Lakshmibaur-Nalair Haor, a freshwater wetland ecosystem is situated in the north-eastern region of Bangladesh. This place hosts the second largest freshwater swamp forest in Bangladesh. Containing rich biodiversity, this unique area experiences significant landscape changes. This study examines land-use and land-cover (LULC) changes between 1989 and 2019 in the Lakshmibaur-Nalair Haor area by operating Landsat multispectral imageries through remote sensing (RS) and geographic information system (GIS) techniques. The changing status of the haor was analyzed by initiating normalized difference vegetation index (NDVI) and modified normalized difference water index (MNDWI). The unsupervised classification technique was implemented to classify these images into five major classes (vegetation, cropland, bare soil, shallow water, and deep water bodies) using threshold values of NDVI and MNDWI. After accuracy assessment, the post-classification comparison method was performed to evaluate the change detection. This study demonstrates that this valuable area lost ~ 2208.6 ha (37.54%) of the deep water body and 489.6 ha (8.34%) of vegetation over the last 3 decades. However, it has gained about 1729 ha (29.39%) of cropland, 2673 ha (45.44%) of shallow water and 1124 ha (28%) of bare soil. Such changes indicate significant human interventions such as expansion of croplands with increased population pressure. Gradual change of deep water into shallow water over time is enabling local community to expand agricultural lands and activities during the dry season. This study’s findings are useful in understanding and tracking changes in wetlands in Bangladesh and other similar settings.

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Soil erosion remains one of the main causes of land degradation, affecting many countries across the globe including South Africa. In rural communities with much reliance on agriculture, soil erosion is an important threat to food security. Therefore, mapping erosion-prone areas is an essential step towards adopting appropriate erosion mitigation and soil conservation measures. The objectives of this study were to (i) assess and model soil erosion vulnerability based on the Analytic Hierarchy Process (AHP) approach in Hoffenthal and KwaMaye communities within the uThukela Catchment, South Africa; and (ii) identify the relevant sustainable interventions and remedial strategies to combat soil erosion in the study area. The AHP was employed to map soil erosion vulnerability and derive the percentage weights of geo-environmental parameters contributing to soil erosion: rainfall, slope, drainage density, soil type, vegetation cover, and land use/land cover. The AHP model showed that slope, vegetation cover, and rainfall had the most considerable influence on soil erosion with factor weights of 29, 23, and 18%, respectively, in the study area. Further, this study revealed that high-risk soil erosion areas occupy 21% of the total study area, while very high-risk areas are about 14%, and the east and central areas are most vulnerable to soil erosion. Validation of the AHP model (overall accuracy = 85%; kappa coefficient = 0.70) results suggests that the predictive capacity of the model was satisfactory. Therefore, the developed soil erosion vulnerability model can serve as an important planning tool to prioritize areas for soil conservation and erosion management approaches like sustainable agriculture and bioengineering interventions.