Optical remote sensing-based cloud detection and extraction method for tropical and subtropical vegetation areas

doi:10.6046/zrzyyg.2024151

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Abstract

Optical satellite remote sensing images of tropical and subtropical vegetation areas are often affected by cloud cover, leading to missing remote sensing information of surface features. Effectively detecting clouds, classifying clouds and objects, and extracting cloud cover information remain hot topics and challenges in remote sensing research. Many optical cameras in domestic satellites lack the short-wave and thermal infrared spectral bands, which are used in prevailing cloud detection algorithms, reducing the image data availability after cloud removal. Hence, this study suggested detecting the spatial distribution of cloud cover by utilizing only several spectral bands in the visible light - near-infrared range (400 nm to 1 000 nm). Based on the hyperspectral remote sensing images from the Zhuhai-1 satellite, this study constructed feature space scatter plots using spectral indices, including normalized difference vegetation index (NDVI) and normalized differential water index (NDWI), for cloud/object classification and detection. Moreover, this study extracted the cloud, water, and vegetation cover information from mixed pixels. The results demonstrate that compared to conventional cloud detection methods using spectral index thresholds, the cloud detection algorithm under the NDWI-NDVI feature space used in this study exhibited a superior cloud-water separation capability and simple operability. It can precisely describe the spatial distribution characteristics of cloud cover by suppressing the shadow effect on cloud cover. Overall, this study offers a novel technical approach for further developing cloud detection, cloud-water separation, and cloud cover information extraction algorithms for domestic optical satellite remote sensing data.

Keywords spectral index hyperspectral remote sensing cloud detection feature space tropic and subtropic Zhuhai-1 satellite

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Issue Date: 03 September 2025

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	Fe HUANG
	Xiaoqiong WANG
	Guanrui NIE
	Jun YAN
	Xianyi LI
	Jia TIAN
	Cuicui ZHU
	Qianjing LI
	Qingjiu TIAN

Cite this article:

Fe HUANG,Xiaoqiong WANG,Guanrui NIE, et al. Optical remote sensing-based cloud detection and extraction method for tropical and subtropical vegetation areas[J]. Remote Sensing for Natural Resources, 2025, 37(4): 58-67.

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https://www.gtzyyg.com/EN/10.6046/zrzyyg.2024151 OR https://www.gtzyyg.com/EN/Y2025/V37/I4/58

Fig.1 Study area location diagram

Fig.2 OHS false-color and true-color images in the study area

Fig.3 Spectral curves of cloud and ground objects

Fig.4 Histogram threshold and Image segmentation of NDVI and NDWI

Tab.1 Segmentation featwe points of threshold of NDVI and NDWI

Fig.5 Feature space scatter plot of NDWI-NDVI

Fig.6 Process of feature space threshold classification of NDVI-NDWI

Fig.7 Result of single index threshold classification

Fig.8 Result of scatter classification NDWI-NDVI

Fig.9 Cloud coverage distribution map based on triangular space method

Fig.10 Comparison of different cloud detection methods

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