Using remote sensing data to study anthropogenic land degradation in Khulna Division, Bangladesh for SDG indicator 15.3.1.

The Sustainable Development Goals (SDGs) include a goal on land degradation: indicator 15.3.1 (proportion of degraded land over total land). It is not always easy to monitor the SDGs, and remote sensing could be an effective tool for monitoring several SDGs. This study assessed land degradation in Bangladesh's Khulna Division over the past two decades. The Trends.Earth toolset was used to assess land degradation during the baseline period (2001-2015) and the reporting period (2016-2020). Inputs include data from the United Nations Convention on Desertification, and outputs include three sub-indicators: land productivity, land cover change, and soil organic carbon (SOC) stocks. Over the past 20 years, the land use and land cover, land productivity, and SOC content of the study area have undergone substantial changes. A significant change was observed in croplands, water bodies, and built-up areas. Croplands have been converted into settlements and tree cover. Nonetheless, there is an increase in land productivity in the area (>64 %) accompanied by a small percentage of decreasing productivity (approximately 9 %). Accordingly, the SOC in major land areas (84.68 %) is stable with 66,475 tons of carbon lost from croplands. Overall, this area reveals substantial progress in SDG indicator 15.3.1 with a clear transformation of degraded land (from 10.38 % to 8.46 %) into stable land (32.09 %-64.01 %). Land degradation is mostly seen in Khulna, Bagerhat, Satkhira, Kushtia, and Jashore areas. Land covers change for urbanisation, developments, water logging, and salinity intrusion cause land degradation. Despite poor representation of the SOC and normalised difference vegetation index datasets in the waterlogged areas, the Trends.Earth-generated results are informative and stand alone. With the results of this study, policymakers may be able to develop more appropriate land management plans by better understanding the complex interconnections of land change processes.