Temporal segmentation of MODIS time series for improving crop classification in Central Asian irrigation systems
By C. Conrad, R. Colditz, S. Dech, D. Klein, Paul L. G. Vlek. 2011
107 citations recorded by the source corpus.
Subfields: Atmospheric Science, Ecology, Global and Planetary Change
View Paper: https://www.semanticscholar.org/paper/7cd2dc61d66e233892b917d72eeea9f7947d07a1
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Citations in the corpus
- 3D Convolutional Neural Networks for Crop Classification with Multi-Temporal Remote Sensing Images (2018, methodology): “divided MODIS 250 m NDVI time series into several temporal segments, from which metrics were derived as input features for crop classification [7].”