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

Pietro De Marinis, Samuele De Petris, Filippo Sarvia, Giacinto Manfron, Evelyn Joan Momo, Tommaso Orusa, Gianmarco Corvino, Guido Sali and Enrico Mondino Borgogno
Additional contact information
Pietro De Marinis: Department of Agricultural and Environmental Science, Production, Landscape and Agroenergy, University of Milan, 20133 Milano, Italy
Samuele De Petris: Department of Agriculture, Forest and Food Sciences, Torino University, 10124 Turin, Italy
Filippo Sarvia: Department of Agriculture, Forest and Food Sciences, Torino University, 10124 Turin, Italy
Giacinto Manfron: Department of Agricultural and Environmental Science, Production, Landscape and Agroenergy, University of Milan, 20133 Milano, Italy
Evelyn Joan Momo: Department of Agriculture, Forest and Food Sciences, Torino University, 10124 Turin, Italy
Tommaso Orusa: Department of Agriculture, Forest and Food Sciences, Torino University, 10124 Turin, Italy
Gianmarco Corvino: Department of Agriculture, Forest and Food Sciences, Torino University, 10124 Turin, Italy
Guido Sali: Department of Agricultural and Environmental Science, Production, Landscape and Agroenergy, University of Milan, 20133 Milano, Italy
Enrico Mondino Borgogno: Department of Agriculture, Forest and Food Sciences, Torino University, 10124 Turin, Italy

Land, 2021, vol. 10, issue 12, 1-22

Abstract: 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.

Keywords: eastern DRC; Masisi; agricultural production system; entropy analysis; Sentinel-2A; land use land cover (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://www.mdpi.com/2073-445X/10/12/1368/pdf (application/pdf)
https://www.mdpi.com/2073-445X/10/12/1368/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jlands:v:10:y:2021:i:12:p:1368-:d:700133

Access Statistics for this article

Land is currently edited by Ms. Carol Ma

More articles in Land from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().