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The main objective of the present study is to project the future scenario of land use/ land cover... more The main objective of the present study is to project the future scenario of land use/ land cover on the basis of their past pattern of change. Indus basin with its diverse physiography is an ideal study area. Remote sensing sources from Landsat (MSS), LISS-I and LISS-III (1985-2005), were used to assess the past land use at a scale of 1:250,000. A statistical driver-based model was used to simulate the land use scenarios for 2015 and 2025. The model output was validated by comparing the simulated maps with reference ones for 2005 and 2015. All the land use classes displayed an overall accuracy of 85-90% with the exception of the classes -built-up‖ and -wasteland‖.
Remote sensing (RS) offers an efficient and reliable means to map features on Earth. Crop type ma... more Remote sensing (RS) offers an efficient and reliable means to map features on Earth. Crop type mapping using RS at various temporal and spatial resolutions plays an important role spanning from environmental to economical. The main objective of the current study was to evaluate the significance of optical data in a multi-temporal crop type classification-based on very high spatial resolution and high spatial resolution imagery. With this aim, three images from WorldView-3 and Sentinel-2 were acquired over Coalville (UK) between April and July 2016. Three vegetation indices (VIs); the normalized difference vegetation index, the green normalized difference vegetation index and soil adjusted vegetation index were generated using red, green and near-infrared spectral bands; then a supervised classification was performed using ground reference data collected from field surveys, Random forest (RF) and decision tree (DT) classification algorithms. Accuracy assessment was undertaken by comparing the classified output with the reference data. An overall accuracy of 91% and κ coefficient of 0·90 were estimated using the combination of RF and DT classification algorithms. Therefore, it can be concluded that integrating very high-and high-resolution imagery with different VIs can be implemented effectively to produce large-scale crop maps even with a limited temporal-dataset.
Journal of Land and Rural Studies, 2015
Human society has been utilising the natural resources from the dawn of its civilisation in varyi... more Human society has been utilising the natural resources from the dawn of its civilisation in varying intensity to improve their living standard. Over the course of time, the extraction of the amenities required for such developmental purpose, affects the resource use pattern and access. This has resulted in a change in the existing land use practices in the region. Thus, socio-economic setting of any region and the land use are interlinked and affect each other. This article presents a new socio-economic index (SEI) to quantify the socioeconomic status of any river basin. UNDP's Human Development Index of 1990 has been used and modified to compute the index, in which various aspects of human life are considered and collected from National Survey Samples to reflect on the basin's land use scenario. Results of the analysis are presented on Narmada River basin as a case study.
The main objective of the present study is to project the future scenario of land use/ land cover... more The main objective of the present study is to project the future scenario of land use/ land cover on the basis of their past pattern of change. Indus basin with its diverse physiography is an ideal study area. Remote sensing sources from Landsat (MSS), LISS-I and LISS-III (1985-2005), were used to assess the past land use at a scale of 1:250,000. A statistical driver-based model was used to simulate the land use scenarios for 2015 and 2025. The model output was validated by comparing the simulated maps with reference ones for 2005 and 2015. All the land use classes displayed an overall accuracy of 85-90% with the exception of the classes -built-up‖ and -wasteland‖.
Remote sensing (RS) offers an efficient and reliable means to map features on Earth. Crop type ma... more Remote sensing (RS) offers an efficient and reliable means to map features on Earth. Crop type mapping using RS at various temporal and spatial resolutions plays an important role spanning from environmental to economical. The main objective of the current study was to evaluate the significance of optical data in a multi-temporal crop type classification-based on very high spatial resolution and high spatial resolution imagery. With this aim, three images from WorldView-3 and Sentinel-2 were acquired over Coalville (UK) between April and July 2016. Three vegetation indices (VIs); the normalized difference vegetation index, the green normalized difference vegetation index and soil adjusted vegetation index were generated using red, green and near-infrared spectral bands; then a supervised classification was performed using ground reference data collected from field surveys, Random forest (RF) and decision tree (DT) classification algorithms. Accuracy assessment was undertaken by comparing the classified output with the reference data. An overall accuracy of 91% and κ coefficient of 0·90 were estimated using the combination of RF and DT classification algorithms. Therefore, it can be concluded that integrating very high-and high-resolution imagery with different VIs can be implemented effectively to produce large-scale crop maps even with a limited temporal-dataset.
Journal of Land and Rural Studies, 2015
Human society has been utilising the natural resources from the dawn of its civilisation in varyi... more Human society has been utilising the natural resources from the dawn of its civilisation in varying intensity to improve their living standard. Over the course of time, the extraction of the amenities required for such developmental purpose, affects the resource use pattern and access. This has resulted in a change in the existing land use practices in the region. Thus, socio-economic setting of any region and the land use are interlinked and affect each other. This article presents a new socio-economic index (SEI) to quantify the socioeconomic status of any river basin. UNDP's Human Development Index of 1990 has been used and modified to compute the index, in which various aspects of human life are considered and collected from National Survey Samples to reflect on the basin's land use scenario. Results of the analysis are presented on Narmada River basin as a case study.