The progress and potential directions in the remote sensing of farmland abandonment - Prishchepov, Alexander V.; Anders, Katharina; Feranec, Jan; Goga, Tomáš; Gradinaru, Simona R.; Kolář, Jan; Pazúr, Róbert; Potůčková, Markéta; Zagajewski, Bogdan; Kupková, Lucie (Remote sensing of environment, 2025)
The world is facing increasing land scarcity due to growing demand for agricultural products and urban expansion. At the same time, farmland abandonment is emerging as a widespread global land-use change phenomenon. Remote sensing plays a critical role in identifying abandonment across diverse farming systems. Here, we synthesized current knowledge through a systematic literature review of 131 publications to assess progress in remote-sensing-based monitoring of farmland abandonment. Our review highlights the growing use of remote sensing techniques and the increasing utility of multisource satellite data. However, research remains primarily skewed toward publicly available optical Landsat and Sentinel-2 data, with limited integration of other sources and a lack of global-scale assessments. We propose research directions to guide future studies, focusing on underrepresented land-use types, such as grasslands, terraces, and plantations, as well as regions like Africa, Central and Southeast Asia, and South America. We emphasize the importance of diversifying data sources and integrating ancillary information, including cadastral data and historical land-use records, to better understand abandonment processes and associated vegetation changes. We advocate for multi-scale, temporally explicit analyses to improve scalability and enable the development of regional and continental products. As most studies focus on biophysical changes, future work should also consider socio-economic contexts and integrate remote-sensing-based proxies of land-use change. Finally, we recommend improving communication by clearly defining abandonment, providing visual examples, validating with diverse reference data, documenting uncertainty, and sharing data, code, and outputs.