Spatio-temporal Dynamics of Land Use Land Cover Changes and Future Prediction Using Geospatial Techniques

Land use land cover (LULC) plays a key role in earth surface processes, and it is important to understand the spatio-temporal dynamics of LULC in an area. The study is carried out in the Meenachil and Manimala basins in Kerala, India, using land change modeller (LCM) to predict future LULC. The Random Forest (RF) classifier is used to classify the LULC in Google Earth Engine (GEE) for the years 1990, 2000, 2008, 2018 and 2021. The overall accuracy obtained for the years 1990, 2000, 2008, 2018 and 2021 is 92.53%, 91.42%, 96.92%, 87.79% and 95.54%, respectively, followed by a Kappa coefficient of 90.67%, 89.27%, 96.12%, 84.55% and 94.39%. LCM is utilised for LULC change detection, the model is validated successfully in predicting the LULC distribution in 2021, and the results were compared with the actual 2021 LULC. The results revealed the expansion of the built-up area and the decline of the agriculture class in these basins. The study then utilised LCM to predict future LULC up to the year 2050 at decadal intervals. The predicted future LULC maps revealed the drastic expansion of built-up; these basins might witness in the coming decades. The built area from 1990 to 2050 is expected to increase to 100.88 km(2) and 60.75 km(2) in Meenachil and Manimala basins, respectively. The agriculture area showed a decrease from 861.7 to 728.29 km(2) in Meenachil and 743.5-676.89 km(2) in Manimala basin. The outcome of the study showed the transformation of the considered land cover classes due to developmental activities in the region. The outcomes of the study can be considered as suitable inputs to land use planners for effective land use planning and management.

Automated summary

This study utilizes land change modeling and random forest classification to analyze the spatio-temporal dynamics of land use and land cover in the Meenachil and Manimala basins in Kerala, India, and predicts future changes. The results show an expansion of built-up areas and a decline in agriculture. The outcomes of this study provide important insights for land use planning and management.