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CLASSIFICATION OF CROPLANDS THROUGH FUSION OF OPTICAL AND SAR TIME SERIES DATA
Multi-temporal Data fusion Landsat 5 Radarsat-1 Machine learning Crop classification Paddy rice index
2016/11/24
Many satellite sensors including Landsat series have been extensively used for land cover classification. Studies have been conducted to mitigate classification problems associated with the use of sin...
ESTIMATING RELIABILITY OF DISTURBANCES IN SATELLITE TIME SERIES DATA BASED ON STATISTICAL ANALYSIS
Multi-temporal Anomaly Detection Change Detection Disturbance Detection Confidence Level Time Series
2016/7/27
Normally, the status of land cover is inherently dynamic and changing continuously on temporal scale. However, disturbances or abnormal changes of land cover — caused by such as forest fire, flood, de...
ENSO IMPACT ON THE VEGETATION IN MURRAY-DARLING BASIN:A SATELLITE MONITORING FROM 1998-2007 BASED ON SPOT/VEGETATION NDVI TIME SERIES DATA
ENSO SPOT/VEGETATION vegetation NDVI land use SOI
2016/1/3
The El Niflo Southern Oscillation (ENSO) phenomenon produces an important inter-annual variability of oceanic and atmospheric conditions with irregular periods and amplitudes in many regions of the wo...
Enhanced filtering of modis time series data for the analysis of desertification processes in northeast brazil
land cover change detection algorithms
2015/8/20
Long time series of satellite data provide key input for geographically explicit monitoring and modelling of the environmental
condition in the context of land use and land cover change (LUCC) analys...
VULNERABILITY OF VEGETATION IN PARTS OF HIMALAYAS AND DYNAMIC GLOBAL VEGETATION MODELLING (DGVM) – STUDY USING VNIR AND THERMAL RESPONSES OF MODIS TIME SERIES DATA
Multitemporal Global-Environmental-Databases Vegetation Temperature Modelling and Retrieval
2014/5/6
Vegetation responses to changing climate patterns need to be understood to devise adaptation strategy for a sustainable development, especially in the light of increasing climate related vulnerability...