Knowledge Resource Center for Ecological Environment in Arid Area
DOI | 10.1145/3109761.3158394 |
Every Drop Counts: Unleashing the prospective locations for Water Harvesting using Geospatial Analytics | |
Gupta, Aparana; Garg, Anshul; Rawat, Namrata; Chigurupati, Sandeep; Kumar, Dinesh U. | |
通讯作者 | Gupta, Aparana |
会议名称 | International Conference on Internet of Things and Machine Learning (IML) |
会议日期 | OCT 17-18, 2017 |
会议地点 | Liverpool, ENGLAND |
英文摘要 | Water is at the heart of 'Sustainable Development Goals (SDGs)'set by United Nations- with an objective to balance the three dimensions of sustainable development: Environment, Social and Economic - and is indirectly associated with the success of all the other Goals. But, with changing climatic patterns, untimely rains, prolonged dry spells, depleting ground water and drought making every drop of water extremely precious, the need of the hour is to gauge and work towards the major aspects of water harvesting- 'Catchment'. Water Harvesting must be a key element of any strategy to bring an end to India's perennial swings between drought and flood and to meet the following SDGs for sustained development. This study presents a structured and meticulous approach, wielding `Geospatial Analytics'to identify the prospective locations for Water Harvesting in arid and semi-arid parts of the country for sustainable development.This paper is structured as follows. Section 1 describes the background and motivation for this idea. Section 2 details out the objective. In section 3 we present the 'Literature Survey 'on the work that has already been carried out in this field. While section 4 discerns our area of study, Section 5 provides process flow starting from Data gathering, Data extraction,Data pre-processing, Model selection and Multi Criteria Decision Making (Model Application). In Section 6, we present and validate our experimental results achieved using the proposed methodology. Section 7 concludes our study followed by Section 8 on Recommendations for future enhancements and next steps. |
英文关键词 | Geospatial Analytics AHP Analytical Hierarchy Process LAND SAT-8 Digital Elevation Model Image Processing Rain Water Harvesting Water Tanks RWH optimum location selection GIS Sliding Window Algorithm Flood Fill Model Smart Water |
来源出版物 | PROCEEDINGS OF THE 1ST INTERNATIONAL CONFERENCE ON INTERNET OF THINGS AND MACHINE LEARNING (IML'17) |
出版年 | 2017 |
EISBN | 978-1-4503-5243-7 |
出版者 | ASSOC COMPUTING MACHINERY |
类型 | Proceedings Paper |
语种 | 英语 |
国家 | India |
收录类别 | CPCI-S |
WOS记录号 | WOS:000463548100046 |
WOS类目 | Computer Science, Artificial Intelligence ; Computer Science, Theory & Methods ; Engineering, Electrical & Electronic |
WOS研究方向 | Computer Science ; Engineering |
资源类型 | 会议论文 |
条目标识符 | http://119.78.100.177/qdio/handle/2XILL650/306871 |
作者单位 | Indian Inst Management, Bangalore, Karnataka, India |
推荐引用方式 GB/T 7714 | Gupta, Aparana,Garg, Anshul,Rawat, Namrata,et al. Every Drop Counts: Unleashing the prospective locations for Water Harvesting using Geospatial Analytics[C]:ASSOC COMPUTING MACHINERY,2017. |
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