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首页> 外文期刊>IEEE Geoscience and Remote Sensing Letters >Correlation Between Corn Progress Stages and Fractal Dimension From MODIS-NDVI Time Series
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Correlation Between Corn Progress Stages and Fractal Dimension From MODIS-NDVI Time Series

机译：MODIS-NDVI时间序列的玉米发育阶段与分形维数之间的相关性

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摘要

In this letter, the relationship between corn crop progress stages and fractal dimension derived from remote sensing data has been revealed. Due to the effects of soil background and farming practices on emerged and harvested stages of the corn crop, the roughness of their corresponding normalized difference vegetation index (NDVI) images significantly changes. Therefore, image fractals, which normally indicate such roughness, are proposed to detect corn progress stages. There are four steps in the proposed procedure: 1) NDVI maximum composite process is conducted to eliminate the influence of cloud cover or missing data; 2) Cropland Data Layer (CDL) is used to remove noncorn pixels; 3) fractal dimension is calculated to estimate the spatial roughness of NDVI image; and 4) curve fitting is used to detect peaks that infer the certain progress stages. It is worth mentioning that a dimensionality-reduction-based differential box-counting algorithm is developed to estimate the fractal dimension of NDVI image in an irregular region of interest. The algorithm is applicable for masked NDVI image. Experiments based on Moderate Resolution Imaging Spectroradiometer NDVI time series and CDL of the State of Iowa are conducted. Comparison of the results with corn crop statistics from the National Agricultural Statistics Service indicates that the proposed method is able to detect corn emerged and harvested stages with success.
机译：在这封信中，已经揭示了玉米作物生长阶段与从遥感数据得出的分形维数之间的关系。由于土壤背景和耕作方式对玉米作物出苗和收获阶段的影响，其对应的归一化差异植被指数（NDVI）图像的粗糙度会发生显着变化。因此，提出了通常表示这种粗糙度的图像分形来检测玉米的进展阶段。建议的过程包括四个步骤：1）进行NDVI最大复合处理，以消除云量或数据丢失的影响； 2）农田数据层（CDL）用于删除非玉米像素； 3）计算分形维数以估计NDVI图像的空间粗糙度；和4）曲线拟合用于检测推断某些进展阶段的峰。值得一提的是，开发了一种基于降维的差分盒计数算法来估计不规则感兴趣区域中NDVI图像的分形维数。该算法适用于屏蔽的NDVI图像。进行了基于中等分辨率成像光谱仪NDVI时间序列和爱荷华州CDL的实验。将结果与国家农业统计局的玉米作物统计数据进行比较表明，该方法能够成功检测出玉米的出苗和收获阶段。

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