Skip to main content

page search

Library Vegetation dynamics of Zimbabwe investigated using NOAA-AVHRR NDVI from 1982 to 2006: a principal component analysis

Vegetation dynamics of Zimbabwe investigated using NOAA-AVHRR NDVI from 1982 to 2006: a principal component analysis

Vegetation dynamics of Zimbabwe investigated using NOAA-AVHRR NDVI from 1982 to 2006: a principal component analysis

Resource information

Date of publication
December 2013
Resource Language
ISBN / Resource ID
AGRIS:US201400169053
Pages
6764-6779

The dominant modes of vegetation variability over Zimbabwe are investigated using principal component analysis (PCA) on National Oceanic and Atmospheric Administration Advanced Very High Resolution Radiometer (NOAA-AVHRR) normalized difference vegetation index (NDVI) monthly imagery from 1982 to 2006. Spectral analysis is also used to determine the periodicities of the component loadings. NDVI PCA-1 corresponds to the major vegetation types of Zimbabwe, and we demonstrated that grasslands and dry savannah have the strongest relationship with mean annual precipitation. Furthermore, the March–April loadings showed the highest correlation (r = 0.73) with mean annual precipitation. NDVI PCA-1 sheds some light on the land reform challenge in Zimbabwe. NDVI PCA-2 is highly correlated (r = 0.87) with the mean annual relative variability of the rainfall map indicating a southeast/north mode of anomalies associated with the convectional rainfall-bearing systems over Zimbabwe. NDVI PCA-2 is also highly correlated (r = 0.86) with precipitation PCA-2. NDVI PCA-3 shows a southeast/west mode and is highly correlated (r = 0.87) with precipitation PCA-3. A high correlation (r = 0.66) is also noted between NDVI PCA-4 and the elevation map. Spectral analysis of the PCA loadings revealed several periodicities corresponding to those found in tropical sea surface temperatures (SSTs).

Share on RLBI navigator
NO

Authors and Publishers

Author(s), editor(s), contributor(s)

Mberego, Seth
Sanga-Ngoie, Kazadi
Kobayashi, Shoko

Publisher(s)
Data Provider
Geographical focus