Using multiple radiometric correction images to estimate leaf area index
文献类型：期刊论文
| 作者 | Gu, Zhujun1,2,3; Shi, Xuezheng1; Li, Lin4; Yu, Dongsheng1; Liu, Liusong1; Zhang, Wentai1 |
| 刊名 | INTERNATIONAL JOURNAL OF REMOTE SENSING
 |
| 出版日期 | 2011 |
| 卷号 | 32期号:24页码:9441-9454 |
| ISSN号 | 0143-1161 |
| DOI | 10.1080/01431161.2011.562251 |
| 通讯作者 | Shi, Xuezheng(xzshi@issas.ac.cn) |
| 英文摘要 | Ecological applications of remote-sensing techniques are generally limited to images after atmospheric correction, though other radiometric correction data are potentially valuable. In this article, six spectral vegetation indices (VIs) were derived from a SPOT 5 image at four radiometric correction levels: digital number (DN), at-sensor radiance (SR), top of atmosphere reflectance (TOA) and post-atmospheric correction reflectance (PAC). These VIs include the normalized difference vegetation index (NDVI), ratio vegetation index (RVI), slope ratio of radiation curve (K), general radiance level (L), visible-infrared radiation balance (B) and band radiance variation (V). They were then related to the leaf area index (LAI), acquired from in situ measurement in Hetian town, Fujian Province, China. The VI-LAI correlation coefficients varied greatly across vegetation types, VIs as well as image radiometric correction levels, and were not surely increased by image radiometric corrections. Among all 330 VI-LAI models established, the R(2) of multi-variable models were generally higher than those of the single-variable ones. The independent variables of the best VI-LAI models contained all VIs from all radiometric correction levels, showing the potentials of multi-radiometric correction images in LAI estimating. The results indicated that the use of VIs from multiple radiometric correction images can better exploit the capabilities of remote-sensing information, thus improving the accuracy of LAI estimating. |
| 收录类别 | SCI |
| WOS关键词 | ATMOSPHERIC CORRECTION ; SATELLITE DATA ; ETM+ DATA ; VEGETATION ; VALIDATION ; REGRESSION ; MODEL ; ALGORITHM ; NETWORK ; IKONOS |
| WOS研究方向 | Remote Sensing ; Imaging Science & Photographic Technology |
| WOS类目 | Remote Sensing ; Imaging Science & Photographic Technology |
| 语种 | 英语 |
| WOS记录号 | WOS:000298376000030 |
| 出版者 | TAYLOR & FRANCIS LTD |
| URI标识 | http://www.irgrid.ac.cn/handle/1471x/2558866 |
| 专题 | 南京土壤研究所 |
| 通讯作者 | Shi, Xuezheng |
| 作者单位 | 1.Chinese Acad Sci, Inst Soil Sci, State Key Lab Soil & Sustainable Agr, Nanjing 210008, Peoples R China 2.Nanjing Xiaozhuang Univ, Sch Biochem & Environm Engn, Nanjing 211171, Jiangsu, Peoples R China 3.Nanjing Univ, Int Inst Earth Syst Sci, Nanjing 210093, Jiangsu, Peoples R China 4.Indiana Univ Purdue Univ Indianapolis, Dept Earth Sci, Indianapolis, IN 46202 USA |
| 推荐引用方式 GB/T 7714 | Gu, Zhujun,Shi, Xuezheng,Li, Lin,et al. Using multiple radiometric correction images to estimate leaf area index[J]. INTERNATIONAL JOURNAL OF REMOTE SENSING,2011,32(24):9441-9454. |
| APA | Gu, Zhujun,Shi, Xuezheng,Li, Lin,Yu, Dongsheng,Liu, Liusong,&Zhang, Wentai.(2011).Using multiple radiometric correction images to estimate leaf area index.INTERNATIONAL JOURNAL OF REMOTE SENSING,32(24),9441-9454. |
| MLA | Gu, Zhujun,et al."Using multiple radiometric correction images to estimate leaf area index".INTERNATIONAL JOURNAL OF REMOTE SENSING 32.24(2011):9441-9454. |
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来源：南京土壤研究所
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