Remote Sensing Letters · 2016 · 12 citations · 10 references
Natural ResourcesEarth SciencesForestryForest InventoryForest ManagementRemote SensingChange DetectionForest Change DetectionLand Cover Change DetectionRemote Sensing Change DetectionVegetation Change DetectionVegetation IndicesChange Detection From Multispectral ImageryChange Detection From Remote SensingChange Detection From Time SeriesForest Cover Change MappingForest MonitoringForest-cover ChangeReal-time MonitoringTemporal Land Cover Dynamics
Regarding to the deforestation and forest degradation issue in Indonesia, it is an urgent need to develop near real-time forest monitoring that can be seen by the public to make sure the transparency of forest resources management. Remote-sensing technology seems to be a powerful tool for monitoring and assessing the changes in forest cover immediately. We explored 250 m multi-temporal Moderate Resolution Imaging Spectroradiometer (MODIS) data sets to assign a change of temporal land surface dynamics based on two indices; normalized difference vegetation index (NDVI) and open area index (OAI). The data sets were filtered by two filtering approaches, median moving window and linear interpolation, in order to reduce the overall noise so as not to lose useful information from the time-series data. Our results indicated that the use of MODIS data as a basic information in the near real-time system offers great promise to detect the forest cover change in Indonesia’s forestland, since about 90.07% of area assigned to be a change area had actually changed. Meanwhile, about 34.97% of the forest cover change was not assigned to be a change area by the system. This result showed the need to evaluate the threshold in detecting forest cover change. Although the threshold issue is quite problematic in forest cover change detection, the results show that the methodology proposed in this study provides sufficient and useful information in forest monitoring; this includes the location, time and trajectories of the changes. The results of the detection system developed in this article will be available for potential users.
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Overview of the radiometric and biophysical performance of the MODIS vegetation indices
Alfredo Huete, Kamel Didan, Tomoaki Miura et al. · Remote Sensing of Environment · 2002 · 9.6K citations
Agriculture, Ecology, Geography +14
Joseph Knight, Ross S. Lunetta, Jayantha Ediriwickrema et al. · GIScience & Remote Sensing · 2006 · 179 citations · Full text
Natural Sciences, Earth Sciences, Landscape Change Detection +16