@article{UereyenBachoferKuenzer2022,
  author    = {Uereyen, Soner and Bachofer, Felix and Kuenzer, Claudia},
  title     = {A framework for multivariate analysis of land surface dynamics and driving variables — a case study for Indo-Gangetic river basins},
  series = {Remote Sensing},
  volume    = {14},
  journal   = {Remote Sensing},
  number    = {1},
  issn      = {2072-4292},
  doi       = {10.3390/rs14010197},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-255295},
  year      = {2022},
  abstract  = {The analysis of the Earth system and interactions among its spheres is increasingly important to improve the understanding of global environmental change. In this regard, Earth observation (EO) is a valuable tool for monitoring of long term changes over the land surface and its features. Although investigations commonly study environmental change by means of a single EO-based land surface variable, a joint exploitation of multivariate land surface variables covering several spheres is still rarely performed. In this regard, we present a novel methodological framework for both, the automated processing of multisource time series to generate a unified multivariate feature space, as well as the application of statistical time series analysis techniques to quantify land surface change and driving variables. In particular, we unify multivariate time series over the last two decades including vegetation greenness, surface water area, snow cover area, and climatic, as well as hydrological variables. Furthermore, the statistical time series analyses include quantification of trends, changes in seasonality, and evaluation of drivers using the recently proposed causal discovery algorithm Peter and Clark Momentary Conditional Independence (PCMCI). We demonstrate the functionality of our methodological framework using Indo-Gangetic river basins in South Asia as a case study. The time series analyses reveal increasing trends in vegetation greenness being largely dependent on water availability, decreasing trends in snow cover area being mostly negatively coupled to temperature, and trends of surface water area to be spatially heterogeneous and linked to various driving variables. Overall, the obtained results highlight the value and suitability of this methodological framework with respect to global climate change research, enabling multivariate time series preparation, derivation of detailed information on significant trends and seasonality, as well as detection of causal links with minimal user intervention. This study is the first to use multivariate time series including several EO-based variables to analyze land surface dynamics over the last two decades using the causal discovery algorithm PCMCI.},
  language  = {en}
}
@article{AppelHardaker2022,
  author    = {Appel, Alexandra and Hardaker, Sina},
  title     = {Einzelhandel als Katalysator f{\"u}r nachhaltige urbane Radlogistik? - W{\"u}Livery, ein Fallbeispiel aus W{\"u}rzburg},
  series = {Standort},
  volume    = {46},
  journal   = {Standort},
  number    = {1},
  issn      = {1432-220X},
  doi       = {10.1007/s00548-021-00758-y},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-268437},
  pages     = {9-15},
  year      = {2022},
  abstract  = {Die Covid-19-Pandemie gilt in vielen gesellschaftlichen Teilbereichen als Beschleuniger f{\"u}r Transformationsprozesse. Auch im Bereich der Organisation urbaner Logistik und Einzelhandelslandschaften etablieren sich neue Akteur*innen und Funktionen. Logistiker*innen integrieren lokale Onlinemarktpl{\"a}tze in ihre Profile und der station{\"a}re Einzelhandel generiert Wettbewerbsf{\"a}higkeit gegen{\"u}ber großen Onlineh{\"a}ndler*innen {\"u}ber die Nutzung lokaler Radlogistiknetzwerke, mittels derer Lieferungen noch am Tag der Bestellung (Same-Day-Delivery) verteilt werden k{\"o}nnen. Damit leisten die involvierten Akteur*innen potenziell auch einen Beitrag zur Nachhaltigkeitstransformation im Bereich urbaner Logistiksysteme. Im Fokus steht das Fallbeispiel W{\"u}Livery, ein Kooperationsprojekt des Stadtmarketingvereins, der Wirtschaftsf{\"o}rderung, Radlogistiker*innen sowie Einzelh{\"a}ndler*innen in W{\"u}rzburg, welches w{\"a}hrend des zweiten coronabedingten Lockdowns im November 2020 umgesetzt wurde. Die entstehenden Dynamiken und Organisationsformen werden auf Basis von 11 Expert*inneninterviews dargestellt und analysiert. Es kann gezeigt werden, dass st{\"a}dtische Akteur*innen grundlegende Mediator*innen f{\"u}r Transformationsprozesse darstellen und Einzelh{\"a}ndler*innen und lokale Onlinemarktpl{\"a}tze als Katalysator*innen fungieren k{\"o}nnen. Das ist auch vor dem Hintergrund planerischer und politischer Kommunikationsprozesse zur Legitimation neuer Verkehrsinfrastrukturen nutzbar, da die einzelnen Akteur*innengruppen in Austausch kommen und ein gesteigertes Bewusstsein f{\"u}r die jeweiligen Bedarfe entsteht.},
  language  = {de}
}
@article{KleemannZamoraVillacisChiluisaetal.2022,
  author    = {Kleemann, Janina and Zamora, Camilo and Villacis-Chiluisa, Alexandra Belen and Cuenca, Pablo and Koo, Hongmi and Noh, Jin Kyoung and F{\"u}rst, Christine and Thiel, Michael},
  title     = {Deforestation in continental Ecuador with a focus on protected areas},
  series = {Land},
  volume    = {11},
  journal   = {Land},
  number    = {2},
  issn      = {2073-445X},
  doi       = {10.3390/land11020268},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-262078},
  year      = {2022},
  abstract  = {Forest conservation is of particular concern in tropical regions where a large refuge of biodiversity is still existing. These areas are threatened by deforestation, forest degradation and fragmentation. Especially, pressures of anthropogenic activities adjacent to these areas significantly influence conservation effectiveness. Ecuador was chosen as study area since it is a globally relevant center of forest ecosystems and biodiversity. We identified hotspots of deforestation on the national level of continental Ecuador between 1990 and 2018, analyzed the most significant drivers of deforestation on national and biome level (the Coast, the Andes, The Amazon) as well as inside protected areas in Ecuador by using multiple regression analysis. We separated the national system of protected areas (SNAP) into higher and lower protection levels. Besides SNAP, we also considered Biosphere Reserves (BRs) and Ramsar sites. In addition, we investigated the rates and spatial patterns of deforestation in protected areas and buffer zones (5 km and 10 km outwards the protected area boundaries) using landscape metrics. Between 1990 and 2018, approximately 4\% of the accumulated deforestation occurred within the boundaries of SNAP, and up to 25.5\% in buffer zones. The highest rates of deforestation have been found in the 5 km buffer zone around the protected areas with the highest protection level. Protected areas and their buffer zones with higher protection status were identified as the most deforested areas among SNAP. BRs had the highest deforestation rates among all protected areas but most of these areas just became BRs after the year 2000. The most important driver of deforestation is agriculture. Other relevant drivers differ between the biomes. The results suggest that the SNAP is generally effective to prevent deforestation within their protection boundaries. However, deforestation around protected areas can undermine conservation strategies to sustain biodiversity. Actions to address such dynamics and patterns of deforestation and forest fragmentation, and developing conservation strategies of their landscape context are urgently needed especially in the buffer zones of areas with the highest protection status.},
  language  = {en}
}
@article{RoeschPlank2022,
  author    = {R{\"o}sch, Moritz and Plank, Simon},
  title     = {Detailed mapping of lava and ash deposits at Indonesian volcanoes by means of VHR PlanetScope change detection},
  series = {Remote Sensing},
  volume    = {14},
  journal   = {Remote Sensing},
  number    = {5},
  issn      = {2072-4292},
  doi       = {10.3390/rs14051168},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-262232},
  year      = {2022},
  abstract  = {Mapping of lava flows in unvegetated areas of active volcanoes using optical satellite data is challenging due to spectral similarities of volcanic deposits and the surrounding background. Using very high-resolution PlanetScope data, this study introduces a novel object-oriented classification approach for mapping lava flows in both vegetated and unvegetated areas during several eruptive phases of three Indonesian volcanoes (Karangetang 2018/2019, Agung 2017, Krakatau 2018/2019). For this, change detection analysis based on PlanetScope imagery for mapping loss of vegetation due to volcanic activity (e.g., lava flows) is combined with the analysis of changes in texture and brightness, with hydrological runoff modelling and with analysis of thermal anomalies derived from Sentinel-2 or Landsat-8. Qualitative comparison of the mapped lava flows showed good agreement with multispectral false color time series (Sentinel-2 and Landsat-8). Reports of the Global Volcanism Program support the findings, indicating the developed lava mapping approach produces valuable results for monitoring volcanic hazards. Despite the lack of bands in infrared wavelengths, PlanetScope proves beneficial for the assessment of risk and near-real-time monitoring of active volcanoes due to its high spatial (3 m) and temporal resolution (mapping of all subaerial volcanoes on a daily basis).},
  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}
}
@article{LappeUllmannBachofer2022,
  author    = {Lappe, Ronja and Ullmann, Tobias and Bachofer, Felix},
  title     = {State of the Vietnamese coast — assessing three decades (1986 to 2021) of coastline dynamics using the Landsat archive},
  series = {Remote Sensing},
  volume    = {14},
  journal   = {Remote Sensing},
  number    = {10},
  issn      = {2072-4292},
  doi       = {10.3390/rs14102476},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-275281},
  year      = {2022},
  abstract  = {Vietnam's 3260 km coastline is densely populated, experiences rapid urban and economic growth, and faces at the same time a high risk of coastal hazards. Satellite archives provide a free and powerful opportunity for long-term area-wide monitoring of the coastal zone. This paper presents an automated analysis of coastline dynamics from 1986 to 2021 for Vietnam's entire coastal zone using the Landsat archive. The proposed method is implemented within the cloud-computing platform Google Earth Engine to only involve publicly and globally available datasets and tools. We generated annual coastline composites representing the mean-high water level and extracted sub-pixel coastlines. We further quantified coastline change rates along shore-perpendicular transects, revealing that half of Vietnam's coast did not experience significant change, while the remaining half is classified as erosional (27.7\%) and accretional (27.1\%). A hotspot analysis shows that coastal segments with the highest change rates are concentrated in the low-lying deltas of the Mekong River in the south and the Red River in the north. Hotspots with the highest accretion rates of up to +47 m/year are mainly associated with the construction of artificial coastlines, while hotspots with the highest erosion rates of -28 m/year may be related to natural sediment redistribution and human activity.},
  language  = {en}
}
@article{YangYaoLietal.2022,
  author    = {Yang, Xuting and Yao, Wanqiang and Li, Pengfei and Hu, Jinfei and Latifi, Hooman and Kang, Li and Wang, Ningjing and Zhang, Dingming},
  title     = {Changes of SOC content in China's Shendong coal mining area during 1990-2020 investigated using remote sensing techniques},
  series = {Sustainability},
  volume    = {14},
  journal   = {Sustainability},
  number    = {12},
  issn      = {2071-1050},
  doi       = {10.3390/su14127374},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-278939},
  year      = {2022},
  abstract  = {Coal mining, an important human activity, disturbs soil organic carbon (SOC) accumulation and decomposition, eventually affecting terrestrial carbon cycling and the sustainability of human society. However, changes of SOC content and their relation with influential factors in coal mining areas remained unclear. In the study, predictive models of SOC content were developed based on field sampling and Landsat images for different land-use types (grassland, forest, farmland, and bare land) of the largest coal mining area in China (i.e., Shendong). The established models were employed to estimate SOC content across the Shendong mining area during 1990-2020, followed by an investigation into the impacts of climate change and human disturbance on SOC content by a Geo-detector. Results showed that the models produced satisfactory results (R\(^2\) > 0.69, p < 0.05), demonstrating that SOC content over a large coal mining area can be effectively assessed using remote sensing techniques. Results revealed that average SOC content in the study area rose from 5.67 gC·kg\(^{-1}\) in 1990 to 9.23 gC·kg\(^{-1}\) in 2010 and then declined to 5.31 gC·Kg\(^{-1}\) in 2020. This could be attributed to the interaction between the disturbance of soil caused by coal mining and the improvement of eco-environment by land reclamation. Spatially, the SOC content of farmland was the highest, followed by grassland, and that of bare land was the lowest. SOC accumulation was inhibited by coal mining activities, with the effect of high-intensity mining being lower than that of moderate- and low-intensity mining activities. Land use was found to be the strongest individual influencing factor for SOC content changes, while the interaction between vegetation coverage and precipitation exerted the most significant influence on the variability of SOC content. Furthermore, the influence of mining intensity combined with precipitation was 10 times higher than that of mining intensity alone.},
  language  = {en}
}
@article{Hardaker2022,
  author    = {Hardaker, Sina},
  title     = {More Than Infrastructure Providers - Digital Platforms' Role and Power in Retail Digitalisation in Germany},
  series = {Tijdschrift voor Economische en Sociale Geografie},
  volume    = {113},
  journal   = {Tijdschrift voor Economische en Sociale Geografie},
  number    = {3},
  doi       = {10.1111/tesg.12511},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-287297},
  pages     = {310 -- 328},
  year      = {2022},
  abstract  = {Digital platforms, such as Amazon, represent the major beneficiaries of the Covid-19 crisis. This study examines the role of digital platforms and their engagement in digitalisation initiatives targeting (small) brick-and-mortar retailers in Germany, thereby contributing to a better understanding of how digital platforms augment, substitute or reorganise physical retail spaces. This study applies a mixed-method approach based on qualitative interviews, participant observation as well as media analysis. First, the study illustrates the controversial role of digital platforms by positioning themselves as supporting partners of the (offline) retailers, while simultaneously shifting power towards the platforms themselves. Second, digital platforms have established themselves not only as infrastructure providers but also as actors within these infrastructures, framing digital as well as physical retail spaces, inter alia due to their role as publicly legitimised retail advisers. Third, while institutions want to help retailers to survive, they simultaneously enhance retailers' dependency on digital platforms.},
  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{AyalaCarrilloFarfanCardenasNielsenetal.2022,
  author    = {Ayala-Carrillo, Mariana and Farf{\´a}n, Michelle and C{\´a}rdenas-Nielsen, Anah{\´i} and Lemoine-Rodr{\´i}guez, Richard},
  title     = {Are wildfires in the wildland-urban interface increasing temperatures? A land surface temperature assessment in a semi-arid Mexican city},
  series = {Land},
  volume    = {11},
  journal   = {Land},
  number    = {12},
  issn      = {2073-445X},
  doi       = {10.3390/land11122105},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-297308},
  year      = {2022},
  abstract  = {High rates of land conversion due to urbanization are causing fragmented and dispersed spatial patterns in the wildland-urban interface (WUI) worldwide. The occurrence of anthropogenic fires in the WUI represents an important environmental and social issue, threatening not only vegetated areas but also periurban inhabitants, as is the case in many Latin American cities. However, research has not focused on the dynamics of the local climate in the WUI. This study analyzes whether wildfires contribute to the increase in land surface temperature (LST) in the WUI of the metropolitan area of the city of Guanajuato (MACG), a semi-arid Mexican city. We estimated the pre- and post-fire LST for 2018-2021. Spatial clusters of high LST were detected using hot spot analysis and examined using ANOVA and Tukey's post-hoc statistical tests to assess whether LST is related to the spatial distribution of wildfires during our study period. Our results indicate that the areas where the wildfires occurred, and their surroundings, show higher LST. This has negative implications for the local ecosystem and human population, which lacks adequate infrastructure and services to cope with the effects of rising temperatures. This is the first study assessing the increase in LST caused by wildfires in a WUI zone in Mexico.},
  language  = {en}
}