@article{MoreauxMeirelesSonneetal.2022, author = {Moreaux, C{\´e}line and Meireles, Desir{\´e}e A. L. and Sonne, Jesper and Badano, Ernesto I. and Classen, Alice and Gonz{\´a}lez-Chaves, Adrian and Hip{\´o}lito, Juliana and Klein, Alexandra-Maria and Maruyama, Pietro K. and Metzger, Jean Paul and Philpott, Stacy M. and Rahbek, Carsten and Saturni, Fernanda T. and Sritongchuay, Tuanjit and Tscharntke, Teja and Uno, Shinsuke and Vergara, Carlos H. and Viana, Blandina F. and Strange, Niels and Dalsgaard, Bo}, title = {The value of biotic pollination and dense forest for fruit set of Arabica coffee: A global assessment}, series = {Agriculture, Ecosystems \& Environment}, volume = {323}, journal = {Agriculture, Ecosystems \& Environment}, doi = {10.1016/j.agee.2021.107680}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-370982}, year = {2022}, abstract = {Animal pollinators are globally threatened by anthropogenic land use change and agricultural intensification. The yield of many food crops is therefore negatively impacted because they benefit from biotic pollination. This is especially the case in the tropics. For instance, fruit set of Coffea arabica has been shown to increase by 10-30\% in plantations with a high richness of bee species, possibly influenced by the availability of surrounding forest habitat. Here, we performed a global literature review to (1) assess how much animal pollination enhances coffee fruit set, and to (2) examine the importance of the amount of forest cover, distance to nearby forest and forest canopy density for bee species richness and coffee fruit set. Using a systematic literature review, we identified eleven case studies with a total of 182 samples where fruit set of C. arabica was assessed. We subsequently gathered forest data for all study sites from satellite imagery. We modelled the effects of open (all forest with a canopy density of ≥25\%), closed (≥50\%) and dense (≥75\%) forests on pollinator richness and fruit set of coffee. Overall, we found that animal pollination increases coffee fruit set by ~18\% on average. In only one of the case studies, regression results indicate a positive effect of dense forest on coffee fruit set, which increased with higher forest cover and shorter distance to the forest. Against expectations, forest cover and distance to open forest were not related to bee species richness and fruit set. In summary, we provide strong empirical support for the notion that animal pollinators increase coffee fruit set. Forest proximity had little overall influence on bee richness and coffee fruit set, except when farms were surrounded by dense tropical forests, potentially because these may provide high-quality habitats for bees pollinating coffee. We, therefore, advocate that more research is done to understand the biodiversity value of dense forest for pollinators, notably assessing the mechanisms underlying the importance of forest for pollinators and their pollination services.}, language = {en} } @article{TaubenboeckWeigandEschetal.2019, author = {Taubenb{\"o}ck, H. and Weigand, M. and Esch, T. and Staab, J. and Wurm, M. and Mast, J. and Dech, S.}, title = {A new ranking of the world's largest cities—Do administrative units obscure morphological realities?}, series = {Remote Sensing of Environment}, volume = {232}, journal = {Remote Sensing of Environment}, doi = {10.1016/j.rse.2019.111353}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-240634}, year = {2019}, abstract = {With 37 million inhabitants, Tokyo is the world's largest city in UN statistics. With this work we call this ranking into question. Usually, global city rankings are based on nationally collected population figures, which rely on administrative units. Sprawling urban growth, however, leads to morphological city extents that may surpass conventional administrative units. In order to detect spatial discrepancies between the physical and the administrative city, we present a methodology for delimiting Morphological Urban Areas (MUAs). We understand MUAs as a territorially contiguous settlement area that can be distinguished from low-density peripheral and rural hinterlands. We design a settlement index composed of three indicators (settlement area, settlement area proportion and density within the settlements) describing a gradient of built-up density from the urban center to the periphery applying a sectoral monocentric city model. We assume that the urban-rural transition can be defined along this gradient. With it, we re-territorialize the conventional administrative units. Our data basis are recent mapping products derived from multi-sensoral Earth observation (EO) data - namely the Global Urban Footprint (GUF) and the GUF Density (GUF-DenS) - providing globally consistent knowledge about settlement locations and densities. For the re-territorialized MUAs we calculate population numbers using WorldPop data. Overall, we cover the 1692 cities with >300,000 inhabitants on our planet. In our results we compare the consistently re-territorialized MUAs and the administrative units as well as their related population figures. We find the MUA in the Pearl River Delta the largest morphologically contiguous urban agglomeration in the world with a calculated population of 42.6 million. Tokyo, in this new list ranked number 2, loses its top position. In rank-size distributions we present the resulting deviations from previous city rankings. Although many MUAs outperform administrative units by area, we find that, contrary to what we assumed, in most cases MUAs are considerably smaller than administrative units. Only in Europe we find MUAs largely outweighing administrative units in extent.}, language = {en} } @article{ReinermannAsamGessneretal.2023, author = {Reinermann, Sophie and Asam, Sarah and Gessner, Ursula and Ullmann, Tobias and Kuenzer, Claudia}, title = {Multi-annual grassland mowing dynamics in Germany}, series = {Frontiers in Environmental Science}, volume = {11}, journal = {Frontiers in Environmental Science}, issn = {2296-665X}, doi = {10.3389/fenvs.2023.1040551}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-320700}, year = {2023}, abstract = {Introduction: Grasslands cover one third of the agricultural area in Germany and are mainly used for fodder production. However, grasslands fulfill many other ecosystem functions, like carbon storage, water filtration and the provision of habitats. In Germany, grasslands are mown and/or grazed multiple times during the year. The type and timing of management activities and the use intensity vary strongly, however co-determine grassland functions. Large-scale spatial information on grassland activities and use intensity in Germany is limited and not openly provided. In addition, the cause for patterns of varying mowing intensity are usually not known on a spatial scale as data on the incentives of farmers behind grassland management decisions is not available. Methods: We applied an algorithm based on a thresholding approach utilizing Sentinel-2 time series to detect grassland mowing events to investigate mowing dynamics in Germany in 2018-2021. The detected mowing events were validated with an independent dataset based on the examination of public webcam images. We analyzed spatial and temporal patterns of the mowing dynamics and relationships to climatic, topographic, soil or socio-political conditions. Results: We found that most intensively used grasslands can be found in southern/south-eastern Germany, followed by areas in northern Germany. This pattern stays the same among the investigated years, but we found variations on smaller scales. The mowing event detection shows higher accuracies in 2019 and 2020 (F1 = 0.64 and 0.63) compared to 2018 and 2021 (F1 = 0.52 and 0.50). We found a significant but weak (R2 of 0-0.13) relationship for a spatial correlation of mowing frequency and climate as well as topographic variables for the grassland areas in Germany. Further results indicate a clear value range of topographic and climatic conditions, characteristic for intensive grassland use. Extensive grassland use takes place everywhere in Germany and on the entire spectrum of topographic and climatic conditions in Germany. Natura 2000 grasslands are used less intensive but this pattern is not consistent among all sites. Discussion: Our findings on mowing dynamics and relationships to abiotic and socio-political conditions in Germany reveal important aspects of grassland management, including incentives of farmers.}, language = {en} } @article{KunzUllmannKneiseletal.2023, author = {Kunz, Julius and Ullmann, T. and Kneisel, C. and Baumhauer, R.}, title = {Three-dimensional subsurface architecture and its influence on the spatiotemporal development of a retrogressive thaw slump in the Richardson Mountains, Northwest Territories, Canada}, series = {Arctic, Antarctic, and Alpine Research}, volume = {55}, journal = {Arctic, Antarctic, and Alpine Research}, number = {1}, issn = {1523-0430}, doi = {10.1080/15230430.2023.2167358}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-350147}, year = {2023}, abstract = {The development of retrogressive thaw slumps (RTS) is known to be strongly influenced by relief-related parameters, permafrost characteristics, and climatic triggers. To deepen the understanding of RTS, this study examines the subsurface characteristics in the vicinity of an active thaw slump, located in the Richardson Mountains (Western Canadian Arctic). The investigations aim to identify relationships between the spatiotemporal slump development and the influence of subsurface structures. Information on these were gained by means of electrical resistivity tomography (ERT) and ground-penetrating radar (GPR). The spatiotemporal development of the slump was revealed by high-resolution satellite imagery and unmanned aerial vehicle-based digital elevation models (DEMs). The analysis indicated an acceleration of slump expansion, especially since 2018. The comparison of the DEMs enabled the detailed balancing of erosion and accumulation within the slump area between August 2018 and August 2019. In addition, manual frost probing and GPR revealed a strong relationship between the active layer thickness, surface morphology, and hydrology. Detected furrows in permafrost table topography seem to affect the active layer hydrology and cause a canalization of runoff toward the slump. The three-dimensional ERT data revealed a partly unfrozen layer underlying a heterogeneous permafrost body. This may influence the local hydrology and affect the development of the RTS. The results highlight the complex relationships between slump development, subsurface structure, and hydrology and indicate a distinct research need for other RTSs.}, language = {en} } @article{ReinersSobrinoKuenzer2023, author = {Reiners, Philipp and Sobrino, Jos{\´e} and Kuenzer, Claudia}, title = {Satellite-derived land surface temperature dynamics in the context of global change — a review}, series = {Remote Sensing}, volume = {15}, journal = {Remote Sensing}, number = {7}, issn = {2072-4292}, doi = {10.3390/rs15071857}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-311120}, year = {2023}, abstract = {Satellite-derived Land Surface Temperature (LST) dynamics have been increasingly used to study various geophysical processes. This review provides an extensive overview of the applications of LST in the context of global change. By filtering a selection of relevant keywords, a total of 164 articles from 14 international journals published during the last two decades were analyzed based on study location, research topic, applied sensor, spatio-temporal resolution and scale and employed analysis methods. It was revealed that China and the USA were the most studied countries and those that had the most first author affiliations. The most prominent research topic was the Surface Urban Heat Island (SUHI), while the research topics related to climate change were underrepresented. MODIS was by far the most used sensor system, followed by Landsat. A relatively small number of studies analyzed LST dynamics on a global or continental scale. The extensive use of MODIS highly determined the study periods: A majority of the studies started around the year 2000 and thus had a study period shorter than 25 years. The following suggestions were made to increase the utilization of LST time series in climate research: The prolongation of the time series by, e.g., using AVHRR LST, the better representation of LST under clouds, the comparison of LST to traditional climate change measures, such as air temperature and reanalysis variables, and the extension of the validation to heterogenous sites.}, language = {en} } @article{KleinCoccoUereyenetal.2022, author = {Klein, Igor and Cocco, Arturo and Uereyen, Soner and Mannu, Roberto and Floris, Ignazio and Oppelt, Natascha and Kuenzer, Claudia}, title = {Outbreak of Moroccan locust in Sardinia (Italy): a remote sensing perspective}, series = {Remote Sensing}, volume = {14}, journal = {Remote Sensing}, number = {23}, issn = {2072-4292}, doi = {10.3390/rs14236050}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-297232}, year = {2022}, abstract = {The Moroccan locust has been considered one of the most dangerous agricultural pests in the Mediterranean region. The economic importance of its outbreaks diminished during the second half of the 20th century due to a high degree of agricultural industrialization and other human-caused transformations of its habitat. Nevertheless, in Sardinia (Italy) from 2019 on, a growing invasion of this locust species is ongoing, being the worst in over three decades. Locust swarms destroyed crops and pasture lands of approximately 60,000 ha in 2022. Drought, in combination with increasing uncultivated land, contributed to forming the perfect conditions for a Moroccan locust population upsurge. The specific aim of this paper is the quantification of land cover land use (LCLU) influence with regard to the recent locust outbreak in Sardinia using remote sensing data. In particular, the role of untilled, fallow, or abandoned land in the locust population upsurge is the focus of this case study. To address this objective, LCLU was derived from Sentinel-2A/B Multispectral Instrument (MSI) data between 2017 and 2021 using time-series composites and a random forest (RF) classification model. Coordinates of infested locations, altitude, and locust development stages were collected during field observation campaigns between March and July 2022 and used in this study to assess actual and previous land cover situation of these locations. Findings show that 43\% of detected locust locations were found on untilled, fallow, or uncultivated land and another 23\% within a radius of 100 m to such areas. Furthermore, oviposition and breeding sites are mostly found in sparse vegetation (97\%). This study demonstrates that up-to-date remote sensing data and target-oriented analyses can provide valuable information to contribute to early warning systems and decision support and thus to minimize the risk concerning this agricultural pest. This is of particular interest for all agricultural pests that are strictly related to changing human activities within transformed habitats.}, language = {en} } @article{AnsahAbuKleemannetal.2022, author = {Ansah, Christabel Edena and Abu, Itohan-Osa and Kleemann, Janina and Mahmoud, Mahmoud Ibrahim and Thiel, Michael}, title = {Environmental contamination of a biodiversity hotspot — action needed for nature conservation in the Niger Delta, Nigeria}, series = {Sustainability}, volume = {14}, journal = {Sustainability}, number = {21}, issn = {2071-1050}, doi = {10.3390/su142114256}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-297214}, year = {2022}, abstract = {The Niger Delta belongs to the largest swamp and mangrove forests in the world hosting many endemic and endangered species. Therefore, its conservation should be of highest priority. However, the Niger Delta is confronted with overexploitation, deforestation and pollution to a large extent. In particular, oil spills threaten the biodiversity, ecosystem services, and local people. Remote sensing can support the detection of spills and their potential impact when accessibility on site is difficult. We tested different vegetation indices to assess the impact of oil spills on the land cover as well as to detect accumulations (hotspots) of oil spills. We further identified which species, land cover types, and protected areas could be threatened in the Niger Delta due to oil spills. The results showed that the Enhanced Vegetation Index, the Normalized Difference Vegetation Index, and the Soil Adjusted Vegetation Index were more sensitive to the effects of oil spills on different vegetation cover than other tested vegetation indices. Forest cover was the most affected land-cover type and oil spills also occurred in protected areas. Threatened species are inhabiting the Niger Delta Swamp Forest and the Central African Mangroves that were mainly affected by oil spills and, therefore, strong conservation measures are needed even though security issues hamper the monitoring and control.}, language = {en} } @article{KacicKuenzer2022, author = {Kacic, Patrick and Kuenzer, Claudia}, title = {Forest biodiversity monitoring based on remotely sensed spectral diversity — a review}, series = {Remote Sensing}, volume = {14}, journal = {Remote Sensing}, number = {21}, issn = {2072-4292}, doi = {10.3390/rs14215363}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-290535}, year = {2022}, abstract = {Forests are essential for global environmental well-being because of their rich provision of ecosystem services and regulating factors. Global forests are under increasing pressure from climate change, resource extraction, and anthropologically-driven disturbances. The results are dramatic losses of habitats accompanied with the reduction of species diversity. There is the urgent need for forest biodiversity monitoring comprising analysis on α, β, and γ scale to identify hotspots of biodiversity. Remote sensing enables large-scale monitoring at multiple spatial and temporal resolutions. Concepts of remotely sensed spectral diversity have been identified as promising methodologies for the consistent and multi-temporal analysis of forest biodiversity. This review provides a first time focus on the three spectral diversity concepts "vegetation indices", "spectral information content", and "spectral species" for forest biodiversity monitoring based on airborne and spaceborne remote sensing. In addition, the reviewed articles are analyzed regarding the spatiotemporal distribution, remote sensing sensors, temporal scales and thematic foci. We identify multispectral sensors as primary data source which underlines the focus on optical diversity as a proxy for forest biodiversity. Moreover, there is a general conceptual focus on the analysis of spectral information content. In recent years, the spectral species concept has raised attention and has been applied to Sentinel-2 and MODIS data for the analysis from local spectral species to global spectral communities. Novel remote sensing processing capacities and the provision of complementary remote sensing data sets offer great potentials for large-scale biodiversity monitoring in the future.}, language = {en} } @article{HaHuthBachoferetal.2022, author = {Ha, Tuyen V. and Huth, Juliane and Bachofer, Felix and Kuenzer, Claudia}, title = {A review of Earth observation-based drought studies in Southeast Asia}, series = {Remote Sensing}, volume = {14}, journal = {Remote Sensing}, number = {15}, issn = {2072-4292}, doi = {10.3390/rs14153763}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-286258}, year = {2022}, abstract = {Drought is a recurring natural climatic hazard event over terrestrial land; it poses devastating threats to human health, the economy, and the environment. Given the increasing climate crisis, it is likely that extreme drought phenomena will become more frequent, and their impacts will probably be more devastating. Drought observations from space, therefore, play a key role in dissimilating timely and accurate information to support early warning drought management and mitigation planning, particularly in sparse in-situ data regions. In this paper, we reviewed drought-related studies based on Earth observation (EO) products in Southeast Asia between 2000 and 2021. The results of this review indicated that drought publications in the region are on the increase, with a majority (70\%) of the studies being undertaken in Vietnam, Thailand, Malaysia and Indonesia. These countries also accounted for nearly 97\% of the economic losses due to drought extremes. Vegetation indices from multispectral optical remote sensing sensors remained a primary source of data for drought monitoring in the region. Many studies (~21\%) did not provide accuracy assessment on drought mapping products, while precipitation was the main data source for validation. We observed a positive association between spatial extent and spatial resolution, suggesting that nearly 81\% of the articles focused on the local and national scales. Although there was an increase in drought research interest in the region, challenges remain regarding large-area and long time-series drought measurements, the combined drought approach, machine learning-based drought prediction, and the integration of multi-sensor remote sensing products (e.g., Landsat and Sentinel-2). Satellite EO data could be a substantial part of the future efforts that are necessary for mitigating drought-related challenges, ensuring food security, establishing a more sustainable economy, and the preservation of the natural environment in the region.}, language = {en} } @article{SognoKleinKuenzer2022, author = {Sogno, Patrick and Klein, Igor and Kuenzer, Claudia}, title = {Remote sensing of surface water dynamics in the context of global change — a review}, series = {Remote Sensing}, volume = {14}, journal = {Remote Sensing}, number = {10}, issn = {2072-4292}, doi = {10.3390/rs14102475}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-275274}, year = {2022}, abstract = {Inland surface water is often the most accessible freshwater source. As opposed to groundwater, surface water is replenished in a comparatively quick cycle, which makes this vital resource — if not overexploited — sustainable. From a global perspective, freshwater is plentiful. Still, depending on the region, surface water availability is severely limited. Additionally, climate change and human interventions act as large-scale drivers and cause dramatic changes in established surface water dynamics. Actions have to be taken to secure sustainable water availability and usage. This requires informed decision making based on reliable environmental data. Monitoring inland surface water dynamics is therefore more important than ever. Remote sensing is able to delineate surface water in a number of ways by using optical as well as active and passive microwave sensors. In this review, we look at the proceedings within this discipline by reviewing 233 scientific works. We provide an extensive overview of used sensors, the spatial and temporal resolution of studies, their thematic foci, and their spatial distribution. We observe that a wide array of available sensors and datasets, along with increasing computing capacities, have shaped the field over the last years. Multiple global analysis-ready products are available for investigating surface water area dynamics, but so far none offer high spatial and temporal resolution.}, language = {en} }