Search results for "multi-temporal images"

showing 1 items of 1 documents

Vegetation Types Mapping Using Multi-Temporal Landsat Images in the Google Earth Engine Platform

2021

Vegetation Types (VTs) are important managerial units, and their identification serves as essential tools for the conservation of land covers. Despite a long history of Earth observation applications to assess and monitor land covers, the quantitative detection of sparse VTs remains problematic, especially in arid and semiarid areas. This research aimed to identify appropriate multi-temporal datasets to improve the accuracy of VTs classification in a heterogeneous landscape in Central Zagros, Iran. To do so, first the Normalized Difference Vegetation Index (NDVI) temporal profile of each VT was identified in the study area for the period of 2018, 2019, and 2020. This data revealed strong se…

Earth observation010504 meteorology & atmospheric sciencesComputer scienceNDVIScienceQvegetation types classification04 agricultural and veterinary sciences15. Life on landTime optimal01 natural sciencesNormalized Difference Vegetation IndexRandom forestIdentification (information)Vegetation typesmachine learning040103 agronomy & agriculturevegetation types classification; multi-temporal images; machine learning; Google Earth Engine; NDVI0401 agriculture forestry and fisheriesGeneral Earth and Planetary SciencesGoogle Earth EngineCartographymulti-temporal images0105 earth and related environmental sciencesRemote Sensing
researchProduct