Assessing the potential of using high spatial resolution daily NDVI-time-series from planet CubeSat images for crop monitoring

文献类型： 外文期刊

第一作者： Teixeira Crusiol, Luis Guilherme

作者： Teixeira Crusiol, Luis Guilherme;Sun, Liang;Chen, Ruiqing;Sun, Zheng;Chen, Zhongxin;Wuyun, Deji;Teixeira Crusiol, Luis Guilherme;Nanni, Marcos Rafael;Zhang, Dejun;Nepomuceno, Alexandre Lima;Boucas Farias, Jose Renato

作者机构：

期刊名称：INTERNATIONAL JOURNAL OF REMOTE SENSING （ 影响因子：3.151； 五年影响因子：3.266 ）

ISSN： 0143-1161

年卷期： 2021 年 42 卷 18 期

页码：

收录情况： SCI

摘要： The agricultural land use combined with agronomic management practices shall be structured on sustainable practices, guaranteeing both the maximization of productivity and environment preservation. NDVI (Normalized Difference Vegetation Index) time-series has been recognized as a useful methodology to monitor crop development and its spatial distribution. However, there is always a trade-off between spatial and temporal resolutions in satellite data. Hence, high spatial and temporal resolutions from Planet CubeSat represent a possibility to overcome this trade-off. This paper investigated the potential of using high spatial resolution daily NDVI-time-series from Planet CubeSat images for crop monitoring. One hundred nineteen images from 2017, at 3 m ground sampling distance, over cotton, spring corn and winter wheat fields, were acquired and converted into NDVI. The harmonic analysis of time series (HANTS) algorithm was applied to obtain a smoothed cloud and gap-free daily time-series. The 3 m daily time-series were resized to daily 9 and 30 m resolution; and resampled to temporal resolutions at 4, 8 and 16 days intervals to assess the impact of spatial and temporal resolution on NDVI time-series. NDVI time-series were evaluated by their minimum, maximum, average and coefficient of variation across the year. Principal component analysis (PCA) and the stepwise procedure were applied to assess optimum features (days across the year) to assist the NDVI-time-series interpretation. PCA and stepwise highlighted the best time across the year for NDVI-time-series interpretation. As the spatial resolution decreases, the range of NDVI and its standard deviation within field also decreases, leading to loss of within field spectral variability. At daily temporal resolution, slight differences in crop development can be detected in a very short time interval, but as the temporal resolution decreases the changes in crop development are detected at larger rates. The high temporal and spatial resolutions from Planet CubeSat images demonstrated great potential to monitor agricultural systems and can subsidize, on forthcoming research, the local and regional monitoring of agricultural areas and contribute to better management regarding strategic planning of governmental and corporate decision making over technical issues.

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