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近日,同济大学测绘与地理信息学院王群明教授课题组在遥感领域顶级期刊《Remote Sensing of Environment》发表了1篇论文。本研究受到国家自然基金项目(41971297)资助。
Coral reefs, among the world’s most biodiverse and productive submerged habitats, have faced several mass bleaching events due to climate change during the past 35 years. In the course of this century...
Seagrasses are one of the most productive and widespread yet threatened coastal ecosystems on Earth. Despite their importance, they are declining due to various threats, which are mainly anthropogenic...
Model based analysis or explicit definition/listing of all models/assumptions used in the derivation of a pan-sharpening method allows us to understand the rationale or properties of existing methods ...
Mixed pixels, which are inevitable in remote sensing images, often result in a lot of limitations in their applications. A novel approach for mixed pixel's fully constrained unmixing, Fully Constraine...
Aiming at the disadvantage of hard per-parcel classification which can't solve the difficulty of mixed parcel resulting in the low accuracy, a new method of soft per-parcel classification is presented...
This paper presents a study about the potential of spectral unmixing of hyperspectral satellite image data for targeting and quantification of mineral content in limestone and bauxite rich areas in so...
Surface emissivity is a measure of inherent efficiency of land surface. It is applied to convert heat energy into radiant energy. In this study, an unmixing pixel based algorithm was proposed to compu...
Estimating forest variables, such as photosynthetic light use efficiency, from satellite reflectance data requires understanding the contribution of photosynthetic vegetation (PV) and nonphotosynthet...
The linear spectral mixing model is a widely used technique in remote sensing to estimate the fractions of several individual surface components present in an image pixel and the pure reflectance spe...
The possibilities of using MERIS full resolution (FR) data to extract sub-pixel land cover composition over The Netherlands are explored in this paper. More precisely, the use of MERIS FR time series...
Anthropogenic land use activities are significantly contributing to the ecological degradation of the Earth system. Therefore, having actual and reliable land cover information is fundamental to stud...
In this study, advanced techniques for oil spill detection and oil spill type identification using hyperspectral AVIRIS data are presented. Spectrally complex areas are highly dimensional and are co...
In this paper, we explore the possibility of sparse regression, a new direction in unmixing, for vegetation and urban area classification. SUnSAL (Sparse unmixing via variable splitting and augmented ...
Super resolution-based spectral unmixing (SRSU) is a recently developed method for spectral unmixing of remotely sensed imagery, but it is too complex to implement for common users who are interested ...

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