The concept of stochastic resonance (SR) has been introduced into the analysis of satellite thermal infrared images. Six kinds of anomalous phenomena related to crustal movement were recognized in satellite thermal in...The concept of stochastic resonance (SR) has been introduced into the analysis of satellite thermal infrared images. Six kinds of anomalous phenomena related to crustal movement were recognized in satellite thermal infrared images. Six diagnostic indicators for the prediction of global earthquakes with magnitude ≥6.0 and their quantitative evaluation standards have been established. The microscopic behavior of global crustal movement is successfully controlled by using satellite thermal infrared imagery, and the occurrence time and magnitude of over 80% of global strong earthquakes occurred since the foundation of the observation station have been successfully predicted. It is believed that the combination of satellite thermal infrared information with macroscopic anomalous phenomena will play an important role in earthquake hazard reduction.展开更多
Understanding forest health is of great importance for the conservation of the integrity of forest ecosystems.The monitoring of forest health is,therefore,indispensable for the long-term conservation of forests and th...Understanding forest health is of great importance for the conservation of the integrity of forest ecosystems.The monitoring of forest health is,therefore,indispensable for the long-term conservation of forests and their sustainable management.In this regard,evaluating the amount and quality of dead wood is of utmost interest as they are favorable indicators of biodiversity.Apparently,remote sensing-based Machine Learning(ML)techniques have proven to be more efficient and sustainable with unprecedented accuracy in forest inventory.However,the application of these techniques is still in its infancy with respect to dead wood mapping.This study,for the first time,automatically categorizing individual coniferous trees(Norway spruce)into five decay stages(live,declining,dead,loose bark,and clean)from combined Airborne Laser Scanning(ALS)point clouds and color infrared(CIR)images using three different ML methods−3D point cloud-based deep learning(KPConv),Convolutional Neural Network(CNN),and Random Forest(RF).First,CIR colorized point clouds are created by fusing the ALS point clouds and color infrared images.Then,individual tree segmentation is conducted,after which the results are further projected onto four orthogonal planes.Finally,the classification is conducted on the two datasets(3D multispectral point clouds and 2D projected images)based on the three ML algorithms.All models achieved promising results,reaching overall accuracy(OA)of up to 88.8%,88.4%and 85.9%for KPConv,CNN and RF,respectively.The experimental results reveal that color information,3D coordinates,and intensity of point clouds have significant impact on the promising classification performance.The performance of our models,therefore,shows the significance of machine/deep learning for individual tree decay stages classification and landscape-wide assessment of the dead wood amount and quality by using modern airborne remote sensing techniques.The proposed method can contribute as an important and reliable tool for monitoring biodiversity in forest ecosystems.展开更多
A general review is presented of the development of infrared scene targetsimulators; special characters and advantages of scene simulators based on computer-MOSresistor array are discussed by comparing with scaled mod...A general review is presented of the development of infrared scene targetsimulators; special characters and advantages of scene simulators based on computer-MOSresistor array are discussed by comparing with scaled model simulators; the system principle, structure, key technologies, software and hardware implementation are described.展开更多
This paper introduces a sliding-window mean removal high pass filter by which background clutter of infrared multispectral image is obtained. The method of selecting the optimum size of the sliding-window is based on ...This paper introduces a sliding-window mean removal high pass filter by which background clutter of infrared multispectral image is obtained. The method of selecting the optimum size of the sliding-window is based on the skewness-kurtosis test. In the end, a multivariate Gaussian distribution mathematical expression of background clutter image is given.展开更多
Thermal infrared satellite imagery is increasingly utilized in permafrost studies.One useful application of the land surface temperature(LST)products is classification and mapping of landscapes in permafrost regions,a...Thermal infrared satellite imagery is increasingly utilized in permafrost studies.One useful application of the land surface temperature(LST)products is classification and mapping of landscapes in permafrost regions,as LST values can help differentiate between frozen and unfrozen ground.This article describes a new approach to the use of LST.The essence of the new approach lies in the fact that in the territory where it is impossible to determine(indicate)the state of the underlying ground according to the same morphological characteristics(relief,vegetation,soil composition,etc.),the LST parameter,which reflects the thermal state of the landscape,allows as an additional criterion(indicator)identify frozen/un-frozen landscapes.In this work,using the above approach,a map has been compiled,which shows the permafrost natural-territorial complexes of the Elkon Massif,Eastern Siberia,including topography,slope aspect,slope angle,vegetation,snow cover and LST.The map provides a more detailed and updated description of permafrost distribution in the study area.展开更多
Investigating urban expansion patterns aids in the management of urbanization and in ameliorating the socioeconomic and environmental issues associated with economic transformation and sustainable development.Applying...Investigating urban expansion patterns aids in the management of urbanization and in ameliorating the socioeconomic and environmental issues associated with economic transformation and sustainable development.Applying Harmonized Defense Meteorological Satellite Program-Operational Line-scan System(DMSP-OLS)and the Suomi National Polar-Orbiting Partnership-Visible Infrared Imagery Radiometer Suite(NPP-VIIRS)Nighttime Light(NTL)data,this paper investigated the characteristics of urban landscape in West Africa.Using the harmonized NTL data,spatial comparison and empirical threshold methods were employed to detect urban changes from 1993 to 2018.We examined the rate of urban change and calculated the direction of the urban expansion of West Africa using the center-of-gravity method for urban areas.In addition,we used the landscape expansion index method to assess the processes and stages of urban growth in West Africa.The accuracy of urban area extraction based on NTL data were R^(2)=0.8314 in 2000,R^(2)=0.8809 in 2006,R^(2)=0.9051 in 2012 for the DMSP-OLS and the simulated NPP-VIIRS was R^(2)=0.8426 in 2018,by using Google Earth images as validation.The results indicated that there was a high rate and acceleration of urban landscapes in West Africa,with rates of 0.0160,0.0173,0.0189,and 0.0686,and accelerations of 0.31,0.42,0.54,and 0.90 for the periods of 1998–2003,2003–2008,2008–2013,and 2013–2018,respectively.The expansion direction of urban agglomeration in West Africa during 1993–2018 was mainly from the coast to inland.However,cities located in the Sahel Region of Africa and in the middle zone expanded from north to south.Finally,the results showed that the urban landscape of West Africa was mainly in a scattered and disordered’diffusion’process,whereas only a few cities located in coastal areas experiencing the process of’coalescence’according to urban growth phase theory.This study provides urban planners with relevant insights for the urban expansion characteristics of West Africa.展开更多
Infrared signatures of aircraft are the basis for detection and monitoring. In past years, most of the studies focused on the aircraft＇s infrared signature in the mid-wave spectral region and long-wave spectral regio...Infrared signatures of aircraft are the basis for detection and monitoring. In past years, most of the studies focused on the aircraft＇s infrared signature in the mid-wave spectral region and long-wave spectral region for missile guidance or aircraft survivability studies. For the security of civil aviation, methods and instruments that can detect and monitor aircrafts from space are expected to be developed in the coming years. A short-wave infrared hyperspectral imager aboard the Tiangong-1 spacecraft acquired some civil aircraft＇s spectral data. The differences between the aircraft and the background in their spectral signatures are analyzed and discussed. Less absorption in the vapor absorption bands and a reflection spike is discovered at the 1.84 μm spectral band. The result shows that 1.84 μm and other vapor absorption bands can make contributions to aircraft detection in the daytime.展开更多
文摘The concept of stochastic resonance (SR) has been introduced into the analysis of satellite thermal infrared images. Six kinds of anomalous phenomena related to crustal movement were recognized in satellite thermal infrared images. Six diagnostic indicators for the prediction of global earthquakes with magnitude ≥6.0 and their quantitative evaluation standards have been established. The microscopic behavior of global crustal movement is successfully controlled by using satellite thermal infrared imagery, and the occurrence time and magnitude of over 80% of global strong earthquakes occurred since the foundation of the observation station have been successfully predicted. It is believed that the combination of satellite thermal infrared information with macroscopic anomalous phenomena will play an important role in earthquake hazard reduction.
基金supported by the National Natural Science Foundation of China[Grant No.42171361]the Research Grants Council of the Hong Kong Special Administrative Region,China[Grant No.PolyU 25211819]supported by The Hong Kong Polytechnic University,China[Grant No.1-ZVN6,1-ZECE].
文摘Understanding forest health is of great importance for the conservation of the integrity of forest ecosystems.The monitoring of forest health is,therefore,indispensable for the long-term conservation of forests and their sustainable management.In this regard,evaluating the amount and quality of dead wood is of utmost interest as they are favorable indicators of biodiversity.Apparently,remote sensing-based Machine Learning(ML)techniques have proven to be more efficient and sustainable with unprecedented accuracy in forest inventory.However,the application of these techniques is still in its infancy with respect to dead wood mapping.This study,for the first time,automatically categorizing individual coniferous trees(Norway spruce)into five decay stages(live,declining,dead,loose bark,and clean)from combined Airborne Laser Scanning(ALS)point clouds and color infrared(CIR)images using three different ML methods−3D point cloud-based deep learning(KPConv),Convolutional Neural Network(CNN),and Random Forest(RF).First,CIR colorized point clouds are created by fusing the ALS point clouds and color infrared images.Then,individual tree segmentation is conducted,after which the results are further projected onto four orthogonal planes.Finally,the classification is conducted on the two datasets(3D multispectral point clouds and 2D projected images)based on the three ML algorithms.All models achieved promising results,reaching overall accuracy(OA)of up to 88.8%,88.4%and 85.9%for KPConv,CNN and RF,respectively.The experimental results reveal that color information,3D coordinates,and intensity of point clouds have significant impact on the promising classification performance.The performance of our models,therefore,shows the significance of machine/deep learning for individual tree decay stages classification and landscape-wide assessment of the dead wood amount and quality by using modern airborne remote sensing techniques.The proposed method can contribute as an important and reliable tool for monitoring biodiversity in forest ecosystems.
文摘A general review is presented of the development of infrared scene targetsimulators; special characters and advantages of scene simulators based on computer-MOSresistor array are discussed by comparing with scaled model simulators; the system principle, structure, key technologies, software and hardware implementation are described.
文摘This paper introduces a sliding-window mean removal high pass filter by which background clutter of infrared multispectral image is obtained. The method of selecting the optimum size of the sliding-window is based on the skewness-kurtosis test. In the end, a multivariate Gaussian distribution mathematical expression of background clutter image is given.
文摘Thermal infrared satellite imagery is increasingly utilized in permafrost studies.One useful application of the land surface temperature(LST)products is classification and mapping of landscapes in permafrost regions,as LST values can help differentiate between frozen and unfrozen ground.This article describes a new approach to the use of LST.The essence of the new approach lies in the fact that in the territory where it is impossible to determine(indicate)the state of the underlying ground according to the same morphological characteristics(relief,vegetation,soil composition,etc.),the LST parameter,which reflects the thermal state of the landscape,allows as an additional criterion(indicator)identify frozen/un-frozen landscapes.In this work,using the above approach,a map has been compiled,which shows the permafrost natural-territorial complexes of the Elkon Massif,Eastern Siberia,including topography,slope aspect,slope angle,vegetation,snow cover and LST.The map provides a more detailed and updated description of permafrost distribution in the study area.
基金Under the auspices of National Natural Science Foundation of China(No.41971202)。
文摘Investigating urban expansion patterns aids in the management of urbanization and in ameliorating the socioeconomic and environmental issues associated with economic transformation and sustainable development.Applying Harmonized Defense Meteorological Satellite Program-Operational Line-scan System(DMSP-OLS)and the Suomi National Polar-Orbiting Partnership-Visible Infrared Imagery Radiometer Suite(NPP-VIIRS)Nighttime Light(NTL)data,this paper investigated the characteristics of urban landscape in West Africa.Using the harmonized NTL data,spatial comparison and empirical threshold methods were employed to detect urban changes from 1993 to 2018.We examined the rate of urban change and calculated the direction of the urban expansion of West Africa using the center-of-gravity method for urban areas.In addition,we used the landscape expansion index method to assess the processes and stages of urban growth in West Africa.The accuracy of urban area extraction based on NTL data were R^(2)=0.8314 in 2000,R^(2)=0.8809 in 2006,R^(2)=0.9051 in 2012 for the DMSP-OLS and the simulated NPP-VIIRS was R^(2)=0.8426 in 2018,by using Google Earth images as validation.The results indicated that there was a high rate and acceleration of urban landscapes in West Africa,with rates of 0.0160,0.0173,0.0189,and 0.0686,and accelerations of 0.31,0.42,0.54,and 0.90 for the periods of 1998–2003,2003–2008,2008–2013,and 2013–2018,respectively.The expansion direction of urban agglomeration in West Africa during 1993–2018 was mainly from the coast to inland.However,cities located in the Sahel Region of Africa and in the middle zone expanded from north to south.Finally,the results showed that the urban landscape of West Africa was mainly in a scattered and disordered’diffusion’process,whereas only a few cities located in coastal areas experiencing the process of’coalescence’according to urban growth phase theory.This study provides urban planners with relevant insights for the urban expansion characteristics of West Africa.
基金supported by the Innovation Funds from Chinese Academy of SciencesChinese Manned Space Engineering, who funded the R&D of the high-resolution hyperspectral imager
文摘Infrared signatures of aircraft are the basis for detection and monitoring. In past years, most of the studies focused on the aircraft＇s infrared signature in the mid-wave spectral region and long-wave spectral region for missile guidance or aircraft survivability studies. For the security of civil aviation, methods and instruments that can detect and monitor aircrafts from space are expected to be developed in the coming years. A short-wave infrared hyperspectral imager aboard the Tiangong-1 spacecraft acquired some civil aircraft＇s spectral data. The differences between the aircraft and the background in their spectral signatures are analyzed and discussed. Less absorption in the vapor absorption bands and a reflection spike is discovered at the 1.84 μm spectral band. The result shows that 1.84 μm and other vapor absorption bands can make contributions to aircraft detection in the daytime.
