Johannes Reiche
Associate Professor
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About
Johannes Reiche is an Associate Professor at Wageningen University & Research in the Netherlands. His research areas include remote sensing, forest monitoring, and environmental assessment, as evidenced by his recent publications on forest biomass mapping, tropical forest degradation, and the application of satellite data in understanding land use changes. He is actively involved in developing methodologies to enhance forest disturbance detection and improve the timeliness of environmental alerts.
Articles (17)
Critical Assessment of Cocoa Classification with Limited Reference Data: A Study in Côte d’Ivoire and Ghana Using Sentinel-2 and Random Forest Model
Cocoa is the economic backbone of Côte d’Ivoire and Ghana, making them the leading cocoa-producing countries in the world. However, cocoa farming has been a major driver of deforestation and landscape degradation in West Africa. Various stakeholders are striving for a zero-deforestation cocoa sector by implementing sustainable farming strategies and a more transparent supply chain. In the context of tracking cocoa sources and contributing to cocoa-driven deforestation monitoring, the demand for accurate and up-to-date maps of cocoa plantations is increasing. Yet, access to limited reference data and imperfect data quality can impose challenges in producing reliable maps. This study classified full-sun-cocoa-growing areas using limited reference data relative to the large and heterogeneous study areas in Côte d’Ivoire and Ghana. A Sentinel-2 composite image of 2021 was generated to train a random forest model. We undertook reference data refinement, selection of the most important handcrafted features and data sampling to ensure spatial independence. After refining the quality of the reference data and despite their size reduction, the random forest performance was improved, achieving an overall accuracy of 85.1 ± 2.0% and an F1 score of 84.6 ± 2.4% (mean ± one standard deviation from ten bootstrapping iterations). Emphasis was given to the qualitative visual assessment of the map using very high-resolution images, which revealed cases of strong and weak generalisation capacity of the random forest. Further insight was gained from the comparative analysis of our map with two previous cocoa classification studies. Implications of the use of cocoa maps for reporting were discussed.
Year:
2024
Collaborators (9)
Diego Marcos
Inria Centre de Recherche Sophia Antipolis Méditerranée
Marielos Peña-Claros
Professor at Wageningen University & Research
Wageningen University & Research
R. Valbuena
Bangor University
Xiaocheng Shang
University of Birmingham
Karimon Nesha
Wageningen University & Research
Jan Verbesselt
Wageningen University & Research
Casey Ryan
Senior Lecturer in Ecosystem Services and Global Change
University of Edinburgh
Krzysztof Stereńczak
profressor IBL
Instytut Matki i Dziecka
Martin Herold
Professor and section head
Helmholtz Centre Potsdam – GFZ German Research Centre for Geosciences

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