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Relationships between soil respiration and photosynthesis-related spectral vegetation indices in two cropland ecosystems

文献类型： 外文期刊

作者： Huang, Ni 1 ; Niu, Zheng 1 ; Zhan, Yulin 1 ; Xu, Shiguang 1 ; Tappert, Michelle C. 3 ; Wu, Chaoyang 1 ; Huang, Wenjian 1 ;

作者机构： 1.Chinese Acad Sci, Inst Remote Sensing Applicat, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China

2.Chinese Acad Sci, Grad Sch, Beijing 100039, Peoples R China

3.Univ Alberta, Dept Earth & Atmospher Sci, Edmonton, AB T6G 2E3, Canada

4.Beijing Acad Agr & Forestry Sci, Natl Engn Res Ctr Informat Technol Agr, Beijing 100097, Peoples R China

关键词： agricultural land;agriculture;chlorophyll;crop production;ecology;ecosystems;indexes;leaf area;leaf area index;maize;meteorology;photosynthesis;plant ecology;reflectance;remote sensing;respiration;soil;soil chemistry.time series;variation;vegetation;wheat;winter;winter wheat;Triticum;Zea mays;Zea;Poaceae;Cyperales;monocotyledons;angiosperms;Spermatophyta;plants;eukaryotes;carbon assimilation;carbon dioxide fixation;corn;farmland;LAI

期刊名称：AGRICULTURAL AND FOREST METEOROLOGY （ 影响因子：5.734； 五年影响因子：5.964 ）

ISSN：

年卷期：

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收录情况： SCI

摘要： Empirical evidence for the link between vegetation photosynthesis and soil respiration (R-s) is reported for most ecosystems, but the quantification of photosynthesis parameters seldom use remote sensing data. In an attempt to clarify this issue, we focused on the growing season and examined direct relationships between R-s and photosynthesis-related vegetation indices (VIs) in maize and winter wheat agroecosystems. At seasonal time scale, crop biophysical parameters, such as leaf chlorophyll content (Chl(leaf)) and green leaf area index (GLAI), explained most R-s variation in the maize and winter wheat fields. Among the selected VIs, enhanced vegetation index (EVI) and red edge chlorophyll index (CIred edge) showed stronger correlations with Chl(leaf) for maize or GLAI for winter wheat than normalized difference vegetation index (NOVI). Moreover, for both fields, the relationship between daily mean R-s and either EVI or CIred edge was consistently stronger than the relationship between daily mean R-s and NDVI. The reason may be attributed to the saturate of NDVI at high vegetation densities and sensitivity of NDVI to background reflectance. Our results demonstrated that simple VIs (i.e. EVI and CIred edge) based entirely on remote-sensing data can provide better correlations with R-s than a number of variables which are more frequently correlated with R-s in field studies for both maize and winter wheat over the growing season. These results will be helpful for the development of future R-s model over a large spatial scale. (C) 2012 Elsevier B.V. All rights reserved.

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