首页> 外文会议>International Symposium on Remote Sensing of Environment >THE TASSELED CAP TRANSFORMATION FOR RAPIDEYE DATA AND THE ESTIMATION OF VITAL AND SENESCENT CROP PARAMETERS
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THE TASSELED CAP TRANSFORMATION FOR RAPIDEYE DATA AND THE ESTIMATION OF VITAL AND SENESCENT CROP PARAMETERS

机译:Rapideye数据的流苏帽改造及衰老衰老和衰老作物参数

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The retrieval of crop biophysical parameters using spectral indices obtained from high temporal and spatial resolution satellite data, is a valuable tool to monitor crop growth and status. Tasseled Cap Features (TCFs) for RapidEye data were derived from spectral variances typically present in agricultural scenes. The TCF Greenness (GRE) was aligned to the spectral variance of vital vegetation, and therefore, it represents the typical reflectance characteristics of green vegetation, with relatively higher reflectance at the near-infrared (NIR) range. The TCF Yellowness (YEL) was aligned to correspond to the reflectance characteristics of senescent crops, with relatively higher reflectance in the visible portion of the spectrum due to chlorophyll breakdown, and lower reflectance in the NIR range due to cell structure decomposition compared to vital green vegetation. The goal of this work was to assess the potential of RapidEye's TCFs for the prediction of green leaf area index (LAI), plant chlorophyll (Chl), and nitrogen (N) concentration, as well as the identification of senescence patterns. The linear relationships between the biophysical parameters and the TCFs were compared to the performance of the widely used indices NDVI and PSRI. Preliminary results indicate that GRE is strongly related to LAI in vital crops and suggests a higher predictive power than NDVI. YEL demonstrated a strong linear relation and a higher potential to estimate Chl and N concentration in senescent soft white winter wheat (Triticum aestivum L.) in comparison to PSRI. PSRI showed a stronger correlation to Chl in senescent soft white spring wheat (Triticum aestivum L.), compared to YEL. Results indicate that YEL may be used to characterize the variability in senescence status within fields. This information, in conjunction with soil fertility and yield maps, can potentially be used to designate precision management zones.
机译:使用从高时间和空间分辨率卫星数据获得的频谱指标的裁剪生物物理参数检索是一种有价值的工具,可以监测作物生长和状态。用于缩放数据的流苏帽特征(TCF)来自农业场景中通常存在的光谱差异。 TCF绿色(GRE)与重要植被的光谱方差对齐,因此,它代表了绿色植被的典型反射特性,在近红外(NIR)范围内具有相对较高的反射率。 TCF yellowness(Yel)对应于衰老作物的反射特性,由于叶绿素分解,由于叶绿素击穿,并且由于细胞结构分解而导致的叶绿素击穿,并且在NIR范围内的较低反射率。与重要绿色相比植被。这项工作的目标是评估Rapideye的TCF的潜力,用于预测绿叶面积指数(LAI),植物叶绿素(CHL)和氮气(N)浓度,以及衰老模式的鉴定。将生物物理参数与TCF之间的线性关系与广泛使用的索引和PSRI的性能进行了比较。初步结果表明,GRE与重要作物中的LAI强烈相关,表明比NDVI更高的预测力。与PSRI相比,YEL展示了强烈的线性关系和估计CHL和N浓度的潜力更高的潜力。与叶片相比,PSRI显示出与衰老软白春小麦(Triticum Aestivum L)的CHL相关性。结果表明,yel可用于表征衰老状态的衰弱。这些信息与土壤肥力和产量图一起可以用于指定精度管理区域。

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