Temporal responses of NDVI to precipitation and temperature in the central Great Plains, USA
Authors: WANG, J.; RICH, P. M.; PRICE, K. P.
Source: International Journal of Remote Sensing, Volume 24, Number 11, 2003 , pp. 1-1(1)
Publisher: Taylor and Francis Ltd
Abstract:Normalized Difference Vegetation Index (NDVI) is generally recognized as a good indicator of terrestrial vegetation productivity. Understanding climatic influences, in particular precipitation and temperature, on NDVI enables prediction of productivity changes under different climatic scenarios. We examined temporal responses of remotely sensed NDVI to precipitation and temperature during a nine-year period (1989-97) in Kansas. Biweekly (every two weeks) and monthly precipitation data were derived from 410 weather stations and biweekly temperature data were derived from 17 weather stations inside and around the borders of Kansas. Biweekly and monthly climate maps were derived by interpolation. Biweekly growing season (March-October) NDVI values for Kansas were calculated using National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) NDVI images. Average growing season NDVI values were highly correlated with precipitation received during the current growing season and seven preceding months (15-month duration); biweekly NDVI values were correlated with precipitation received during 2-4 preceding biweekly periods; and response time of NDVI to a major precipitation event was typical 1-2 biweekly periods (2-4 weeks). Temperature was positively correlated with NDVI early and late in the growing season, and there was a weak negative correlation between temperature and NDVI in the mid growing season. Precipitation has the primary influence on NDVI and, by inference, on productivity. The relationship between precipitation and NDVI is strong and predictable when viewed at the appropriate spatial scale.
Document Type: Research Article
Affiliations: Department of Geography and Kansas Applied Remote Sensing Program, University of Kansas, Lawrence, KS 66045, USA
Publication date: 2003