Abstract
Since the outbreak of the Russia-Ukraine conflict in 2022, Ukraine has experienced different types of abandoned cropland, such as unused and unattended cropland, as a result of war damage, agricultural infrastructure destruction, and refugee outflows. Common methods for detecting abandoned cropland have difficulty effectively identifying and distinguishing these different types. This study proposes a Dual-period Change Detection method to reveal the spatial distribution and changes of different types of abandoned cropland in Ukraine, which can aid in agricultural assessments and international assistance in conflict-affected areas. The method mainly utilizes time-series NDVI data to fit the crop curves corresponding to cropland on a pixel-by-pixel basis, and then establishes discrimination rules for different types of abandoned cropland based on the crop curves, so as to detect unused cropland in the pre-conflict period (2015-2021) as well as unused cropland and unattended cropland in the post-conflict period (2022-2023). Finally, the detection results are validated and accuracy assessed using medium and high resolution spatiotemporal remote sensing imagery interpretation. The results show that the overall accuracy of the abandoned cropland extraction in Ukraine ranges from 83 to 96% during the study period. Before the conflict, the national average unused rate was 1.6%, with the lowest in 2021 and the highest in 2018. In 2022, the unused cropland area was approximately twice the average unused area before the conflict, and it was widely distributed, with the area of unattended cropland reaching 462,000 hectares, mainly in the eastern part of Ukraine. In 2023, compared to 2022, the unused cropland area decreased by 67.8%, while unattended cropland increased by 116.7%. Both types of abandoned cropland exhibited spatial clustering, with major clusters identified in the Crimea region, Kherson Oblast, Zaporizhzhia Oblast, and Donetsk Oblast.