Land use and land cover change assessment and future modeling of the Ken-Betwa River Link Project in India using machine learning | |
| Author | Ganapathi, Valivety Adithya Uma Kedara |
| Call Number | AIT RSPR no.RS-22-05 |
| Subject(s) | Land use--India--Remote sensing Land cover--India--Data processing Google Earth Machine learning |
| Note | A research submitted in partial fulfillment of the requirements for the degree of Master of Engineering in Remote Sensing and Geographic Information Systems |
| Publisher | Asian Institute of Technology |
| Abstract | India is a large country with a variety of water resources including lakes, natural water habitats, wetlands, several rivers, and their tributaries etc., which meet the country's year-round water needs. Among all these water systems, especially, Rivers add prominence when it comes to serving the direct hydrological needs in nook and corner of the country. In fact, only 4% of the world's useable water—needed to support 16% of the world's population—is available in India. Only the idea of River Linking can provide the better planning and channelization to meet this enormous need. Development of River linking projects like KBLP can alleviate the national scarcity of water by transferring the excessive waters of a particular river basin into other using a channel of linking canals. The KBLP is a one of its kind multi-purpose projects which is proposed to irrigate 9,04,000 Hectares along the command area which intersects with the India’s severely drought prone area of Bundelkhand region. Current rainfalls average at a rate of 785.44 mm/year which is 9% less while compared to the normal average of 863mm/year in this region. This research tried to map the agricultural patterns and the LULC change trends over a decade starting from 2011-2021 to understand and analyze how hydrological facilities are a top priority to benefit in these worsening conditions. With the help of Google Earth Engine based LULC classification of Landsat archives, it is evident that the region is struggling to maintain the vegetational equilibrium. The computed NDVI, EVI, MNDWI indices support the findings of the classification results. This gave a scope to develop a future scenario to simulate, observe and understand the very necessity of a project like KBLP which can give rise to an immense benefit in all socio-economic aspects. The prediction models revealed that central region of the study area towards the Mahoba district of Uttara Pradesh to be the most barren by the year 2032.These results support the Indian government’s decision in the most recent budget briefing in the month of February 2022 to complete the project within 8 years i.e., by 2030.The ministry of Jal shakti has been showing a great deal of effort to achieve the target. All these advancements make this research worthy enough and proves to the maximum; the innumerable utilization of this project plus enable the people of the region reap the benefits of this inter linking. |
| Year | 2022 |
| Type | Research Study Project Report (RSPR) |
| School | School of Engineering and Technology |
| Department | Department of Information and Communications Technologies (DICT) |
| Academic Program/FoS | Remote Sensing and Geographic Information Systems (RS) |
| Chairperson(s) | Tripathi, Nitin K.; |
| Examination Committee(s) | Shanmugam, Mohana Sundaram;Mozumder, Chitrini; |
| Scholarship Donor(s) | AIT Fellowship; |
| Degree | Research Studies Project Report (M.Eng.) - Asian Institute of Technology, 2022 |