We estimate tree heights using polarimetric interferometric synthetic aperture radar(PolInSAR)data constructed by the dual-polarization(dual-pol)SAR data and random volume over the ground(RVoG)model.Considering the Se...We estimate tree heights using polarimetric interferometric synthetic aperture radar(PolInSAR)data constructed by the dual-polarization(dual-pol)SAR data and random volume over the ground(RVoG)model.Considering the Sentinel-1 SAR dual-pol(SVV,vertically transmitted and vertically received and SVH,vertically transmitted and horizontally received)configuration,one notes that S_(HH),the horizontally transmitted and horizontally received scattering element,is unavailable.The S_(HH)data were constructed using the SVH data,and polarimetric SAR(PolSAR)data were obtained.The proposed approach was first verified in simulation with satisfactory results.It was next applied to construct PolInSAR data by a pair of dual-pol Sentinel-1A data at Duke Forest,North Carolina,USA.According to local observations and forest descriptions,the range of estimated tree heights was overall reasonable.Comparing the heights with the ICESat-2 tree heights at 23 sampling locations,relative errors of 5 points were within±30%.Errors of 8 points ranged from 30%to 40%,but errors of the remaining 10 points were>40%.The results should be encouraged as error reduction is possible.For instance,the construction of PolSAR data should not be limited to using SVH,and a combination of SVH and SVV should be explored.Also,an ensemble of tree heights derived from multiple PolInSAR data can be considered since tree heights do not vary much with time frame in months or one season.展开更多
In this paper, the IHSL transform and the Fuzzy C-Means (FCM) segmentation algorithm are combined together to perform the unsupervised classification for fully polarimetric Synthetic Ap-erture Rader (SAR) data. We app...In this paper, the IHSL transform and the Fuzzy C-Means (FCM) segmentation algorithm are combined together to perform the unsupervised classification for fully polarimetric Synthetic Ap-erture Rader (SAR) data. We apply the IHSL colour transform to H/α/SPANspace to obtain a new space (RGB colour space) which has a uniform distinguishability among inner parameters and contains the whole polarimetric information in H/α/SPAN.Then the FCM algorithm is applied to this RGB space to finish the classification procedure. The main advantages of this method are that the parameters in the color space have similar interclass distinguishability, thus it can achieve a high performance in the pixel based segmentation algorithm, and since we can treat the parameters in the same way, the segmentation procedure can be simplified. The experiments show that it can provide an improved classification result compared with the method which uses the H/α/SPANspace di-rectly during the segmentation procedure.展开更多
The purpose of this paper is to study about the interrelationship between the backscattering intensity of PALSAR data and the laboratory measurement of dielectric constant and soil moisture. The characterization of th...The purpose of this paper is to study about the interrelationship between the backscattering intensity of PALSAR data and the laboratory measurement of dielectric constant and soil moisture. The characterization of the dielectric constant of arid soils in the 0.3 - 3 GHz frequency range, particularly focused in L-band was analyzed in varied soil moisture content and soil textures. The interrelationship between the relative dielectric constant with soil textures and backscattering of PALSAR data was also analyzed and statistical model was computed. In this study, after collecting the soil samples in the field from top soil (0 - 10 cm) in a homogeneous area then, the dielectric constant was measured using a dielectric probe tool kit. For investigated of the characteristics and behaviors of the dielectric constant and relationship with backscattering a variety of moisture content from 0% to 40% and soil fraction conditions was tested in laboratory condition. All data were analyzed by integrating it with other geophysical data in GIS, such as land cover and soil texture. Thus, the regression model computed between measured soil moisture and backscattering coefficient of PALSR data which were extracted as same point of each soil sample pixel. Finally, after completing the preprocessing, such as removing the speckle noise by averaging, the model was applied to the PALSAR data for retrieving the soil moisture map in arid region of Iran. The analysis of dielectric constant properties result has shown the soil texture after the moisture content has the largest effected on dielectric constant. In addition, the PALSAR data in dual polarization are also able to derive the soil moisture using statistical method. The dielectric constant and backscattering shown have the exponential relationship and the HV polarization mode is more sensitive than the HH mode to soil moisture and overestimated the soil moisture as well. The validation of result has shown the 4.2 Vol-% RMSE of soil moisture. It means that the backscattering analysis should consider about other factors such a surface roughness and mix pixel of vegetation effective.展开更多
As an important advanced technique in the field of Earth observations,Synthetic Aperture Radar(SAR)plays a key role in the study of global environmental change,resources exploration,disaster mitigation,urban environme...As an important advanced technique in the field of Earth observations,Synthetic Aperture Radar(SAR)plays a key role in the study of global environmental change,resources exploration,disaster mitigation,urban environments,and even lunar exploration.However,studies on imaging,image processing,and Earth factor inversions have often been conducted independently for a long time,which significantly limits the application effectiveness of SAR remote sensing due to the lack of an overall integrated design scheme and integrated information processing.Focusing on this SAR application issue,this paper proposes and describes a new SAR data processing methodology–SAR data integrated processing(DIP)oriented on Earth environment factor inversions.The simple definition,typical integrated modes and overall implementation ideas are introduced.Finally,focusing on building information extraction(man-made targets)and sea ice classification(natural targets)applications,three SAR DIP methods and experiments are conducted.Improved results are obtained under the guidance of the SAR DIP framework.Therefore,the SAR DIP theoretical framework and methodology represent a new SAR science application mode that has the capability to improve the SAR remote sensing quantitative application level and promote the development of new theories and methodologies.展开更多
Synthetic aperture radar (SAR) is portrayed as a multiple access channel. An information theory approach is applied to the SAR imaging system, and the information content about a target that can be extracted from its ...Synthetic aperture radar (SAR) is portrayed as a multiple access channel. An information theory approach is applied to the SAR imaging system, and the information content about a target that can be extracted from its radar image is evaluated by the average mutual information measure. A conditional (transition) probability density function (PDF) of the SAR imaging system is derived by analyzing the system and a closed form of the information content is found. It is shown that the information content obtained by the SAR imaging system from an independent sample of echoes will decrease and the total information content obtained by the SAR imaging system will increase with an increase in the number of looks. Because the total average mutual information is also used to define a measure of radiometric resolution for radar images, it is shown that the radiometric resolution of a radar image of terrain will be improved by spatial averaging. In addition, the imaging process and the data compression process for SAR are each treated as an independent generalized communication channel. The effects of data compression upon radiometric resolution for SAR are studied and some conclusions are obtained.展开更多
文摘We estimate tree heights using polarimetric interferometric synthetic aperture radar(PolInSAR)data constructed by the dual-polarization(dual-pol)SAR data and random volume over the ground(RVoG)model.Considering the Sentinel-1 SAR dual-pol(SVV,vertically transmitted and vertically received and SVH,vertically transmitted and horizontally received)configuration,one notes that S_(HH),the horizontally transmitted and horizontally received scattering element,is unavailable.The S_(HH)data were constructed using the SVH data,and polarimetric SAR(PolSAR)data were obtained.The proposed approach was first verified in simulation with satisfactory results.It was next applied to construct PolInSAR data by a pair of dual-pol Sentinel-1A data at Duke Forest,North Carolina,USA.According to local observations and forest descriptions,the range of estimated tree heights was overall reasonable.Comparing the heights with the ICESat-2 tree heights at 23 sampling locations,relative errors of 5 points were within±30%.Errors of 8 points ranged from 30%to 40%,but errors of the remaining 10 points were>40%.The results should be encouraged as error reduction is possible.For instance,the construction of PolSAR data should not be limited to using SVH,and a combination of SVH and SVV should be explored.Also,an ensemble of tree heights derived from multiple PolInSAR data can be considered since tree heights do not vary much with time frame in months or one season.
文摘In this paper, the IHSL transform and the Fuzzy C-Means (FCM) segmentation algorithm are combined together to perform the unsupervised classification for fully polarimetric Synthetic Ap-erture Rader (SAR) data. We apply the IHSL colour transform to H/α/SPANspace to obtain a new space (RGB colour space) which has a uniform distinguishability among inner parameters and contains the whole polarimetric information in H/α/SPAN.Then the FCM algorithm is applied to this RGB space to finish the classification procedure. The main advantages of this method are that the parameters in the color space have similar interclass distinguishability, thus it can achieve a high performance in the pixel based segmentation algorithm, and since we can treat the parameters in the same way, the segmentation procedure can be simplified. The experiments show that it can provide an improved classification result compared with the method which uses the H/α/SPANspace di-rectly during the segmentation procedure.
文摘The purpose of this paper is to study about the interrelationship between the backscattering intensity of PALSAR data and the laboratory measurement of dielectric constant and soil moisture. The characterization of the dielectric constant of arid soils in the 0.3 - 3 GHz frequency range, particularly focused in L-band was analyzed in varied soil moisture content and soil textures. The interrelationship between the relative dielectric constant with soil textures and backscattering of PALSAR data was also analyzed and statistical model was computed. In this study, after collecting the soil samples in the field from top soil (0 - 10 cm) in a homogeneous area then, the dielectric constant was measured using a dielectric probe tool kit. For investigated of the characteristics and behaviors of the dielectric constant and relationship with backscattering a variety of moisture content from 0% to 40% and soil fraction conditions was tested in laboratory condition. All data were analyzed by integrating it with other geophysical data in GIS, such as land cover and soil texture. Thus, the regression model computed between measured soil moisture and backscattering coefficient of PALSR data which were extracted as same point of each soil sample pixel. Finally, after completing the preprocessing, such as removing the speckle noise by averaging, the model was applied to the PALSAR data for retrieving the soil moisture map in arid region of Iran. The analysis of dielectric constant properties result has shown the soil texture after the moisture content has the largest effected on dielectric constant. In addition, the PALSAR data in dual polarization are also able to derive the soil moisture using statistical method. The dielectric constant and backscattering shown have the exponential relationship and the HV polarization mode is more sensitive than the HH mode to soil moisture and overestimated the soil moisture as well. The validation of result has shown the 4.2 Vol-% RMSE of soil moisture. It means that the backscattering analysis should consider about other factors such a surface roughness and mix pixel of vegetation effective.
基金This study was supported by the Key project of National Natural Science Foundation of China(No.61132006)the Major project of National Natural Science Foundation of China(No.41590852).
文摘As an important advanced technique in the field of Earth observations,Synthetic Aperture Radar(SAR)plays a key role in the study of global environmental change,resources exploration,disaster mitigation,urban environments,and even lunar exploration.However,studies on imaging,image processing,and Earth factor inversions have often been conducted independently for a long time,which significantly limits the application effectiveness of SAR remote sensing due to the lack of an overall integrated design scheme and integrated information processing.Focusing on this SAR application issue,this paper proposes and describes a new SAR data processing methodology–SAR data integrated processing(DIP)oriented on Earth environment factor inversions.The simple definition,typical integrated modes and overall implementation ideas are introduced.Finally,focusing on building information extraction(man-made targets)and sea ice classification(natural targets)applications,three SAR DIP methods and experiments are conducted.Improved results are obtained under the guidance of the SAR DIP framework.Therefore,the SAR DIP theoretical framework and methodology represent a new SAR science application mode that has the capability to improve the SAR remote sensing quantitative application level and promote the development of new theories and methodologies.
文摘Synthetic aperture radar (SAR) is portrayed as a multiple access channel. An information theory approach is applied to the SAR imaging system, and the information content about a target that can be extracted from its radar image is evaluated by the average mutual information measure. A conditional (transition) probability density function (PDF) of the SAR imaging system is derived by analyzing the system and a closed form of the information content is found. It is shown that the information content obtained by the SAR imaging system from an independent sample of echoes will decrease and the total information content obtained by the SAR imaging system will increase with an increase in the number of looks. Because the total average mutual information is also used to define a measure of radiometric resolution for radar images, it is shown that the radiometric resolution of a radar image of terrain will be improved by spatial averaging. In addition, the imaging process and the data compression process for SAR are each treated as an independent generalized communication channel. The effects of data compression upon radiometric resolution for SAR are studied and some conclusions are obtained.
