1.       Mumtaz, F., Li, J., Liu, Q., Dong, Y., Liu, C., Gu, C., . . . Li, G. (2025). A comprehensive framework for evaluating ecosystem quality changes and human activity contributions in Inner Mongolia and Xinjiang, China. Land Use Policy, 151, 107494. doi: https://doi.org/10.1016/j.landusepol.2025.107494

2.       Mumtaz, F., Li, J., Liu, Q., et al. (2023). Spatio-temporal dynamics of land use transitions associated with human activities over Eurasian Steppe: Evidence from improved residual Analysis. Science of the Total Environment, 905, 166940. DOI: https://doi.org/10.1016/j.scitotenv.2023.166940

3.       Mumtaz, F.; Li, J.; Liu, Q.; Tariq, A.; Arshad, A.; Dong, Y.; Zhao, J.; Bashir, B.; Zhang, H.; Gu, C.; Liu, C. (2023). Impacts of Green Fraction Changes on Surface Temperature and Carbon Emissions: Comparison under Forestation and Urbanization Reshaping Scenarios. Remote Sensing, 15, 859. DOI: https://doi.org/10.3390/rs15030859

4.       Mumtaz, F., Arshad, A., Mirchi, A., Aqil, T., Dakang, W., & Tao Y (2021). Impacts of Reduced Deposition of Atmospheric Nitrogen on Coastal Marine Ecosystem During Substantial Shift in Human Activities in the 21st Century. Geomatics Natural Hazards & Risk, 12(1), 2023-2047. Doi: 10.1080/19475705.2021.1949396

5.       Mumtaz, F., Tao, Y., de Leeuw, G., Zhao, L., Fan, C., Elnashar, A., Naeem, S. (2020). Modeling Spatio-temporal Land Transformation and Its Associated Impacts on land Surface Temperature (LST). Remote Sensing, 12(18), 2987. Doi: 10.3390/rs12182987

6.       Mumtaz, F* et al (2022).Integrated Influencing Mechanism of Potential Drivers on Seasonal Variability of LST in Kolkata Municipal Corporation, India. Land, 11, 1461. DOI: https://doi.org/10.3390/land11091461

7.       Mumtaz, F* et al (2024). Satellite-based rainwater harvesting sites assessment for Dera Ghazi Khan, Punjab, Pakistan. Environmental Science and Pollution Research DOI : 10.1007/s11356-024-34195-9

8.       Mumtaz, F* et al (2025). Urban heat island dynamics in Rawalpindi: a 30-year remote sensing analysis and future projections. Scientific Reports, 15(1), 32760. DOI: https://doi.org/10.1038/s41598-025-13844-0

9.       Mumtaz, F., Tao, Y., Bashir, W. A., Kareem, M., Gengke, W., Li, L., & Bashir, B. (2020). Transition of LULC and future predictions by using CA-Markov Chain Model (A case study of metropolitan city Lahore, Pakistan). Earth Sciences Malaysia, 4(2), 141-146. Doi: 10.26480/esmy.02.2020.141.146

10.   Mumtaz, F., Tao, Y., Bashir, B., Ahmad, A., Li, L., & Hassan, U. H. (2020). The relationship between vegetation dynamics and land surface temperature by using different satellite imageries; A Case study of Metropolitan cities of Pakistan. North American Academic Research, 3, 1-15. Doi: 10.5281/zenodo.3923796

11.   Mumtaz, F., Tao, Y., Bashir, B., Faiz H., Kareem M., Ahmad, A & Hassan, U. H. (2020). The Impact of the lockdown on air quality in result of COVID-19 pandemic over Hubei Province, China. Environment & Ecosystem Science, 2021. 05(01): p. 15-22. DOI: 10.26480/ees.01.2021.15.22

12.   Gu, C., J. Li, Q. Liu, H. Zhang, A. Huete, H. Fang, L. Liu, F. Mumtaz, S. Lin, X. Wang,

Y. Dong, J. Zhao, J. Bai, W. Yu, C. Liu and L. Guan (2025). "Deriving leaf-scale chlorophyll index (CIleaf) from canopy reflectance by correcting for the canopy multiple scattering based on spectral invariant theory."Remote Sensing of Environment 322: 114692. DOI: https://doi.org/10.1016/j.rse.2025.114692

13.   Bashir, B., Liang, D., Cai, R., Mumtaz, F., Kong, L., & Zou, Y. (2025). Spectral properties and remote sensing of snow algal blooms in the Antarctic Peninsula. Remote Sensing of Environment, 328, 114839. doi: https://doi.org/10.1016/j.rse.2025.114839

14.   Zhang, H., Li, J., Gu, C., Guan, L., Wang, X., Mumtaz, F., . . . Yu, W. (2025). A high-resolution global leaf chlorophyll content product using the Sentinel-2 data. Scientific Data, 12(1), 1997. doi: 10.1038/s41597-025-05831-x

15.   Liu C, Li J, Liu Q, Gao J, Mumtaz F, Dong Y, et al. (2023).Combined influence of ENSO and North Atlantic Oscillation (NAO) on Eurasian Steppe during 1982–2018. Science of the Total Environment 2023: 164735. Doi: 10.1016/j.scitotenv.2023.164735

16.   Zhang, H., Li, J., Liu, Q., Lin, S., Huete, A., Liu, L., Croft, H., Clevers, J. G. P., Zeng, Y.,

Wang, X., Gu, C., Zhang, Z., Zhao, J., Dong, Y., Mumtaz, F., & Yu, W. (2022). A novel red-edge spectral index for retrieving the leaf chlorophyll content. Methods in Ecology and Evolution, 00, 1–17. DOI: https://doi.org/10.1111/2041-210X.13994

17.   Gu, C., J. Li, Q. Liu, H. Zhang, L. Liu, F. Mumtaz, Y. Dong, J. Zhao, X. Wang and C. Liu (2023). "Retrieving decametric-resolution leaf chlorophyll content from GF-6 WFV by assessing the applicability of red-edge vegetation indices." Computers and Electronics in Agriculture 215: 108455. DOI: https://doi.org/10.1016/j.compag.2023.108455

18.   Huang, Y., Long, H., Jiang, Y., Feng, D., Ma, Z., & Mumtaz, F. (2024). Motivating factors of farmers' adaptation behaviors to climate change in China: A meta-analysis. Journal of Environmental Management, 359, 121105. https://doi.org/10.1016/j.jenvman.2024.121105

19.   Wang, X., Li, J., Zhang, H., Liu, Q., Liu, L., Gu, C., Mumtaz, F., Zhao, J., Dong, Y., Bai, J., Chu, T., Liu, C., Guan, L., & Huang, W. (2024). Intercomparison and validation of five existing leaf chlorophyll content products over China. International Journal of Applied Earth Observation and Geoinformation, 130, 103930. doi: https://doi.org/10.1016/j.jag.2024.103930

20.   Li, J., Zhang, H., López-Lozano, R., Weiss, M., Gu, C., Mumtaz, F., . . . Liu, X. (2025). Can 3D model improve the accuracy of leaf chlorophyll content estimation using UAV and sentinel-2 data? International Journal of Applied Earth Observation and Geoinformation, 143, 104810. DOI: https://doi.org/10.1016/j.jag.2025.104810

21.   Bashir, B., Cai, R., Wang, S., Liang, D., Cao, C., Xu, M., Mumtaz, F.,. . . Ali, I. (2025). Understanding Vegetation Greening in the Mu Us and Thar Deserts: The Role of Climate Change and Human Interventions. Earth Systems and Environment. doi: 10.1007/s41748-025-00821-w

22.   Naeem, M., Zhang, Y., Tian, X., Miao, P., Li, C., Mumtaz, F., . . . He, S. (2025). Assessing and predicting Bojiang lake area and LULC changes from 2000 to 2045.Journal of Hydrology: Regional Studies, 58, 102216. doi: https://doi.org/10.1016/j.ejrh.2025.102216

23.   Hussain, S., M. Mubeen, W. Nasim, F. Mumtaz, H. G. Abdo, R. Mostafazadeh and S. Fahad (2024). "Assessment of future prediction of urban growth and climate change in district Multan, Pakistan using CA-Markov method." Urban Climate 53: 101766. DOI: https://doi.org/10.1016/j.uclim.2023.101766

24.   Chu, T.; Li, J.; Zhao, J.; Gu, C.; Mumtaz, F.; Dong, Y.; Zhang, H.; Liu, Q. Regional Analysis of Dominant Factors Influencing Leaf Chlorophyll Content in Complex Terrain Regions Using a Geographic Statistical Model. Remote Sensing. 2024, 16, 479. https://doi.org/10.3390/rs16030479

25.   Tariq, A., Yan, J., Alexandre S,G., Khan, M.R., & Mumtaz, F,. (2022): Mapping of cropland, cropping patterns and crop types by combining optical remote sensing images with decision tree classifier and random forest, Geo-spatial Information Science, DOI: https://doi.org/10.1080/10095020.2022.2100287

26.   Bashir, B., Cao, C., Naeem, S., Zamani Joharestani, M., Bo, X., Afzal, H., Mumtaz, F. (2020). Spatio-Temporal Vegetation Dynamic and Persistence under Climatic and Anthropogenic Factors. Remote Sensing 12(16), 2612. Doi: 10.3390/ rs12162612

27.   Wang, D., Yu, T., Liu, Y., Gu, X., Mi, X., Shi, S., Ma, M., Chen, X., Zhang, Y., Liu, Q., Mumtaz, F., Zhan, Y. (2021). Estimating Daily Actual Evapotranspiration at a Landsat-Like Scale Utilizing Simulated and Remote Sensing Surface Temperature. Remote Sensing. 2021, 13, 225. Doi: 10.3390/ rs13020225

28.   Tariq, A., Shu, H., Gagnon, AS., Li, Q., Mumtaz, F., Hysa, A., Siddique, MA. Munir, A., (2021). Assessing Burned Areas in Wildfires and Prescribed Fires with Spectral Indices and SAR Images in the Margalla Hills of Pakistan. Forests. Doi: 10.3390/f12101371

29.   Ahmad A, SR Ahmad, G Hammad, T Aqil, Na Zhao*, Aslam RW and Mumtaz F. (2021). A Synthesis of Spatial Forest Assessment Studies Using Remote Sensing Data and Techniques in Pakistan. Forests, 2021. 12(9): p. 1211. Doi: 10.3390/f12091211

30.   Chen, X.; Gu, X.; Zhan, Y.; Wang, D.; Zhang, Y.; Mumtaz, F.; Shi, S.; Liu, Q. (2022). The Impact of Central Heating on the Urban Thermal Environment Based on Multi- Temporal Remote Sensing Images. Remote Sensing, 14, 2327. DOI: https://doi.org/10.3390/rs14102327

31.   Bashir, B.; Cao, C.; Xie, B.; Chen, Y.; Huang, Z.; Lin, X.; Gul, H.N.; Mumtaz, F.; Duerler, R.S.; Ahmad, A.; Hassan, T. (2022). Unfolding the Success of Positive Human Interventions in Combating Land Degradation. Forests, 13, 818. DOI: https://doi.org/10.3390/f13060818

32.   Ahmad, N.; Ullah, S.; Zhao, N.; Mumtaz, F.; Ali, A.; Ali, A.; Tariq, A.; Kareem, M.; Imran, A.B.; Khan, I.A.; Shakir, M. (2023). Comparative Analysis of Remote Sensing and Geo- Statistical Techniques to Quantify Forest Biomass. Forests, 14, 379. DOI: https://doi.org/10.3390/f14020379

33.   Liu, C.; Li, J.; Liu, Q.; Xu, B.; Dong, Y.; Zhao, J.; Mumtaz, F.; Gu, C.; Zhang, H. (2023). Global Comparison of Leaf Area Index Products over Water-Vegetation Mixed Heterogeneous Surface Network (HESNet-WV). Remote Sensing, 15, 1337. DOI: https://doi.org/10.3390/rs15051337

34.   Li, L., Yu, T., Zhao, L., Zhan, Y., Zheng, F., Mumtaz, F. . . . Wang, C. (2019). Characteristics and trend analysis of the relationship between land surface temperature and nighttime light intensity levels over China. Infrared Physics & Technology, 97, 381-390. Doi: 10.1016/j.infrared.2019.01.018

35.   Chen, X., Gu, X., Liu, P., Wang, D., Mumtaz, F., Shi, S., . . . Zhan, Y. (2022). Impacts of inter-annual cropland changes on land surface temperature based on multi-temporal thermal infrared images. Infrared Physics & Technology, 122, 104081. DOI: 10.1016/j.infrared.2022.104081

36.   Tariq, A., Mumtaz, F., Zeng, X., Baloch, M. Y. J., & Moazzam, M. F. U. (2022). Spatio- temporal variation of seasonal heat islands mapping of Pakistan during 2000–2019, using day-time and night-time land surface temperatures MODIS and meteorological stations data. Remote Sensing Applications: Society and Environment, 100779. DOI: https://doi.org/10.1016/j.rsase.2022.100779

37.   Tariq, A., J. Yan, and F. Mumtaz (2022). Land change modeler and CA-Markov chain analysis for land use land cover change using satellite data of Peshawar, Pakistan. Physics and Chemistry of the Earth, Parts A/B/C,. 128: p. 103286. DOI: https://doi.org/10.1016/j.pce.2022.103286

38.   Tariq, A., Mumtaz, F., Majeed, M., & Zeng, X. (2022). Spatio-temporal assessment of land use land cover based on trajectories and cellular automata Markov modelling and its impact on land surface temperature of Lahore district Pakistan. Environmental Monitoring and Assessment, 195, 114. DOI: https://doi.org/10.1007/s10661-022-10738-w

39.   Tariq, A., & Mumtaz, F. (2023). Modeling spatio-temporal assessment of land use land cover of Lahore and its impact on land surface temperature using multi-spectral remote sensing data. Environmental Science and Pollution Research, 30, 23908-23924 DOI: https://doi.org/10.1007/s11356-022-23928-3

40.   Tariq, A., & Mumtaz, F. (2023). A series of spatio-temporal analyses and predicting modeling of land use and land cover changes using an integrated Markov chain and cellular automata  models. Environmental  Science  and  Pollution  Research  DOI: https://doi.org/10.1007/s11356-023-25722-1

41.   Shah, A., Yan, J., Ullah, I., Aslam, B., Tariq, A., Zhang, Lili and Mumtaz, F. (2021). Classification of Aquifer Vulnerability by Using the DRASTIC Index and Geo-Electrical Techniques. Water, 13(16), 2144. Doi: 10.3390/w13162144

42.   Hu, P., Sharifi, A., Tahir, M. N., Tariq, A., Zhang, L., Mumtaz, F., et al. (2021). Evaluation of Vegetation Indices and Phenological Metrics Using Time-Series MODIS Data for Monitoring Vegetation Change in Punjab, Pakistan. Water, 13(18), 2550. Doi: 10.3390/w13182550

43.   Majeed, M., Tariq, A., Anwar, M. M., Khan, A. M., Arshad, F., Mumtaz, F., et al. (2021). Monitoring of Land Use–Land Cover Change and Potential Causal Factors of Climate Change in Jhelum District, Punjab, Pakistan, through GIS and Multi-Temporal Satellite Data. Land, 10(10), 1026. Doi: 10.3390/land10101026

44.   Liu, Q., Gu, X., Chen, X., Mumtaz, F., Liu, Y., Wang, C., . . . Zhan, Y. (2022). Soil Moisture Content Retrieval from Remote Sensing Data by Artificial Neural Network Based on Sample Optimization. Sensors, 22(4), 1611. DOI: 10.3390/s22041611

45.   Iqbal, M.M.; Li, L.; Hussain, S.; Lee, J.L.; Mumtaz, F.; Elbeltagi, A.; Waqas, M.S.; Dilawar, A. (2022). Analysis of Seasonal Variations in Surface Water Quality over Wet and Dry Regions. Water, 14, 1058. DOI: https://doi.org/10.3390/w14071058

46.   Hussain, S.; Lu, L.; Mubeen, M.; Nasim, W.; Karuppannan, S.; Fahad, S.; Tariq, A.; Mousa, B.G.; Mumtaz, F.; Aslam, M. (2022). Spatiotemporal Variation in Land Use Land Cover in the Response to Local Climate Change Using Multispectral Remote Sensing Data. Land, 11, 595. https://doi.org/10.3390/land11050595

47.   Ahmad, ., Zhang, J., Bashir, B., Mumtaz, F et al. Exploring vegetation trends and restoration possibilities in Pakistan by using Hurst exponent. Environ Sci Pollut Res 30, 91915–91928 (2023). DOI: https://doi.org/10.1007/s11356-023-28822-0

48.   Hussan, H. U., Li, H., Liu, Q., & Mumtaz, F. (2024). Evaluation of Billion Tree Tsunami Project and Its Impacts on Land Surface Temperature: A Satellite Data-Based Investigation. Paper presented at the IGARSS 2024-2024 IEEE International Geoscience and Remote Sensing Symposium. DOI: https://doi.org/10.1109/IGARSS53475.2024.10640950

49.   Shi, S., Ma, Y., Bao, F., Mumtaz, F., (2021). A Satellite Data Based Detailed Study of the Aerosol Emitted from Open Biomass Burning in Northeast China. Atmosphere. 12(12):1700. Doi: 10.3390/atmos12121700

50.   He, D., Zhou, X., Huang, X., Zhang, W., Tian, Q., Xu, N., Xi, Y., Tian, J., Mumtaz, F., (2022) Tempo-differentially selected growth-rate model development and improved extraction of remotely sensed phenology in the Qinghai-Tibet Plateau. J. Appl. Remote Sens. 16 (1), 01850, Doi: 10.1117/1.JRS.16.018501

51.   Hussain, S.; Qin, S.; Nasim, W.; Bukhari, M.A.; Mubeen, M.; Fahad, S.; … Tariq, A.; Mousa, B.G.; Mumtaz, F.; Aslam, M. (2022). Monitoring the Dynamic Changes in Vegetation Cover Using Spatio-Temporal Remote Sensing Data from 1984 to 2020. Atmosphere, 13, 1609. DOI: https://doi.org/10.3390/atmos13101609

52.   Monteiro, L.d.S.; Oliveira-Júnior, J.F.d.; Ghaffar, B.; Tariq, A.; Qin, S.; Mumtaz, F.; Kuriqi, A. (2022). Rainfall in the Urban Area and Its Impact on Climatology and Population Growth. Atmosphere, 13, 1610. DOI: https://doi.org/10.3390/atmos13101610

53.   Wang, Z., Jiang, S., Xu, S., Zhang, J., Mumtaz, F., & Zhang, M. (2024). Spatial patterns and its influencing factors on villages around the Ji-shape bend of the Yellow River. Frontiers in Environmental Science, 12. doi: 10.3389/fenvs.2024.1477693

54.   Muhammad B, Rehman AUR, Mumtaz F, Qun Y and Zhongkui J (2024). Estimation of above-ground biomass in dry temperate forests using Sentinel-2 data and random forest: a case study of the Swat area of Pakistan. Front. Environ. Sci. 12:1448648. doi: 10.3389/fenvs.2024.1448648

55.   Arshad MJ, Ali S, Khan SN, Arshad A, Liu J, Mumtaz F, Waqas MM, Bashir B, Arshad RH (2024). Multispectral Assessment of Net Radiations Using Comprehensive Multi- Satellite Data. Water. 2024; 16(23):3378. DOI: https://doi.org/10.3390/w16233378

56.   Liu, Q., Du, H., Zhan, Y., & Mumtaz, F. (2025). Soil Moisture Retrieval in North America with Passive Microwave and Auxiliary Data Based on Variable Spatial Optimization. Water, 17(11), 1604. DOI: https://doi.org/10.3390/w17111604