine land-use/land-cover (LULC) changes, could be useful in the analysis of livestock ecosystem transformations. In the last two decades, before Landsat images were free, developing countries could not afford monitoring through remote sensing because of the high cost of acquiring satellite imagery and commercial software. However, Landsat time series nowadays allows the characterization of changes in vegetation across large areas over time. The aim of this study is to analyse the LULC changes affecting forest frontiers and traditional silvopastoral systems (TSPS) in a representative livestock area of Nicaragua. Nearly cloud-free Landsat scenes - a Landsat 5 Thematic Mapper (TM) scene from 1986 and a Landsat 8 Operational Land Imager (OLI) scene from 2015 - have been the data sets used in the study. A process chain following a four-step definition of the remote-sensing process was conceptually developed and implemented based onfree open source software components and by applying the random forest (RF) algorithm. A conceptual LULC classification scheme representing TSPS was developed. Although the imagery shows a heterogeneous surface cover and mixed pixels, it is possible to achieve promising classification results with the RF algorithm with out-of-the-bag (OOB) errors below 13\% for both images along with an overall accuracy level of 85.9\% for the 2015 subset and 85.2\% for the 1986 subset. The classification shows that from 1986 to 2015 (29years) the intervened secondary forest (ISF) increased 2.6 times, whereas the degraded pastures decreased by 34.5\%. The livestock landscape in Matiguas is in a state of constant transformation, but the main changes head towards the positive direction of tree-cover recovery and an increased number of areas of natural regeneration.}, language = {en} } @article{SchernthannerAscheGonschoreketal.2017, author = {Schernthanner, Harald and Asche, Hartmut and Gonschorek, Julia and Scheele, Lasse}, title = {Spatial Modeling and Geovisualization of Rental Prices for Real Estate portals}, series = {International journal of agricultural and environmental information systems : an official publication of the Information Resources Management Association}, volume = {8}, journal = {International journal of agricultural and environmental information systems : an official publication of the Information Resources Management Association}, publisher = {IGI Global}, address = {Hershey}, issn = {1947-3192}, doi = {10.4018/IJAEIS.2017040106}, pages = {78 -- 91}, year = {2017}, language = {en} } @incollection{CardenasSchernthanner2022, author = {C{\´a}rdenas, Aura and Schernthanner, Harald}, title = {The role of livestock wastes in clean energy}, series = {Handbook of waste biorefinery}, booktitle = {Handbook of waste biorefinery}, editor = {Jacob-Lopes, Eduardo and Queiroz Zepka, Leila and Costa Depr{\´a}, Mariany}, publisher = {Springer}, address = {Cham}, isbn = {978-3-031-06561-3}, doi = {10.1007/978-3-031-06562-0_12}, pages = {337 -- 343}, year = {2022}, abstract = {Agricultural production worldwide has been increasing in the last decades at a very fast pace and with it the waste generation. Livestock activities are one of the largest producers of residues in the agricultural sector and contribute greatly to climate change. The present chapter gives an introduction and an in-depth analysis of the waste management of livestock for the conversion in a circular agriculture and economy based on research and experience in the sector conducted in the last decades. The conversion of animal waste into energy generation is an opportunity for farmers to obtain additional economic benefits, while contributing to the environment by preventing the release of GHGs into the atmosphere. The use of animal waste for energy generation through anaerobic digestion is a progressive technique and is being widely accepted in Europe, where Germany is the leading country in the use of biogas plants for energy production among others in the European Union. Economically speaking, the livestock industry faces the challenge of converting its production into a clean and more profitable production. The goal of this chapter is to analyze the economic benefit as well as the environmental contribution and future challenges of the use of livestock waste in the biorefineries sector from different perspectives, based on an intensive literature review. This review is accompanied by a geospatial analysis component, mapping biogas reactor hotspots and clusters in Germany, by means of methods of spatial statistics as analysis methods as kernel density estimations (KDE) and K-means clustering, based on volunteer geographic data. The applied methods easily can be transferred to other regions and allow a quick macroscopic overview over existing biogas reactors; furthermore, an identification of cluster and hotspots with a high biogas potential, that in a subsequent step can be analyzed in depth in larger scales.}, language = {en} }