Supporting Pro-Poor Reforms of Agricultural Systems in Eastern DRC (Africa) with Remotely Sensed Data: A Possible Contribution of Spatial Entropy to Interpret Land Management Practices

In the eastern Democratic Republic of Congo, agriculture represents the most important economic sector, and land control can be considered a perpetual source of conflict. Knowledge of the existing production system distribution is fundamental for both informing national land tenure reforms and guiding more effective agricultural development interventions. The present paper focuses on existing agricultural production systems in Katoyi collectivity, Masisi territory, where returning Internally and Externally Displaced People are resettling. We aim to define a repeatable methodology for building evidence-based and updated knowledge concerning the spatial distribution of the two existing production systems: subsistence-oriented agriculture (SOA) and business-oriented agriculture (BOA). To this aim, we used a supervised object-based classification approach on remotely sensed Sentinel-2 imagery to classify land cover. To classify production systems further within the agriculture and pasture land use classes, binary classification based on an entropy value threshold was performed. An iterative approach was adopted to define the final H-NDVI threshold that minimised commission and omission errors and maximised overall accuracy and class separability. The methodology achieved acceptable observed accuracy (OA equal to 80-90% respectively for agricultural and pasture areas) in the assessment. SOA and BOA respectively covered 24.4 and 75.6% of the collectivity area (34,606 ha). The results conclude that land use and entropy analysis can draw an updated picture of existing land distribution among different production systems, supporting better-adapted intervention strategies in development cooperation and pro-poor agrarian land tenure reforms in conflict-ridden landscapes.

Automated summary

The study focuses on existing agricultural production systems in the eastern Democratic Republic of Congo, using remote sensing imagery and entropy analysis to investigate the spatial distribution of subsistence-oriented agriculture (SOA) and business-oriented agriculture (BOA) in the Katoyi collectivity of Masisi territory. The results show that land use and entropy analysis can provide updated information on existing land distribution among different production systems, supporting better intervention strategies in development cooperation and pro-poor agrarian land tenure reforms in conflict-ridden landscapes.