References
- 1.Batty M. 2018. Artificial intelligence and smart cities. Environment and Planning B: Urban Analytics and City Science, 45(1): 3-6
- 2.Bo Q, Li X L, Tao D C and Lu X Q. 2016. Deep semantic understanding of high resolution remote sensing image//2016 International Conference on Computer, Information and Telecommunication Systems (CITS). Kunming: IEEE: 1-5
- 3.Boualleg Y, Farah M and Farah I R. 2019. Remote sensing scene classification using convolutional features and deep forest classifier. IEEE Geoscience and Remote Sensing Letters, 16(12): 1944-1948
- 4.Cao H Y, Liu F Q, Zhao C G and Dai J. 2021. The study of high resolution stereo mapping satellite. National Remote Sensing Bulletin, 25(7): 1400-1410
- 5.Chen A L, Li J Y, Zhang S J, Zhu Y X, Zhao S J, Sun W, Zhang Q. 2020. Application of satellite remote sensing yield estimation technology in regional revenue protection crop insurance: a case of soybean. Smart Agriculture, 2(3): 139-152
- 6.Chen H R X, Wu C, Du B, Zhang L P and Wang L. 2020a. Change detection in multisource VHR images via deep Siamese convolutional multiple-layers recurrent neural network. IEEE Transactions on Geoscience and Remote Sensing, 58(4): 2848-2864
- 7.Chen K Y, Chen H X, Zhou C L, Huang Y C, Qi X Y, Shen R Q, Liu F R, Zuo M, Zou X Y, Wang J F, Zhang Y, Chen D, Chen X G, Deng Y F and Ren H Q. 2020b. Comparative analysis of surface water quality prediction performance and identification of key water parameters using different machine learning models based on big data. Water Research, 171: 115454
- 8.Chen L, Liu K H, Zhou B D, Li Q Q. 2021. Key technologies of multi-agent collaborative high definition map construc-tion. Acta Geodaetica et Cartographica Sinica, 50(11): 1447-1456
- 9.Chen Q, Yu R H, Hao Y L, Wu L H, Zhang W X, Zhang Q and Bu X N. 2018. A new method for mapping aquatic vegetation especially underwater vegetation in Lake Ulansuhai using GF-1 satellite data. Remote Sensing, 10(8): 1279
- 10.Chen R, Guo X Y, Du J and Hu X. 2020. Monitoring of disturbance on ecological environment caused by earthquake and post-disaster reconstruction at Heye Village area of Jiuzhaigou using the high-resolution remote sensing imageries. Quaternary Sciences, 2020, 40(5): 1350-1358
- 11.Chen R Z, Wang L, Li D R, Chen L and Fu W J. 2019. A survey on the fusion of the navigation and the remote sensing techniques. Acta Geodaetica et Cartographica Sinica, 48(12): 1507-1522
- 12.Chen Z X, Hao P Y, Liu J, An M and Han B. 2019. Technical demands for agricultural remote sensing satellites in China. Smart Agriculture, 1(1): 32-42
- 13.Cheng G, Han J W, Guo L, Liu Z B, Bu S H and Ren J C. 2015. Effective and efficient midlevel visual elements-oriented land-use classification using VHR remote sensing images. IEEE Transactions on Geoscience and Remote Sensing, 53(8): 4238-4249
- 14.Cheng G, Han J W, Zhou P C and Xu D. 2019. Learning rotation-invariant and fisher discriminative convolutional neural networks for object detection. IEEE Transactions on Image Processing, 28(1): 265-278
- 15.Cheng G, Si Y J, Hong H L, Yao X W and Guo L. 2021. Cross-scale feature fusion for object detection in optical remote sensing images. IEEE Geoscience and Remote Sensing Letters, 18(3): 431-435
- 16.Cheng G, Yang C Y, Yao X W, Guo L and Han J W. 2018. When deep learning meets metric learning: remote sensing image scene classification via learning discriminative CNNs. IEEE Transactions on Geoscience and Remote Sensing, 56(5): 2811-2821
- 17.Darwish N, Kaiser M, Koch M and Gaber A. 2021. Assessing the accuracy of ALOS/PALSAR-2 and Sentinel-1 radar images in estimating the land subsidence of coastal areas: a case study in Alexandria City, Egypt. Remote Sensing, 13(9): 1838
- 18.Dembski F, Wössner U, Letzgus M, Ruddat M and Yamu C. 2020. Urban digital twins for smart cities and citizens: the case study of Herrenberg, Germany. Sustainability, 12(6): 2307
- 19.Dian R W, Li S T, Sun B and Guo A J. 2021. Recent advances and new guidelines on hyperspectral and multispectral image fusion. Information Fusion, 69: 40-51
- 20.Dou M G, Chen J Y, Chen D, Chen X D, Deng Z, Zhang X G, Xu K and Wang J. 2014. Modeling and simulation for natural disaster contingency planning driven by high-resolution remote sensing images. Future Generation Computer Systems, 37: 367-377
- 21.Du P J, Liu S C and Tan K. 2012. Rapid monitoring of Japan earthquake-triggered tsunami disaster based on a fusion of multiple features derived from HJ small satellite images. Science and Technology Review, 30(4): 31-36
- 22.Du Z Q, Li Y, Zhang Y T, Tan Y Q and Zhao W H. 2020. Knowledge graph construction method on natural disaster emergency. Geomatics and Information Science of Wuhan University, 45(9): 1344-1355
- 23.Duan P H, Ghamisi P, Kang X D, Rasti B, Li S T and Gloaguen R. 2021. Fusion of dual spatial information for hyperspectral image classification. IEEE Transactions on Geoscience and Remote Sensing, 59(9): 7726-7738
- 24.Duan P H, Lai J B, Kang J, Kang X D, Ghamisi P and Li S T. 2020. Texture-aware total variation-based removal of sun glint in hyperspectral images. ISPRS Journal of Photogrammetry and Remote Sensing, 166: 359-372
- 25.Fan Y D, Wu W, Wang W, Liu M and Wen Q. 2016. Research progress of disaster remote sensing in China. Journal of Remote Sensing, 20(5): 1170-1184
- 26.Feng W L, Zheng H Y. 2021. Analysis on Application of Remote Sensing Technology in Agricultural Insurance. Rural finance research, 7:3-8
- 27.Feng X X, Han J W, Yao X W and Cheng G. 2020a. Progressive contextual instance refinement for weakly supervised object detection in remote sensing images. IEEE Transactions on Geoscience and Remote Sensing, 58(11): 8002-8012
- 28.Feng Y, Liu S C and Tang L Y. 2020b. Automatic extraction and change monitoring of fire disaster event based on high-resolution nighttime light remote sensing images//Proceedings Volume 11533, Image and Signal Processing for Remote Sensing XXVI. Edinburgh: SPIE: 57-65
- 29.Gao L R, Gu D X, Zhuang L N, Ren J C, Yang D and Zhang B. 2020. Combining t-distributed stochastic neighbor embedding with convolutional neural networks for hyperspectral image classification. IEEE Geoscience and Remote Sensing Letters, 17(8): 1368-1372
- 30.Gao L R, Sun X, Luo W F, Tang M F and Zhang B. 2018. Swarm intelligence algorithms for spectral unmixing in hyperspectral image. Journal of Nanjing University of Information Science and Technology (Natural Science Edition), 10(1): 81-91
- 31.Gao W, Tian Y H and Wang J. 2018. Digital retina: revolutionizing camera systems for the smart city. Scientia Sinica Informationis, 48(8): 1076-1082
- 32.Gao Y N, Li Q, Wang S S and Gao J F. 2018. Adaptive neural network based on segmented particle swarm optimization for remote-sensing estimations of vegetation biomass. Remote Sensing of Environment, 211: 248-260
- 33.Ghaffarian S, Valente J, van der Voort M and Tekinerdogan B. 2021. Effect of attention mechanism in deep learning-based remote sensing image processing: a systematic literature review. Remote Sensing, 13(15): 2965
- 34.Gong J Y and Zhong Y F. 2016. Survey of intelligent optical remote sensing image processing. Journal of Remote Sensing, 20(5): 733-747
- 35.Gong J Y. 2018. Chances and challenges for development of surveying and remote sensing in the age of artificial intelligence. Geomatics and Information Science of Wuhan University, 43(12): 1788-1796
- 36.Gong P, Liu H, Zhang M N, Li C C, Wang J, Huang H B, Clinton N, Ji L Y, Li W Y, Bai Y Q, Chen B, Xu B, Zhu Z L, Yuan C, Suen H P, Guo J, Xu N, Li W J, Zhao Y Y, Yang J, Yu C Q, Wang X, Fu H H, Yu L, Dronova I, Hui F M, Cheng X, Shi X L, Xiao F J, Liu Q F and Song L C. 2019. Stable classification with limited sample: transferring a 30-m resolution sample set collected in 2015 to mapping 10-m resolution global land cover in 2017. Science Bulletin, 64(6): 370-373
- 37.Gong P, Zhang H, Zhang H Y, Liang L and Wang L. 2011. Mapping tsunami damaged area caused by the magnitude 9.0 Japan earthquake using China’s HJ-1 satellite imagery. Journal of Remote Sensing, 15(4): 863-868
- 38.Gu X F and Tong X D. 2015. Overview of China earth observation satellite programs [space agencies]. IEEE Geoscience and remote Sensing Magazine, 3(3): 113-129
- 39.Gu Y F, Liu T Z and Li J. 2019. Superpixel tensor model for spatial-spectral classification of remote sensing images. IEEE Transactions on Geoscience and Remote Sensing, 57(7): 4705-4719
- 40.Gu Y F, Liu T Z, Gao G M, Ren G B, Ma Y, Chanussot J and Jia X P. 2021. Multimodal hyperspectral remote sensing: an overview and perspective. Science China Information Sciences, 64(2): 121301
- 41.Guan Z F, Cheng X, Liu Y, Qu Y T and Li T. 2021. Extracting icebergs freeboard from the shadows in Landsat-8 panchromatic images. Journal of Remote Sensing, 0
- 42.Guo H D, Fu W X and Liu G. 2019. Chinese earth observation satellites//Guo H D, Fu W X and Liu G, eds. Scientific Satellite and Moon-Based Earth Observation for Global Change. Singapore: Springer: 189-243
- 43.Guo H D, Wang L Z and Liang D. 2016. Big Earth Data from space: a new engine for Earth science. Science Bulletin, 61(7): 505-513
- 44.Hu Y, Li X D, Gu Y F and Jacob M. 2020. Hyperspectral image recovery using nonconvex sparsity and low-rank regularizations. IEEE Transactions on Geoscience and Remote Sensing, 58(1): 532-545
- 45.Huang B and Zhao Y Q. 2017. Research status and prospect of spatiotemporal fusion of multi-source satellite remote sensing imagery. Acta Geodaetica et Cartographica Sinica, 46(10): 1492-1499
- 46.Jin K L and Hao L. 2020. Evapotranspiration estimation in the Jiangsu-Zhejiang-Shanghai Area based on remote sensing data and SEBAL model. Remote Sensing for Land and Resources, 32(2): 204-212
- 47.Jin X L, Li Z H, Feng H K, Ren Z B and Li S K. 2020. Deep neural network algorithm for estimating maize biomass based on simulated Sentinel 2A vegetation indices and leaf area index. The Crop Journal, 8(1): 87-97
- 48.Kaku K. 2019. Satellite remote sensing for disaster management support: a holistic and staged approach based on case studies in Sentinel Asia. International Journal of Disaster Risk Reduction, 33: 417-432
- 49.Kang X D, Li S T and Benediktsson J A. 2014. Feature extraction of hyperspectral images with image fusion and recursive filtering. IEEE Transactions on Geoscience and Remote Sensing, 52(6): 3742-3752
- 50.Kang X D, Li S T, Fang L Y and Benediktsson J A. 2015. Intrinsic image decomposition for feature extraction of hyperspectral images. IEEE Transactions on Geoscience and Remote Sensing, 53(4): 2241-2253
- 51.Kang X D, Xiang X L, Li S T and Benediktsson J A. 2017. PCA-based edge-preserving features for hyperspectral image classification. IEEE Transactions on Geoscience and Remote Sensing, 55(12): 7140-7151
- 52.Kattenborn T, Leitloff J, Schiefer F and Hinz S. 2021. Review on Convolutional Neural Networks (CNN) in vegetation remote sensing. ISPRS Journal of Photogrammetry and Remote Sensing, 173: 24-49
- 53.Kleynhans T, Montanaro M, Gerace A and Kanan C. 2017. Predicting top-of-atmosphere thermal radiance using MERRA-2 atmospheric data with deep learning. Remote Sensing, 9(11): 1133
- 54.Lary D J, Alavi A H, Gandomi A H, Walker A L. 2016. Machine learning in geosciences and remote sensing. Geoscience frontiers, 7(1): 3-10
- 55.Li D R, Ding L and Shao Z F. 2021. Application-oriented real-time remote sensing service technology. National Remote Sensing Bulletin, 25(1): 15-24
- 56.Li D R, Yao Y and Shao Z F. 2014a. Big data in smart city. Geomatics and Information Science of Wuhan University, 39(6): 631-640
- 57.Li D R, Zhang L P and Xia G S. 2014b. Automatic analysis and mining of remote sensing big data. Acta Geodaetica et Cartographica Sinica, 43(12): 1211-1216
- 58.Li D R. 2019a. How to realize intelligent service of spatial information in 5G era. Scientific Chinese, (19): 44-45
- 59.Li D R. 2019b. The intelligent processing and service of spatiotemporal big data. Journal of Geo-Information Science, 21(12): 1825-1831
- 60.Li F G, Li E Z, Samat A, Zhang L P, Liu W and Hu J S. 2020. Estimation of large-scale impervious surface percentage by fusion of multi-source time series remote sensing data. Journal of Remote Sensing, 24(10):1243-1254
- 61.Li J Y, Yan G R, Li Z G and Bai Z G. 2020. Research on technology development of the intelligent remote sensing satellites system. Spacecraft Recovery and Remote Sensing, 41(6): 34-44
- 62.Li J, Huang X, Gong J. 2019. Deep neural network for remote-sensing image interpretation: status and perspectives. National Science Review, 6(6): 1082-1086
- 63.Li K, Cheng G, Bu S H and You X. 2018a. Rotation-insensitive and context-augmented object detection in remote sensing images. IEEE Transactions on Geoscience and Remote Sensing, 56(4): 2337-2348
- 64.Li K, Wan G, Cheng G, Meng L Q and Han J W. 2020a. Object detection in optical remote sensing images: a survey and a new benchmark. ISPRS Journal of Photogrammetry and Remote Sensing, 159: 296-307
- 65.Li S T, Dian R, Fang L Y and Bioucas-Dias J M. 2018b. Fusing hyperspectral and multispectral images via coupled sparse tensor factorization. IEEE Transactions on Image Processing, 27(8): 4118-4130
- 66.Li S T, Li C Y and Kang X D. 2021. Development status and future prospects of multi-source remote sensing image fusion. National Remote Sensing Bulletin, 25(1): 148-166
- 67.Li T W, Shen H F, Yuan Q Q, Zhang X C and Zhang L P. 2017. Estimating ground-level PM2.5 by fusing satellite and station observations a geo-intelligent deep learning approach Geophysical Research Letters, 44(23): 11985-11993
- 68.Li W L, Zhu J, Zhu X L, Fu L, Zhang Y H, Hu Y, He Q L and Huang P C. 2019. A exploratory analysis method of VR scene in landslide based on UAV remote sensing data. Geomatics and Information Science of Wuhan University, 44(7): 1065-1072
- 69.Li X, Zhu J, Yin X D, Yao J C, Huang J L and Li M T. 2019. Mapping construction land of Guangzhou based on Luojia No. 1 nightlight data. Journal of Geo-Information Science, 21(11): 1802-1810
- 70.Liao W Z, Coillie F V, Gao L R, Li L W, Zhang B and Chanussot J. 2018. Deep learning for fusion of APEX hyperspectral and full-waveform LiDAR Remote sensing data for tree species mapping. IEEE Access, 6: 68716-68729
- 71.Liao X H. 2020. Advance of geographic sciences and new technology applications. Progress in Geography, 39(5): 709-715
- 72.Liao X H. 2021. Scientific and technological progress and development prospect of the earth observation in China in the past 20 years. National Remote Sensing Bulletin, 25(1): 267-275
- 73.Lin H, Chen M, Lu G N, Zhu Q, Gong J H, You X, Wen Y N, Xu B L and Hu M Y. 2013. Virtual Geographic Environments (VGEs): a new generation of geographic analysis tool. Earth-Science Reviews, 126: 74-84
- 74.Liu H and Gong P. 2021. 21st century daily seamless data cube reconstruction and seasonal to annual land cover and land use dynamics mapping-iMap (China) 1.0. National Remote Sensing Bulletin, 25(1): 126-147
- 75.Liu J. 2021. Performance of cloud fraction of three satellite cloud climate date records over the Tibetan Plateau. National Remote Sensing Bulletin, 25(7): 1445-1459
- 76.Liu M W, Zhu J, Zhu Q, Qi H, Yin L Z, Zhang X, Feng B, He H G, Yang W J and Chen L Y. 2017a. Optimization of simulation and visualization analysis of dam-failure flood disaster for diverse computing systems. International Journal of Geographical Information Science, 31(9): 1891-1906
- 77.Liu S C, Chi M M, Zou Y X, Samat A, Benediktsson J A and Plaza A. 2017b. Oil spill detection via multitemporal optical remote sensing images: a change detection perspective. IEEE Geoscience and Remote Sensing Letters, 14(3): 324-328
- 78.S C, Zheng Y J, Du Q, Samat A, Tong X H and Dalponte M. 2021a. A novel feature fusion approach for VHR remote sensing image classification. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 14: 464-473
- 79.Liu X J, Zhao C Y, Zhang Q, Lu Z, Li Z H, Yang C S, Zhu W, Liu-Zeng J, Chen L Q and Liu C J. 2021b. Integration of Sentinel-1 and ALOS/PALSAR-2 SAR datasets for mapping active landslides along the Jinsha River corridor, China. Engineering Geology, 284: 106033
- 80.Lu N M, Zheng W, Wang X, Gao L, Liu Q H, Wu S L, Jiang J Y, Gu S Y and Fang X. 2017. Overview of meteorological satellite and its data application in weather analysis, climate and environment disaster monitoring. Journal of Marine Meteorology, 37(1): 20-30
- 81.Lu X Q, Sun H and Zheng X T. 2019. A feature aggregation convolutional neural network for remote sensing scene classification. IEEE Transactions on Geoscience and Remote Sensing, 57(10): 7894-7906
- 82.Lu X Q, Wang B Q and Zheng X T. 2020. Sound active attention framework for remote sensing image captioning. IEEE Transactions on Geoscience and Remote Sensing, 58(3): 1985-2000
- 83.Luo R, Wang L, Xiao Y J, He Y and Zhao D F. 2020. Application of deep learning technology in military field. Command Control and Simulation, 42(1): 1-5
- 84.Ma D A, Tang P and Zhao L J. 2019a. SiftingGAN: generating and sifting labeled samples to improve the remote sensing image scene classification baseline in vitro. IEEE Geoscience and Remote Sensing Letters, 16(7): 1046-1050
- 85.Ma L, Liu Y, Zhang X L, Ye Y X, Yin G F and Johnson B A. 2019b. Deep learning in remote sensing applications: a meta-analysis and review. ISPRS Journal of Photogrammetry and Remote Sensing, 152: 166-177
- 86.Misra N N, Dixit Y, Al-Mallahi A, Bhullar M, Upadhyay R, Martynenko A I. 2022. IoT, Big Data, and Artificial Intelligence in Agriculture and Food Industry. IEEE Internet of Things Journal, 9(9): 6305-6324 [DOI10.1109/JIOT.2020.2998584]
- 87.Mou L C, Bruzzone L and Zhu X X. 2019. Learning spectral-spatial-temporal features via a recurrent convolutional neural network for change detection in multispectral imagery. IEEE Transactions on Geoscience and Remote Sensing, 57(2): 924-935
- 88.Ning X G, Chang W T, Wang H, Zhang H C and Zhu Q D. 2022. Extraction of marsh wetland in Heilongjiang Basin based on GEE and multi-source remote sensing data. National Remote Sensing Bulletin, 26(2): 386-396
- 89.Peterson K T, Sagan V and Sloan J J. 2020. Deep learning-based water quality estimation and anomaly detection using Landsat-8/Sentinel-2 virtual constellation and cloud computing. GIScience and Remote Sensing, 57(4): 510-525
- 90.Ran Q, Yu H Y, Gao L R, Li W and Zhang B. 2018. Superpixel and subspace projection-based support vector machines for hyperspectral image classification. Journal of Image and Graphics, 23(1): 95-105
- 91.Sagan V, Peterson K T, Maimaitijiang M, Sidike P, Sloan J, Greeling B A, Maalouf S and Adams C. 2020. Monitoring inland water quality using remote sensing: potential and limitations of spectral indices, bio-optical simulations, machine learning, and cloud computing. Earth-Science Reviews, 205: 103187
- 92.Schmidhuber J. 2015. Deep learning in neural networks: An overview. Neural networks, 61:85-117
- 93.Shen X, Cao L and She G H. 2016. Subtropical forest biomass estimation based on hyperspectral and high-resolution remotely sensed data. Journal of Remote Sensing, 20(6): 1446-1460
- 94.Shi K Q, Zou B, Chen S G, Xue C, Shi L J and Zhang T L. 2021. Remote sensing inversion of sea ice concentration by a middle-resolution imaging spectrometer. National Remote Sensing Bulletin, 25(3): 753-764
- 95.State Council of the PRC. 2017. New generation artificial intelligence development plan.
- 96.Sun W W, Yang G, Chen C, Chang M H, Huang K, Meng X Z and Liu L Y. 2020. Development status and literature analysis of China’s earth observation remote sensing satellites. Journal of Remote Sensing (Chinese), 24(5): 479-510
- 97.Sun Z N, He R, Wang L, Kan M N, Feng J J, Zheng F, Zheng W S, Zuo W M, Kang W X, Deng W H, Zhang J, Han H, Shan S G, Wang Y L, Ru Y W, Zhu Y H, Liu Y F and He Y. 2021. Overview of biometrics research. Journal of Image and Graphics, 26(6): 1254-1329
- 98.Tang S F, Tian Q J, Xu K J, Xu N X and Yue J B. 2020. Age information retrieval of Larix gmelinii forest using Sentinel-2 data. Journal of Remote Sensing, 24(12): 1511-1524
- 99.Tong Q X. 2021. Going along with the progress of remote sensing: for the 25th anniversary of the renaming of National Remote Sensing Bulletin. National Remote Sensing Bulletin, 25(1): 1-12
- 100.Tong X D. 2016. Development of China high-resolution earth observation system. Journal of Remote Sensing, 20(5): 775-780
- 101.Tong X H, Pan H Y, Liu S C, Li B B, Luo X, Xie H and Xu X. 2020. A novel approach for hyperspectral change detection based on uncertain area analysis and improved transfer learning. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 13: 2056-2069
- 102.Vogt M. 2018. An overview of deep learning techniques. at - Automatisierungstechnik, 66(9):690-703
- 103.Wang B Q, Zheng X T, Qu B and Lu X Q. 2020. Retrieval topic recurrent memory network for remote sensing image captioning. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 13: 256-270
- 104.Wang F, Guo Q and Ge X Q. 2021. Pan-sharpening by deep recursive residual network. National Remote Sensing Bulletin, 25(6): 1244-1256
- 105.Wang Q and Liu S H. 2016. Research and implementation of national environmental remote sensing monitoring system. Journal of Remote Sensing, 20(5): 1161-1169
- 106.Wang Q, Liu S T, Chanussot J and Li X L. 2019. Scene classification with recurrent attention of VHR remote sensing images. IEEE Transactions on Geoscience and Remote Sensing, 57(2): 1155-1167
- 107.Wang Q. 2021. Progress of environmental remote sensing monitoring technology in China and some related frontier issues. National Remote Sensing Bulletin, 25(1): 25-36
- 108.Wang Y P, Li R, Hu J H, Wang X W, Kabeja C, Min Q L and Wang Y. 2021. Evaluations of MODIS and microwave based satellite evapotranspiration products under varied cloud conditions over East Asia forests. Remote Sensing of Environment, 264: 112606
- 109.Wen F P, Zhao W, Hu L, Xu H X and Cui Q. 2021. SMAP passive microwave soil moisture spatial downscaling based on optical remote sensing data: a case study in Shandian River basin. National Remote Sensing Bulletin, 25(4): 962-973
- 110.Wolanin A, Camps-Valls G, Gómez-Chova L, Mateo-García G, van der Tol C, Zhang Y G and Guanter L. 2019. Estimating crop primary productivity with Sentinel-2 and Landsat 8 using machine learning methods trained with radiative transfer simulations. Remote Sensing of Environment, 225: 441-457
- 111.Xia G S, Bai X, Ding J, Zhu Z, Belongie S, Luo J B, Datcu M, Pelillo M and Zhang L P. 2018. DOTA: a large-scale dataset for object detection in aerial images//2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition. 3974-3983
- 112.Xiao A R, Wang Z Y, Wang L and Ren Y X. 2018. Super-resolution for “Jilin-1”satellite video imagery via a convolutional network. Sensors, 18(4): 1194
- 113.Xiao C J, Li Y, Zhang H Q and Chen J. 2020. Semantic segmentation of remote sensing image based on deep fusion networks and conditional random field. Journal of Remote Sensing, 24(3): 254-264
- 114.Xiao L, Liu P F and Li H. 2020. Progress and challenges in the fusion of multisource spatial-spectral remote sensing images. Journal of Image and Graphics, 25(5): 851-863
- 115.Xu G H, Liu Q H, Chen L F and Liu L Y. 2016. Remote sensing for China's sustainable development: opportunities and challenges. Journal of Remote Sensing, 20(5): 679-688
- 116.Xu W, Gong J Y and Wang M. 2014. Development, application, and prospects for Chinese land observation satellites. Geo-Spatial Information Science, 17(2): 102-109
- 117.Xu Y M, Ho H C, Wong M S, Deng C B, Shi Y, Chan T C and Knudby A. 2018. Evaluation of machine learning techniques with multiple remote sensing datasets in estimating monthly concentrations of ground-level PM2.5. Environmental Pollution, 242: 1417-1426
- 118.Xuan S Y, Li S Y, Han M F, Wan X and Xia G S. 2020. Object tracking in satellite videos by improved correlation filters with motion estimations. IEEE Transactions on Geoscience and Remote Sensing, 58(2): 1074-1086
- 119.Yang H and Hang J. 2014. Diagnosis of oil spills in Shanghai coastal area based on multi-source satellite MODIS and HJ-1. Marine Sciences, 38(10): 90-97
- 120.Yao X W, Han J W, Cheng G, Qian X M and Guo L. 2016. Semantic annotation of high-resolution satellite images via weakly supervised learning. IEEE Transactions on Geoscience and Remote Sensing, 54(6): 3660-3671
- 121.Ye Z, Kang J, Yao J, Song W P, Liu S C, Luo X, Xu Y S and Tong X H. 2020. Robust fine registration of multisensor remote sensing images based on enhanced subpixel phase correlation. Sensors, 20(15): 4338
- 122.Yin L Z, Zhu J, Li Y, Zeng C, Zhu Q, Qi H, Liu M W, Li W L, Cao Z Y, Yang W J and Zhang P C. 2017. A virtual geographic environment for debris flow risk analysis in residential areas. ISPRS International Journal of Geo-Information, 6(11): 377
- 123.Yuan Q Q, Shen H F, Li T W, Li Z W, Li S W, Jiang Y, Xu H Z, Tan W W, Yang Q Q, Wang J W, Gao J H and Zhang L P. 2020. Deep learning in environmental remote sensing: achievements and challenges. Remote Sensing of Environment, 241: 111716
- 124.Zang N, Cao Y, Wang Y B, Huang B, Zhang L Q and Mathiopoulos P T. 2021. Land-use mapping for high-spatial resolution remote sensing image via deep learning: a review. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 14: 5372-5391
- 125.Zhang B, Chen Z C, Peng D L, Benediktsson J A, Liu B, Zou L, Li J and Plaza A. 2019a. Remotely sensed big data: evolution in model development for information extraction [point of view]. Proceedings of the IEEE, 107(12): 2294-2301
- 126.Zhang B, Zhu J and Su H. 2020. Toward the third generation of artificial intelligence. Science in China (Information Sciences), 50(9): 1281-1302
- 127.Zhang B. 2018. Remotely sensed big data era and intelligent information extraction. Geomatics and Information Science of Wuhan University, 43(12): 1861-1871
- 128.Zhang C, Sargent I, Pan X, Li H P, Gardiner A, Hare J and Atkinson P M. 2019b. Joint Deep Learning for land cover and land use classification. Remote Sensing of Environment, 221: 173-187
- 129.Zhang H Q, Liu X Y, Yang S and Li Y. 2017. Retrieval of remote sensing images based on semisupervised deep learning. Journal of Remote Sensing, 21(3): 406-414
- 130.Zhang J X, Li H T, Gu H Y, Zhang H, Yang Y, Tan X R, Li M and Shen J. 2021. Study on man-machine collaborative intelligent extraction for natural resource features. Acta Geodaetica et Cartographica Sinica, 50(8): 1023-1032
- 131.Zhang N, Yang G J, Zhao C J, Zhang J C, Yang X D, Pan Y C, Huang W J, Xu B, Li M, Zhu X C and Li Z H. 2021. Progress and prospects of hyperspectral remote sensing technology for crop diseases and pests. National Remote Sensing Bulletin, 25(1): 403-422
- 132.Zhang T, Xie S, Huang B, Fan J H, Chen J P and Tong L Q. 2021. Detection of active landslides in central Maoxian County using Sentinel-1 and ALOS-2 data. Remote Sensing for Land and Resources, 33(2): 213-219
- 133.Zhang X C, Li S Y, Zhou Q M and Sun Y. 2021. The rationale and innovative thinking of building Digital Twin City. Science of Surveying and Mapping, 46(3): 147-152, 168
- 134.Zhang Y S, Wu L, Ren H Z, Deng L C and Zhang P C. 2020. Retrieval of water quality parameters from hyperspectral images using hybrid Bayesian probabilistic neural network. Remote Sensing, 12(10): 1567
- 135.Zhang Z N and An Y S. 2019. Imagination of ocean application of multi-base cooperative multi-source fusion of sky, ground and sea. Satellite Application, 2: 24-29, 32-33
- 136.Zhao S, Blaabjerg F, Wang H. 2021. An Overview of Artificial Intelligence Applications for Power Electronics. IEEE Transactions on Power Electronics, 36(4): 4633-4658
- 137.Zhao W B. 2019. Phase research and practice of upgrading earth observation from test application to system effectiveness in China. Journal of Remote Sensing, 23(6): 1036-1045
- 138.Zhao W D, Li S S, Li A, Zhang B and Chen J. 2021. Deep fusion of hyperspectral images and multi-source remote sensing data for classification with convolutional neural network. National Remote Sensing Bulletin, 25(7): 1489-1502
- 139.Zhao X Y,Tian B,Niu Y,Chen C P and Zhou Y X. 2022. Classification of coastal salt marsh based on Sentinel-1 time series backscattering characteristics: The case of the Yangtze River delta. National Remote Sensing Bulletin, 26(4):672-682
- 140.Zheng X T, Guan S P, Ren H G, Xu R L and Xiang B. 2021. Application of using knowledge graph to explore the knowledge pedigree of the environmental researches in Northeast land. Journal of Geo-Information Science, 23(6): 1002-1016
- 141.Zheng Z G, Fu K, Xu C Y, Wu Z Y and Zhou C F. 2019. Remote sensing data user request merging technology. Journal of National University of Defense Technology, 41(2): 115-123
- 142.Zheng Z, Wang J F, Zou B, Gao Y H, Yang S Q and Wang Y Q. 2021. Initial assessment of burn severity using transfer learning model. Journal of Remote Sensing, 0
- 143.Zhou K and Cao L. 2021. The status and prospects of remote sensing applications in precision silviculture. National Remote Sensing Bulletin, 25(1): 423-438
- 144.Zhou L, Mu H W, Ma H J and Chen G X. 2019. Remote sensing estimation on yield of winter wheat in North China based on convolutional neural network. Transactions of the Chinese Society of Agricultural Engineering, 35(15): 119-128
- 145.Zhou P C, Cheng G, Yao X W and Han J W. 2021. Machine learning paradigms in high-resolution remote sensing image interpretation. National Remote Sensing Bulletin, 25(1): 182-197
- 146.Zhou Z H. 2016. Machine Learning. Beijing: Tsinghua University Press. 10-13
- 147.Zhu J F, Zhou Y, Wang S X, Wang L T, Liu W L, Li H T and Mei J J. 2019. Analysis of changes of Baiyangdian wetland from 1975 to 2018 based on remote sensing. Journal of Remote Sensing, 23(5): 971-986
- 148.Zhu J Z, Shi Q, Chen F E, Shi X D, Dong Z M and Qin Q Q. 2016. Research status and development trends of remote sensing big data. Journal of Image and Graphics, 21(11): 1425-1439
- 149.Zou T Y, Ding H P, Wang W Z and Xiao Q. 2019. Discussion on artificial intelligence application of space-based remote sensing big data. Satellite Application, (6): 38-44


