GF-14 satellite is a new generation of sub-meter stereo surveying and mapping satellite in China,carrying dual-line array stereo mapping cameras to achieve 1∶10000 scale topographic mapping without Ground Control Poi...GF-14 satellite is a new generation of sub-meter stereo surveying and mapping satellite in China,carrying dual-line array stereo mapping cameras to achieve 1∶10000 scale topographic mapping without Ground Control Points(GCPs).In fact,space-based high-precision mapping without GCPs is a challenging task that depends on the close cooperation of several payloads and links,of which on-orbit geometric calibration is one of the most critical links.In this paper,the on-orbit geometric calibration of the dual-line array cameras of GF-14 satellite was performed using the control points collected in the high-precision digital calibration field,and the calibration parameters of the dual-line array cameras were solved as a whole by alternate iterations of forward and backward intersection.On this basis,the location accuracy of the stereo images using the calibration parameters was preliminarily evaluated by using several test fields around the world.The evaluation result shows that the direct forward intersection accuracy of GF-14 satellite images without GCPs after on-orbit geometric calibration reaches 2.34 meters(RMS)in plane and 1.97 meters(RMS)in elevation.展开更多
Various land use and land cover(LULC)products have been produced over the past decade with the development of remote sensing technology.Despite the differences in LULC classification schemes,there is a lack of researc...Various land use and land cover(LULC)products have been produced over the past decade with the development of remote sensing technology.Despite the differences in LULC classification schemes,there is a lack of research on assessing the accuracy of their application to croplands in a unified framework.Thus,this study evaluated the spatial and area accuracies of cropland classification for four commonly used global LULC products(i.e.,MCD12Q1V6,GlobCover2009,FROM-GLC and GlobeLand30)based on the harmonised FAO criterion,and quantified the relationships between four factors(i.e.,slope,elevation,field size and crop system)and cropland classification agreement.The validation results indicated that MCD12Q1 and GlobeLand30 performed well in cropland classification regarding spatial consistency,with overall accuracies of 94.90 and 93.52%,respectively.The FROMGLC showed the worst performance,with an overall accuracy of 83.17%.Overlaying the cropland generated by the four global LULC products,we found the proportions of complete agreement and disagreement were 15.51 and 44.72% for the cropland classification,respectively.High consistency was mainly observed in the Northeast China Plain,the Huang-Huai-Hai Plain and the northern part of the Middle-lower Yangtze Plain,China.In contrast,low consistency was detected primarily on the eastern edge of the northern and semiarid region,the Yunnan-Guizhou Plateau and southern China.Field size was the most important factor for mapping cropland.For area accuracy,compared with China Statistical Yearbook data at the provincial scale,the accuracies of different products in descending order were:GlobeLand30,FROM-GLC,MCD12Q1,and GlobCover2009.The cropland classification schemes mainly caused large area deviations among the four products,and they also resulted in the different ranks of spatial accuracy and area accuracy among the four products.Our results can provide valuable suggestions for selecting cropland products at the national or provincial scale and help cropland mapping and reconstruction,which is essential for food security and crop management,so they can also contribute to achieving the Sustainable Development Goals issued by the United Nations.展开更多
Ephemeral gullies are widely distributed in the hilly and gully region of the Loess Plateau and play a unique role in the slope gully erosion system.Rapid and accurate identification of ephemeral gullies impacts the d...Ephemeral gullies are widely distributed in the hilly and gully region of the Loess Plateau and play a unique role in the slope gully erosion system.Rapid and accurate identification of ephemeral gullies impacts the distribution law and development trend of soil erosion on the Loess Plateau.Deep learning algorithms can quickly and accurately process large data samples that recognize ephemeral gullies from remote sensing images.Here,we investigated ephemeral gullies in the Zhoutungou watershed in the hilly and gully region of the Loess Plateau in China using satellite and unmanned aerial vehicle images and combined a deep learning image semantic segmentation model to realize automatic recognition and feature extraction.Using Accuracy,Precision,Recall,F1value,and AUC,we compared the ephemeral gully recognition results and accuracy evaluation of U-Net,R2U-Net,and SegNet image semantic segmentation models.The SegNet model was ranked first,followed by the R2U-Net and U-Net models,for ephemeral gully recognition in the hilly and gully region of the Loess Plateau.The ephemeral gully length and width between predicted and measured values had RMSE values of 6.78 m and 0.50 m,respectively,indicating that the model has an excellent recognition effect.This study identified a fast and accurate method for ephemeral gully recognition in the hilly and gully region of the Loess Plateau based on remote sensing images to provide an academic reference and practical guidance for soil erosion monitoring and slope and gully management in the Loess Plateau region.展开更多
To solve the complex weight matrix derivative problem when using the weighted least squares method to estimate the parameters of the mixed additive and multiplicative random error model(MAM error model),we use an impr...To solve the complex weight matrix derivative problem when using the weighted least squares method to estimate the parameters of the mixed additive and multiplicative random error model(MAM error model),we use an improved artificial bee colony algorithm without derivative and the bootstrap method to estimate the parameters and evaluate the accuracy of MAM error model.The improved artificial bee colony algorithm can update individuals in multiple dimensions and improve the cooperation ability between individuals by constructing a new search equation based on the idea of quasi-affine transformation.The experimental results show that based on the weighted least squares criterion,the algorithm can get the results consistent with the weighted least squares method without multiple formula derivation.The parameter estimation and accuracy evaluation method based on the bootstrap method can get better parameter estimation and more reasonable accuracy information than existing methods,which provides a new idea for the theory of parameter estimation and accuracy evaluation of the MAM error model.展开更多
When multiple ground-based radars(GB-rads)are utilized together to resolve three-dimensional(3-D)deformations,the resolving accuracy is related with the measurement geometry constructed by these radars.This paper focu...When multiple ground-based radars(GB-rads)are utilized together to resolve three-dimensional(3-D)deformations,the resolving accuracy is related with the measurement geometry constructed by these radars.This paper focuses on constrained geometry analysis to resolve 3-D deformations from three GB-rads.The geometric dilution of precision(GDOP)is utilized to evaluate 3-D deformation accuracy of a single target,and its theoretical equation is derived by building a simplified 3-D coordinate system.Then for a 3-D scene,its optimal accuracy problem is converted into determining the minimum value of an objective function with a boundary constraint.The genetic algorithm is utilized to solve this constrained optimization problem.Numerical simulations are made to validate the correctness of the theoretical analysis results.展开更多
Most crops in northern China are irrigated,but the topography affects the water use,soil erosion,runoff and yields.Technologies for collecting high-resolution topographic data are essential for adequately assessing th...Most crops in northern China are irrigated,but the topography affects the water use,soil erosion,runoff and yields.Technologies for collecting high-resolution topographic data are essential for adequately assessing these effects.Ground surveys and techniques of light detection and ranging have good accuracy,but data acquisition can be time-consuming and expensive for large catchments.Recent rapid technological development has provided new,flexible,high-resolution methods for collecting topographic data,such as photogrammetry using unmanned aerial vehicles(UAVs).The accuracy of UAV photogrammetry for generating high-resolution Digital Elevation Model(DEM)and for determining the width of irrigation channels,however,has not been assessed.A fixed-wing UAV was used for collecting high-resolution(0.15 m)topographic data for the Hetao irrigation district,the third largest irrigation district in China.112 ground checkpoints(GCPs)were surveyed by using a real-time kinematic global positioning system to evaluate the accuracy of the DEMs and channel widths.A comparison of manually measured channel widths with the widths derived from the DEMs indicated that the DEM-derived widths had vertical and horizontal root mean square errors of 13.0 and 7.9 cm,respectively.UAV photogrammetric data can thus be used for land surveying,digital mapping,calculating channel capacity,monitoring crops,and predicting yields,with the advantages of economy,speed and ease.展开更多
In the past decades,global land cover datasets have been produced but also been criticized for their low accuracies,which have been affecting the applications of these datasets.Producing a new global dataset requires ...In the past decades,global land cover datasets have been produced but also been criticized for their low accuracies,which have been affecting the applications of these datasets.Producing a new global dataset requires a tremendous amount of efforts;however,it is also possible to improve the accuracy of global land cover mapping by fusing the existing datasets.A decision-fuse method was developed based on fuzzy logic to quantify the consistencies and uncertainties of the existing datasets and then aggregated to provide the most certain estimation.The method was applied to produce a 1-km global land cover map(SYNLCover)by integrating five global land cover datasets and three global datasets of tree cover and croplands.Efforts were carried out to assess the quality:1)inter-comparison of the datasets revealed that the SYNLCover dataset had higher consistency than these input global land cover datasets,suggesting that the data fusion method reduced the disagreement among the input datasets;2)quality assessment using the human-interpreted reference dataset reported the highest accuracy in the fused SYNLCover dataset,which had an overall accuracy of 71.1%,in contrast to the overall accuracy between 48.6%and 68.9%for the other global land cover datasets.展开更多
The measurement accuracy of the Mobile Mapping System (MMS) is the main problem, which restricts its development and application, so how to calibrate the MMS to improve its measure-ment accuracy has always been a rese...The measurement accuracy of the Mobile Mapping System (MMS) is the main problem, which restricts its development and application, so how to calibrate the MMS to improve its measure-ment accuracy has always been a research hotspot in the industry. This paper proposes a position and attitude calibration method with error correction based on the combination of the feature point and feature surface. First, the initial value of the spatial position relation-ship between each sensor of MMS is obtained by close-range photogrammetry. Second, the optimal solution for error correction is calculated by feature points in global coordinates jointly measured with International GNSS Service (IGS) stations. Then, the final transformation para-meters are solved by combining the initial values obtained originally, thereby realizing the rapid calibration of the MMS. Finally, it analyzed the RMSE of MMS point cloud after calibration, and the results demonstrate the feasibility of the calibration approach proposed by this method. Under the condition of a single measurement sensor accuracy is low, the plane and elevation absolute accuracy of the point cloud after calibration can reach 0.043 m and 0.072 m, respectively, and the relative accuracy is smaller than 0.02 m. It meets the precision require-ments of data acquisition for MMS. It is of great significance for promoting the development of MMS technology and the application of some novel techniques in the future, such as auton-omous driving, digital twin city, urban brain et al.展开更多
基金Independent Project of State Key Laboratory of Geo-information Engineering(SKLGIE2022-ZZ-01)The Youth Science Innovation Fund(No.2023-01)。
文摘GF-14 satellite is a new generation of sub-meter stereo surveying and mapping satellite in China,carrying dual-line array stereo mapping cameras to achieve 1∶10000 scale topographic mapping without Ground Control Points(GCPs).In fact,space-based high-precision mapping without GCPs is a challenging task that depends on the close cooperation of several payloads and links,of which on-orbit geometric calibration is one of the most critical links.In this paper,the on-orbit geometric calibration of the dual-line array cameras of GF-14 satellite was performed using the control points collected in the high-precision digital calibration field,and the calibration parameters of the dual-line array cameras were solved as a whole by alternate iterations of forward and backward intersection.On this basis,the location accuracy of the stereo images using the calibration parameters was preliminarily evaluated by using several test fields around the world.The evaluation result shows that the direct forward intersection accuracy of GF-14 satellite images without GCPs after on-orbit geometric calibration reaches 2.34 meters(RMS)in plane and 1.97 meters(RMS)in elevation.
基金supported by the National Key Research and Development Program of China(2022YFB3903503)the National Natural Science Foundation of China(U1901601)the Science and Technology Project of the Department of Education of Jiangxi Province,China(GJJ210541)。
文摘Various land use and land cover(LULC)products have been produced over the past decade with the development of remote sensing technology.Despite the differences in LULC classification schemes,there is a lack of research on assessing the accuracy of their application to croplands in a unified framework.Thus,this study evaluated the spatial and area accuracies of cropland classification for four commonly used global LULC products(i.e.,MCD12Q1V6,GlobCover2009,FROM-GLC and GlobeLand30)based on the harmonised FAO criterion,and quantified the relationships between four factors(i.e.,slope,elevation,field size and crop system)and cropland classification agreement.The validation results indicated that MCD12Q1 and GlobeLand30 performed well in cropland classification regarding spatial consistency,with overall accuracies of 94.90 and 93.52%,respectively.The FROMGLC showed the worst performance,with an overall accuracy of 83.17%.Overlaying the cropland generated by the four global LULC products,we found the proportions of complete agreement and disagreement were 15.51 and 44.72% for the cropland classification,respectively.High consistency was mainly observed in the Northeast China Plain,the Huang-Huai-Hai Plain and the northern part of the Middle-lower Yangtze Plain,China.In contrast,low consistency was detected primarily on the eastern edge of the northern and semiarid region,the Yunnan-Guizhou Plateau and southern China.Field size was the most important factor for mapping cropland.For area accuracy,compared with China Statistical Yearbook data at the provincial scale,the accuracies of different products in descending order were:GlobeLand30,FROM-GLC,MCD12Q1,and GlobCover2009.The cropland classification schemes mainly caused large area deviations among the four products,and they also resulted in the different ranks of spatial accuracy and area accuracy among the four products.Our results can provide valuable suggestions for selecting cropland products at the national or provincial scale and help cropland mapping and reconstruction,which is essential for food security and crop management,so they can also contribute to achieving the Sustainable Development Goals issued by the United Nations.
基金This research was supported by the National Natural Science Foundation of China(41977064)the Fundamental Research Funds for the Central Universities(2452021158+1 种基金2452021036)the 111 Project of the Ministry of Education and the State Administration of Foreign Experts Affairs(B12007)。
文摘Ephemeral gullies are widely distributed in the hilly and gully region of the Loess Plateau and play a unique role in the slope gully erosion system.Rapid and accurate identification of ephemeral gullies impacts the distribution law and development trend of soil erosion on the Loess Plateau.Deep learning algorithms can quickly and accurately process large data samples that recognize ephemeral gullies from remote sensing images.Here,we investigated ephemeral gullies in the Zhoutungou watershed in the hilly and gully region of the Loess Plateau in China using satellite and unmanned aerial vehicle images and combined a deep learning image semantic segmentation model to realize automatic recognition and feature extraction.Using Accuracy,Precision,Recall,F1value,and AUC,we compared the ephemeral gully recognition results and accuracy evaluation of U-Net,R2U-Net,and SegNet image semantic segmentation models.The SegNet model was ranked first,followed by the R2U-Net and U-Net models,for ephemeral gully recognition in the hilly and gully region of the Loess Plateau.The ephemeral gully length and width between predicted and measured values had RMSE values of 6.78 m and 0.50 m,respectively,indicating that the model has an excellent recognition effect.This study identified a fast and accurate method for ephemeral gully recognition in the hilly and gully region of the Loess Plateau based on remote sensing images to provide an academic reference and practical guidance for soil erosion monitoring and slope and gully management in the Loess Plateau region.
基金supported by the National Natural Science Foundation of China(No.42174011 and No.41874001).
文摘To solve the complex weight matrix derivative problem when using the weighted least squares method to estimate the parameters of the mixed additive and multiplicative random error model(MAM error model),we use an improved artificial bee colony algorithm without derivative and the bootstrap method to estimate the parameters and evaluate the accuracy of MAM error model.The improved artificial bee colony algorithm can update individuals in multiple dimensions and improve the cooperation ability between individuals by constructing a new search equation based on the idea of quasi-affine transformation.The experimental results show that based on the weighted least squares criterion,the algorithm can get the results consistent with the weighted least squares method without multiple formula derivation.The parameter estimation and accuracy evaluation method based on the bootstrap method can get better parameter estimation and more reasonable accuracy information than existing methods,which provides a new idea for the theory of parameter estimation and accuracy evaluation of the MAM error model.
基金supported by the National Natural Science Foundation of China(61960206009,61971037,31727901)the Natural Science Foundation of Chongqing+1 种基金China(2020jcyj-jq X0008)Chongqing Key Laboratory of Geological Environment Monitoring and Disaster Early-warning in Three Gorges Reservoir Area(ZD2020A0101)。
文摘When multiple ground-based radars(GB-rads)are utilized together to resolve three-dimensional(3-D)deformations,the resolving accuracy is related with the measurement geometry constructed by these radars.This paper focuses on constrained geometry analysis to resolve 3-D deformations from three GB-rads.The geometric dilution of precision(GDOP)is utilized to evaluate 3-D deformation accuracy of a single target,and its theoretical equation is derived by building a simplified 3-D coordinate system.Then for a 3-D scene,its optimal accuracy problem is converted into determining the minimum value of an objective function with a boundary constraint.The genetic algorithm is utilized to solve this constrained optimization problem.Numerical simulations are made to validate the correctness of the theoretical analysis results.
基金This work was financially supported by Major Project of National Key R&D Plan from the MOST of China(2017YFC0403203)National Natural Science Foundation of China(41771315,41301283,61402374,41371274,41301507)+2 种基金Natural Science Foundation of Shaanxi Province(2015JM4142)EU Horizon 2020 research and innovation programme(ISQAPER:635750)State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau(A314021402-1702).
文摘Most crops in northern China are irrigated,but the topography affects the water use,soil erosion,runoff and yields.Technologies for collecting high-resolution topographic data are essential for adequately assessing these effects.Ground surveys and techniques of light detection and ranging have good accuracy,but data acquisition can be time-consuming and expensive for large catchments.Recent rapid technological development has provided new,flexible,high-resolution methods for collecting topographic data,such as photogrammetry using unmanned aerial vehicles(UAVs).The accuracy of UAV photogrammetry for generating high-resolution Digital Elevation Model(DEM)and for determining the width of irrigation channels,however,has not been assessed.A fixed-wing UAV was used for collecting high-resolution(0.15 m)topographic data for the Hetao irrigation district,the third largest irrigation district in China.112 ground checkpoints(GCPs)were surveyed by using a real-time kinematic global positioning system to evaluate the accuracy of the DEMs and channel widths.A comparison of manually measured channel widths with the widths derived from the DEMs indicated that the DEM-derived widths had vertical and horizontal root mean square errors of 13.0 and 7.9 cm,respectively.UAV photogrammetric data can thus be used for land surveying,digital mapping,calculating channel capacity,monitoring crops,and predicting yields,with the advantages of economy,speed and ease.
基金Funding support for this work were provided by the following programs:the Strategic Priority Research Program of the Chinese Academy of Sciences[Grant No.XDA20100104]the Basic Resources Investigation of Science and Technology[Grant No.2017FY100900]and the National Earth System Science Data Sharing Infrastructure,National Science&Technology Infrastructure of China[Grant No.2005DKA32300].
文摘In the past decades,global land cover datasets have been produced but also been criticized for their low accuracies,which have been affecting the applications of these datasets.Producing a new global dataset requires a tremendous amount of efforts;however,it is also possible to improve the accuracy of global land cover mapping by fusing the existing datasets.A decision-fuse method was developed based on fuzzy logic to quantify the consistencies and uncertainties of the existing datasets and then aggregated to provide the most certain estimation.The method was applied to produce a 1-km global land cover map(SYNLCover)by integrating five global land cover datasets and three global datasets of tree cover and croplands.Efforts were carried out to assess the quality:1)inter-comparison of the datasets revealed that the SYNLCover dataset had higher consistency than these input global land cover datasets,suggesting that the data fusion method reduced the disagreement among the input datasets;2)quality assessment using the human-interpreted reference dataset reported the highest accuracy in the fused SYNLCover dataset,which had an overall accuracy of 71.1%,in contrast to the overall accuracy between 48.6%and 68.9%for the other global land cover datasets.
基金This research was funded by the National Natural Science Foundation of China[grant number 41971350 and 41571437]Beijing Advanced Innovation Centre for Future Urban Design Project[grant number UDC2019031724]+4 种基金Teacher Support Program for Pyramid Talent Training Project of Beijing University of Civil Engineering and Architecture[grant number JDJQ20200307]State Key Laboratory of Geo-Information Engineering[grant number SKLGIE2019-Z-3-1]Open Research Fund Program of LIESMARS[grant number 19E01]National Key Research and Development Program of China[grant number 2019YFC1520100]The Fundamental Research Funds for Beijing University of Civil Engineering and Architecture[grant number X18050].
文摘The measurement accuracy of the Mobile Mapping System (MMS) is the main problem, which restricts its development and application, so how to calibrate the MMS to improve its measure-ment accuracy has always been a research hotspot in the industry. This paper proposes a position and attitude calibration method with error correction based on the combination of the feature point and feature surface. First, the initial value of the spatial position relation-ship between each sensor of MMS is obtained by close-range photogrammetry. Second, the optimal solution for error correction is calculated by feature points in global coordinates jointly measured with International GNSS Service (IGS) stations. Then, the final transformation para-meters are solved by combining the initial values obtained originally, thereby realizing the rapid calibration of the MMS. Finally, it analyzed the RMSE of MMS point cloud after calibration, and the results demonstrate the feasibility of the calibration approach proposed by this method. Under the condition of a single measurement sensor accuracy is low, the plane and elevation absolute accuracy of the point cloud after calibration can reach 0.043 m and 0.072 m, respectively, and the relative accuracy is smaller than 0.02 m. It meets the precision require-ments of data acquisition for MMS. It is of great significance for promoting the development of MMS technology and the application of some novel techniques in the future, such as auton-omous driving, digital twin city, urban brain et al.
