The promptness of industrialisation and expanding urbanisation to achieve targets of economics are resulting in the transfiguration of permeable surfaces into impervious ones through LULC adaptation, leaving a herculean footprint on the ecosystem. The LULC escalates land surface temperature (LST), which further stimulates urban heat islands (UHIs), ultimately remaining in tune with high levels of air pollution, energy use, and corresponding health hazards. The present evaluation first used Landsat TM/OLI satellite data to identify the labyrinth of the LULC rotation and, secondly, gauged its effects on the LST in the Cachar district of Assam, India, for the years 1990, 2000, 2010, and 2020. It embraces Cellular Automata (CA) and GIS methodologies to pull out the urbanization pattern and its ramifications in various LULC brackets of Cachar, India. It also embraces spatiotemporal LULC monitoring (1990–2020) and urban growth modelling (2030–2040). From the period 1990 to 2020, satellite-based LULC showed a net urban expansion of 269.43 km² (7.13% increase). Some correlations were developed to show the relationship between spatial indices such as NDVI, NDBI, and NDWI with Land Surface Temperature (LST). Resultantly, a positive relation exists between LST and NDBI, but a negative correlation prevails between LST and NDVI, as well as NDWI. This evaluation will be of service to urban and environmental planners, providing them with detailed knowledge on how land cover is changing uniquely in northeast India.

Alluvial rivers all over the world have one common problem, which is their meandering pattern. This meander formation is because of natural and anthropogenic processes. Barak River is dynamic, and due to this, it is exposed to regular shifting and creates many problems for the people who reside near the river. The livelihood of many people depends on agriculture, which they conduct on the nearby sides of the river. However, the regular shifting of riverbanks makes their life miserable and leads to severe economic losses. Further, roadways and railways run along the banks of the Barak River, and during monsoon, Assam (Silchar), along with three states, Mizoram, Manipur, and Tripura, become disconnected from the rest of India because the road and rail connections fail due to riverbank erosion. Therefore, considering the catchment area and the importance of this river, we have tried to understand the spatiotemporal changes (erosion, deposition, and unchanged area) in the Barak River. From our analysis, we found that the maximum and minimum amount of erosion occurred from 2012–2017 and 2002–2012 and were 727.56 ha and 332.69 ha, respectively. While the highest amount of deposition that occurred during 1984–2017 was 1054.21 ha, the minimum amount of deposition that occurred during 2012–2017 was 351.32. Overall, it was identified that the area under the deposition was more dynamic than the erosion from 1984–2017. Moreover, from the temporal analysis of land use/land cover from 1984–2017, it was found that the area that comes under the settlement and arable land has increased by 10.47% and 5.05%, respectively. The dynamic factors, such as the nature of channel gradient, land use/land cover, and riparian vegetative cover, could be the probable driving forces that cause changes in the erosional and depositional areas. This study will help us understand the dynamics of the Barak River and other rivers of this type worldwide. This study shall help implement strategies that will help manage bank erosion by adapting scientific bank protection measures.

As we navigate the fast-paced era of urban expansion, the integration of machine learning (ML) and remote sensing (RS) has become a cornerstone in environmental management. This research, focusing on Silchar City, a non-attainment city under the National Clean Air Program (NCAP), leverages these advanced technologies to understand the urban microclimate and its implications on the health, resilience, and sustainability of the built environment. The rise in land surface temperature (LST) and changes in land use and land cover (LULC) have been identified as key contributors to thermal dynamics, particularly focusing on the development of urban heat islands (UHIs). The Urban Thermal Field Variance Index (UTFVI) can assess the influence of UHIs, which is considered a parameter for ecological quality assessment. This research examines the interlinkages among urban expansion, LST, and thermal dynamics in Silchar City due to a substantial rise in air temperature, poor air quality, and particulate matter PM_2.5. Using Landsat satellite imagery, LULC maps were derived for 2000, 2010, and 2020 by applying a supervised classification approach. LST was calculated by converting thermal band spectral radiance into brightness temperature. We utilized Cellular Automata (CA) and Artificial Neural Networks (ANNs) to project potential scenarios up to the year 2040. Over the two-decade period from 2000 to 2020, we observed a 21% expansion in built-up areas, primarily at the expense of vegetation and agricultural lands. This land transformation contributed to increased LST, with over 10% of the area exceeding 25 °C in 2020 compared with just 1% in 2000. The CA model predicts built-up areas will grow by an additional 26% by 2040, causing LST to rise by 4 °C. The UTFVI analysis reveals declining thermal comfort, with the worst affected zone projected to expand by 7 km². The increase in PM_2.5 and aerosol optical depth over the past two decades further indicates deteriorating air quality. This study underscores the potential of ML and RS in environmental management, providing valuable insights into urban expansion, thermal dynamics, and air quality that can guide policy formulation for sustainable urban planning.

In northeast India, Barak river is among one of the principal rivers, which is highly meandering in nature in its flood plain area. For infrastructural development and river protection works, it is essential to know the behavior of banklines shifting on landuse and landcover changes. This study is to evaluate the impact of bank lines shifting on land use and land cover changes. In order to fulfill the purpose of the present study 12 reaches with 41 cross-sections have been selected. The whole work has been done with the help of RS and GIS techniques using Landsat images and hybrid classification for the landuse and landcover classification. The result of the study shows that in the upper reach of the alluvial plain, there is an active shifting. Also, it is observed that at the lower reach, the river has moved in both north and south direction. It is observed that maximum migration rate is 130.2 m/year with a mean migration rate (9.43 m/year). The sinuosity estimated for the same reach with 12 bends is in the range 1.24–3.89. Among all the sections, the minimum and maximum changes of width are 0.26m and 249.93m respectively with an average value of 84.51m. It is found that the Barak river can be classified into sinuous channel (1.05 to 1.5), as well as meandering channel (>1.5). The investigation of changes in the pattern of land use land cover (LULC) of the Barak basin over 33 year’s period (1984–2017) shows that urban/built-up and agricultural land was increased gradually, e.g., urban increased by 40.6% for 1984–1992, 72.14% for 2002–2012, 180.15% for 1984–2017. While, agricultural land increased by 18.9% for 1984–1992, 41.15% for 1992–2002 and 93.20% for 1984–2017. In addition water bodies increased by 19% and 41.73% from 1984–1992 and 1984–2017 respectively. In contrast, dense vegetation decreased by 5.6% for 1984–1992 and 21.77% for 2002–2012 and 39.14% for 1984–2017. Open vegetation showed a decreasing trend by 11.1% for 1984–1992, 26.83% for 1992–2002, and 36.27% for 1984–2017. Rapid population growth, migration of rural people to urban, unawareness of biophysical limitations and poverty are some of the probable reasons behind the changes in the LULC. The results of the hybrid classification of the LULC of the Barak River for the Landsat 1(1984; MSS), Landsat 2 (1992; TM), Landsat 5 (2002; TM), Landsat 7(2012; ETM⁺) and Landsat 8(2017; OLI) showed overall classification accuracy of 90.83%, 86.67%, 90.56%, 93.33% and 86.11% with overall kappa statistics of 0.8900, 0.8400, 0.8867, 0.9200 and 0.8333 respectively. The channel migration directly affects the land use and land use change and has direct effect on the flood plain dwellers of the study area. All the assessments of this study highlight a significant message of immense vulnerability of the Barak river and also provide news about geomorpho-logical instabilities of the study area