| Technology and Methodology |
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Comparative study of canopy spectral reflectance characteristics of spring wheat in irrigated land and dry land |
| JIN Yanhua1,3, XIONG Heigang2,3, ZHANG Fang1,3 |
1. College of Resources & Environment Science, Xinjiang University, Urumqi 830046, China;
2. College of Art & Science, Beijing United University, Beijing 100083, China;
3. Key Laboratory of Oasis Ecology, Ministry of Education, Urumqi 830046, China |
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Abstract Canopy data from hyperspectral remote sensing of irrigated land and dry land at different growth stages were used to analyze the difference between irrigated land and dry land. According to the bands of TM image,the measured spectrum was divided into four bands,the comparison of the spectra between irrigated land and dry land at each band was made and, on such a basis, the best band to identify irrigated land and dry land for spring wheat was chosen. The results show that canopy spectral reflectance in the visible region and in the near-infrared region of spring wheat has complete variation regularity: at the first band,the order is sunny land>double-sided land>shady land>irrigated land,which is opposite to the things of the near-infrared band. From setting to milk stage,in the visible band,spring wheat of irrigated land and dry land shows the order of setting stage>milk stage>jointing stage>heading stage>flowering stage; in the near-infrared band, the order is flowering stage>heading stage>jointing stage>setting stage>milk stage. The spectral curves are different because of chlorophyll content and coverage. In the visible band,spectral curves of spring wheat at setting and milk stage have their own lines but become two lines in the middle period; i.e.,sunny land and double-sided land are completely coincident with each other,whereas shady land and irrigated land are basically coincident with each other. The spectral range of 760~900 nm is the optimal band for identifying spring wheat in irrigated land and dry land.
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| Keywords
ground measured spectra
soil organic matter(SOM)
multiple regression analysis
fuzzy mathematics
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Issue Date: 01 July 2014
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2014,
Vol. 26
