Remote Sens. 2013, 5(12), 6513-6538; doi:10.3390/rs5126513
Combined Spatial and Temporal Effects of Environmental Controls on Long-Term Monthly NDVI in the Southern Africa Savanna
1
Agricultural and Biological Engineering Department, University of Florida, 287 Frazier Rogers Hall, P.O. Box 110570, Gainesville, FL 32611, USA
2
Projects and Rural Engineering Department, Public University of Navarre, Ed. Los Olivos, E-31006 Pamplona, Spain
3
Geography Department, University of Florida, 3141 Turlington Hall, P.O. Box 117330, Gainesville, FL 32611, USA
*
Author to whom correspondence should be addressed.
Received: 15 September 2013 / Revised: 10 October 2013 / Accepted: 28 October 2013 / Published: 3 December 2013
(This article belongs to the Special Issue Monitoring Global Vegetation with AVHRR NDVI3g Data (1981-2011))
Abstract
Deconstructing the drivers of large-scale vegetation change is critical to predicting and managing projected climate and land use changes that will affect regional vegetation cover in degraded or threated ecosystems. We investigate the shared dynamics of spatially variable vegetation across three large watersheds in the southern Africa savanna. Dynamic Factor Analysis (DFA), a multivariate time-series dimension reduction technique, was used to identify the most important physical drivers of regional vegetation change. We first evaluated the Advanced Very High Resolution Radiometer (AVHRR)- vs. the Moderate Resolution Imaging Spectroradiometer (MODIS)-based Normalized Difference Vegetation Index (NDVI) datasets across their overlapping period (2001–2010). NDVI follows a general pattern of cyclic seasonal variation, with distinct spatio-temporal patterns across physio-geographic regions. Both NDVI products produced similar DFA models, although MODIS was simulated better. Soil moisture and precipitation controlled NDVI for mean annual precipitation (MAP) < 750 mm, and above this, evaporation and mean temperature dominated. A second DFA with the full AVHRR (1982–2010) data found that for MAP < 750 mm, soil moisture and actual evapotranspiration control NDVI dynamics, followed by mean and maximum temperatures. Above 950 mm, actual evapotranspiration and precipitation dominate. The quantification of the combined spatio-temporal environmental drivers of NDVI expands our ability to understand landscape level changes in vegetation evaluated through remote sensing and improves the basis for the management of vulnerable regions, like the southern Africa savannas. View Full-TextKeywords:
dynamic factor analysis; time-series analysis; NDVI; land cover change; climate change; temperature; mean annual precipitation; soil moisture; potential evapotranspiration
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).
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MDPI and ACS Style
Campo-Bescós, M.A.; Muñoz-Carpena, R.; Southworth, J.; Zhu, L.; Waylen, P.R.; Bunting, E. Combined Spatial and Temporal Effects of Environmental Controls on Long-Term Monthly NDVI in the Southern Africa Savanna. Remote Sens. 2013, 5, 6513-6538.
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