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:快速数据的CAPS变换以及重要和重要作物参数的估计

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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 (Chi), 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 Chi and N concentration in senescent soft white winter wheat (Triticum aestivum L.) in comparison to PSRI. PSRI showed a stronger correlation to Chi 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:利用从高时空分辨率卫星数据获得的光谱指数检索作物生物物理参数,是监测作物生长和状况的宝贵工具。 RapidEye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绿度(GRE)与重要植被的光谱变化一致,因此,它代表了绿色植被的典型反射特性,在近红外(NIR)范围具有相对较高的反射率。 TCF黄色度(YEL)与衰老作物的反射特性相对应,与叶绿素相比,由于叶绿素分解,在光谱的可见部分具有相对较高的反射率,而由于细胞结构分解,在NIR范围内具有较低的NIR反射率植被。这项工作的目的是评估RapidEye TCF在预测绿叶面积指数(LAI),植物叶绿素(Chi)和氮(N)浓度以及鉴定衰老模式方面的潜力。将生物物理参数和TCF之间的线性关系与广泛使用的指标NDVI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密切相关,并表明其预测能力比NDVI高。与PSRI相比,YEL表现出很强的线性关系,并且具有较高的潜力来估计衰老的软白冬小麦(Triticum aestivum L.)中的Chi和N浓度。与YEL相比,PSRI在衰老的软白春小麦(Triticum aestivum L)中与Chi的相关性更强。结果表明,YEL可用于表征田间衰老状态的变异性。该信息与土壤肥力和产量图一起可以潜在地用于指定精确的管理区域。

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