Subpixel Mapping Based On Abundance And Temperature Of Wide Spectrum Remote Sensing Image

With the continuous development of remote sensing technology,hyperspectral remote sensing data obtained by people not only made great progress in spatial resolution and spectral resolution,but also greatly expanded their band range.Wide spectrum remote sensing images cover visible/near infrared and thermal infrared bands,and provide more complete and sufficient remote sensing information for researchers.Because of the inherent imaging mechanism of visible/near infrared sensors and thermal infrared sensors,the remote sensing images obtained have their own characteristics,reflecting different physical and chemical characteristics of ground targets.The former has a higher spatial resolution and contains rich structure and spectral information of targets.The latter has the lower spatial resolution,but because of the characteristics of thermal radiation imaging,infrared data contains temperature and radiation information of the target.In this paper,a method of subpixel mapping based on abundance and temperature of wide spectrum remote sensing image is proposed for full use of wide spectrum remote sensing data information.First of all,visible remote sensing images can provide abundant spatial and structural information for its higher spatial resolution.Traditional endmember extraction algorithms only focus on spectral information to extract endmembers,but ignore the spatial characteristics of remote sensing images.Therefore,the endmember extraction algorithm without spatial information is sensitive to noise and abnormal signals,which leads to the reduction of endmember extraction precision,so the error will be transferred to sub-pixel mapping process.This paper proposes an endmember extraction algorithm based on orthogonal subspace and local spatial correlation to solve this problem.The algorithm uses spatial information to determine,update and extend the extracted endmembers,thus ensuring the effectiveness of endmember extraction algorithm and providing accurate abundance for subpixel mapping.Secondly,thermal infrared remote sensing images contain abundant information about temperature and emissivity.Through the study and analysis of the traditional temperature inversion algorithm,a sub-pixel temperature inversion algorithm is proposed to get temperature information of each component in mixed pixels.The algorithm uses the abundance information to distinguish the pure pixels and the mixed pixels,and processes them separately.For pure pixels,the traditional temperature emissivity separation algorithm is used to achieve the estimation of temperature and emissivity.For mixed pixels,the algorithm is based on the linear mixed model of atmospheric bottom radiation,and solves the temperature of different components in mixed pixels.This part realizes the sub-pixel temperature retrieval of thermal infrared image,and provides the surface temperature information for sub-pixel mapping.Finally,a complete mapping algorithm of abundance and temperature is proposed,combining the advantages of visible / near infrared remote sensing images and thermal infrared remote sensing images.The algorithm uses the spatial information of the remote sensing image abundance in the visible band to estimate the abundance of the pixels in the pixels to get the localization of the pure pixels and the mixed pixels.Using the temperature information provided by the thermal infrared band,the temperature and radiance information of the pure pixels and the mixed pixels are retrieved by combining the obtained abundances.In sub-pixel mapping,the algorithm uses pixel attraction model to allocate and adjust sub-pixel spatial location,so that the mapping results are more consistent with the distribution of real objects.