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  • 标题:Segmentation and Classification of Land use Land Cover Change Detection Using Remotely Sensed Data for Coimbatore District, India
  • 本地全文:下载
  • 作者:Dr. K. Thanushkodi ; Y. Baby Kalpana ; M. Sharrath
  • 期刊名称:International Journal of Computer Science & Technology
  • 印刷版ISSN:2229-4333
  • 电子版ISSN:0976-8491
  • 出版年度:2012
  • 卷号:3
  • 期号:4
  • 页码:814-818
  • 语种:English
  • 出版社:Ayushmaan Technologies
  • 摘要:Land Use is clearly constrained by environmental factors like soil characteristics, climatic conditions, water sources and vegetation. Changes in Land Use and Land Cover is a dynamic process taking place on the earth surface, and the spatial distribution of the changes that have taken place over a period of time and space is of immense importance in many natural studies. Whether regional or local in scope, remote sensing offers a means of acquiring and presenting land cover data in timely manner. The environmental factors reflect the importance of land as a key and finite resource for most human activities including agriculture, industry, forestry, energy production, settlement, recreation and water sources and storage. Often improper land use is causing various forms of environmental humiliation. For sustainable utilization of the land ecosystems, it is essential to know the natural characteristics, extent and location, its quality, productivity, suitability and limitations of various land uses. Land use/Land cover change has become an important component in current strategies for managing natural resources and monitoring environmental changes. The advancement in the concept of vegetation of the spread and health of the world’s forest, grassland and agricultural resources has become an important priority. Viewing the earth from space is now crucial to the understanding of the influence of man’s activities on his natural resource base over time. Over past years, data from Earth sensing satellites (digital imagery) has become vital in mapping the Earth’s features and infrastructures, managing natural resources and studying environmental change.
  • 关键词:Digital Imagery;Remote Sensing;Forests;Climatic Conditions; LULC Classification;Environmental Factor
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