TY - JOUR A1 - Weigand, Matthias A1 - Wurm, Michael A1 - Dech, Stefan A1 - Taubenböck, Hannes T1 - Remote sensing in environmental justice research—a review JF - ISPRS International Journal of Geo-Information N2 - Human health is known to be affected by the physical environment. Various environmental influences have been identified to benefit or challenge people's physical condition. Their heterogeneous distribution in space results in unequal burdens depending on the place of living. In addition, since societal groups tend to also show patterns of segregation, this leads to unequal exposures depending on social status. In this context, environmental justice research examines how certain social groups are more affected by such exposures. Yet, analyses of this per se spatial phenomenon are oftentimes criticized for using “essentially aspatial” data or methods which neglect local spatial patterns by aggregating environmental conditions over large areas. Recent technological and methodological developments in satellite remote sensing have proven to provide highly detailed information on environmental conditions. This narrative review therefore discusses known influences of the urban environment on human health and presents spatial data and applications for analyzing these influences. Furthermore, it is discussed how geographic data are used in general and in the interdisciplinary research field of environmental justice in particular. These considerations include the modifiable areal unit problem and ecological fallacy. In this review we argue that modern earth observation data can represent an important data source for research on environmental justice and health. Especially due to their high level of spatial detail and the provided large-area coverage, they allow for spatially continuous description of environmental characteristics. As a future perspective, ongoing earth observation missions, as well as processing architectures, ensure data availability and applicability of ’big earth data’ for future environmental justice analyses. KW - satellite remote sensing KW - review KW - environmental justice KW - big earth data KW - urban environments Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-196950 SN - 2220-9964 VL - 8 IS - 1 ER - TY - JOUR A1 - Philipp, Marius A1 - Dietz, Andreas A1 - Buchelt, Sebastian A1 - Kuenzer, Claudia T1 - Trends in satellite earth observation for permafrost related analyses — A review JF - Remote Sensing N2 - Climate change and associated Arctic amplification cause a degradation of permafrost which in turn has major implications for the environment. The potential turnover of frozen ground from a carbon sink to a carbon source, eroding coastlines, landslides, amplified surface deformation and endangerment of human infrastructure are some of the consequences connected with thawing permafrost. Satellite remote sensing is hereby a powerful tool to identify and monitor these features and processes on a spatially explicit, cheap, operational, long-term basis and up to circum-Arctic scale. By filtering after a selection of relevant keywords, a total of 325 articles from 30 international journals published during the last two decades were analyzed based on study location, spatio- temporal resolution of applied remote sensing data, platform, sensor combination and studied environmental focus for a comprehensive overview of past achievements, current efforts, together with future challenges and opportunities. The temporal development of publication frequency, utilized platforms/sensors and the addressed environmental topic is thereby highlighted. The total number of publications more than doubled since 2015. Distinct geographical study hot spots were revealed, while at the same time large portions of the continuous permafrost zone are still only sparsely covered by satellite remote sensing investigations. Moreover, studies related to Arctic greenhouse gas emissions in the context of permafrost degradation appear heavily underrepresented. New tools (e.g., Google Earth Engine (GEE)), methodologies (e.g., deep learning or data fusion etc.)and satellite data (e.g., the Methane Remote Sensing LiDAR Mission (Merlin) and the Sentinel-fleet)will thereby enable future studies to further investigate the distribution of permafrost, its thermal state and its implications on the environment such as thermokarst features and greenhouse gas emission rates on increasingly larger spatial and temporal scales. KW - satellite remote sensing KW - permafrost KW - degradation KW - thaw KW - thermokarst Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-234198 VL - 13 IS - 6 ER - TY - THES A1 - Kirschke, Stefanie T1 - Bilanzierung des Methanaustauschs zwischen Biosphäre und Atmosphäre in Periglazialräumen mit Hilfe von Fernerkundung und Modellen am Beispiel des Lena Deltas T1 - Balancing Methane Exchange between Biosphere and Atmosphere in Periglacial Regions Using Remote Sensing and Modeling: A Case Study for the Lena River Delta N2 - Verbleibende Unsicherheiten im Kohlenstoffhaushalt in Ökosystemen der hohen nördlichen Breiten können teilweise auf die Schwierigkeiten bei der Erfassung der räumlich und zeitlich hoch variablen Methanemissionsraten von Permafrostböden zurückgeführt werden. Methan ist ein global abundantes atmosphärisches Spurengas, welches signifikant zur Erwärmung der Atmosphäre beiträgt. Aufgrund der hohen Sensibilität des arktischen Bodenkohlenstoffreservoirs sowie der großen von Permafrost unterlagerten Landflächen sind arktische Gebiete am kritischsten von einem globalen Klimawandel betroffen. Diese Dissertation adressiert den Bedarf an Modellierungsansätzen für die Bestimmung der Quellstärke nordsibirischer permafrostbeeinflusster Ökosysteme der nassen polygonalen Tundra mit Hinblick auf die Methanemissionen auf regionalem Maßstab. Die Arbeit präsentiert eine methodische Struktur in welcher zwei prozessbasierte Modelle herangezogen werden, um die komplexen Wechselwirkungen zwischen den Kompartimenten Pedosphäre, Biosphäre und Atmosphäre, welche zu Methanemissionen aus Permafrostböden führen, zu erfassen. Es wird ein Upscaling der Gesamtmethanflüsse auf ein größeres, von Permafrost unterlagertes Untersuchungsgebiet auf Basis eines prozessbasierten Modells durchgeführt. Das prozessbasierte Vegetationsmodell Biosphere Energy Hydrology Transfer Model (BETHY/DLR) wird für die Berechnung der Nettoprimärproduktion (NPP) arktischer Tundravegetation herangezogen. Die NPP ist ein Maß für die Substratverfügbarkeit der Methanproduktion und daher ein wichtiger Eingangsparameter für das zweite Modell: Das prozessbasierte Methanemissionsmodell wird anschließend verwendet, um die Methanflüsse einer gegebenen Bodensäule explizit zu berechnen. Dabei werden die Prozesse der Methanogenese, Methanotrophie sowie drei verschiedene Transportmechanismen – molekulare Diffusion, Gasblasenbildung und pflanzengebundener Transport durch vaskuläre Pflanzen – berücksichtigt. Das Methanemissionsmodell ist für Permafrostbedingungen modifiziert, indem das tägliche Auftauen des Permafrostbodens in der kurzen arktischen Vegetationsperiode berücksichtigt wird. Der Modellantrieb besteht aus meteorologischen Datensätzen des European Center for Medium-Range Weather Forecasts (ECMWF). Die Eingangsdatensätze werden mit Hilfe von in situ Messdaten validiert. Zusätzliche Eingangsdaten für beide Modelle werden aus Fernerkundungsdaten abgeleitet, welche mit Feldspektralmessungen validiert werden. Eine modifizierte Landklassifikation auf der Basis von Landsat-7 Enhanced Thematic Mapper Plus (ETM+) Daten wird für die Ableitung von Informationen zu Feuchtgebietsverteilung und Vegetationsbedeckung herangezogen. Zeitserien der Auftautiefe werden zur Beschreibung des Auftauens bzw. Rückfrierens des Bodens verwendet. Diese Faktoren sind die Haupteinflussgrößen für die Modellierung von Methanemissionen aus permafrostbeeinflussten Tundraökosystemen. Die vorgestellten Modellergebnisse werden mittels Eddy-Kovarianz-Messungen der Methanflüsse validiert, welche während der Vegetationsperioden der Jahre 2003-2006 im südlichen Teil des Lena Deltas (72°N, 126°E) vom Alfred Wegener Institut für Polar- und Meeresforschung (AWI) durchgeführt wurden. Das Untersuchungsgebiet Lena Delta liegt an der Laptewsee in Nordostsibirien und ist durch Ökosysteme der arktischen nassen polygonalen Tundra sowie kalten kontinuierlichen Permafrost charakterisiert. Zeitlich integrierte Werte der modellierten Methanflüsse sowie der in situ Messungen zeigen gute Übereinstimmungen und weisen auf eine leichte Modellunterschätzung von etwa 10%. N2 - Remaining uncertainties in the carbon budget of high latitude ecosystems are partly due to difficulties in assessing methane emission rates from permafrost soils the source strengths of which are highly variable in space and time. Methane is a globally abundant atmospheric trace gas that contributes significantly to the warming of the atmosphere. Due to the high sensitivity of the arctic soil carbon reservoir and the large surface area underlain by permafrost, arctic regions are most critically influenced by a changing climate. This dissertation addresses the need for modelling approaches to determine the source strength of northern Siberian permafrost affected wet polygonal tundra ecosystems with regard to methane emission on the regional scale. It presents a methodical structure wherein two process-based models are used to capture the complex interrelated processes between pedosphere, biosphere and atmosphere that lead to methane emission from permafrost soils on the regional scale. Upscaling of methane fluxes for a larger permafrost site is performed using results of a process-based model. The process-based vegetation model Biosphere Energy Transfer Hydrology Model (BETHY/DLR) is applied to estimate net primary productivity (NPP) of arctic tundra vegetation. NPP is parameterized as a measure for substrate availability for methane production and thus an important input parameter for the second model: the process-based wetland methane emission model is subsequently used to explicitly model methane fluxes for a given soil column, taking into account methanogenesis, methane oxidation and three different transport mechanisms, namely molecular diffusion, ebullition and plant-mediated transport through vascular plants. The methane emission model is modified for permafrost conditions by explicitly considering daily thawing of permafrost during the short arctic growing season. Model forcing consists of meteorological data sets obtained from the European Center for Medium-Range Weather Forecasts (ECMWF). Input data sets are validated against field measurements. Auxiliary input data for both models are derived from satellite imagery and validated by field spectral measurements. A modified land use/land classification (LULC) scheme based on Landsat-7 Enhanced Thematic Mapper Plus (ETM+) data is used to derive information on wetland distribution and vegetation cover. Time series of active layer thickness are used to describe thawing/freezing of soils. These parameters are key factors in modelling methane emissions from permafrost influenced tundra ecosystems. Validation of presented model results is performed using eddy covariance measurements of methane flux on the landscape scale carried out during the growing seasons 2003-2006 in the southern part of the Lena Delta (72°N, 126°E) by Alfred Wegener Institute for Polar and Marine Research (AWI). The Lena Delta study site is located at the Laptev Sea in northeast Siberia and is characterized by arctic wet polygonal tundra ecosystems and cold continuous permafrost. Timeintegrated values for modelled methane fluxes and in situ measurements compare reasonably well and indicate a moderate model underestimation of about 10%. KW - Methanemission KW - Satellitenfernerkundung KW - Modellierung KW - Lenadelta KW - Treibhausgas KW - Tundra KW - Kohlenstoffkreislauf KW - methane emission KW - satellite remote sensing KW - modeling KW - Lena River Delta KW - carbon cycle Y1 - 2008 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-29024 ER -