Identification of citrus orchard under vegetation indexes using multi-temporal remote sensing

Chenxin Liang, Qiting Huang, Si Wang, Cong Wan, Qiangyi Yu, Wenbin Wu

Abstract

Citrus is widely planted in southern China. Due to cloudy and rainy weather, complex planting types, and other factors, it is difficult to use spectral information to directly identify citrus orchard information. Based on the unique phenological characteristics of citrus, this study put forward the hypothesis that “the vegetation information of citrus orchards may be weakened during the growth and expansion of citrus fruit”. According to this feature, a method of citrus orchard information identification is proposed, and the threshold of the key time window is determined. Taking Wuming District, Nanning City, and Guangxi Zhuang Autonomous Region as the research area, an empirical study on remote sensing identification of citrus orchard information is carried out. First, multi-temporal Sentinel-2 remote sensing images of the study area in 2018 were obtained, and a normalized difference vegetation index was constructed. NDVI, Green Normalized Difference Vegetation Index (GNDVI), Difference Vegetation Index (DVI), Sentinel-derived red-edge spectral indices (RESI), and other vegetation spectral indices Secondly, according to the ground sample point information, the difference in remote sensing vegetation information of different vegetation types in different periods was compared, and then the optimal features of citrus orchard identification were determined. The results showed that there was no significant difference in spectral characteristics between citrus orchards and other major crop types in the study area (such as sugarcane, banana, corn, rice, etc.), but the multi-temporal remote sensing vegetation index of the study area showed that the NDVI of citrus orchards in October was 0.47 lower than that of November, which was significantly lower than that of other crop types. In October, the GNDVI of the citrus orchard also showed a low value of 0.43, but the difference was not obvious compared with other months. However, the dispersion degree of citrus orchard DVI was low, and the separation was not strong. According to the crop phenological calendar, the period of rapid expansion of citrus fruits was from September to October, which verified the scientific hypothesis proposed in this study that the vegetation information of citrus orchards would be weakened during this period. The dispersion degree of different vegetation indexes in the citrus fruit expansion stage was obviously different, and the dispersion degree of NDVI was the highest, and the difference was the strongest. According to the phenological characteristics of the citrus orchard NDVI in October, to further build the normalized index, by using the threshold value method to identify the spatial distribution of the citrus orchard, the identification method had an overall accuracy of 82.75%, better than other identification results of vegetation index. The results of the study for citrus orchard information and remote sensing identification research provide better support for theory and practice.

Keywords

remote sensing; classification; phenology; citrus; vegetation index; Sentinel-2; Google earth engine

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