干旱区生态环境知识资源中心(Arid): Optimization of Rocky Desertification Classification Model Based on Vegetation Type and Seasonal Characteristic

Arid

DOI	10.3390/rs13152935
	Optimization of Rocky Desertification Classification Model Based on Vegetation Type and Seasonal Characteristic
	Qian, Chunhua; Qiang, Hequn; Wang, Feng; Li, Mingyang
通讯作者	Li, MY (corresponding author), Nanjing Forestry Univ, Sch Forestry, Nanjing 210037, Peoples R China.
来源期刊	REMOTE SENSING
EISSN	2072-4292
出版年	2021
卷号	13 期号:15
英文摘要	Building a high-precision, stable, and universal automatic extraction model of the rocky desertification information is the premise for exploring the spatiotemporal evolution of rocky desertification. Taking Guizhou province as the research area and based on MODIS and continuous forest inventory data in China, we used a machine learning algorithm to build a rocky desertification model with bedrock exposure rate, temperature difference, humidity, and other characteristic factors and considered improving the model accuracy from the spatial and temporal dimensions. The results showed the following: (1) The supervised classification method was used to build a rocky desertification model, and the logical model, RF model, and SVM model were constructed separately. The accuracies of the models were 73.8%, 78.2%, and 80.6%, respectively, and the kappa coefficients were 0.61, 0.672, and 0.707, respectively. SVM performed the best. (2) Vegetation types and vegetation seasonal phases are closely related to rocky desertification. After combining them, the model accuracy and kappa coefficient improved to 91.1% and 0.861. (3) The spatial distribution characteristics of rocky desertification in Guizhou are obvious, showing a pattern of being heavy in the west, light in the east, heavy in the south, and light in the north. Rocky desertification has continuously increased from 2001 to 2019. In conclusion, combining the vertical spatial structure of vegetation and the differences in seasonal phase is an effective method to improve the modeling accuracy of rocky desertification, and the SVM model has the highest rocky desertification classification accuracy. The research results provide data support for exploring the spatiotemporal evolution pattern of rocky desertification in Guizhou.
英文关键词	rocky desertification supervised classification method MODIS data feature extraction spatial and temporal distribution
类型	Article
语种	英语
开放获取类型	gold
收录类别	SCI-E
WOS记录号	WOS:000682316000001
WOS关键词	KARST AREAS ; QUANTITY DISAGREEMENT ; TEMPORAL EVOLUTION ; NORTHWEST GUANGXI ; GUIZHOU PROVINCE ; COUNTY ; LAND ; REGION ; CHINA
WOS类目	Environmental Sciences ; Geosciences, Multidisciplinary ; Remote Sensing ; Imaging Science & Photographic Technology
WOS研究方向	Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/364469
作者单位	[Qian, Chunhua; Li, Mingyang] Nanjing Forestry Univ, Sch Forestry, Nanjing 210037, Peoples R China; [Qian, Chunhua; Qiang, Hequn; Wang, Feng] Suzhou Polytech Inst Agr, Sch Smart Agr, Suzhou 215008, Peoples R China; [Qiang, Hequn] Soochow Univ, Sch Comp Sci & Technol, Suzhou 215301, Peoples R China
推荐引用方式 GB/T 7714	Qian, Chunhua,Qiang, Hequn,Wang, Feng,et al. Optimization of Rocky Desertification Classification Model Based on Vegetation Type and Seasonal Characteristic[J],2021,13(15).
APA	Qian, Chunhua,Qiang, Hequn,Wang, Feng,&Li, Mingyang.(2021).Optimization of Rocky Desertification Classification Model Based on Vegetation Type and Seasonal Characteristic.REMOTE SENSING,13(15).
MLA	Qian, Chunhua,et al."Optimization of Rocky Desertification Classification Model Based on Vegetation Type and Seasonal Characteristic".REMOTE SENSING 13.15(2021).