| 田间作物NDVI测量仪可靠性分析及标定环境研究 |
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| 引用本文： | 杨钧森,杨贵军,徐波,张凯选,杨小冬,李振海,李贺丽,杨浩,韩亮.田间作物NDVI测量仪可靠性分析及标定环境研究[J].农业工程学报,2019,35(8):230-236. |
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| 作者姓名： | 杨钧森 杨贵军 徐波 张凯选 杨小冬 李振海 李贺丽 杨浩 韩亮 |
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| 作者单位： | 1. 辽宁工程技术大学测绘与地理科学学院，阜新 123000；2. 农业部农业遥感机理与定量遥感重点试验室，北京农业信息技术研究中心，北京 100097,2. 农业部农业遥感机理与定量遥感重点试验室，北京农业信息技术研究中心，北京 100097,2. 农业部农业遥感机理与定量遥感重点试验室，北京农业信息技术研究中心，北京 100097,1. 辽宁工程技术大学测绘与地理科学学院，阜新 123000；,2. 农业部农业遥感机理与定量遥感重点试验室，北京农业信息技术研究中心，北京 100097,2. 农业部农业遥感机理与定量遥感重点试验室，北京农业信息技术研究中心，北京 100097,2. 农业部农业遥感机理与定量遥感重点试验室，北京农业信息技术研究中心，北京 100097,2. 农业部农业遥感机理与定量遥感重点试验室，北京农业信息技术研究中心，北京 100097,2. 农业部农业遥感机理与定量遥感重点试验室，北京农业信息技术研究中心，北京 100097；3. 山西大同大学建筑与测绘工程学院，大同 037003 |
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| 基金项目： | 国家重点研发计划（2017YFE0122500）；北京市自然科学基金（6182011）；北京市农林科学院科技创新能力建设项目（KJCX20170423） |
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| 摘 要： | 传统对田间作物NDVI测量仪定标大多采用单通道定标方法,该方法存在定标后在室外测量过程中数据偏差较大的问题。针对此类问题,该文以Crop Sense作物长势参量测量仪和SRS-NDVI归一化植被指数测量仪为待定标传感器,以ASD FieldSpec 4地物光谱仪为参考传感器,在室外复杂光照环境下对比多种定标物待定标传感器和参考传感器的测量结果并分析误差,得到田间作物NDVI测量仪的最适宜使用条件及可靠性分析结果。试验结果表明,田间作物NDVI测量仪的适宜测量条件为光照强度大于5.2 klx的情况,在该情况下光照强度和太阳高度角对田间作物NDVI测量仪的影响不显著,在其他条件下可靠性下降。在适宜测量条件下,晴天Crop Sense作物长势参量测量仪和SRS-NDVI归一化植被指数测量仪获取的NDVI与ASD FieldSpec 4地物光谱仪获取的NDVI间的RMSE分别为0.074 5～0.104 9和0.026 8～0.054 3,阴天RMSE分别为0.094 2～0.117 9和0.029 9～0.070 3。经室外定标模型校正后,晴天Crop Sense作物长势参量测量仪和SRS-NDVI归一化植被指数测量仪获取的NDVI与ASDField Spec4地物光谱仪获取的NDVI间的RMSE分别降低了37.1%～41.4%和10.7%～31.5%,阴天CropSense作物长势参量测量仪和SRS-NDVI归一化植被指数测量仪的RMSE减少33.8%～48.3%和48.7%～62.6%。此研究成果为被动式NDVI测量类传感器的标定及应用提供了科学的参考依据。
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| 关 键 词： | 作物 光照测量 可靠性 NDVI 测量仪 交叉辐射定标 光照强度 太阳高度角 |
| 收稿时间： | 2018/10/23 0:00:00 |
| 修稿时间： | 2019/2/26 0:00:00 |
Reliability analysis and calibration environment of field crop NDVI measuring instruments |
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| Yang Junsen,Yang Guijun,Xu Bo,Zhang Kaixuan,Yang Xiaodong,Li Zhenhai,Li Heli,Yang Hao and Han Liang.Reliability analysis and calibration environment of field crop NDVI measuring instruments[J].Transactions of the Chinese Society of Agricultural Engineering,2019,35(8):230-236. |
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| Authors: | Yang Junsen Yang Guijun Xu Bo Zhang Kaixuan Yang Xiaodong Li Zhenhai Li Heli Yang Hao and Han Liang |
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| Institution: | 1. School of Geomatics, Liaoning Technical University, Fuxin 123000, China; 2. Key Laboratory of Quantitative Remote Sensing in Agriculture of Ministry of Agriculture P. R. China, Beijing Research Center for Information Technology in Agriculture, Beijing 100097, China;,2. Key Laboratory of Quantitative Remote Sensing in Agriculture of Ministry of Agriculture P. R. China, Beijing Research Center for Information Technology in Agriculture, Beijing 100097, China;,2. Key Laboratory of Quantitative Remote Sensing in Agriculture of Ministry of Agriculture P. R. China, Beijing Research Center for Information Technology in Agriculture, Beijing 100097, China;,1. School of Geomatics, Liaoning Technical University, Fuxin 123000, China;,2. Key Laboratory of Quantitative Remote Sensing in Agriculture of Ministry of Agriculture P. R. China, Beijing Research Center for Information Technology in Agriculture, Beijing 100097, China;,2. Key Laboratory of Quantitative Remote Sensing in Agriculture of Ministry of Agriculture P. R. China, Beijing Research Center for Information Technology in Agriculture, Beijing 100097, China;,2. Key Laboratory of Quantitative Remote Sensing in Agriculture of Ministry of Agriculture P. R. China, Beijing Research Center for Information Technology in Agriculture, Beijing 100097, China;,2. Key Laboratory of Quantitative Remote Sensing in Agriculture of Ministry of Agriculture P. R. China, Beijing Research Center for Information Technology in Agriculture, Beijing 100097, China; and 2. Key Laboratory of Quantitative Remote Sensing in Agriculture of Ministry of Agriculture P. R. China, Beijing Research Center for Information Technology in Agriculture, Beijing 100097, China; 3. College of Architecture and Geomatics Engineering, Shanxi Datong University, Datong 037003, China |
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| Abstract: | Abstract: Normalized difference vegetation index (NDVI) is one of the vegetation indices (VI) most widely used. It is related to quite a few indices indicating crop growth, such as leaf area index (LAI), leaf nitrogen accumulation (LNA), chlorophyll content and so on. Several researchers have developed various field crop NDVI measuring instruments to acquire NDVIs, which contains passive sensors and active sensors. Greenseeker, Crop Circle, CropSpec, RapidScan are in common use, and numerous researches are based on them. However, few domestic devices have been developed and corresponding researches haven''t, either. This study assessed the reliability of a novel field crop NDVI measuring instrument based on CropSense crop growth parameter meter (CropSense) together with spectral reflectance sensor (SRS) in varied illumination condition. Field crop NDVI measuring instruments are susceptible to illumination conditions, the height above the canopy and other factors, and it was supposed to detect the performance of sensors through radiometric calibration, which contains laboratory calibration and on-orbit calibration. Integrating sphere was mostly employed for traditional radiometric calibration on field crop NDVI measuring instruments. What was used as the calibration model was the functional relationship between the radiance of integrating sphere and the DN digital number of each channel fitted into the field crop NDVI measuring instruments. Nevertheless, it was found that deviations tended to increase after calibrated by the model built via indoor calibration in the outdoor measurement, with a decline of R2 from 0.997 1 at least of all the calibration model to 0.698 0 for CropSense and 0.877 3 for SRS. In order to deal with such problems, cross calibration method was proposed in this study for the field crop NDVI measuring instruments in the outdoors, with CropSense together with SRS to be calibrated and ASD FieldSpec 4 hyperspectral radiometer (ASD) as reference which can all gather NDVIs. NDVIs were obtained on several objects, referring to diffuse white reference panel, gray cloth, green cloth, blue cloth, cement pavement, naked soil and wheat in varied test periods from 5:30 to 18:30 in sunny days and from 5:30 to 15:00 in cloudy days. The functional relationship between NDVIs acquired through the sensor to be calibrated and ones measured by the reference sensor was taken as an outdoor calibration model to adjust the testing data of CropSense and SRS. Comparing the R2, RMSE and MAE got between field crop NDVI instruments and reference sensor before calibrated, the accuracy and the most suitable conditions for the field crop NDVI measuring instruments were determined. The results showed that RMSEs of NDVIs between CropSense and ASD were 0.074 5-0.104 9 and that between SRS and ASD were 0.026 8-0.054 3 during 6:00-18:00 in sunny days with light intensity from 6.4 to 92.3 klx, and 0.094 2-0.117 9 for CropSense and 0.029 9- 0.070 3 for SRS during 6:00-15:00 in cloudy days with light intensity from 5.2 to 10.8 klx. After calibrated by the model built through outdoor calibration, RMSEs were decreased by 37.1%-41.4% for CropSense and by 10.7%-31.5% for SRS in sunny days; RMSEs were decreased by 33.8%-48.3% for CropSense and by 48.7%-62.6% for SRS in cloudy days. At the same time, the light intensity and solar elevation angle have certain impacts on the accuracy of field crop NDVI measuring instruments. Within the conditions allowed for the instruments to be employed, the performance of the field crop NDVI measuring instruments improves with the increasement of the light intensity; and there is a slight fluctuation with the change of the solar elevation angle. However, the both factors, generally speaking, have no significant influence on the accuracy of the instruments, as long as they are utilized in the illumination conditions more than 5.2 klx. This research results provide a scientific calibration method and momentous reference for passive instruments of vegetation indices measurement. |
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| Keywords: | crops light measurement reliability NDVI measuring instruments cross radiometric calibration light intensity solar elevation angle |
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