Agricultural Yield Trends in Malawi: Utilizing Remote Sensing to Observe Crop Productivity and Sensitivity to Biophysical and Social Drivers

Abstract:

The primary objective of this research is to distinguish primary and secondary trends in the spatiotemporal variability of agricultural productivity in Malawi. The assessment was performed by analyzing the Net Primary Productivity (NPP) product derived from NASA MODIS satellite imagery and by drawing comparisons between individual land areas and the country-wide statistics. The data were categorized by placing each individual land area into one of six categories: low, average, or high productivity, and whether or not they were resilient or sensitive to biophysical and/or social production drivers. In order to mitigate productivity interference from forest and other land cover types, a custom agricultural land use was developed. Five land cover datasets, including FAO, GLC, IFPRI, GlobCover, and MODIS were combined to minimize errors of commission. Model assessment occurred via field work in Malawi. Approximately 200 sites were visited across nearly the entire extent of the country. Cropland and land cover were assessed via visual inspection, true color/near-infrared photography, and on-site interviews with farmers and extension officers to inquire about productivity and limiting factors for yield. Additionally, we present a continental scale application of the model to demonstrate its performance across scales.