Fine-grained sediments are Quaternary sediments with grain sizes of not more than 2 mm.They startfirst when meeting water,their stability is related to the initial water volume triggering debrisflow,and thus plays an ...Fine-grained sediments are Quaternary sediments with grain sizes of not more than 2 mm.They startfirst when meeting water,their stability is related to the initial water volume triggering debrisflow,and thus plays an important role in debrisflow hazards early warning.The permeability coefficient is the inter-controlled factor offine-grained sediment stability.However,there is no hyperspectral model for detecting thefine-grained sediment permeability coefficient in large areas,which seriously affects the progress of debrisflow hazards early warning.Therefore,it is of great significance to establish a hyperspectral detection model for the permeability coefficient offine-grained sediments.Taking Beichuan County,Southwestern China as the case,a permeability coefficient hyperspectral detection model was established.The results show that eight bands are sensitive to the permeability coefficient with correlation coefficient(R)of 0.6343.T-test on the model shows that P-a values for sensitive bands are all less than 0.05,indicating the established model has a good prediction ability with a precision of 85.83%.These sensitive bands also indicate the spectral characteristics of the permeability coefficient.Therefore,it provides a scientific basis forfine-grained sediment stability detection in large areas and lays a theoretical foundation for debrisflow hazards’early warning.展开更多
Hyperspectral images(HSI)provide a new way to exploit the internal physical composition of the land scene.The basic platform for acquiring HSI data-sets are airborne or spaceborne spectral imaging.Retrieving useful in...Hyperspectral images(HSI)provide a new way to exploit the internal physical composition of the land scene.The basic platform for acquiring HSI data-sets are airborne or spaceborne spectral imaging.Retrieving useful information from hyperspectral images can be grouped into four categories.(1)Classification:Hyperspectral images provide so much spectral and spatial information that remotely sensed image classification has become a complex task.(2)Endmember extraction and spectral unmixing:Among images,only HSI have a complete model to represent the internal structure of each pixel where the endmembers are the elements.Identification of endmembers from HSI thus becomes the foremost step in interpretation of each pixel.With proper endmembers,the corresponding abundances can also be exactly calculated.(3)Target detection:Another practical problem is how to determine the existence of certain resolved or full pixel objects from a complex background.Constructing a reliable rule for separating target signals from all the other background signals,even in the case of low target occurrence and high spectral variation,comprises the key to this problem.(4)Change detection:Although change detection is not a new problem,detecting changes from hyperspectral images has brought new challenges,since the spectral bands are so many,accurate band-to-band correspondences and minor changes in subclass land objects can be depicted in HSI.In this paper,the basic theory and the most canonical works are discussed,along with the most recent advances in each aspect of hyperspectral image processing.展开更多
基金funded in part by the Innovative Research Program of the International Research Center of Big Data for Sustainable Development Goals[grant number CBAS2022IRP03]the National Natural Science Foundation of China[grant number 42071312]the Hainan Hundred Special Project[grant number 31,JTT[2018]].
文摘Fine-grained sediments are Quaternary sediments with grain sizes of not more than 2 mm.They startfirst when meeting water,their stability is related to the initial water volume triggering debrisflow,and thus plays an important role in debrisflow hazards early warning.The permeability coefficient is the inter-controlled factor offine-grained sediment stability.However,there is no hyperspectral model for detecting thefine-grained sediment permeability coefficient in large areas,which seriously affects the progress of debrisflow hazards early warning.Therefore,it is of great significance to establish a hyperspectral detection model for the permeability coefficient offine-grained sediments.Taking Beichuan County,Southwestern China as the case,a permeability coefficient hyperspectral detection model was established.The results show that eight bands are sensitive to the permeability coefficient with correlation coefficient(R)of 0.6343.T-test on the model shows that P-a values for sensitive bands are all less than 0.05,indicating the established model has a good prediction ability with a precision of 85.83%.These sensitive bands also indicate the spectral characteristics of the permeability coefficient.Therefore,it provides a scientific basis forfine-grained sediment stability detection in large areas and lays a theoretical foundation for debrisflow hazards’early warning.
基金This work was supported in part by the National Basic Research Program of China(973 Program)under Grant 2012CB719905 and 2011CB707105the National Natural Science Foundation of China under Grant 61102128+2 种基金HuBei Province Natural Science Foundation under Grant No.2011CDB455China’s Post-doctoral Science Foundation under 211–180,788the Fundamental Research Funds for the Central Universities under 211-274633.
文摘Hyperspectral images(HSI)provide a new way to exploit the internal physical composition of the land scene.The basic platform for acquiring HSI data-sets are airborne or spaceborne spectral imaging.Retrieving useful information from hyperspectral images can be grouped into four categories.(1)Classification:Hyperspectral images provide so much spectral and spatial information that remotely sensed image classification has become a complex task.(2)Endmember extraction and spectral unmixing:Among images,only HSI have a complete model to represent the internal structure of each pixel where the endmembers are the elements.Identification of endmembers from HSI thus becomes the foremost step in interpretation of each pixel.With proper endmembers,the corresponding abundances can also be exactly calculated.(3)Target detection:Another practical problem is how to determine the existence of certain resolved or full pixel objects from a complex background.Constructing a reliable rule for separating target signals from all the other background signals,even in the case of low target occurrence and high spectral variation,comprises the key to this problem.(4)Change detection:Although change detection is not a new problem,detecting changes from hyperspectral images has brought new challenges,since the spectral bands are so many,accurate band-to-band correspondences and minor changes in subclass land objects can be depicted in HSI.In this paper,the basic theory and the most canonical works are discussed,along with the most recent advances in each aspect of hyperspectral image processing.