As a master's supervisor, I serve as a council member of the Youth Promotion Association of the Chinese Academy of Sciences' Aerospace Information Innovation Institute, the secretary of the Party branch of the Eighth Department (China Remote Sensing Satellite Ground Station), and the secretary of the Youth League branch. I explore and research international frontier issues in remote sensing image intelligent processing, focusing on remote sensing image retrieval, remote sensing data services, and global heat source heavy industry identification. I have led more than 10 projects funded by the National Natural Science Foundation of China and other sources. As the chief designer, I have participated in over 40 national key research and development projects, the National High-Tech Research and Development Program (863 Program), and Category A leading projects of the Chinese Academy of Sciences. I have published nearly 60 scientific research papers, and as the first author/corresponding author, I have written more than 50 papers indexed by SCI, EI, and CSCD, including 23 SCI papers (first author/corresponding, 17 papers). I have applied for 13 invention patents as the first applicant (accumulated to 17 patents, with 8 granted), and obtained 12 software copyrights. I have been honored as a Young Female Scientist by the China Remote Sensing Application Association, a member of the Youth Innovation Promotion Association of the Chinese Academy of Sciences, and a Future Star Talent Plan member of the Aerospace Information Innovation Institute of the Chinese Academy of Sciences. Additionally, I serve as a member of the Space Electronics Branch of the Chinese Institute of Electronics, a member of the Women Scientists and Technologists Association of the China Remote Sensing Application Association, and a member of the Engineering and Equipment Branch of the Youth Innovation Promotion Association of the Chinese Academy of Sciences.

1. Li, T., Ma, C.*, Yang, J., et al.The spatial and temporal distribution of industrial/biomass fire points during the decade 2012–2021 in China [J]. Geo-spatial Information Science , 2025,（SCI）, DOI: 10.1080/10095020.2025.2514823

2. Zeng Y., Liao, R., Ma, C.*, et al. An Approach to Multiclass Industrial Heat Source Detection Using Optical Remote Sensing Images [J]. Energies, 2025, 18(1), 865.（SCI8）

3. Ma, C., Li, T.*., Sui, X.., et al. Annual dynamics of global remote industrial heat sources dataset from 2012 to 2021 [J]. Scientific Data, 2024, 11,631.（SCI）

4. Ma, C., Sui, X., Guan, L.*, et al. An Industrial Heat Source Dataset Based on Remotely Sensed Active Fire/Hotspot Detection in China from 2012 to 2021 [J]. Geoscience Data Journal, 2024, 00：1-13.（SCI）

5. Li, T., Ma, C.*., Lv Y., et al. An Approach to large-scale Cement Plant Detection Using Multisource Remote Sensing Imagery [J]. Remote Sens. , 2024, 16(4), 729.（SCI）

6. Zeng Y., Sui, X., Ma, C.*, et al. IHS-Related PM2.5 Concentrations Estimates and Analysis using new three-stage model in the Beijing-Tianjin-Hebei Region [J]. Atmosphere, 2024, 15(1), 131.（SCI）

7. Xie, Y., Ma, C.*.,Zhao, Y., et al.The Potential of using SDGSAT-1 TIS Data to Identify Industrial Heat Sources in the Beijing-Tianjin-Hebei Region [J]. Remote Sens. , 2024, 16(5), 768.（SCI）

8. Wang D., Xie, Y., Ma, C.*, et al.Industrial Heat Source Production Areas Identification based on SDGSAT-1 Thermal Infrared Data [J]. Applied Sciences, 2024, 14(6), 2450.（SCI）

9. Ma, C., Yang, J.*, Xia. W., et al. A model for expressing industrial information based on object-oriented industrial heat sources detected using multi-source thermal anomaly data in China [J]. Remote Sens. 2022, 14(4), 835（SCI）

10. Ma, C., Sui, X*., Zeng, Y., et al. Classification of Industrial Heat Source Objects Based on Active Fire Point Density Segmentation and Spatial Topological Correlation Analysis in the Beijing-Tianjin-Hebei Region [J]. Sustainability, 2022, 14(18), 11228.（SCI）

11. Xia, W., Chen J., Liu J., Ma, C.*, Liu W., et al. Landslide Extraction from High-Resolution Remote Sensing Imagery Using  Fully Convolutional Spectral-Topographic Fusion Network [J]. Remote Sens. 2021, 13, 5116.（SCI）

12. Ma, Y., Ma, C.*, Liu P., et al. Spatial-Temporal Distribution Analysis of Industrial Heat Sources in the US with Geocoded, Tree-Based, Large-Scale Clustering [J]. Remote Sens. 2020, 12(18), 3069.（SCI）

13. Ma, C., Niu, Z., Ma, Y., Chen, F., Yang, J., Liu, J. Assessing the Distribution of Heavy Industrial Heat Sources in India between 2012 and 2018 [J]. ISPRS Int. J. Geo-Inf. 2019, 8(12), 568. （SCI）

14. Ma, C., Yang, J., Chen, F., et al. Assessing Heavy Industrial Heat Source Distribution in China Using Real-Time VIIRS Active Fire/Hotspot Data [J]. Sustainability, 2018, 10(12), 4419. （SCI）

15. Ma, C, Xia W, Chen F, et al. A Content-Based Remote Sensing Image Change Information Retrieval Model [J]. ISPRS Int. J. Geo-Inf., 2017, 6(10), 310. （SCI）

16. Ma, C, Dai, Q., Liu, J., et al. An improved SVM model for relevance feedback in remote sensing image retrieval [J]. International Journal of Digital Earth, 2014, 7(9):725-745. （SCI）

17. Wang W., Zhao Y., Ma, C. et al. Exploring Relationships Between Spatial Pattern Change of Steel Plants and Land Cover Change in Tangshan CityIdentification and Analysis of Production–Living–Ecological  Space Based on Multi-Source Geospatial Data: A Case Study of Xuzhou City [J]. Sustainability, 2025, 15(12), 9729. （SCI）

18. Ni M., Zhao Y., Ma, C. et al. Spatial Identification and Change Analysis of Production-Living-Ecological Space Using Multi-Source Geospatial Data: A Case Study in Jiaodong Peninsula, China [J]. Land, 2023, 12(9), 1748. （SCI）

19. Ni M., Zhao Y., Ma, C. et al. Exploring Relationships Between Spatial Pattern Change of Steel Plants and Land Cover Change in Tangshan City [J]. Sustainability, 2023, 15(12), 9729. （SCI）

20. Zhang, S., Lei.L., Sheng, M., Song, H., Li, L, Guo, K., Ma, C., Liu, L.,  Zeng, Z.. Evaluating Anthropogenic CO2 Bottom-Up Emission Inventories Using Satellite Observations from GOSAT and OCO-2 [J]. Remote Sens. 2022, 14(19), 5024（SCI）

21. Xia, W., Ma, C., Liu, J., Liu, S., Chen, F., Yang, Z., Duan, J. High-Resolution Remote Sensing Imagery Classification of Imbalanced Data Using Multistage Sampling Method and Deep Neural Networks. Remote Sens. 2019, 11, 2523. (SCI）

22. Guo R, Liu J, Li N, Liu S, Chen F, Cheng B, Duan J, Li X, Ma C. Pixel-Wise Classification Method for High Resolution Remote Sensing Imagery Using Deep Neural Networks[J]. International Journal of Geo-Information, 2018, 7(3):110. （SCI）

23. Xie, S.; Duan, J.; Liu, S.; Dai, Q.; Liu, W.; Ma, Y.; Guo, R.; Ma, C. Crowdsourcing Rapid Assessment of Collapsed Buildings Early after the Earthquake Based on Aerial Remote Sensing Image: A Case Study of Yushu Earthquake. Remote Sens. 2016, 8, 759. （SCI）

24. Ma, C., Chen, F., Yang, J., et al. A Remote Sensing Image Retrieval Model based on an Ensemble Neural Networks[J]. Big Earth Data, 2019, 2(4):351-367. （EI）

25. Ma, C. Global remote industrial heat sources dataset. Zenodo https://doi.org/10.5281/zenodo.8308133 (2023).

26. Ma. C., & Sui X. (2023). Data of industrial heat source between 2012 and 2021 using long-term Active Fire/Hotspot data in China [Dataset]. Zenodo. https://doi.org/10.5281/zenodo.7824014.

27. 马彩虹, 戴芹, 刘士彬. 一种融合PSO和Isodata的遥感图像分割新方法[J]. 武汉大学学报：信息科学版, 2012, 37(1):35-38.（EI）

28. 廖芮琳, 马彩虹*,谢燕妹, 等. 2012~2021年印度地区在营工业热源区域数据集[J/OL]. 中国科学数据, 2025 10(1). . DOI: 10.11922/11-6035.noda.2023.0006.zh.（CSCD）

29. 马彩虹*,廖芮琳. 2012~2021年印度地区在营工业热源区域数据集[DS/OL]. Science Data Bank, 2024 .9(2).[2023-02-08]. https://cstr.cn/31253.11.sciencedb.j00001.00547.（CSCD）

30. 谢燕妹, 马彩虹*,隋欣, 等. 2012-2021年东盟10国高耗能产业数据[J/OL]. 中国科学数据, 2024 .9(2). (2023-02-09). DOI: 10.11922/11-6035.csd.2022.0069.zh.（CSCD）

31. 马彩虹*,谢燕妹. 2012-2021年东盟10国高耗能产业产品数据集[DS/OL]. Science Data Bank, 2022.[2023-02-08]. https://cstr.cn/31253.11.sciencedb.j00001.00547.（CSCD）

32. 隋欣, 马彩虹*,杨进, 等. 2012–2020 年京津冀区域在营工业热源产品数据集[J/OL]. 中国科学数据, 2022.7(2):1-11（CSCD）

33. 马彩虹, 隋欣. 2012年—2020年京津冀区域在营工业热源对象产品数据集[DS/OL]. Science Data Bank, 2022[2022-08-04].. DOI:10.57760/sciencedb.j00001.00430.

34. 马彩虹, 王大成,杨进, 等. 基于工业热源区域识别的邯郸市热异常产品分析[J]. 遥感技术与应用, 2022. 37(1):34-44（CSCD，引用0）

35. 马彩虹, 杨进, 李信鹏, 等. 中国区域Landsat-8高温异常点产品[J/OL]. 中国科学数据, 2022.7(2):1-8（CSCD）

36. 杨进, 马彩虹*, 李信鹏, 等. 中国区域Landsat-8高温异常点产品[DS/OL]. Science Data Bank, 2021. (2021-03-12) DOI: 10.11922/sciencedb.j00001.00211.（CSCD）

37. 马彩虹, 关琳琳, 陈甫,等. 基于内容的遥感图像变化信息检索概念模型设计[J]. 遥感技术与应用, 2020, 35(3):685-693. (CSCD，引用6)

38. 马彩虹, 陈甫, 杨进,等. 东盟地区热源重工业近6年的时空格局研究与分析[J]. 中国-东盟研究, 2019(01):21-33. (CSCD)

39. 刘建波, 马彩虹*, 陈甫,等. 遥感卫星数据实时主动服务系统设计与实现[J]. 遥感信息, 2016, 31(3):61-67. (CSCD，引用6)

40. 马彩虹, 张静, 段建波,等. 基于JBPM的遥感产品在线定制系统[J]. 计算机系统应用, 2014, 23(3):31-39. (CSCD，引用 11)

41. 马彩虹, 戴芹, 王建民,等. 基于分块优化的不规则三角网的快速构成方法[J]. 计算机工程与应用, 2012, 48(3):169-172. (CSCD，引用 7)

42. 马彩虹, 陈甫, 杨进,等. 基于长时序火点数据的全球重工业热源区域识别[C] . 首届中国数字地球大会, 2019, 北京，P179

43. 王玉娴, 段建波, 刘士彬, 马彩虹. 基于众包的遥感灾害监测与评估模型[J]. 国土资源遥感, 2017, 29(2):104-109. (CSCD，引用4)

44. 魏然然, 戴芹, 刘士彬,马彩虹．改进五叉树分解法在遥感图像检索中的应用[J]. 计算机工程与应用. 49(22)，2013，pp: 173-179 (CSCD) 

45. X. Hou, C. Ma*, Y. Zhao, et al. Analysis of Steel Plant Segmentation and Temperature Distribution Changes in Tangshan City[C]. 2024 5th International Conference on Geology, Mapping and Remote Sensing (ICGMRS 2024), Wuhan, China, 2024 132230R,  DOI: 10.1117/12.3035521（EI）

46. R. Liao, C. Ma*, Y. Zeng, et al. Detection of Industrial Heat Source in Remote Sensing Images Using Modified YOLO[C]. 2024 5th International Conference on Geology, Mapping and Remote Sensing (ICGMRS 2024), Wuhan, China, 2024 174-177,  DOI: 10.1109/ICGMRS62107.2024.10581221 （EI）

47. D. Wang, P. Zhang, Q. Teng,, C. Ma*. Fire type detection and online quickly analysis based on multi-sources fire Data [C]. 2024 IEEE International Geoscience and Remote Sensing Symposium (IGRASS), Athens, 2024 p:384-387（EI）

48. Y. Xie, C. Ma*, G. Wan, et al. Cloud Detection using SDGSAT-1 Thermal Infrared Data [C]. 2023 SPIE Sensors+Imaging , Amsterdam, 2023 1273OOA, DOI: 10.1117/12.2674217（EI）

49. X. Hou, C. Ma*, X. Sui, et al. Analysis of spatial and temporal changes of industrial heat sources in Ukraine from 2012 to 2022[C]. 2023 International Conference on Geographic Information and Remote Sensing Technology (GIRST 2023), Qingdao, China, 2023 127970A,  DOI: 10.1117/12.3007440  （EI）

50. T. Li, C. Ma*, R. Liao, et al. Enhanced Detection of Cement Plants in Remote Sensing Images using Modified Faster R-CNN[C]. 2023 International Conference on Geographic Information and Remote Sensing Technology (GIRST 2023), Qingdao, China, 2023 1279717,  DOI: 10.1117/12.3007968 （EI）

51. X. Sui, C. Ma*, X. Hou, et al. Long-Term Analysis of PM2.5 Spatiotemporal Patterns from Industrial Heat Sources in the Beijing-Tianjin-Hebei Region[C]. 2023 International Conference on Geographic Information and Remote Sensing Technology (GIRST 2023), Qingdao, China, 2023 1279709,  DOI: 10.1117/12.3007976 （EI）

52. P. Zhang, C. Ma*, Y. Xie, et al. Real-time Monitoring and Analysis of Industrial Heat Sources Based on Data: Hangzhou City as an example[C]. 2023 International Conference on Geographic Information and Remote Sensing Technology (GIRST 2023), Qingdao, China, 2023 1279722,  DOI: 10.1117/12.3007509 （EI）

53. Y. Xie, C. Ma*, Y. Zhao, et al. Regulation of Surface Thermal Environment by Different Land Cover Types Based on Google Earth Engine[C]. 2023 International Conference on Remote Sensing, Mapping and Geographic Information Systems (RSMG2023), Zhengzhou, 2023 128151N, DOI: 10.1117/12.3011209（EI）

54. C. Ma, L.Guan, D. Wang. Identification of Offshore Oil and Gas Drilling Platforms Based on Multi-source Remote Sensing Data [C]. 2019  the 7th International Conference on Geology Resource Management and Sustianable Development, Beijing, 2020 P:76-80 (EI)

55. C. Ma, J.Yang, J. Liu. Assessing the Heavy Industrial Heat Sources Distribution in Venezuela between 2012 and 2017 [C]. 2021 7th Annual International Conference on Network and Information Systems for Computers (ICNISC), Guiyang, China, 2021 P: 384-387

56. C. Ma, F. Chen, J. Liu and J. Duan. An improved SVM+GA relevance feedback in the remote sensing image change information retrieval [C]. IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium, Valencia, 2018, pp. 5013-5016. （EI）

57. Ma C, Dai Q, Li X, et al. The analysis of East Dongting lake water change based on time series of remote sensing data[C]// Signal Processing (ICSP), 2014 12th International Conference on. IEEE, 2014:718-722. （EI）

58. Ma C, Chen F, Liu J, et al. A New Method of Cloud Detection Based on Cascaded AdaBoost[C]  IOP Conference Series: 8th International Symposium of the Digital Earth, ISDE 2014, 12026（EI）

59. Ma Cai-hong,Dai Qin,Liu Shi-Bin. A Hybrid Pso-isodata Algorithm For Remote Sensing Image Segmentation[C].Ieee Computer Soc.2012,1371-1375. （EI）

60. Ma, Cai-Hong,Dai, Qin,Liu, Shi-Bin. A Hybrid Pso And Active Learning Svm Model For Relevance Feedback In The Content-based Images Retrieval[C].Ieee Computer Society.2012, 130-133. （EI）

61. Ma Cai-hong,Dai Qin,Liu Shi-Bin. A Hybrid Ga And Active Learning Svm Model For Relevance Feedback In The Content-based Images Retrival[C].Amer Soc Mechanical Engineers.2011, 429-432. 

62. Duan J B, Ma C H (*), Liu S B, et al. The remote sensing image retrieval based on multi-feature[C]// Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series. Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series, 2013:88921X-88921X-6. （EI）

63. Dai, Qin, Liu, Jianbo,Liu, Shibin,et al. The Research On Intelligent Content-based Remote Sensing Image Retrieval With Multi-features[C].Acta Press.2012, 390-397. （EI）

Welcome students with backgrounds in remote sensing, computer science, surveying, and related fields who are interested in intelligent recognition and mining of remote sensing information to join us.

Enrollment Majors:

       081002 - Signal and Information Processing

       085401 - Next Generation Electronic Information Technology (including quantum technology, etc.) / Intelligent Processing and Mining of Remote Sensing Data

Enrollment Directions:

• Intelligent Processing and Mining of Remote Sensing Data

• Multimodal Information Mining

• Typical Target Supervision in Global Scale