Refine
Has Fulltext
- yes (201)
Is part of the Bibliography
- yes (201)
Year of publication
Document Type
- Journal article (201) (remove)
Keywords
- remote sensing (30)
- climate change (14)
- time series (13)
- MODIS (12)
- Sentinel-2 (12)
- Google Earth Engine (9)
- machine learning (9)
- Landsat (8)
- earth observation (8)
- Germany (7)
- NDVI (7)
- SAR (7)
- Sentinel-1 (7)
- West Africa (7)
- drought (7)
- forest (7)
- permafrost (7)
- agriculture (6)
- deep learning (6)
- random forest (6)
- validation (6)
- Earth observation (5)
- TerraSAR-X (5)
- biodiversity (5)
- change detection (5)
- conservation (5)
- land use (5)
- review (5)
- winter wheat (5)
- Burkina Faso (4)
- Earth Observation (4)
- InSAR (4)
- RapidEye (4)
- South Africa (4)
- dynamics (4)
- geography (4)
- geomorphology (4)
- land cover (4)
- movement ecology (4)
- radar (4)
- time series analysis (4)
- AVHRR (3)
- Alps (3)
- Antarctica (3)
- Bavaria (3)
- PolSAR (3)
- Radarsat-2 (3)
- arctic (3)
- food security (3)
- hydrology (3)
- neural networks (3)
- phenology (3)
- protected areas (3)
- satellite data (3)
- schistosomiasis (3)
- surface water (3)
- tundra (3)
- water (3)
- AI (2)
- Antarctic ice sheet (2)
- CNN (2)
- CORDEX Africa (2)
- Cambrian (2)
- Central Asia (2)
- Europe (2)
- Geologie (2)
- Iran (2)
- Kilombero (2)
- LST (2)
- Landsat time series (2)
- LiDAR (2)
- Mekong (2)
- PlanetScope (2)
- TIMELINE (2)
- TanDEM-X (2)
- Tian Shan (2)
- UAV (2)
- Uzbekistan (2)
- West Gondwana (2)
- Western Cape (2)
- Western Europe (2)
- Zambia (2)
- artificial intelligence (2)
- atmospheric circulation (2)
- bias correction (2)
- biodiversity conservation (2)
- biomass (2)
- change vector analysis (2)
- circulation type (2)
- coastal erosion (2)
- coherence (2)
- convolutional neural network (2)
- convolutional neural networks (2)
- cropping systems (2)
- data fusion (2)
- decision-making (2)
- dual polarimetry (2)
- energy (2)
- evapotranspiration (2)
- flood (2)
- forecast (2)
- forest ecology (2)
- forest health (2)
- fusion (2)
- geoarchaeology (2)
- glaciers (2)
- global change (2)
- grazing (2)
- image segmentation (2)
- irrigation (2)
- land surface (2)
- land surface temperature (2)
- landsat (2)
- landscape metrics (2)
- locust outbreak (2)
- models (2)
- national parks (2)
- object detection (2)
- object-based classification (2)
- object-based image analysis (2)
- open spaces (2)
- optical (2)
- optical remote sensing (2)
- paleogeography (2)
- pasture (2)
- precision agriculture (2)
- probability (2)
- public health (2)
- random forest classification (2)
- renewable energy (2)
- rice (2)
- satellite (2)
- satellite remote sensing (2)
- sectoral planning (2)
- sedimentology (2)
- segmentation (2)
- semantic segmentation (2)
- sentinel-2 (2)
- supraglacial lakes (2)
- sustainable agriculture (2)
- synthetic aperture RADAR (2)
- synthetic aperture radar (2)
- time-series (2)
- trend analysis (2)
- variability (2)
- wetland (2)
- wind speed (2)
- (dis-)embeddedness (1)
- 3D (1)
- 3D GIS analysis (1)
- 3D remote sensing (1)
- 3‐D electrical resistivity imaging (1)
- ALOS (1)
- ALOS-2 (1)
- ASAR (1)
- ASCAT (1)
- AVHRR data (1)
- Accountability (1)
- Afghanistan (1)
- Africa (1)
- Africa south of the equator (1)
- Aggeneys (1)
- Agricultural soil science (1)
- Alento hydrological observatory (1)
- Alpen (1)
- Amu Darya (1)
- Anas crecca (1)
- Angola (1)
- Animal Tracking (1)
- Archaeology (1)
- Arctic (1)
- Asia (1)
- Atacama (1)
- Bavarian Forest (1)
- Bayern (1)
- Berchtesgaden (1)
- Berchtesgaden NP (1)
- Biostratigraphy (1)
- Blue Spot Analysis (1)
- Brazil (1)
- Broken Hill (1)
- Burma (1)
- COVID-19 (1)
- Canada (1)
- Chile (1)
- China (1)
- Clay mineralogy (1)
- Congo Basin (1)
- Coordinated Regional Climate Downscaling Experiment (CORDEX)-South Asia (1)
- Costa Rica (1)
- Covid‐19 (1)
- Côte d’Ivoire (1)
- DBH (1)
- DEM (1)
- DEUQUA (1)
- DSM (1)
- Deep learning (1)
- Digital platforms (1)
- Dociostaurus maroccanus (1)
- Dongting Lake (1)
- ENVISAT ASAR WSM (1)
- EO data (1)
- ERI (1)
- ERT (1)
- ESTARFM (1)
- ESTARFM framework (1)
- EVI (1)
- Ecosystem services (1)
- Einzelhandel (1)
- El Niño (1)
- Elissen-Palm flux (1)
- Envisat (1)
- Equipment (1)
- Erholungsplanung (1)
- Extreme flows (1)
- Eyjafjallajökull 2010 (1)
- FAIR (1)
- Fernerkundung (1)
- Flächenmonitoring (1)
- Forecasting (1)
- Fractional cover analysis (1)
- Freiraumstruktur (1)
- GCC (1)
- GEDI (1)
- GIS (1)
- GIS-analysis (1)
- GPS tracking (1)
- GPS-Tracking (1)
- GSV (1)
- Gamsberg (1)
- Getz Ice Shelf (1)
- Ghana (1)
- Gletscher (1)
- GlobALS (1)
- Global Ecosystem Dynamics Investigation (1)
- Google Earth (1)
- Google Earth Engine (GEE) (1)
- Graptolithoidea (1)
- Greenland (1)
- Greenland ice sheet (1)
- Heat Wave Magnitude Index (HWMI) (1)
- Herodotus (1)
- Himalaya Karakoram (1)
- Hunsrueck (1)
- Hyrcanian forest (1)
- IACS (1)
- InSAR height (1)
- Indus-Ganges-Brahmaputra-Meghna (1)
- Isheru (1)
- Kenya (1)
- Klima (1)
- Kunduz River Basin (1)
- LULCC (1)
- Land Change Modeler (1)
- Land Surface Temperature (1)
- Land Surface Temperature (LST) (1)
- Land Use/Land Cover (1)
- Land use monitoring (1)
- Landsat 8 (1)
- Landsat archive (1)
- Landsat-8 (1)
- Lantana camara (1)
- Lieberoser Heide (1)
- Limestone (1)
- Luxembourg (1)
- MOD13Q1 (1)
- MODIS image (1)
- MODIS time-series (1)
- Machine learning (1)
- Mann-Kendall test (1)
- Markov chains (1)
- Mato Grosso (1)
- Meat (1)
- Mediterranean environment (1)
- Mekong-Delta (1)
- Mesoarchaean (1)
- Modell (1)
- Morocco (1)
- Mozambique (1)
- Munigua (1)
- Myanmar (1)
- NDVI thresholds (1)
- Nachhaltigkeitstransformation (1)
- Namibia (1)
- Neolithic agriculture (1)
- Neolithic period (1)
- Neuronales Netz (1)
- Nile Delta (1)
- Nile Delta (Egypt) (1)
- Nile delta (1)
- Nile flow (1)
- Northern Bald Ibis (1)
- Northern Xinjiang (1)
- OCSVM (1)
- Oesling (1)
- Open spaces (1)
- Oshana (1)
- PEST (1)
- Pakistan (1)
- Paleopedology (1)
- Pamir (1)
- PhenoCam (1)
- Picea mariana (1)
- Platform economy (1)
- Pleistocene (1)
- Polanyi (1)
- Polarimetric Synthetic Aperture Radar (PolSAR) (1)
- Q. brantii (1)
- R (1)
- RADARSAT Constellation Mission (1)
- RADARSAT-2 (1)
- REMO-iMOVE (1)
- Ramsar Convention on Wetlands (1)
- Random Forests (1)
- Remote sensing (1)
- SAR backscatters (1)
- SAR imagery (1)
- SBAS (1)
- SDG 11.3.1 (1)
- SOC content prediction (1)
- SPOT-6 (1)
- SST (1)
- STARFM (1)
- SVM (1)
- SWAT (1)
- SWAT model (1)
- Sahel (1)
- Savannas (1)
- Scenario analysis (1)
- Sebennitic (1)
- Sediment (1)
- Sentine-1 (1)
- Sentinel-1 (S-1) synthetic aperture radar (SAR) (1)
- Sentinel-1 single-look complex data (1)
- Sentinel-2 multispectral indices (1)
- Sentinel–1 (1)
- Serengeti (1)
- Settlement and traffic area (1)
- Shannon entropy (1)
- Siedlungs-und Verkehrsfläche (1)
- Singhbhum Craton (1)
- Snow Line Elevation (1)
- Soil and Water Assessment Tool (SWAT) (1)
- South Indian Ocean (1)
- South-western Burkina Faso (1)
- Southeast Asia (1)
- Southeast China (1)
- Southern Annular Mode (1)
- Specimen grinding (1)
- Standardized Precipitation Evapotranspiration Index (SPEI) (1)
- Stratified scree (1)
- Stratigraphy (1)
- Struktur (1)
- Support vector machines (1)
- Surface Urban Heat Island (SUHI) (1)
- Switzerland (1)
- Synthetic Aperture Radar (SAR) (1)
- Syr Darya (1)
- Systematics (1)
- Sápmi (1)
- TIMESAT (1)
- TNPI (1)
- Tanzania (1)
- Tell Basta (1)
- Trees (1)
- Trilobita (1)
- U-Net (1)
- Urban sprawl (1)
- Vietnam (1)
- WSM (1)
- West African refugee crisis (1)
- West-Africa (1)
- World Heritage Sites (1)
- Zagros Forests (1)
- Zagros oak forests (1)
- Zersiedelung (1)
- abandoned land (1)
- abiotic formation (1)
- access (1)
- accessibility (1)
- accessibility analysis (1)
- accuracy (1)
- agricultural drought (1)
- agricultural irrigation (1)
- agricultural mapping (1)
- agricultural pests (1)
- agricultural productivity (1)
- agroforestry systems (1)
- air quality (1)
- algorithm (1)
- alpha diversity (1)
- amenity migration (1)
- ancient Egypt (1)
- ancillary data (1)
- animal ecology (1)
- animal movement (1)
- animal tracking (1)
- animation (1)
- anthroposphere (1)
- appliances (1)
- aquaculture (1)
- aral sea basin (1)
- archwires (1)
- arctic greening (1)
- arthropods (1)
- ash (1)
- atmosphere (1)
- atmospheric correction (1)
- atmospheric waves (1)
- automatic processing (1)
- bale mountains national park (1)
- band SAR data (1)
- base metal deposit (1)
- bats (1)
- benchmarking (1)
- beta diversity (1)
- bi-temporal (1)
- big data (1)
- big earth data (1)
- biocompatibility (1)
- biocrusts activity (1)
- biosphere (1)
- biostratigraphy (1)
- birds (1)
- birth hospitals (1)
- black carbon AOD (1)
- bohemian forest ecosystem (1)
- boreholes (1)
- breast cancer (1)
- buildings (1)
- burn severity (1)
- calibration and validation (1)
- calving front (1)
- cannons (1)
- canopy cover loss (1)
- canopy height (1)
- cardiovascular diseases (1)
- catchment (1)
- causal networks (1)
- central asia (1)
- circulation patterns (1)
- circulation type (CT) (1)
- circulation types (1)
- circum-Arctic (1)
- cities (1)
- class homogeneity (1)
- classifiaction (1)
- classification (1)
- climate (1)
- climate extremes (1)
- climate impact (1)
- climate models (1)
- climate parameters (1)
- climate related trends (1)
- climate scenarios (1)
- cloud (1)
- cloud gap filling (1)
- clustering (1)
- coal (1)
- coal fire (1)
- coal mining area (1)
- coastal zone (1)
- coastline (1)
- coastline dynamics (1)
- cocoa mapping (1)
- common teal (1)
- community (1)
- composition (1)
- conflicts (1)
- coniferous species (1)
- connectivity (1)
- consumptive water use (1)
- continous fields (1)
- coppice (1)
- crop growth models (1)
- crop identification (1)
- crop mapping (1)
- crop modeling (1)
- crop models (1)
- crop monitoring (1)
- crop statistics (1)
- cropland abandonment (1)
- cropland vegetation phenology (1)
- crown delineation (1)
- cryosphere (1)
- culturable command area (1)
- cutting events (1)
- damage assessment disaster (1)
- data acquisition (1)
- data pool (1)
- data science (1)
- data visualization (1)
- database (1)
- de-commodification (1)
- debris-covered glaciers (1)
- decadal predictability (1)
- decision making (1)
- decline (1)
- decomposition (1)
- deer cervus-eldi (1)
- deforestation (1)
- degradation (1)
- demographic change (1)
- dental casting alloys (1)
- dependence (1)
- derivatives (1)
- deseases (1)
- development policy (1)
- difference water index (1)
- digital agriculture (1)
- digitalisation initiative (1)
- digitalization (1)
- disaster (1)
- distributary (1)
- disturbance index (1)
- diurnal (1)
- drainage ratio (1)
- drilling (1)
- driving forces (1)
- drought impact (1)
- drought index (1)
- drought monitoring (1)
- dynamical downscaling (1)
- eCognition (1)
- earthquake (1)
- ecological connectivity (1)
- ecological relevant model (1)
- ecology (1)
- ecosystem (1)
- ecosystem functioning (1)
- ecosystem services (1)
- edge detection (1)
- electrical resistivity imaging (1)
- electrical resistivity tomography (1)
- electron probe microanalysis (1)
- elevation (1)
- emissivity (1)
- empirical quantile mapping (1)
- entrainment (1)
- environmental degradation (1)
- environmental health (1)
- environmental impact (1)
- environmental justice (1)
- environmental modeling (1)
- epidemic (1)
- epidemology (1)
- error estimation (1)
- eruption rate (1)
- evaluation (1)
- evidence-based policy (1)
- evidence‐based medicine (1)
- experimental archaeology (1)
- explosive volcanism (1)
- expolsions (1)
- exposure (1)
- e‐commerce (1)
- faulting (1)
- flood detection (1)
- flood hazard index (1)
- floodpath lake (1)
- fluoride (1)
- flux (1)
- food production (1)
- forest degradation (1)
- forest disturbances (1)
- forest ecosystem science (1)
- forest ecosystems (1)
- forest fragmentaion (1)
- forest monitoring (1)
- forest resources inventory (1)
- forest structure Germany (1)
- forests (1)
- fragmentation (1)
- framing (1)
- function (1)
- future prediction (1)
- fuzzy classification (1)
- galamsey (1)
- galvanic corrosion (1)
- gamma diversity (1)
- general circulation model (1)
- geoanalysis (1)
- geoarcheology (1)
- geoelectrical monitoring (1)
- geographic information science (1)
- geographical information system (1)
- geographically weighted regression (1)
- geomorphological mapping (1)
- geophysical prospection (1)
- geovisualization (1)
- gis (1)
- glacier front (1)
- glacier terminus (1)
- glacier–permafrost interaction (1)
- global (1)
- global warming (1)
- gold (1)
- grassland (1)
- gray level co-occurrence matrix (1)
- ground penetrating radar (1)
- groundwater (1)
- ground‐penetrating radar (1)
- growing season length (GSL) (1)
- habitat preferences (1)
- habitat use (1)
- habitats (1)
- harmonic analysis (1)
- harmonization (1)
- harvests (1)
- health care service research (1)
- heat transfer (1)
- heat wave (1)
- heat waves (1)
- heavy rainfall (1)
- high resolution population data (1)
- highland malaria (1)
- highlands (1)
- historical (1)
- hotspot analysis (1)
- hotspots (1)
- human disturbance (1)
- human pressure (1)
- hydrological drought (1)
- hydrological modelling (1)
- hydrological regime (1)
- ice sheet dynamics (1)
- ice sheet hydrology (1)
- image (1)
- image artifacts (1)
- impact (1)
- impervious surface (1)
- impervious surface areas (1)
- in situ forest monitoring (1)
- index analysis (1)
- indicator importance assessment (1)
- individual mobility (1)
- infrasound (1)
- insect monitoring (1)
- integration (1)
- intensity analysis (1)
- interactive vegetation (1)
- intercomparison (1)
- interferometry (1)
- intermediate host snail (1)
- interpolation (1)
- inundation (1)
- inverse parameterization (1)
- irrigated agriculture (1)
- irrigated cropland extent (1)
- irrigation pricing (1)
- issues (1)
- jet stream (1)
- jets (1)
- laboratory measurements (1)
- land (1)
- land and water management (1)
- land cover change (1)
- land surface dynamics (1)
- land surface phenology (1)
- land surface temperature (LST) (1)
- land use change (1)
- land use/cover pattern (LUCP) (1)
- land-atmosphere interaction (1)
- land-cover (1)
- land-cover change (1)
- land-cover classification (1)
- land-use/land-cover change (1)
- landcover changes (1)
- landsat central asia (1)
- large‐scale atmospheric circulation modes (1)
- lava (1)
- letzte Meile (1)
- life history (1)
- linear scaling (1)
- linear trend analysis (1)
- linked open data (1)
- locust habitat (1)
- locust monitoring (1)
- locust pest (1)
- loess plateau (1)
- logistic regression modeling (1)
- lokaler Onlinemarktplatz (1)
- loss (1)
- low-cost applications (1)
- lower reaches of Amu Darya River (1)
- major river basins (1)
- malaria (1)
- malaria model (1)
- malaria projection (1)
- management (1)
- management zones (1)
- mangrove ecosystems (1)
- mapping (1)
- mass (1)
- meadow (1)
- mekong delta (1)
- metallurgical characterization (1)
- metamorphic sulfidation (1)
- meteorological drought (1)
- methane emissions (1)
- methyl-bromide (1)
- mid-latitude cyclone (1)
- migration (1)
- mineralization (1)
- mineralogy (1)
- mining (1)
- model (1)
- model output statistics (1)
- modeling (1)
- modis (1)
- modis NDVI (1)
- moisture convergence (1)
- mono-temporal image (1)
- monsoon rainfall (1)
- morphology (1)
- mountain permafrost (1)
- mountain pines (1)
- mountains (1)
- movement data (1)
- mowing (1)
- multi scale heterogeneity (1)
- multi-sensor (1)
- multi-source forest health monitoring network (1)
- multi-spectral (1)
- multi-temporal images (1)
- multispectral VNIR (1)
- multispectral data (1)
- multitemporal ALOS/PALSAR imagery (1)
- multitemporal metrics (1)
- multivariate quantile delta mapping (1)
- multi‐model ensemble (1)
- nature conservation (1)
- near surface geophysics (1)
- near surface multidimensional geophysics (1)
- near-field monitoring (1)
- near-surface geophysics (1)
- near-surface soil moisture (1)
- networking (1)
- news media reporting (1)
- niche dynamics (1)
- nickel (1)
- nickel release (1)
- non-communicable disease (1)
- nu SVR (1)
- oil seed rape (1)
- oil spill (1)
- oil-seed rape (1)
- optical diversity (1)
- optimisation (1)
- optimization (1)
- orthodontic brackets (1)
- outdoor recreation (1)
- owner-operated retailers (1)
- paddy (1)
- paddy rice (1)
- palaeontology (1)
- paleoclimate (1)
- paleoenvironment (1)
- palsa development (1)
- pan (1)
- pandemic crisis (1)
- park–people relationships (1)
- partial correlation (1)
- partial least square regression (1)
- path analysis (1)
- peatland (1)
- penetration bias (1)
- percussion core probing (1)
- performance (1)
- performance assessment (1)
- permaforst mountain (1)
- permafrost hydrology (1)
- pilot-point-approach (1)
- pingos (1)
- pixel purity (1)
- pixel size (1)
- plant species richness (1)
- plantation (1)
- platform economy (1)
- plumes (1)
- polarimetery (1)
- polarimetric SAR (1)
- polarimetric decomposition (1)
- polarimetry (1)
- policy cycle (1)
- pollution (1)
- ponds (1)
- population (1)
- population change (1)
- population density (1)
- post-classification comparison (1)
- precipitation (1)
- preclinical research (1)
- predation risk (1)
- prediction (1)
- predictive modeling (1)
- preface (1)
- preventive medicine (1)
- productivity (1)
- products (1)
- protection status (1)
- pulsating explosive eruptions (1)
- quad polarimetry (1)
- quantitative remote sensing (1)
- quartz-pebble conglomerate (1)
- radar data (1)
- rainfall (1)
- rainfall response (1)
- random forest modeling (1)
- random forest models (1)
- random forest regression (1)
- rational model (1)
- regional climate model (1)
- regional climate model (RCM) (1)
- regional development (1)
- regional resilience (1)
- reintroduction (1)
- reliability (1)
- remote (1)
- remote sensing‐enabled essential biodiversity variables (1)
- reproductive disorders (1)
- research priorities (1)
- resilience (1)
- resolution (1)
- resource mapping (1)
- resource suitability (1)
- respiratory signs and symptoms (1)
- resurgence (1)
- retail (1)
- retrogressive thaw slump (1)
- rice mapping (1)
- ring-barking (1)
- risk (1)
- risk profiling (1)
- river discharge (1)
- rivers (1)
- road traffic (1)
- robust change vector analysis (1)
- runoff (1)
- rural tourism (1)
- sacred lakes (1)
- salt lakes (1)
- sar (1)
- satellite rainfall products (1)
- scPDSI (1)
- scale (1)
- scatterometer (1)
- scenario analysis (1)
- scenarios (1)
- science–policy interface (1)
- seasonal (1)
- seasonality (1)
- semantic web (1)
- semi-arid region (1)
- sensitivity analysis (1)
- sentinel (1)
- settlement expansion (1)
- settlement growth (1)
- shock waves (1)
- shorelines (1)
- simulation (1)
- size (1)
- slash-and-burn (1)
- slope bogs (1)
- slope deposits (1)
- snails (1)
- snow (1)
- snow cover (1)
- snow cover area (1)
- snow cover depletion (1)
- snow cover duration (1)
- snow hydrology (1)
- snow parameters (1)
- snow variability (1)
- snowmelt runoff model (1)
- soil and water conservation (1)
- soil erosion (1)
- soil matric potential (1)
- soil moisture (1)
- soil moisture retrieval (1)
- soil water content (1)
- soils/sediments (1)
- source parameters (1)
- southern annular mode (1)
- space-for-time approach (1)
- spatial analyses (1)
- spatial analysis (1)
- spatial behaviour (1)
- spatial error assessment (1)
- spatial modelling (1)
- spatial planning (1)
- spatial planning; sustainable development; cross-border coordination (1)
- spatial risk profiling (1)
- spatial scale (1)
- spatial scales (1)
- spatial water balance (1)
- spatio-temporal analysis (1)
- spatio-thematic coverage (1)
- spatiotemporal slump development (1)
- spatio‐temporal data (1)
- species (1)
- species distribution model (1)
- species distribution modeling (1)
- species richness (1)
- spectral diversity (1)
- spectral mixture analysis (1)
- spectral statistics (1)
- spectral variation hypothesis (1)
- spectroscopy (1)
- sport geography (1)
- spring flood (1)
- standardized precipitation index (1)
- statistical modeling (1)
- storage volume (1)
- stream flow (1)
- structure (1)
- study design (1)
- sub-pixel coastline extraction (1)
- sub-saharan africa (1)
- subpixel (1)
- subsidence (1)
- subsurface hydrology (1)
- subtropical Indian Ocean dipole (1)
- sulfide inclusions (1)
- summer precipitation regions (1)
- summer rainfall (1)
- support vector machines (1)
- surface analysis (1)
- surface melt (1)
- surface reflectances (1)
- surface urban heat island (SUHI) (1)
- surface water area (1)
- sustainable development (1)
- sustainable irrigation system (1)
- tasselled cap (1)
- teleconnection (1)
- temperate Europe (1)
- temperature (1)
- temperature measurement (1)
- temperatures (1)
- temporal statistics (1)
- terrain parameters (1)
- terrestrial LiDAR (1)
- textile sector (1)
- texture analysis (1)
- thaw (1)
- thermal infrared (1)
- thermal remote sensing (1)
- thermokarst (1)
- thrust moraine (1)
- tikhonov regularization (1)
- time geography (1)
- time-series features (1)
- titanium (1)
- topographic aspect (1)
- training sample migration (1)
- transferability (1)
- transmission (1)
- tree structure (1)
- trends (1)
- tropical North-Africa (1)
- tropical dry forest conservation (1)
- tropical forest (1)
- truck detection (1)
- turbulence (1)
- two‐sided markets (1)
- uncertainties (1)
- uncertainty (1)
- uneven-aged mountainous (1)
- urban (1)
- urban environments (1)
- urban growth modelling (1)
- urban modelling (1)
- urban vegetation (1)
- urbane Logistik (1)
- urbanization (1)
- use intensity (1)
- utilization distributions (1)
- vDEUQUA2021 (1)
- value of water (1)
- vegetation dynamics (1)
- vegetation indices (1)
- vegetation phenology (1)
- vegetation response (1)
- vegetation restoration (1)
- volcanic eruption (1)
- volcano (1)
- volcanoes (1)
- vulnerability (1)
- water balance (1)
- water dynamics (1)
- water management (1)
- water retention (1)
- water yield (1)
- watershed (1)
- wetland mapping (1)
- wheat-varieties (1)
- wildlife consumption (1)
- yield (1)
- z-score (1)
- zircon geochronology (1)
- Ökosystemleistungen (1)
Institute
- Institut für Geographie und Geologie (201) (remove)
EU-Project number / Contract (GA) number
- 308377 (2)
- 227159 (1)
- 243964 (1)
- 776019 (1)
- 818182 (1)
- 834709 (1)
- LIFE12 BIO/AT/000143 (1)
- LIFE20 NAT/AT/000049 (1)
Air pollution is associated with morbidity and mortality worldwide. We investigated the impact of improved air quality during the economic lockdown during the SARS-Cov2 pandemic on emergency room (ER) admissions in Germany. Weekly aggregated clinical data from 33 hospitals were collected in 2019 and 2020. Hourly concentrations of nitrogen and sulfur dioxide (NO2, SO2), carbon and nitrogen monoxide (CO, NO), ozone (O3) and particulate matter (PM10, PM2.5) measured by ground stations and meteorological data (ERA5) were selected from a 30 km radius around the corresponding ED. Mobility was assessed using aggregated cell phone data. A linear stepwise multiple regression model was used to predict ER admissions. The average weekly emergency numbers vary from 200 to over 1600 cases (total n = 2,216,217). The mean maximum decrease in caseload was 5 standard deviations. With the enforcement of the shutdown in March, the mobility index dropped by almost 40%. Of all air pollutants, NO2 has the strongest correlation with ER visits when averaged across all departments. Using a linear stepwise multiple regression model, 63% of the variation in ER visits is explained by the mobility index, but still 6% of the variation is explained by air quality and climate change.
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.
Nearly a quarter of the Alpine area is covered by a dense network of large protected areas (LPAs) of the four categories national park(NP), biosphere reserve (BR), nature park and world natural heritage site (WNHS). From the time of early industrialization, the Alpine area has undergone a mixed and increasingly polarized demographic development between the poles of immigration and emigration. This article investigates the possible mutual impact of population development and the existence of LPAs. The research design includes a quantitative survey of all Alpine LPAs in terms of their population development and the structure of immigration in the first decade of the 21st century. This will be linked with qualitative expert interviews in four selected NPs. The overall results allow an interpretation of the statistical
correlations between type of LPA and migration.
The fastest growing regional crisis is happening in West Africa today, with over 8 million people considered persons of concern. A culmination of identity politics, climate-driven disasters, and extreme poverty has led to this humanitarian crisis in the region and is exacerbated by a lack of political will and misplaced media attention. The current state of the art does not present sufficient investigations of the thematic and spatial coverage of news media of this crisis in this region. This paper studies the spatial coverage of this crisis as reported in the media, and the themes associated with those locations, based on a curated dataset. For the time frame 12 March to 15 September 2021, 2017 news articles related to the refugee crisis in West Africa were examined and manually coded based on (1) the geographical locations mentioned in each article; (2) the themes found in the articles in reference to a location (e.g., Relocation of people in Abuja). The dataset introduces a thematic dimension, as never achieved before, to the conflict-ridden areas in West Africa. A comparative analysis with UNHCR (United Nations High Commissioner for Refugees) data showed that 96.8% of refugee-related locations in West Africa were not covered by news during the considered time frame. Contrastingly, 80.4% of locations mentioned in the news do not appear in the UNHCR repository. Most news articles published during this time frame reported on Development aid or Political statements. Linear multiple regression analysis showed GDP per capita and political stability to be among the most influential determinants of news coverage.
A circum-Arctic monitoring framework for quantifying annual erosion rates of permafrost coasts
(2023)
This study demonstrates a circum-Arctic monitoring framework for quantifying annual change of permafrost-affected coasts at a spatial resolution of 10 m. Frequent cloud coverage and challenging lighting conditions, including polar night, limit the usability of optical data in Arctic regions. For this reason, Synthetic Aperture RADAR (SAR) data in the form of annual median and standard deviation (sd) Sentinel-1 (S1) backscatter images covering the months June–September for the years 2017–2021 were computed. Annual composites for the year 2020 were hereby utilized as input for the generation of a high-quality coastline product via a Deep Learning (DL) workflow, covering 161,600 km of the Arctic coastline. The previously computed annual S1 composites for the years 2017 and 2021 were employed as input data for the Change Vector Analysis (CVA)-based coastal change investigation. The generated DL coastline product served hereby as a reference. Maximum erosion rates of up to 67 m per year could be observed based on 400 m coastline segments. Overall highest average annual erosion can be reported for the United States (Alaska) with 0.75 m per year, followed by Russia with 0.62 m per year. Out of all seas covered in this study, the Beaufort Sea featured the overall strongest average annual coastal erosion of 1.12 m. Several quality layers are provided for both the DL coastline product and the CVA-based coastal change analysis to assess the applicability and accuracy of the output products. The predicted coastal change rates show good agreement with findings published in previous literature. The proposed methods and data may act as a valuable tool for future analysis of permafrost loss and carbon emissions in Arctic coastal environments.
Monitoring forest conditions is an essential task in the context of global climate change to preserve biodiversity, protect carbon sinks and foster future forest resilience. Severe impacts of heatwaves and droughts triggering cascading effects such as insect infestation are challenging the semi-natural forests in Germany. As a consequence of repeated drought years since 2018, large-scale canopy cover loss has occurred calling for an improved disturbance monitoring and assessment of forest structure conditions. The present study demonstrates the potential of complementary remote sensing sensors to generate wall-to-wall products of forest structure for Germany. The combination of high spatial and temporal resolution imagery from Sentinel-1 (Synthetic Aperture Radar, SAR) and Sentinel-2 (multispectral) with novel samples on forest structure from the Global Ecosystem Dynamics Investigation (GEDI, LiDAR, Light detection and ranging) enables the analysis of forest structure dynamics. Modeling the three-dimensional structure of forests from GEDI samples in machine learning models reveals the recent changes in German forests due to disturbances (e.g., canopy cover degradation, salvage logging). This first consistent data set on forest structure for Germany from 2017 to 2022 provides information of forest canopy height, forest canopy cover and forest biomass and allows estimating recent forest conditions at 10 m spatial resolution. The wall-to-wall maps of the forest structure support a better understanding of post-disturbance forest structure and forest resilience.
Satellite-derived land surface temperature dynamics in the context of global change — a review
(2023)
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.
The increasing availability and variety of global satellite products and the rapid development of new algorithms has provided great potential to generate a new level of data with different spatial, temporal, and spectral resolutions. However, the ability of these synthetic spatiotemporal datasets to accurately map and monitor our planet on a field or regional scale remains underexplored. This study aimed to support future research efforts in estimating crop yields by identifying the optimal spatial (10 m, 30 m, or 250 m) and temporal (8 or 16 days) resolutions on a regional scale. The current study explored and discussed the suitability of four different synthetic (Landsat (L)-MOD13Q1 (30 m, 8 and 16 days) and Sentinel-2 (S)-MOD13Q1 (10 m, 8 and 16 days)) and two real (MOD13Q1 (250 m, 8 and 16 days)) NDVI products combined separately to two widely used crop growth models (CGMs) (World Food Studies (WOFOST), and the semi-empiric Light Use Efficiency approach (LUE)) for winter wheat (WW) and oil seed rape (OSR) yield forecasts in Bavaria (70,550 km\(^2\)) for the year 2019. For WW and OSR, the synthetic products’ high spatial and temporal resolution resulted in higher yield accuracies using LUE and WOFOST. The observations of high temporal resolution (8-day) products of both S-MOD13Q1 and L-MOD13Q1 played a significant role in accurately measuring the yield of WW and OSR. For example, L- and S-MOD13Q1 resulted in an R\(^2\) = 0.82 and 0.85, RMSE = 5.46 and 5.01 dt/ha for WW, R\(^2\) = 0.89 and 0.82, and RMSE = 2.23 and 2.11 dt/ha for OSR using the LUE model, respectively. Similarly, for the 8- and 16-day products, the simple LUE model (R\(^2\) = 0.77 and relative RMSE (RRMSE) = 8.17%) required fewer input parameters to simulate crop yield and was highly accurate, reliable, and more precise than the complex WOFOST model (R\(^2\) = 0.66 and RRMSE = 11.35%) with higher input parameters. Conclusively, both S-MOD13Q1 and L-MOD13Q1, in combination with LUE, were more prominent for predicting crop yields on a regional scale than the 16-day products; however, L-MOD13Q1 was advantageous for generating and exploring the long-term yield time series due to the availability of Landsat data since 1982, with a maximum resolution of 30 m. In addition, this study recommended the further use of its findings for implementing and validating the long-term crop yield time series in different regions of the world.
Rapid and accurate yield estimates at both field and regional levels remain the goal of sustainable agriculture and food security. Hereby, the identification of consistent and reliable methodologies providing accurate yield predictions is one of the hot topics in agricultural research. This study investigated the relationship of spatiotemporal fusion modelling using STRAFM on crop yield prediction for winter wheat (WW) and oil-seed rape (OSR) using a semi-empirical light use efficiency (LUE) model for the Free State of Bavaria (70,550 km\(^2\)), Germany, from 2001 to 2019. A synthetic normalised difference vegetation index (NDVI) time series was generated and validated by fusing the high spatial resolution (30 m, 16 days) Landsat 5 Thematic Mapper (TM) (2001 to 2012), Landsat 7 Enhanced Thematic Mapper Plus (ETM+) (2012), and Landsat 8 Operational Land Imager (OLI) (2013 to 2019) with the coarse resolution of MOD13Q1 (250 m, 16 days) from 2001 to 2019. Except for some temporal periods (i.e., 2001, 2002, and 2012), the study obtained an R\(^2\) of more than 0.65 and a RMSE of less than 0.11, which proves that the Landsat 8 OLI fused products are of higher accuracy than the Landsat 5 TM products. Moreover, the accuracies of the NDVI fusion data have been found to correlate with the total number of available Landsat scenes every year (N), with a correlation coefficient (R) of +0.83 (between R\(^2\) of yearly synthetic NDVIs and N) and −0.84 (between RMSEs and N). For crop yield prediction, the synthetic NDVI time series and climate elements (such as minimum temperature, maximum temperature, relative humidity, evaporation, transpiration, and solar radiation) are inputted to the LUE model, resulting in an average R\(^2\) of 0.75 (WW) and 0.73 (OSR), and RMSEs of 4.33 dt/ha and 2.19 dt/ha. The yield prediction results prove the consistency and stability of the LUE model for yield estimation. Using the LUE model, accurate crop yield predictions were obtained for WW (R\(^2\) = 0.88) and OSR (R\(^2\) = 0.74). Lastly, the study observed a high positive correlation of R = 0.81 and R = 0.77 between the yearly R\(^2\) of synthetic accuracy and modelled yield accuracy for WW and OSR, respectively.
On a daily basis, political decisions are made, often with their full extent of impact being unclear. Not seldom, the decisions and policy measures implemented result in direct or indirect unintended negative impacts, such as on the natural environment, which can vary in time, space, nature, and severity. To achieve a more sustainable world with equitable societies requires fundamental rethinking of our policymaking. It calls for informed decision making and a monitoring of political impact for which evidence-based knowledge is necessary. The most powerful tool to derive objective and systematic spatial information and, thus, add to transparent decisions is remote sensing (RS). This review analyses how spaceborne RS is used by the scientific community to provide evidence for the policymaking process. We reviewed 194 scientific publications from 2015 to 2020 and analysed them based on general insights (e.g., study area) and RS application-related information (e.g., RS data and products). Further, we classified the studies according to their degree of science–policy integration by determining their engagement with the political field and their potential contribution towards four stages of the policy cycle: problem identification/knowledge building, policy formulation, policy implementation, and policy monitoring and evaluation. Except for four studies, we found that studies had not directly involved or informed the policy field or policymaking process. Most studies contributed to the stage problem identification/knowledge building, followed by ex post policy impact assessment. To strengthen the use of RS for policy-relevant studies, the concept of the policy cycle is used to showcase opportunities of RS application for the policymaking process. Topics gaining importance and future requirements of RS at the science–policy interface are identified. If tackled, RS can be a powerful complement to provide policy-relevant evidence to shed light on the impact of political decisions and thus help promote sustainable development from the core.
The positive phase of the subtropical Indian Ocean dipole (SIOD) is one of the climatic modes in the subtropical southern Indian Ocean that influences the austral summer inter-annual rainfall variability in parts of southern Africa. This paper examines austral summer rain-bearing circulation types (CTs) in Africa south of the equator that are related to the positive SIOD and the dynamics through which specific rainfall regions in southern Africa can be influenced by this relationship. Four austral summer rain-bearing CTs were obtained. Among the four CTs, the CT that featured (i) enhanced cyclonic activity in the southwest Indian Ocean; (ii) positive widespread rainfall anomaly in the southwest Indian Ocean; and (iii) low-level convergence of moisture fluxes from the tropical South Atlantic Ocean, tropical Indian Ocean, and the southwest Indian Ocean, over the south-central landmass of Africa, was found to be related to the positive SIOD climatic mode. The relationship also implies that positive SIOD can be expected to increase the amplitude and frequency of occurrence of the aforementioned CT. The linkage between the CT related to the positive SIOD and austral summer homogeneous regions of rainfall anomalies in Africa south of the equator showed that it is the principal CT that is related to the inter-annual rainfall variability of the south-central regions of Africa, where the SIOD is already known to significantly influence its rainfall variability. Hence, through the large-scale patterns of atmospheric circulation associated with the CT, the SIOD can influence the spatial distribution and intensity of rainfall over the preferred landmass through enhanced moisture convergence.
The July 2021 heavy rainfall episode in parts of Western Europe caused devastating floods, specifically in Germany. This study examines circulation types (CTs) linked to extreme precipitation in Germany. It was investigated if the classified CTs can highlight the anomaly in synoptic patterns that contributed to the unusual July 2021 heavy rainfall in Germany. The North Atlantic Oscillation was found to be the major climatic mode related to the seasonal and inter-annual variations of most of the classified CTs. On average, wet (dry) conditions in large parts of Germany can be linked to westerly (northerly) moisture fluxes. During spring and summer seasons, the mid-latitude cyclone when located over the North Sea disrupts onshore moisture transport from the North Atlantic Ocean by westerlies driven by the North Atlantic subtropical anticyclone. The CT found to have the highest probability of being associated with above-average rainfall in large part of Germany features (i) enhancement and northward track of the cyclonic system over the Mediterranean; (ii) northward track of the North Atlantic anticyclone, further displacing poleward, the mid-latitude cyclone over the North Sea, enabling band of westerly moisture fluxes to penetrate Germany; (iii) cyclonic system over the Baltic Sea coupled with northeast fluxes of moisture to Germany; (iv) and unstable atmospheric conditions over Germany. In 2021, a spike was detected in the amplitude and frequency of occurrence of the aforementioned wet CT suggesting that in addition to the nearly stationary cut-off low over central Europe, during the July flood episode, anomalies in the CT contributed to the heavy rainfall event.
The occurrence of a likely graptolite in lowest Wuliuan strata of the Franconian Forest almost certainly records the oldest known graptolithoid hemichordate in West Gondwana and possibly the oldest graptolite presently known. The fossil is a delicate, erect, apparently unbranched rhabdosome with narrow thecae tentatively assigned to the poorly known genus Ovetograptus of the Dithecodendridae. This report includes an overview of pre-Furongian graptolithoids with slight corrections on the stratigraphic position of earlier reported species.
New U–Pb age and Hf isotope data obtained on detrital zircon grains from Au- and U-bearing Archaean quartz-pebble conglomerates in the Singhbhum Craton, eastern India, specifically the Upper Iron Ore Group in the Badampahar Greenstone Belt and the Phuljhari Formation below the Dhanjori Group provide insights into the zircon provenance and maximum age of sediment deposition. The most concordant, least disturbed \(^{207}\)Pb/\(^{206}\)Pb ages cover the entire range of known magmatic and higher grade metamorphic events in the craton from 3.48 to 3.06 Ga and show a broad maximum between 3.38 and 3.18 Ga. This overlap is also mimicked by Lu–Hf isotope analyses, which returned a wide range in \(_{εHf}\)(t) values from + 6 to − 5, in agreement with the range known from zircon grains in igneous and metamorphic rocks in the Singhbhum Craton. A smaller but distinct age peak centred at 3.06 Ga corresponds to the age of the last major magmatic intrusive event, the emplacement of the Mayurbhanj Granite and associated gabbro, picrite and anorthosite. Thus, these intrusive rocks must form a basement rather than being intrusive into the studied conglomerates as previously interpreted. The corresponding detrital zircon grains all have a subchondritic Hf isotopic composition. The youngest reliable zircon ages of 3.03 Ga in the case of the basal Upper Iron Ore Group in the east of the craton and 3.00 Ga for the Phuljhari Formation set an upper limit on the age of conglomerate sedimentation. Previously published detrital zircon age data from similarly Au-bearing conglomerates in the Mahagiri Quartzite in the Upper Iron Ore Group in the south of the craton gave a somewhat younger maximum age of sedimentation of 2.91 Ga. There, the lower limit on sedimentation is given by an intrusive relationship with a c. 2.8 Ga granite. The time window thus defined for conglomerate deposition on the Singhbhum Craton is almost identical to the age span established for the, in places, Au- and U-rich conglomerates in the Kaapvaal Craton of South Africa: the 2.98–2.78 Ga Dominion Group and Witwatersrand Supergroup in South Africa. Since the recognition of first major concentration of gold on Earth’s surface by microbial activity having taken place at around 2.9 Ga, independent of the nature of the hinterland, the above similarity in age substantially increases the potential for discovering Witwatersrand-type gold and/or uranium deposits on the Singhbhum Craton. Further age constraints are needed there, however, to distinguish between supposedly less fertile (with respect to Au) > 2.9 Ga and more fertile < 2.9 Ga successions.
The effects of drought on tree mortality at forest stands are not completely understood. For assessing their water supply, knowledge of the small-scale distribution of soil moisture as well as its temporal changes is a key issue in an era of climate change. However, traditional methods like taking soil samples or installing data loggers solely collect parameters of a single point or of a small soil volume. Electrical resistivity tomography (ERT) is a suitable method for monitoring soil moisture changes and has rarely been used in forests. This method was applied at two forest sites in Bavaria, Germany to obtain high-resolution data of temporal soil moisture variations. Geoelectrical measurements (2D and 3D) were conducted at both sites over several years (2015–2018/2020) and compared with soil moisture data (matric potential or volumetric water content) for the monitoring plots. The greatest variations in resistivity values that highly correlate with soil moisture data were found in the main rooting zone. Using the ERT data, temporal trends could be tracked in several dimensions, such as the interannual increase in the depth of influence from drought events and their duration, as well as rising resistivity values going along with decreasing soil moisture. The results reveal that resistivity changes are a good proxy for seasonal and interannual soil moisture variations. Therefore, 2D- and 3D-ERT are recommended as comparatively non-laborious methods for small-spatial scale monitoring of soil moisture changes in the main rooting zone and the underlying subsurface of forested sites. Higher spatial and temporal resolution allows a better understanding of the water supply for trees, especially in times of drought.
A fuzzy classification scheme that results in physically interpretable meteorological patterns associated with rainfall generation is applied to classify homogeneous regions of boreal summer rainfall anomalies in Germany. Four leading homogeneous regions are classified, representing the western, southeastern, eastern, and northern/northwestern parts of Germany with some overlap in the central parts of Germany. Variations of the sea level pressure gradient across Europe, e.g., between the continental and maritime regions, is the major phenomenon that triggers the time development of the rainfall regions by modulating wind patterns and moisture advection. Two regional climate models (REMO and CCLM4) were used to investigate the capability of climate models to reproduce the observed summer rainfall regions. Both regional climate models (RCMs) were once driven by the ERA-Interim reanalysis and once by the MPI-ESM general circulation model (GCM). Overall, the RCMs exhibit good performance in terms of the regionalization of summer rainfall in Germany; though the goodness-of-match with the rainfall regions/patterns from observational data is low in some cases and the REMO model driven by MPI-ESM fails to reproduce the western homogeneous rainfall region. Under future climate change, virtually the same leading modes of summer rainfall occur, suggesting that the basic synoptic processes associated with the regional patterns remain the same over Germany. We have also assessed the added value of bias-correcting the MPI-ESM driven RCMs using a simple linear scaling approach. The bias correction does not significantly alter the identification of homogeneous rainfall regions and, hence, does not improve their goodness-of-match compared to the observed patterns, except for the one case where the original RCM output completely fails to reproduce the observed pattern. While the linear scaling method improves the basic statistics of precipitation, it does not improve the simulated meteorological patterns represented by the precipitation regimes.
Cocoa growing is one of the main activities in humid West Africa, which is mainly grown in pure stands. It is the main driver of deforestation and encroachment in protected areas. Cocoa agroforestry systems which have been promoted to mitigate deforestation, needs to be accurately delineated to support a valid monitoring system. Therefore, the aim of this research is to model the spatial distribution of uncertainties in the classification cocoa agroforestry. The study was carried out in Côte d’Ivoire, close to the Taï National Park. The analysis followed three steps (i) image classification based on texture parameters and vegetation indices from Sentinel-1 and -2 data respectively, to train a random forest algorithm. A classified map with the associated probability maps was generated. (ii) Shannon entropy was calculated from the probability maps, to get the error maps at different thresholds (0.2, 0.3, 0.4 and 0.5). Then, (iii) the generated error maps were analysed using a Geographically Weighted Regression model to check for spatial autocorrelation. From the results, a producer accuracy (0.88) and a user’s accuracy (0.91) were obtained. A small threshold value overestimates the classification error, while a larger threshold will underestimate it. The optimal value was found to be between 0.3 and 0.4. There was no evidence of spatial autocorrelation except for a smaller threshold (0.2). The approach differentiated cocoa from other landcover and detected encroachment in forest. Even though some information was lost in the process, the method is effective for mapping cocoa plantations in Côte d’Ivoire.
Performance assessment of CORDEX regional climate models in wind speed simulations over Zambia
(2023)
There is no single solution to cutting emissions, however, renewable energy projects that are backed by rigorous ex-ante assessments play an important role in these efforts. An inspection of literature reveals critical knowledge gaps in the understanding of future wind speed variability across Zambia, thus leading to major uncertainties in the understanding of renewable wind energy potential over the country. Several model performance metrics, both statistical and graphical were used in this study to examine the performance of CORDEX Africa Regional Climate Models (RCMs) in simulating wind speed across Zambia. Results indicate that wind speed is increasing at the rate of 0.006 m s\(^{−1}\) per year. RCA4-GFDL-ESM2M, RCA4-HadGEM2-ES, RCA4-IPSL-CM5A-MR, and RCA4-CSIRO-MK3.6.0 were found to correctly simulate wind speed increase with varying magnitudes on the Sen’s estimator of slope. All the models sufficiently reproduce the annual cycle of wind speed with a steady increase being observed from April reaching its peak around August/September and beginning to drop in October. Apart from RegCM4-MPI-ESM and RegCM4-HadGEM2, the performance of RCMs in simulating spatial wind speed patterns is generally good although they overestimate it by ~ 1 m s\(^{−1}\) in the western and southern provinces of the country. Model performance metrics indicate that with a correlation coefficient of 0.5, a root mean square error of 0.4 m s\(^{−1}\), an RSR value of 7.7 and a bias of 19.9%, RCA4-GFDL-ESM2M outperforms all other models followed by RCA4-HadGEM2, and RCA4-CM5A-MR respectively. These results, therefore, suggest that studies that use an ensemble of RCA4-GFDL-ESM2M, RCA4-HadGEM2, and RCA4-CM5A-MR would yield useful results for informing future renewable wind energy potential in Zambia.
Performance of a regional climate model with interactive vegetation (REMO-iMOVE) over Central Asia
(2022)
The current study evaluates the regional climate model REMO (v2015) and its new version REMO-iMOVE, including interactive vegetation and plant functional types (PFTs), over two Central Asian domains for the period of 2000–2015 at two different horizontal resolutions (0.44° and 0.11°). Various statistical metrices along with mean bias patterns for precipitation, temperature, and leaf area index have been used for the model evaluation. A better representation of the spatial pattern of precipitation is found at 0.11° resolution over most of Central Asia. Regarding the mean temperature, both model versions show a high level of agreement with the validation data, especially at the higher resolution. This also reduces the biases in maximum and minimum temperature. Generally, REMO-iMOVE shows an improvement regarding the temperature bias but produces a larger precipitation bias compared to the REMO conventional version with interannually static vegetation. Since the coupled version is capable to simulate the mean climate of Central Asia like its parent version, both can be used for impact studies and future projections. However, regarding the new vegetation scheme and its spatiotemporal representation exemplified by the leaf area index, REMO-iMOVE shows a clear advantage over REMO. This better simulation is caused by the implementation of more realistic and interactive vegetation and related atmospheric processes which consequently add value to the regional climate model.