...
首页> 外文期刊>Agricultural and Forest Meteorology >Estimation of crop gross primary production (GPP): II. Do scaled MODIS vegetation indices improve performance?
【24h】

Estimation of crop gross primary production (GPP): II. Do scaled MODIS vegetation indices improve performance?

机译:作物初级生产总值(GPP)的估算:II。缩放的MODIS植被指数是否可以改善性能?

获取原文
获取原文并翻译 | 示例
   

获取外文期刊封面封底 >>

       

摘要

Satellite remote sensing estimates of gross primary production (GPP) have routinely been made using spectral vegetation indices (VIs) over the past two decades. The Normalized Difference Vegetation Index (NDVI), the Enhanced Vegetation Index (EVI), the green band Wide Dynamic Range Vegetation Index (WDRVIgreen), and the green band Chlorophyll Index (CIgreen) have been employed to estimate GPP under the assumption that GPP is proportional to the product of VI and photosynthetically active radiation (PAR) (where VI is one of four VIs: NDVI, EVI,WDRVIgreen, or Queen). However, the empirical regressions between VI*PAR and GPP measured locally at flux towers do not pass through the origin (i.e., the zero X-Y value for regressions). Therefore they are somewhat difficult to interpret and apply. This study investigates (1) what are the scaling factors and offsets (i.e., regression slopes and intercepts) between the fraction of PAR absorbed by chlorophyll of a canopy (fAPAR(chl)) and the VIs and (2) whether the scaled VIs developed in (I) can eliminate the deficiency and improve the accuracy of GPP estimates. Three AmeriFlux maize and soybean fields were selected for this study, two of which are irrigated and one is rainfed. The four VIs and fAPAR(chl) of the fields were computed with the MODerate resolution Imaging Spectroradiometer (MODIS)satellite images. The GPP estimation performance for the scaled VIs was compared to results obtained with the original VIs and evaluated with standard statistics: the coefficient of determination (R-2), the root mean square error (RMSE), and the coefficient of variation (CV). Overall, the scaled EVI obtained the best performance. The performance of the scaled NDVI, EVI and WDRVIgreen was improved across sites, crop types and soil/background wetness conditions. The scaled CIgreen did not improve results, compared to the original CIgreen. The scaled green band indices (WDRVIgreen, CIgreen) did not exhibit superior performance to either the scaled EVI or NDVI in estimating crop daily GPP at these agricultural fields. The scaled VIs are more physiologically meaningful than original un-scaled VIs, but scaling factors and offsets may vary across crop types and surface conditions. (C) 2014 Elsevier B.V. All rights reserved.
机译:在过去的二十年中,通常使用光谱植被指数(VI)对卫星初级总产值(GPP)进行卫星遥感估算。在GPP为的前提下,已采用归一化植被指数(NDVI),增强植被指数(EVI),绿带宽动态范围植被指数(WDRVIgreen)和绿带叶绿素指数(CIgreen)来估算GPP。与VI和光合有效辐射(PAR)的乘积成比例(其中VI是四个VI之一:NDVI,EVI,WDRVIgreen或Queen)。但是,在通量塔处局部测量的VI * PAR和GPP之间的经验回归未通过原点(即回归的X-Y值为零)。因此,它们在某种程度上难以解释和应用。这项研究调查(1)冠层的叶绿素(fAPAR(chl))吸收的PAR的比例与VI之间的缩放因子和偏移量(即回归斜率和截距)是什么,以及(2)是否生成了缩放的VI (I)中的A可以消除缺陷并提高GPP估计的准确性。本研究选择了三个AmeriFlux玉米和大豆田,其中两个灌溉,而另一个则是雨养。使用MODerate分辨率成像光谱仪(MODIS)卫星图像计算了场的四个VI和fAPAR(chl)。将缩放后的VI的GPP估计性能与原始VI的结果进行比较,并通过标准统计进行评估:确定系数(R-2),均方根误差(RMSE)和变异系数(CV) 。总体而言,按比例缩放的EVI获得了最佳性能。在不同地点,作物类型和土壤/背景湿度条件下,NDVI,EVI和WDRVIgreen的缩放比例性能得到改善。与原始CIgreen相比,按比例缩放的CIgreen并未改善结果。在估算这些农业领域的农作物日均GPP时,缩放的绿色带指数(WDRVIgreen,CIgreen)没有表现出优于缩放的EVI或NDVI的性能。缩放后的VI比原始未缩放后的VI在生理上更有意义,但是缩放因数和偏移量可能因作物类型和表面条件而异。 (C)2014 Elsevier B.V.保留所有权利。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号