Clustering Methods to Asses Land Cover Samples of MODIS Vegetation Indexes Time Series
- 15 July 2017
- book chapter
- Published by Springer Nature
- p. 662-673
Abstract
No abstract availableKeywords
This publication has 12 references indexed in Scilit:
- Appropriate Learning Rate and Neighborhood Function of Self-organizing Map (SOM) for Specific Humidity Pattern Classification over Southern ThailandInternational Journal of Modeling and Optimization, 2016
- Self-organizing maps as an approach to exploring spatiotemporal diffusion patternsInternational Journal of Health Geographics, 2013
- Analyzing the agricultural transition in Mato Grosso, Brazil, using satellite-derived indicesApplied Geography, 2012
- Land cover classification from MODIS EVI times-series data using SOM neural networkInternational Journal of Remote Sensing, 2005
- Exact indexing of dynamic time warpingKnowledge and Information Systems, 2005
- Land cover characterization of Temperate East Asia using multi-temporal VEGETATION sensor dataRemote Sensing of Environment, 2004
- Sensitivity of vegetation indices to atmospheric aerosols: continental-scale observations in Northern AsiaRemote Sensing of Environment, 2003
- Overview of the radiometric and biophysical performance of the MODIS vegetation indicesRemote Sensing of Environment, 2002
- A comparison of vegetation indices over a global set of TM images for EOS-MODISRemote Sensing of Environment, 1997
- Information and Entropy in Cluster Analysis1994