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Remote Sensing for Natural Resources    2025, Vol. 37 Issue (3) : 142-151     DOI: 10.6046/zrzyyg.2023382
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Data quality assessment of the AMS-3000 wide-field three-linear-array stereoscopic aerial survey system
LI Tianqi1(), ZHANG Xian1(), JIN Dingjian1, GAO Zihong1, HAN Yachao1, XU Ning2, GAO Han3, LI Gongxin2
1. China Aero Geophysical Survey and Remote Sensing Center for Natural Resources, Beijing 100083, China
2. Shandong Provincial No.4 Institute of Geological and Mineral Survey, Weifang 261021, China
3. Shandong Institute of Coal Geology Planning and Exploration, Jinan 250102, China
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Abstract  

The AMS-3000 wide-field three-linear-array stereoscopic aerial survey system (hereafter referred to as the AMS-3000 system) is China’s first independently developed airborne linear-array aerial survey system. It can obtain panchromatic and R-, G-, and B-band multispectral images. However, the data quality of these images lacks quantitative assessments and analyses. Focusing on the area along the Jinsha River within western Panzhihua City, Sichuan Province, this study assessed the spectral quality of the data obtained from the AMS-3000 system in terms of grayscale, texture, and energy features, and noise level. Moreover, this study compared the AMS-3000 system with the internationally recognized ADS100 aerial photography system and assessed the geometric accuracy of the AMS-3000 system using the 1∶2 000-scale terrain data. Additionally, this study analyzed the effectiveness of the AMS-3000 system in the geological industry by applying it to the investigation of the mineral resource exploitation status and geologic hazards. Overall, this study serves as a reference for the application promotion and improvement of the AMS-3000 system.
Keywords airborne remote sensing      wide-field three-linear-array stereoscopic aerial survey system      data quality assessment      geological application     
ZTFLH:  TP79  
Issue Date: 01 July 2025
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Tianqi LI
Xian ZHANG
Dingjian JIN
Zihong GAO
Yachao HAN
Ning XU
Han GAO
Gongxin LI
Cite this article:   
Tianqi LI,Xian ZHANG,Dingjian JIN, et al. Data quality assessment of the AMS-3000 wide-field three-linear-array stereoscopic aerial survey system[J]. Remote Sensing for Natural Resources, 2025, 37(3): 142-151.
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https://www.gtzyyg.com/EN/10.6046/zrzyyg.2023382     OR     https://www.gtzyyg.com/EN/Y2025/V37/I3/142
指标 AMS-3000 ADS100(有效测绘区域)
波段 PAN,R,G,B PAN,R,G,B,NIR
焦距/mm 130 62.5
基高比 0.89 0.78
交汇角/(°) 21,27 14,27
立体成像角度/(°)
(前视,后视,前、后视)		 21,27,48 26,19,45
像素/个 32 768 16 000
2 000 m航高像素
分辨率/m		 0.077 0.16
横向视场角/(°) 64 60
2 000 m航高成图
比例尺		 1∶1 000 1∶2 000
质量/kg 72 50
Tab.1  Main indicator parameters of AMS-3000 and ADS100
Fig.1  Location of the study area
Fig.2  DOM data of the sub-areas
灰度特征 波段 城市 矿区 山区
AMS-3000 ADS100 AMS-3000 ADS100 AMS-3000 ADS100
[最小值,
最大值]		 R [3,253] [0,255] [1,255] [1,255] [9,253] [0,255]
G [9,253] [1,255] [8,255] [1,255] [13,253] [1,255]
B [5,253] [1,255] [5,255] [1,255] [9,253] [2,255]
均值 R 83.572 588 83.242 540 78.393 797 67.800 800 99.149 108 75.454 545
G 81.181 100 93.193 296 74.290 586 73.540 674 89.084 684 69.066 834
B 63.295 291 89.235 888 58.081 662 76.013 724 68.293 584 60.238 720
标准差 R 52.323 057 53.552 480 39.828 969 40.636 635 41.832 207 33.027 923
G 44.248 676 49.221 029 32.615 564 35.067 013 31.444 863 24.655 547
B 40.835 132 47.381 074 28.465 731 31.483 471 24.778 054 18.606 961
Tab.2  Comparison of grayscale information in AMS-3000 and ADS100 data
纹理特征 波段 城市 矿区 山区
AMS-3000 ADS100 AMS-3000 ADS100 AMS-3000 ADS100
同质性 R 0.494 340 0.462 353 0.569 834 0.524 927 0.402 981 0.456 152
G 0.519 803 0.463 152 0.614 883 0.562 582 0.462 169 0.527 081
B 0.589 533 0.544 028 0.685 704 0.654 352 0.554 611 0.674 007
对比度 R 12.800 055 13.759 801 5.134 182 5.540 763 10.659 980 6.292 375
G 10.022 243 11.853 681 3.739 602 3.996 770 6.581 586 3.885 167
B 7.698 285 7.150 093 2.608 960 2.311 272 3.644 220 1.610 590
角二阶矩 R 0.230 291 0.209 421 0.265 584 0.232 212 0.161 592 0.177 437
G 0.239 672 0.204 768 0.292 180 0.246 072 0.180 039 0.211 315
B 0.291 734 0.248 043 0.354 139 0.313 351 0.222 764 0.318 608
熵 R 1.708 204 1.776 137 1.582 664 1.691 923 1.942 928 1.870 011
G 1.670 413 1.786 373 1.488 344 1.626 877 1.859 003 1.730 920
B 1.498 315 1.618 479 1.296 948 1.392 717 1.685 434 1.365 261
Tab.3  Comparison of texture information in AMS-3000 and ADS100 data
能量特征 波段 城市 矿区 山区
AMS-3000 ADS100 AMS-3000 ADS100 AMS-3000 ADS100
细节能量 R 7.538 428 7.877 600 2.820 369 3.096 583 5.798 322 3.503 917
G 5.951 535 6.834 283 2.013 087 2.278 667 3.519 743 2.048 597
B 4.547 111 4.235 989 1.363 186 1.312 545 1.932 782 0.872 410
边缘能量 R 1.676 443 0.819 110 0.746 305 0.584 681 1.956 013 1.358 207
G 1.509 385 0.924 938 0.730 304 0.547 750 1.509 776 0.808 992
B 1.242 619 0.924 938 0.495 589 0.384 763 0.728 511 0.291 373
Tab.4  Comparison of energy information in AMS-3000 and ADS100 data
区域 波段 硬质铺装地 植被 土壤
AMS-3000 ADS100 AMS-3000 ADS100 AMS-3000 ADS100
非阴影区 R 38.888 514 31.233 256 13.925 392 12.723 567 35.683 666 26.081 087
G 34.505 191 31.579 201 13.402 149 14.200 166 25.386 520 25.170 174
B 27.489 724 24.708 639 12.019 379 8.166 513 17.625 233 21.232 276
阴影区 R 7.067 904 10.868 610 10.274 748 5.3230 767 7.342 963 6.019 994
G 7.117 442 9.729 526 10.505 827 5.1982 205 6.661 557 6.044 159
B 6.359 533 6.350 836 10.797 800 7.7845 438 6.296 068 5.399 476
Tab.5  Comparison of noise level in AMS-3000 and ADS100 data
Fig.3  Distribution of geometric accuracy check points
指标 dX dY dXY dZ
中误差 0.276 0.263 0.381 0.506
平均误差 0.027 -0.039 0.351 0.026
最大误差 0.486 -0.495 0.649 1.094
Tab.6  Geometric accuracy evaluation of check points(m)
Fig.4  Example images of coal mining and mine restoration and management
Fig.5  Image example of collapse geological hazard
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