Arid
DOI10.1145/3109761.3158394
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
EISBN978-1-4503-5243-7
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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