In this advanced training, participants learned how to acquire, use, and derive NDVI imagery from Landsat and MODIS. Weekly webinars included lectures, hands-on demonstrations of exercises, and written instructions on how to conduct the exercises. The exercises used QGIS, a cross-platform open source GIS application. Each session guided participants through the exercises.
Learn how to create NDVI imagery, time series, and anomaly maps using NASA data including:
Local, regional, state, federal, and international organizations interested in assessing vegetation condition using satellite imagery. Professional organizations in the public and private sectors engaged in environmental management and monitoring will be given preference over organizations focused primarily on research.
Wednesday, Feb. 10, 2016
An overview of NDVI and an introduction to QGIS.
Wednesday, Feb. 17, 2016
Acquiring a Landsat image and deriving NDVI from Landsat using QGIS.
Wednesday, Feb. 24, 2016
An overview of MODIS NDVI, a demonstration of the MODIS/NDVI Time Series Database from the Global Agriculture Monitoring (GLAM) Project, acquiring MODIS NDVI images, and how to create a time series from MODIS NDVI.
Wednesday, March 2, 2016
An overview of MODIS NDVI anomaly mapping, a demonstration of the GIMMS MODIS Agricultural Monitoring System, and how to create a MODIS NDVI anomaly map.
(2016). ARSET - Creating and Using Normalized Difference Vegetation Index (NDVI) from Satellite Imagery. NASA Applied Remote Sensing Training Program (ARSET). https://www.earthdata.nasa.gov/learn/trainings/creating-using-normalized-difference-vegetation-index-ndvi-from-satellite-imagery.