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Calculation of cotton index in the Weiku Oasis region of Xinjiang
Background Introduction
Cotton is one of my country's important economic crops, and its growth process includes key stages such as seedling stage, budding stage, flowering stage, boll stage, and tufting stage. Traditional cotton management relies on manual field inspections and experience-based judgment, which is not only time-consuming and labor-intensive but also makes it difficult to achieve large-scale, rapid, and objective identification of the growth stage. With the development of remote sensing technology, monitoring cotton growth status using spectral indices has become an efficient, low-cost, and automated method. The Boll Cotton Index (BCI), as a remote sensing index targeting the mid-to-late stages of cotton growth, can sensitively reflect boll hull and boll exposure, leaf yellowing, and changes in canopy structure during the tufting stage, making it one of the important indicators for monitoring cotton growth stages.
Data and Methods
1. Data
This case study uses hyperspectral and multispectral images of the Weiku Oasis region in Xinjiang taken by Xiguang-1 05 satellite (Tianxianpei) on August 10, 2025, and Sentinel-2 on August 11, 2025, with atmospherically corrected L2C-level reflectance data.
2. Methods
The cotton growth status in this region is calculated using the Cotton Index (BCI), as follows:
Among them: Red (red light, 620–680 nm): Strongly absorbed by cotton leaves during the vigorous growth period, but significantly increases during senescence and boll opening. RedEdge (red edge, 705–740 nm): Sensitive to changes in chlorophyll, decreasing as leaves yellow and nitrogen content decreases.
Results Display
The following figure was obtained through BCI calculation:
Figure 1. Xiguang-1 05 satellite (a celestial match) 20250810
Figure 2 Sentinel-2 20250811
The comparison revealed that the results of the two indices were quite consistent. The BCI index can reflect the relationship between band reflectance and crop growth period. During the boll opening stage, the number of leaves decreased and the cotton bolls were exposed, resulting in an increase in Red and a decrease in RedEdge, which significantly reduced the BCI. During the flowering and boll-forming stage, the number of leaves was abundant and the greenness was high, resulting in a low Red and a high RedEdge, which significantly increased the BCI.
The Boll Cotton Index (BCI) fully utilizes the spectral variations of cotton from its full bloom to its boll opening stage, making it a highly sensitive remote sensing index for the later stages of cotton growth. It can be used for various applications, including boll opening monitoring, yield prediction, and cotton field identification. Furthermore, it can be flexibly combined with hyperspectral and multispectral data, making it suitable for regional monitoring and large-scale agricultural management. With the rapid development of hyperspectral satellite and UAV remote sensing, future cotton models based on BCI will become more refined and automated, providing strong technical support for smart agriculture and precision cotton management.