Arid
DOI10.1117/12.972306
Monitoring land cover dynamics in the Aral Sea region by remote sensing
Kozhoridze, Giorgi; Orlovsky, Leah; Orlovsky, Nikolai
通讯作者Kozhoridze, Giorgi
会议名称Conference on Earth Resources and Environmental Remote Sensing/GIS Applications III
会议日期SEP 24-26, 2012
会议地点Edinburgh, SCOTLAND
英文摘要

The Aral Sea ecological crisis resulted from the USSR government decision in 1960s to deploy agricultural project for cotton production in Central Asia. Consequently water flow in the Aral Sea decreased drastically due to the regulation of Amydarya and Syrdarya Rivers for irrigation purposes from 55-60 km(3) in 1950s to 43 km(3) in 1970s, 4 km(3) in 1980s and 9-10 km(3) in 2000s. Expert land cover classification approach gives the opportunity to use the unlimited variable for classification purposes. The band algebra (band5/band4 and Band4/Band3) and remote sensing indices (Normalized differential Salinity Index (NDSI), Salt Pan Index (SPI), Salt Index (SI), Normalized difference Vegetation Index (NDVI), Albedo, Crust Index) utilized for the land cover classification has shown satisfactory result with classification overall accuracy 86.9 % and kappa coefficient 0.85. Developed research algorithm and obtained results can support monitoring system, contingency planning development, and improvement of natural resources rational management.


英文关键词desertification land degradation Central Asia water and soil resources desert Landsat
来源出版物EARTH RESOURCES AND ENVIRONMENTAL REMOTE SENSING/GIS APPLICATIONS III
ISSN0277-786X
出版年2012
卷号8538
EISBN978-0-8194-9278-4
出版者SPIE-INT SOC OPTICAL ENGINEERING
类型Proceedings Paper
语种英语
国家Israel
收录类别CPCI-S
WOS记录号WOS:000313596200052
WOS类目Remote Sensing ; Optics
WOS研究方向Remote Sensing ; Optics
资源类型会议论文
条目标识符http://119.78.100.177/qdio/handle/2XILL650/300843
作者单位Ben Gurion Univ Negev, Jacob Blaustein Inst Desert Res, Dept Solar Energy & Environm Phys, IL-84990 Midreshet Ben Gurion, Israel
推荐引用方式
GB/T 7714
Kozhoridze, Giorgi,Orlovsky, Leah,Orlovsky, Nikolai. Monitoring land cover dynamics in the Aral Sea region by remote sensing[C]:SPIE-INT SOC OPTICAL ENGINEERING,2012.
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