Comparative assessment of homogeneity differences in multi-temporal NDVI strata and the currently used agricultural area frames in Rwanda

Abstract

This study compared two methods used for agricultural statistics generation in Rwanda. The first method is area frame sampling, which is also the currently used method in Rwandan seasonal agricultural surveys; while the second method is the application of remote sensing technique using multi-temporal Normalised Difference Vegetation Index (NDVI) classes to stratify land into homogenous agriculture land classes. The analysis of the methodological flow of Rwanda area frames and the estimated homogeneity in the resulting frames was mainly based on literature review. For the delineation of homogeneous NDVI classes, the study used 10 years data from Moderate Resolution Imaging Spectroradiometer (MODIS) sensor (2004 – 2014). The NDVI data were classified using ISODATA clustering technique, and the focus was put on agriculture-dominated classes, obtained through the intersection with 2010 national land use and land cover data. Analysis of Variance (ANOVA) and Fisher’s Least Significant Difference (LSD) statistical methods were applied to investigate significant differences between and within NDVI classes and the currently used Rwanda strata in terms of area coverage of four (4) dominant crops in Rwanda – banana, maize, cassava, and beans. The results of the analysis revealed homogeneity of 85% within NDVI classes, and 69% within the current Rwanda strata, at p = 0.05. The NDVI classes were also used to improve the Rwanda strata, and the homogeneity has increased by 5%; reaching 74% after NDVI-based reclassification.