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REMOTE SENSING FOR LAND & RESOURCES    2001, Vol. 13 Issue (1) : 9-14     DOI: 10.6046/gtzyyg.2001.01.02
Technology Application |
REMOTE SENSING INVESTIGATION AND RESEARCH ON CONDITIONS OF WATER AND TEMPERATURE IN MOUNTAIN AREA NEAR SHIJIAZHUANG
LI Ming-song, WANG Huai-wu, XIE Ying-chun
China University of Geosciences, Wuhan 430074, China
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Abstract  

In this paper, the instantaneous temperature field was produced based on classifying of TM6 data using computer. The conditions of water and temperature were analyzed according to these maps. It was studied that relation between the instantaneous temperature and the conditions of water and temperature in Mountain Area. It was discussed that the formed mechanism of conditions of water and temperature and characteristic of water and temperature climate. The Mountain Area's zones of conditions water and temperature were divided. The ecological adaptability in zones of water and temperature conditions was evaluated after field survey. All of these supplied basis for fully utilization of water and temperature resources, optimizing natural environment, adjusting agriculture planting structure, promoting economic sustainable development.

Keywords  Polarimetric SAR      Fusion      Land cover mapping     
Issue Date: 02 August 2011
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XIE Chou
WAN Zi
XU Mao-Song
XIA Zhong-Sheng
ZHANG Feng-Li
ZHANG Xing-yan
ZHU Jang-mei
YANG Wei
YU Hong
LIU Yang-bo
Cite this article:   
XIE Chou,WAN Zi,XU Mao-Song, et al. REMOTE SENSING INVESTIGATION AND RESEARCH ON CONDITIONS OF WATER AND TEMPERATURE IN MOUNTAIN AREA NEAR SHIJIAZHUANG[J]. REMOTE SENSING FOR LAND & RESOURCES, 2001, 13(1): 9-14.
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https://www.gtzyyg.com/EN/10.6046/gtzyyg.2001.01.02     OR     https://www.gtzyyg.com/EN/Y2001/V13/I1/9


[1] 薛重生.地学遥感概论【M】.武汉:中国地质大学出版社,2000.

[2] 翁笃呜.小气候和农田小气候【M】.北京:农业出版社,1979.

[3] 北京大学遥感技术应用所.TM图像及其应用译文集【M】.北京:北京大学出版社,1989

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