气候变化领域集成服务门户(CCPortal): Radiometric landscape: a new conceptual framework and operational approach for landscape characterisation and mapping

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DOI	10.1080/10095020.2024.2314558
	Radiometric landscape: a new conceptual framework and operational approach for landscape characterisation and mapping
	Lemettais, Louise; Alleaume, Samuel; Luque, Sandra; Laques, Anne-Elisabeth; Alim, Yonas; Demagistri, Laurent; Begue, Agnes
发表日期	2024
ISSN	1009-5020
EISSN	1993-5153
英文摘要	Landscape mapping has the potential to address some of the most pressing research issues of our time, including climate change, sustainable development, and human well-being. In this paper, we propose an original method that lays the foundations for landscape mapping and overcomes some of the major limitations of existing biophysical methods. Based on the assumption that the primary components of the landscape can be extracted directly from the radiometric information of satellite image time series, this paper presents a new approach to landscape characterization and mapping based solely on remote sensing data. The approach relies on a conceptual model, which links the description, characteristics, structure and functions of the landscape to a set of Remote Sensing-based Essential Landscape Variables (RS-ELVs). The RS-ELVs are then processed according to geographic object-based image analysis (GEOBIA) approach to produce a radiometric landscape map. The model and the remote sensing data processing chain are tested on a case study in central Madagascar (about 13 000 km2) composed of contrasting landscapes resulting from different climatic conditions and agricultural practices. The RS-ELVs are extracted from MODIS image time series for the temporal and spectral variables, and from MODIS and Sentinel-2 images for the texture variables. The parameterization of the segmentation and clustering algorithms is determined by statistical optimization. The final result is a radiometric landscape map in six classes. The landscape classes are then characterized using an independent set of remote sensing variables, a global land cover map and ground observations. The approach successfully identifies and delineates the gradient and major landscape types of the complex region of central Madagascar, confirming our initial hypothesis. The production of such radiometric landscape maps opens the way for integrated territorial development, including the planning and protection of the living environment and human well-being, and the implementation of sectoral policies.
英文关键词	Remote sensing; MODIS; Sentinel-2; essential variables; satellite image time series; Madagascar
语种	英语
WOS研究方向	Remote Sensing
WOS类目	Remote Sensing
WOS记录号	WOS:001187536200001
来源期刊	GEO-SPATIAL INFORMATION SCIENCE
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/304576
作者单位	Institut de Recherche pour le Developpement (IRD); Universite de Montpellier; Universite des Antilles; University of La Reunion; Aix-Marseille Universite; INRAE; AgroParisTech; AgroParisTech; CIRAD; University Antananarivo; Institut de Recherche pour le Developpement (IRD); AgroParisTech; INRAE; Universite de Montpellier; CIRAD; Centre National de la Recherche Scientifique (CNRS)
推荐引用方式 GB/T 7714	Lemettais, Louise,Alleaume, Samuel,Luque, Sandra,et al. Radiometric landscape: a new conceptual framework and operational approach for landscape characterisation and mapping[J],2024.
APA	Lemettais, Louise.,Alleaume, Samuel.,Luque, Sandra.,Laques, Anne-Elisabeth.,Alim, Yonas.,...&Begue, Agnes.(2024).Radiometric landscape: a new conceptual framework and operational approach for landscape characterisation and mapping.GEO-SPATIAL INFORMATION SCIENCE.
MLA	Lemettais, Louise,et al."Radiometric landscape: a new conceptual framework and operational approach for landscape characterisation and mapping".GEO-SPATIAL INFORMATION SCIENCE (2024).