Remote Sensing Applications and Decision Support

Linear and segmented linear trend detection for vegetation cover using GIMMS normalized difference vegetation index data in semiarid regions of Nigeria

[+] Author Affiliations
Babatunde A. Osunmadewa, Christine Wessollek

Technische Universität Dresden, Institute of Photogrammetry and Remote Sensing, Helmholtzstraße 10, Dresden 01069, Germany

Pierre Karrasch

Technische Universität Dresden, Professorship of Geoinformation Systems, Helmholtzstraße 10, Dresden 01069, Germany

J. Appl. Remote Sens. 9(1), 096029 (Jul 08, 2015). doi:10.1117/1.JRS.9.096029
History: Received January 23, 2015; Accepted June 8, 2015
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Abstract.  Quantitative analysis of trends in vegetation cover, especially in Kogi state, Nigeria, where agriculture plays a major role in the region’s economy, is very important for detecting long-term changes in the phenological behavior of vegetation over time. This study employs the use of normalized difference vegetation index (NDVI) [global inventory modeling and mapping studies 3g (GIMMS)] data from 1983 to 2011 with detailed methodological and statistical approach for analyzing trends within the NDVI time series for four selected locations in Kogi state. Based on the results of a comprehensive study of seasonalities in the time series, the original signals are decomposed. Different linear regression models are applied and compared. In order to detect structural changes over time a detailed breakpoint analysis is performed. The quality of linear modeling is evaluated by means of statistical analyses of the residuals. Standard deviations of the regressions are between 0.015 and 0.021 with R2 of 0.22–0.64. Segmented linear regression modeling is performed for improvement and a decreasing standard deviation of 33%–40% (0.01–0.013) and R2 up to 0.82 are obtained. The approach used in this study demonstrates the added value of long-term time series analyses of vegetation cover for the assessment of agricultural and rural development in the Guinea savannah region of Kogi state, Nigeria.

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© 2015 Society of Photo-Optical Instrumentation Engineers

Topics

Modeling ; Vegetation

Citation

Babatunde A. Osunmadewa ; Christine Wessollek and Pierre Karrasch
"Linear and segmented linear trend detection for vegetation cover using GIMMS normalized difference vegetation index data in semiarid regions of Nigeria", J. Appl. Remote Sens. 9(1), 096029 (Jul 08, 2015). ; http://dx.doi.org/10.1117/1.JRS.9.096029


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