Bare soil is a critical element in the urban landscape and plays an essential role in urban environments. Yet, the separation of bare soil and other land cover types using remote sensing techniques remains a significant challenge. There are several remote sensing-based spectral indices for barren detection, but their effectiveness varies depending on land cover patterns and climate conditions. Within this research, we introduced a modified bare soil index (MBI) using shortwave infrared (SWIR) and near-infrared (NIR) wavelengths derived from Landsat 8 (OLI—Operational Land Imager). The proposed bare soil index was tested in two different bare soil patterns in Thailand and Vietnam, where there are large areas of bare soil during the agricultural fallow period, obstructing the separation between bare soil and urban areas. Bare soil extracted from the MBI achieved higher overall accuracy of about 98% and a kappa coefficient over 0.96, compared to bare soil index (BSI), normalized different bare soil index (NDBaI), and dry bare soil index (DBSI). The results also revealed that MBI considerably contributes to the accuracy of land cover classification. We suggest using the MBI for bare soil detection in tropical climatic regions.

This study investigated the spatiotemporal dynamics of tropical deciduous forest including dry dipterocarp forest (DDF) and mixed deciduous forest (MDF) and its phenological changes in responses to El Niño and La Niña during 2001–2016. Based on time series of Normalized Difference Vegetation Index (NDVI) extracted from Moderate Resolution Imaging Spectroradiometer (MODIS), the start of growing season (SOS), the end of growing season (EOS), and length of growing season (LOS) were derived. In absence of climatic fluctuation, the SOS of DDF commonly started on 106 ± 7 DOY, delayed to 132 DOY in El Niño year (2010) and advanced to 87 DOY in La Niña year (2011). Thus, there was a delay of about 19 to 33 days in El Niño and an earlier onset of about 13 to 27 days in La Niña year. The SOS of MDF started almost same time as of DDF on the 107 ± 7 DOY during the neutral years and delayed to 127 DOY during El Niño, advanced to 92 DOY in La Niña year. The SOS of MDF was delayed by about 12 to 28 days in El Niño and was earlier about 8 to 22 days in La Niña. Corresponding to these shifts in SOS and LOS of both DDF and MDF were also induced by the El Niño–Southern Oscillation (ENSO).

Land use and land cover (LULC) in coastal areas is critical in shaping the ecological systems, regional economy, and livelihood of indigenous communities. This study analyzes LULC changes (LULCC) in Soc Trang Province, Vietnam Mekong Delta, from 2010 to 2020 and simulates future LULC for 2030 under four scenarios: natural growth (business as usual, BAU), climate change challenges, profit optimization, and adaptation strategies. Satellite-based LULC maps and geospatial datasets were integrated into a LULC simulation model based on a Markov Chain and Cellular Automata to predict LULC in 2030 under disparate scenarios. Simultaneously, this study also estimates economic values and ecosystem service values as proxies to evaluate benefits and trade-offs between the scenarios. The research findings reveal that the critical LULCC observed during 2010–2020 are transitions from triple rice crops to double rice crops, rice–shrimp to brackish aquaculture, and expansion of perennial plantations. These transitional trends will persist at a modest rate under the BAU scenario in 2030. The climate change challenge scenario will intervene up to 24.2% of the total area, with double rice crops reaching the most extensive area compared to other scenarios, about 106,047 ha. The profit optimization scenario will affect 16.03% of the total area, focusing on aquaculture expansion to the maximum shared proportion of 34% (approximately 57,000 ha). Adaptive solutions will emphasize reducing triple rice crops while expanding double rice crops and reviving rice–shrimp to different extents depending on development pathways. Economic evaluations show a growth trend across scenarios, with maximum returns under profit optimization. Yet, ecosystem service values notably highlight ecological trade-offs, raising concerns about balancing economic benefits and ecological trade-offs in land use planning. The research findings recommend a comprehensive and multitarget approach to land use planning that integrates ecosystem services into initial assessments to balance benefits and trade-offs in coastal areas commonly affected by LULCC. By adopting well-informed and strategic land use plans that minimize ecological and social impacts, local sustainability and resilience to climate change can be significantly enhanced.

Background: Climate change, socioeconomic, market demands and labor restructuring have led to the need for agricultural restructuring in coastal areas in Vietnam. This study was conducted to assess the factors affecting agricultural production and analyze land use scenarios to support the agricultural transformation in the coastal area of the Vietnamese Mekong Delta. Methods: The implementation method is based on surveying the necessary dynamic level of socioeconomic and environmental factors affecting land use; the connection between the land area optimization using linear programming and the CLUMondo. Result: The results proposed 3 scenarios to improve the efficiency of state land management for socioeconomic development and agricultural restructuring in the study area. Scenario 1 (the land-allocated results were similar to the land use map) and scenario 2 (extensive shrimp farming areas in the coastal zone will be firmly converted to intensive shrimp farming) are suitable for the district in the short term. However, Scenario 3 (the shrimp-rice area tends to convert to rice land, while agricultural land near the town will be firmly converted to non-agricultural land) is the most appropriate option when funds are available for high technology advancement.