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Remote sensing analysis of surface t...
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Jensen, Aaron D.
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Remote sensing analysis of surface temperature and landscape feature dynamics.
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Remote sensing analysis of surface temperature and landscape feature dynamics./
作者:
Jensen, Aaron D.
面頁冊數:
119 p.
附註:
Source: Masters Abstracts International, Volume: 46-02, page: 0897.
Contained By:
Masters Abstracts International46-02.
標題:
Remote Sensing. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1446684
ISBN:
9780549189985
Remote sensing analysis of surface temperature and landscape feature dynamics.
Jensen, Aaron D.
Remote sensing analysis of surface temperature and landscape feature dynamics.
- 119 p.
Source: Masters Abstracts International, Volume: 46-02, page: 0897.
Thesis (M.A.)--University of Arkansas, 2007.
Urbanization is a dominant feature of the modern landscape. The resulting changes to natural areas can lead to modification of climatic processes. The modified climate may enhance the formation of the urban heat island, a phenomenon in which urban temperatures are warmer than surrounding rural areas.
ISBN: 9780549189985Subjects--Topical Terms:
1018559
Remote Sensing.
Remote sensing analysis of surface temperature and landscape feature dynamics.
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Urbanization is a dominant feature of the modern landscape. The resulting changes to natural areas can lead to modification of climatic processes. The modified climate may enhance the formation of the urban heat island, a phenomenon in which urban temperatures are warmer than surrounding rural areas.
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This research focused on the dynamics of remote sensing-based surface urban heat island investigations, including the relationships of scale, surface feature classes and surface temperatures. Landsat Thematic Mapper data were used for land cover mapping and estimating surface temperatures. Land cover data included classes for sub-pixel percent impervious surfaces and NDVI-measured vegetation abundance for forest and pasture classes. These data were aggregated from 30m to scales including 90m, 150m, 270m and 450m, and then analyzed for relationships with surface temperature. A secondary statistical analysis was performed to establish the relationships between impervious surfaces, vegetation and surface temperatures, including an assessment of scale impacts.
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It was determined that feature class scale delineation has some impact on both the mean and variability in surface temperatures. Impervious surfaces were shown to have a strong positive relationship with surface temperatures. However, temperature variability tends to increase as the sub-pixel percent impervious surface area increases. NDVI-measured vegetation was shown to have a strong negative relationship with surface temperatures.
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The greater understanding of these relationships helps to more clearly define the fundamental components of surface urban heat island research and enhances our ability to analyze urban thermal patterns. The knowledge of these patterns can assist in improved urban planning and assessment of the impact of development.
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