Karst Rocky Desertification in Southwest China: Remote Sensing Progress, Critical Challenges, and Future Pathways
Source abstract
Abstract
Karst desertification is a major ecological and environmental issue that threatens regional ecological security and sustainable development; its dynamic monitoring is of great significance for evaluating the effectiveness of ecological restoration and promoting regional sustainable development. Based on the Web of Science database, this paper offers a bibliometric-informed narrative review of the evolution of remote sensing monitoring and information extraction technologies for karst desertification from 1987 to 2025. It focuses on analyzing research progress in methods such as multi-source remote sensing data fusion, deep learning models, and integrated GIS analysis, with regard to improving the accuracy of information extraction and the ability to identify spatiotemporal dynamics of karst desertification. This paper also compares the advantages and limitations of different technologies in terms of high-resolution identification and long-term dynamic monitoring. Building on this foundation and drawing on relevant domestic and international research findings, this study examines the development trends and major challenges facing karst desertification monitoring technologies. It further outlines the direction for establishing a long-term, standardized dynamic monitoring system, with the aim of providing a scientific basis for ecological governance and sustainable development in the karst regions of Southwest China.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Karst Systems and Hydrogeology · Geology and Paleoclimatology Research · Groundwater and Watershed Analysis
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Geography & Environmental Science, Guizhou Normal University, Guiyang 550001, China
Anshun Agricultural Environment Field Observation and Research Station, Ministry of Agriculture and Rural Affairs of the People’s Republic China, Anshun 551400, China
Guizhou Provincial Key Laboratory of Intelligent Processing and Application of Remote Sensing Big Data, Guiyang 550001, China
Funding
Science and Technology Department of Guizhou Province · Guizhou Provincial Key Laboratory of Remote Sensing Big Data Intelligent Processing and Application · National Technology Innovation Center for Karst Rocky Desertification Control and Green Development
References (49)
Show source-provided references
1. Ford, D., and Williams, P.D. (2007). Karst Hydrogeology and Geomorphology, John Wiley & Sons.10.1002/9781118684986 ↗
2. The impact of land use and land cover changes on land surface temperature in a karst area of China10.1016/j.jenvman.2006.07.016 ↗
3. D’Ettorre, U.S., Liso, I.S., Parisi, V., and Parise, M. (2024). Desertification Assessment Using the Modified Mediterranean Desertification and Land Use Model in a Karst Plateau. Geosciences, 14.10.3390/geosciences14120320 ↗
4. Characteristics of changes in karst rocky desertification in Southtern and Western China and driving mechanisms10.1007/s11769-021-1243-3 ↗
5. Review status and prospect of karst rocky desertification remote sensing information extraction methods
6. Machine learning algorithm for estimating karst rocky desertification in a peak-cluster depression basin in southwest Guangxi, China10.1038/s41598-022-21684-5 ↗
7. High-Resolution Dynamic Monitoring of Rocky Desertification of Agricultural Land Based on Spatio-Temporal Fusion10.3390/land13122173 ↗
8. The use of remote sensing for desertification studies: A review10.1016/j.jaridenv.2022.104829 ↗
9. Comparing remote sensing methods for monitoring karst rocky desertification at sub-pixel scales in a highly heterogeneous karst region10.1038/s41598-019-49730-9 ↗
10. Identification and factor analysis of rocky desertification severity levels in large-scale karst areas based on deep learning image segmentation10.1016/j.ecolind.2024.112565 ↗
11. Deep learning in remote sensing applications: A meta-analysis and review10.1016/j.isprsjprs.2019.04.015 ↗
12. The comprehensive treatment of karst rocky desertification and its regional restoration effects
13. Trends of Rocky Desertification Evolution in the Karst Mountains of Southwest China
14. Atlas Analysis of spatiat-temporal evolution of Karst Rocky Desertification in LuoDian County Based on GIS and RS Technology—Taking Luodian County of Guizhou Province as an Example
15. Shi, Y., and Shu, Y. (2017). Analysis on Karst Rocky Desertification Temporal and Spatial Variation Characteristics and Driving Factors—A Case Study of Qinglong county of Guizhou Province. For. Resour. Manag., 135–143+152.
16. Research on Karst Rock Desertification Remote Sensing of Guizhou Plateau—Sampling of Qingzhen City in Guizhou
17. A Method of the Percentage of Bare Rock Calculation in Karst Areas Based on Multi-spectrum Remote Sensing Image
18. Spectral analysis of seasonal rock and vegetation changes for detecting karst rocky desertification in southwest China
19. Retrieval of Rock-desertification Degree from Multi-spectral Remote Sensing Images
20. Spectral indices for estimating ecological indicators of karst rocky desertification10.1080/01431160903382892 ↗
21. Remote sensing of indicators for evaluating karst rocky desertification
22. Study on the Relation between Fraction Cover and Mixed Spectra in Karst Enviroment
23. Estimating karst rocky desertification feature abundance by pixel unmixing
24. Estimating ecological indicators of karst rocky desertification by linear spectral unmixing method
25. Monitoring and classification of karst rocky desertification with Landsat 8 OLI images using spectral indices, multi-endmember spectral mixture analysis and support vector machine10.26833/ijeg.1149738 ↗
26. Object-based mapping of karst rocky desertification using a support vector machine10.1002/ldr.2193 ↗
27. Evaluation of rocky desertification degree in karst peak cluster depression based on machine learning
28. Pu, J., Zhao, X., Dong, P., Wang, Q., and Yue, Q. (2021). Extracting Information on Rocky Desertification from Satellite Images: A Comparative Study. Remote Sens., 13.10.3390/rs13132497 ↗
29. Extraction of rocky desertification information based on multi-feature combination optimization and random forest algorithm: A case study of Zhaotong city in Yunnan province
30. Qian, C., Qiang, H., Wang, F., and Li, M. (2021). Optimization of rocky desertification classification model based on vegetation type and seasonal characteristic. Remote Sens., 13.10.3390/rs13152935 ↗
31. Machine Learning-Based Spatial Prediction of Soil Erosion Susceptibility Using Geo-Environmental Variables in Karst Landscapes of Southwest China10.3390/land14112277 ↗
32. Wan, J., Zhou, Z., Zhu, M., Wang, J., Zheng, J., Wang, C., Wu, X., and Liu, R. (2024). Deep learning approach for studying forest types in restored karst rocky landscapes: A case study of Huajiang, China. Forests, 15.10.3390/f15122122 ↗
33. RAP-net: A region affinity propagation-guided semantic segmentation network for plateau karst landform remote sensing imagery10.3390/rs17173082 ↗
34. Improved lightweight DeepLabV3+ for bare rock extraction from high-resolution UAV imagery10.1016/j.ecoinf.2025.103204 ↗
35. Utilizing deep convolutional neural networks and non-negative matrix factorization for multi-modal image fusion
36. Jamshidi, M., El-Badry, M., and Zhang, C. (2021, January 21–25). Sequential concrete crack segmentation using deep fully convolutional neural networks and data fusion. Proceedings of the Automated Visual Inspection and Machine Vision IV, Online.10.1117/12.2592243 ↗
37. Evaluation of Soil Rocky Desertification in Karst Region Based on Deep Belief Network
38. Angel, Y., Houborg, R., and McCabe, M.F. (2019). Reconstructing cloud contaminated pixels using spatiotemporal covariance functions and multitemporal hyperspectral imagery. Remote Sens., 11.10.3390/rs11101145 ↗
39. Wu, Z.G., Xiong, K.N., Zhu, D.Y., and Xiao, J. (2023). Revelation of Coupled Ecosystem Quality and Landscape Patterns for Agroforestry Ecosystem Services Sustainability Improvement in the Karst Desertification Control. Agriculture, 13.10.3390/agriculture13010043 ↗
40. Lesiv, M., See, L., Laso Bayas, J.C., Sturn, T., Schepaschenko, D., Karner, M., Moorthy, I., McCallum, I., and Fritz, S. (2018). Characterizing the spatial and temporal availability of very high resolution satellite imagery in google earth and Microsoft Bing maps as a source of reference data. Land, 7.10.5194/essd-2018-13 ↗
41. Flattening gamma: Radiometric terrain correction for SAR imagery10.1109/TGRS.2011.2120616 ↗
42. Luo, J., Liu, S., Ruan, O., and Hu, H. (2022). Extraction of rocky desertification information using NDVI-Albedo feature space. Bull. Surv. Mapp., 56–60.
43. Wang, M. (2019). Remote Sensing Extraction and Spatiotemporal Evolution Analysis of Karst Rocky Desertification Spatial Distribution. [Master’s Thesis, University of Chinese Academy of Sciences].
44. Polemio, M. (2016). Monitoring and management of karstic coastal groundwater in a changing environment (Southern Italy): A review of a regional experience. Water, 8.10.3390/w8040148 ↗
45. Parise, M., Ravbar, N., Živanović, V., Mikszewski, A., Kresic, N., Mádl-Szőnyi, J., Kukurić, N., Parise, M., Ravbar, N., and Živanović, V. (2015). Hazards in karst and managing water resources quality. Karst Aquifers—Characterization and Engineering, Springer.10.1007/978-3-319-12850-4_17 ↗
46. Karst rocky desertification in southwestern China: Geomorphology, landuse, impact and rehabilitation10.1002/ldr.592 ↗
47. FWDNNet: Cross-Heterogeneous Encoder Fusion via Feature-Level TensorDot Operations for Land-Cover Mapping10.1109/TGRS.2026.3652451 ↗
48. Hybrid deep learning for satellite image classification: Integrating CNN and transformer architectures10.1016/j.softx.2026.102754 ↗
49. LiDAR remote sensing meets weak supervision: Concepts, methods, and perspectives10.1016/j.isprsjprs.2026.03.004 ↗