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Against the background of the COVID-19 pandemic and various armed conflicts, the world is experiencing an unprecedented food crisis. The reclamation of abandoned cropland with food production potential may increase the global food supply in a short period of time, ensuring food security. At present, the extraction of abandoned cropland is mainly based on low- and medium-resolution remote sensing image data, making it difficult to extract fragmented areas in mountainous regions and to distinguish between abandoned cropland and transitional classes (such as fallow cropland). We developed a change-detection method based on within-year Sentinel-2 time series to extract cropland abandoned from 2018 to 2021 and defined four types of croplands, namely spontaneously abandoned, induced abandoned, fallow, and lost cropland, using Linxia County in mountainous China as the study region. First, cropland objects were generated from multi-temporal Sentinel-2 images using the multi-resolution segmentation method, and the land use map of Linxia County from 2017 to 2021 was drawn using random forest classifier. Second, through defining and identifying different cropland types, the interannual dynamic changes in cropland from 2018 to 2021 were extracted by analyzing the annual land use change trajectory. Third, by analyzing the normalized difference vegetation index (NDVI) time series of cropland within-year, the active and cultivated cropland sites within-year were extracted by threshold segmentation. Finally, the changes in the four cropland types were extracted by intersecting the two result types. Our method captured the object level changes well (overall mapping accuracy = 93 ± 5 %), and the extraction accuracy of abandoned cropland reached 81 ± 2 %. Abandoned cropland was mostly located in areas of medium quality and with a moderate distance from rural settlements. Reclamation can potentially increase the grain production in Linxia County by at least 3.6 % and needs to be combined with the local natural geography and human activities. Our method is a robust method for extracting abandoned cropland and may be applied to other research related to land use change., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2023 Elsevier B.V. All rights reserved.)

Improving soil health is necessary for increasing agricultural productivity and providing multiple ecosystem services. In the African Highlands (AH) where conversion of forests to cultivation on steep slopes is leading to soil degradation, sustainable land management practices are vital. Farmers' awareness of soil health indicators (SHI) influences their choice of land management and needs to be better understood to improve communication between land managers and other stakeholders in agricultural systems. This study aims to collate and evaluate case study analyses of farmers' awareness and use of soil health indicators in African Highlands. This is achieved by using a multi-method approach that combines a meta-summary analysis of AH's SHI data from 24 published studies together with farmer interviews in the East Usambara Mountain region of Tanzania (EUM). Our findings show that farmers across the AH use observable attributes of the landscape as SHI. Out of 16 SHI reported by the farmers, vegetation performance/crop yield and soil colour were most frequently used across the AH. These were also the only two SHI that influenced farmers' land management decisions in the EUM, where organic manure addition was the only land management option resulting from observed changes in SHI. Farmers' use of only one or two SHI in land management decisions, as is the case in the EUM, seems to limit their choice and/or adoption of sustainable land management options, highlighting the need to increase awareness and use of more relevant SHI. This could be achieved by sharing SHI knowledge through learning alliances and agricultural extension service. Integration of farmers' observation techniques and conventional soil testing in a hybrid approach is recommended for a more targeted assessment of soil health to inform appropriate and sustainable land management practices., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2021 The Authors.)

In recent years, forest fires have increased in terms of frequency, extent and intensity, especially in Mediterranean countries. Climate characteristics and anthropogenic disturbances lead forest environments to display high vulnerability to wildfires, with their sustainability being threatened by the loss of vegetation, changes on soil properties, and increased soil loss rates. Moreover, wildfires are a great threat to property and human life, especially in Wildland-Urban Interface (WUI) areas. In light of the impacts and trends mentioned above, this study aims to assess the impact of the Mati, Attika wildfire on soil erosion. The event caused 102 fatalities, inducing severe consequences to the local infrastructure network; economy; and natural resources. As such, the Revised Universal Soil Loss Equation (RUSLE) was implemented (pre-; post-fire) at the Rafina, Attika watershed encompassing the Mati WUI. Fire severity was evaluated based on the Normalized Burn Ratio (NBR). This index was developed utilizing innovative remotely sensed Earth Observation data (Sentinel-2). The high post-fire values indicate the fire's devastating effects on vegetation loss and soil erosion. A critical "update" was also made to the CORINE Land Cover (CLC) v. 2018, by introducing a new land use class namely "Urban Forest", in order to distinguish the WUI configuration. Post-fire erosion rates are notably higher throughout the study area (4.53-5.98 t ha -1  y -1 ), and especially within the WUI zone (3.75-18.58 t ha -1  y -1 ), while newly developed and highly vulnerable cites now occupy the greater Mati area. Furthermore, archive satellite data (Landsat-5) revealed how the repeated (historical) wildfires have ultimately impacted vegetation recovery and erosional processes. To our knowledge this is the first time that RUSLE is used to simulate soil erosion at a WUI after a fire event, at least at a Mediterranean basin. The realistic results attest that the model can perform well at such diverse conditions, providing a solid basis for soil loss estimation and identification of high-risk erosion areas., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2019 The Authors.)