气候变化领域集成服务门户(CCPortal): Postfire Forest Regrowth Algorithm Using Tasseled-Cap-Retrieved Indices

CCPortal

DOI	10.3390/rs16030597
	Postfire Forest Regrowth Algorithm Using Tasseled-Cap-Retrieved Indices
	Stankova, Nataliya; Avetisyan, Daniela
发表日期	2024
EISSN	2072-4292
起始页码	16
结束页码	3
卷号	16 期号:3
英文摘要	Wildfires are a common disturbance factor worldwide, especially over the last decade due to global climate change. Monitoring postfire forest regrowth provides fundamental information needed to enhance the management and support of ecosystem recovery after fires. The purpose of this study is to propose an algorithm for postfire forest regrowth monitoring using tasseled-cap-derived indices. A complex approach is used for its implementation, for which a model is developed based on three components-Disturbance Index (DI), Vector of Instantaneous Condition (VIC), and Direction Angle (DA). The final product-postfire regrowth (PFIR)-allows for a quantitative assessment of the intensity of regrowth. The proposed methodology is based on the linear orthogonal transformation of multispectral satellite images-tasseled cap transformation (TCT)-that increases the degree of identification of the three main components that change during a fire-soil, vegetation, and water/moisture-and implies a higher accuracy of the assessments. The results provide a thematic raster representing the intensity of the regrowth classes, which are defined after the PFIR threshold values are determined (HRI-high regrowth intensity; MRI-moderate regrowth intensity; and LRI-low regrowth intensity). The accuracy assessment procedure is conducted using very-high-resolution (VHR) aerial and satellite data from World View (WV) sensors, as well as multispectral Sentinel 2A images. Three different forest test sites affected by fire in Bulgaria are examined. The results show that the classified thematic raster maps are distinguished by a good performance in monitoring the regrowth dynamics, with an average overall accuracy of 62.1% for all three test sites, ranging from 73.9% to 48.4% for the individual forests.
英文关键词	remote sensing; postfire monitoring; forest regrowth; tasseled cap transformation; Disturbance Index; Direction Angle
语种	英语
WOS研究方向	Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology
WOS类目	Environmental Sciences ; Geosciences, Multidisciplinary ; Remote Sensing ; Imaging Science & Photographic Technology
WOS记录号	WOS:001160389100001
来源期刊	REMOTE SENSING
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/299128
作者单位	Bulgarian Academy of Sciences
推荐引用方式 GB/T 7714	Stankova, Nataliya,Avetisyan, Daniela. Postfire Forest Regrowth Algorithm Using Tasseled-Cap-Retrieved Indices[J],2024,16(3).
APA	Stankova, Nataliya,&Avetisyan, Daniela.(2024).Postfire Forest Regrowth Algorithm Using Tasseled-Cap-Retrieved Indices.REMOTE SENSING,16(3).
MLA	Stankova, Nataliya,et al."Postfire Forest Regrowth Algorithm Using Tasseled-Cap-Retrieved Indices".REMOTE SENSING 16.3(2024).