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Date Published:
16/06/2025
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Natural Sciences Issue (Vietnamese)
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Bui, H. T., Huynh, Q. T., Nguyen, T. N., & Nguyen, H. (2025). Monitoring land surface temperature changes in Kien Giang province – a multi-temporal remote sensing approach. Dong Thap University Journal of Science, 14(8), 3-17. https://doi.org/10.52714/dthu.14.8.2025.1547
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Monitoring land surface temperature changes in Kien Giang province – a multi-temporal remote sensing approach
Main Article Content
Abstract
Land Surface Temperature (LST) is a crucial parameter for monitoring climatic conditions, especially amid increasing climate change. This study was to track the LST changes in Kien Giang province from 2005 to 2023. Daily Terra MODIS (MOD11A1) and Aqua MODIS (MYD11A1) satellite imagery were used to extract LST data on the Google Earth Engine platform. The results indicate a significant correlation between land surface temperature and air temperature measured at weather stations, with coefficients of determination of 0.56 for Terra and 0.76 for Aqua. Central areas of districts, towns, and cities exhibit higher temperatures, particularly in densely built-up areas. Among them, Rach Gia city stands out as one of the hottest areas, attributed to rapid urban development and the concentration of construction activities. Conversely, lower temperatures are found in agricultural zones, wetlands, and aquaculture areas. Phu Quoc city, isolated from the mainland and surrounded by a marine environment, has lower temperatures compared to other areas in the province. These obtained results not only provide an overview of LST changes but also offer valuable insights for land-use planners in formulating sustainable development strategies amid the increasing impacts of climate change and urbanization.
Keywords
MODIS, land surface temperature, remote sensing, urban expansion, land use/land cover change, Vietnamese Mekong Delta, GEE
Article Details
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
References
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Congalton, R. G. (2015). Remote Sensing and Image Interpretation. Photogrammetric Engineering & Remote Sensing, 81(8), 615–616. https://doi.org/10.14358/pers.81.8.615
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Firat, M. N., Kaya, Y., & Polat, N. (2022). Calculation of daily land surface temperature values using Google Earth Engine. 5th Intercontinental Geoinformation Days (IGD), 108–111, Netra, India
Firozjaei, M. K., Kiavarz, M., & Alavipanah, S. K. (2022). Impact of surface characteristics and their adjacency effects on urban land surface temperature in different seasonal conditions and latitudes. Building and Environment, 219, 109145. https://doi.org/10.1016/j.buildenv.2022.109145
Gorelick, N., Hancher, M., Dixon, M., Ilyushchenko, S., Thau, D., & Moore, R. (2017). Google Earth Engine: Planetary-scale geospatial analysis for everyone. Remote Sensing of Environment, 202, 18–27. https://doi.org/10.1016/j.rse.2017.06.031
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Jaelani, L., & Handayani, C. (2022). Spatio-temporal Analysis of Land Surface Temperature Changes in Java Island from Aqua and Terra MODIS Satellite Imageries Using Google Earth Engine. International Journal of Geoinformatics, 18(5), 01–12. https://doi.org/10.52939/ijg.v18i5.2365
Javaid, K., Ghafoor, G. Z., Sharif, F., Shahid, M. G., Shahzad, L., Ghafoor, N., Hayyat, M. U., & Farhan, M. (2023). Spatio-temporal analysis of land use land cover change and its impact on land surface temperature of Sialkot City, Pakistan. Scientific Reports, 13(1). https://doi.org/10.1038/s41598-023-49608-x
Kafy, A.-. A., Dey, N. N., Rakib, A. A., Rahaman, Z. A., Nasher, N. M. R., & Bhatt, A. (2021). Modeling the relationship between land use/land cover and land surface temperature in Dhaka, Bangladesh using CA-ANN algorithm. Environmental Challenges, 4, 100190. https://doi.org/10.1016/j.envc.2021.100190
Maulana, J., & Bioresita, F. (2023). Monitoring of Land Surface Temperature in Surabaya, Indonesia from 2013-2021 Using Landsat-8 Imagery and Google Earth Engine. IOP Conference Series Earth and Environmental Science, 1127(1), 012027. https://doi.org/10.1088/1755-1315/1127/1/012027
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Neteler, M. (2010). Estimating daily land surface temperatures in mountainous environments by reconstructed MODIS LST data. Remote Sensing, 2(1), 333–351. https://doi.org/10.3390/rs1020333
Nghia, B. P. Q., Pal, I., Chollacoop, N., & Mukhopadhyay, A. (2022). Applying Google earth engine for flood mapping and monitoring in the downstream provinces of Mekong river. Progress in Disaster Science, 14, 100235. https://doi.org/10.1016/j.pdisas.2022.100235
Nguyen, H., Pham, V. P., & Nguyen, T. H. D. (2022a). Monitoring 15-year land use/land cover change in the Vietnamese Mekong Delta. Dong Thap University Journal of Science, 11(5), 93–103. https://doi.org/10.52714/dthu.11.5.2022.985
Nguyen, H., Trung, T. H., Phan, D. C., Anh Tran, T., Thi Hai Ly, N., Nasahara, K. N., Prishchepov, A. V., & Hölzel, N. (2022b). Transformation of rural landscapes in the Vietnamese Mekong Delta from 1990 to 2019: A spatio-temporal analysis. Geocarto International, 37(26), 13881–13903. https://doi.org/10.1080/10106049.2022.2086623
Pham-Duc, B., Nguyen, H., Phan, H., & Tran-Anh, Q. (2023). Trends and applications of google earth engine in remote sensing and earth science research: A bibliometric analysis using scopus database. Earth Science Informatics, 16(3), 2355–2371. https://doi.org/10.1007/s12145-023-01035-2
Rebecca, L. (ngày 12/01/2011). 2010 Ties 2005 As the Warmest Year on Record. Climate.gov. Truy cập từ: https://www.climate.gov/news-features/featured-images/2010-ties-2005-warmest-year-record
Roy, B., & Bari, E. (2022). Examining the relationship between land surface temperature and landscape features using spectral indices with Google Earth Engine. Heliyon, 8(9), e10668. https://doi.org/10.1016/j.heliyon.2022.e10668
Sajan, N. B., Kanga, N. S., Singh, N. S. K., Mishra, N. V. N., & Durin, N. B. (2023). Spatial variations of LST and NDVI in Muzaffarpur district, Bihar using Google earth engine (GEE) during 1990-2020. Journal of Agrometeorology, 25(2), 262–267. https://doi.org/10.54386/jam.v25i2.2155
Sở Tài nguyên và Môi trường tỉnh Kiên Giang. (2023). Báo cáo kết quả quan trắc chất lượng môi trường tỉnh Kiên Giang đợt 3 (tháng 4) năm 2023. Truy cập từ: https://stnmt.kiengiang.gov.vn/trang/TinTuc/166/2180/Bao-cao-ket-qua-quan-trac-chat-luong-moi-truong-tinh-Kien-Giang-dot-3--thang-4--nam-2023.html
Sơn, L. (ngày 20/06/2017). Kiên Lương đang đối diện với sự tàn phá khủng khiếp. Tuổi Trẻ. Truy cập từ: https://tuoitre.vn/kien-luong-dang-doi-dien-voi-su-tan-pha-khung-khiep-1334511.htm
Tiwari, A. K., & Kanchan, R. (2024). Analytical study on the relationship among land surface temperature, land use/land cover and spectral indices using geospatial techniques. Discover Environment, 2(1). https://doi.org/10.1007/s44274-023-00021-1
Vân, T. T. (2006). Ứng dụng viễn thám nhiệt khảo sát đặc trưng nhiệt độ bề mặt đô thị với sự phân bố các kiểu thảm phủ ở Thành phố Hồ Chí Minh. Tạp chí Phát triển Khoa học và Công nghệ, 09, 70–74.
Vu, H. T. D., Tran, D. D., Schenk, A., Nguyen, C. P., Vu, H. L., Oberle, P., Trinh, V. C., & Nestmann, F. (2022). Land use change in the Vietnamese Mekong Delta: New evidence from remote sensing. Science of The Total Environment, 813, 151918. https://doi.org/10.1016/j.scitotenv.2021.151918
Wang, X., Zhong, L., & Ma, Y. (2022). Estimation of 30 m land surface temperatures over the entire Tibetan Plateau based on Landsat-7 ETM+ data and machine learning methods. International Journal of Digital Earth, 15(1), 1038–1055. https://doi.org/10.1080/17538947.2022.2088873
Yu, W., Ma, M., Wang, X., Song, Y., & Tan, J. (2011). Validation of MODIS land surface temperature products using ground measurements in the Heihe River Basin, China. SPIE Proceedings, Vol. 8174, Remote Sensing for Agriculture, Ecosystems, and Hydrology XIII, 817423. https://doi.org/10.1117/12.897571
Zhang, P., Bounoua, L., Imhoff, M. L., Wolfe, R. E., & Thome, K. (2014). Comparison of MODIS Land Surface Temperature and Air Temperature over the Continental USA Meteorological Stations. Canadian Journal of Remote Sensing, 40(2), 110–122. https://doi.org/10.1080/07038992.2014.935934
Zhenming, W. (2019). MODIS Land Surface Temperature Products Users’ Guide. The Land Processes Distributed Active Archive Center (LP DAAC). Truy cập từ: https://lpdaac.usgs.gov/documents/715/MOD11_User_Guide_V61.pdf
Anh, N. H., Trang, N. T. Đ., Nguyên, N. T. T., Trọng, T. V., & Sơn, T. V. (2021). Ứng dụng ảnh viễn thám khảo sát nhiệt độ bề mặt tại thành phố Hồ Chí Minh giai đoạn 2016–2020. Journal of Hydro-meteorology, 729(9), 29–39. https://doi.org/10.36335/vnjhm.2021(729).29-39
Binh, N. A., Nhut, H. S., An, N. N., Phuong, T. A., Hanh, N. C., Thao, G. T. P., Pham, T. T., Hong, P. V., Ha, L. T. T., Bui, D. T., & Hoa, P. V. (2021). Thirty-Year Dynamics of LULC at the Dong Thap Muoi Area, Southern Vietnam, Using Google Earth Engine. ISPRS International Journal of Geo-Information, 10(4), 226. https://doi.org/10.3390/ijgi10040226
Bình, N. T., Hải, P. M., Tuấn, N. V. (2018). Thành lập bản đồ độ ẩm đất sử dụng tư liệu viễn thám đa thời gian MODIS bằng phương pháp tam giác NDVI/LST, nghiên cứu thí điểm cho lưu vực sông Cả. Tạp chí Khoa học Đo đạc và Bản đồ, 36, 24–31. https://doi.org/10.54491/jgac.2018.36.272.
Congalton, R. G. (2015). Remote Sensing and Image Interpretation. Photogrammetric Engineering & Remote Sensing, 81(8), 615–616. https://doi.org/10.14358/pers.81.8.615
Cục Thống kê tỉnh Kiên Giang. (2023). Điều kiện tự nhiên của tỉnh Kiên Giang. http://cucthongkekg.gov.vn/news.php?id=52
De Almeida, C. R., Teodoro, A. C., & Gonçalves, A. (2021). Study of the Urban Heat Island (UHI) Using Remote Sensing Data/Techniques: A Systematic Review. Environments, 8(10), 105. https://doi.org/10.3390/environments8100105
Du, H., Ai, J., Cai, Y., Jiang, H., & Liu, P. (2019). Combined Effects of the Surface Urban Heat Island with Landscape Composition and Configuration Based on Remote Sensing: A Case Study of Shanghai, China. Sustainability, 11(10), 2890. https://doi.org/10.3390/su11102890
Firat, M. N., Kaya, Y., & Polat, N. (2022). Calculation of daily land surface temperature values using Google Earth Engine. 5th Intercontinental Geoinformation Days (IGD), 108–111, Netra, India
Firozjaei, M. K., Kiavarz, M., & Alavipanah, S. K. (2022). Impact of surface characteristics and their adjacency effects on urban land surface temperature in different seasonal conditions and latitudes. Building and Environment, 219, 109145. https://doi.org/10.1016/j.buildenv.2022.109145
Gorelick, N., Hancher, M., Dixon, M., Ilyushchenko, S., Thau, D., & Moore, R. (2017). Google Earth Engine: Planetary-scale geospatial analysis for everyone. Remote Sensing of Environment, 202, 18–27. https://doi.org/10.1016/j.rse.2017.06.031
Hải, P. M. và Khang, N. V. (2017). Phân tích hiện tượng đảo nhiệt đô thị mới liên hệ giữa nhiệt độ bề mặt đất và bề mặt không thấm nước. Tạp chí Khoa học Đo đạc và Bản đồ, 31, 17–22. https://doi.org/10.54491/jgac.2017.31.206.
Hồng, N. V., Nguyên, V. T., Ngọc, L. A., Mi, N. T. C. (2021). Xu thế biến đổi các yếu tố khí hậu tại tỉnh Kiên Giang. Tạp chí Khoa học Biến đổi khí hậu, 18(2021), 19–25.
Huy, H. A. (2016). Nghiên cứu sự phân bố nhiệt độ bề mặt đất khu vực thành phố Thái Nguyên trên cơ sở sửu dụng vệ tinh LANDSAT-8, kênh hồng ngoại nhiệt (TIRS). Tạp chí Khí tượng Thủy văn, 10(2016), 26–32.
Jaelani, L., & Handayani, C. (2022). Spatio-temporal Analysis of Land Surface Temperature Changes in Java Island from Aqua and Terra MODIS Satellite Imageries Using Google Earth Engine. International Journal of Geoinformatics, 18(5), 01–12. https://doi.org/10.52939/ijg.v18i5.2365
Javaid, K., Ghafoor, G. Z., Sharif, F., Shahid, M. G., Shahzad, L., Ghafoor, N., Hayyat, M. U., & Farhan, M. (2023). Spatio-temporal analysis of land use land cover change and its impact on land surface temperature of Sialkot City, Pakistan. Scientific Reports, 13(1). https://doi.org/10.1038/s41598-023-49608-x
Kafy, A.-. A., Dey, N. N., Rakib, A. A., Rahaman, Z. A., Nasher, N. M. R., & Bhatt, A. (2021). Modeling the relationship between land use/land cover and land surface temperature in Dhaka, Bangladesh using CA-ANN algorithm. Environmental Challenges, 4, 100190. https://doi.org/10.1016/j.envc.2021.100190
Maulana, J., & Bioresita, F. (2023). Monitoring of Land Surface Temperature in Surabaya, Indonesia from 2013-2021 Using Landsat-8 Imagery and Google Earth Engine. IOP Conference Series Earth and Environmental Science, 1127(1), 012027. https://doi.org/10.1088/1755-1315/1127/1/012027
Mumtaz, F., Tao, Y., De Leeuw, G., Zhao, L., Fan, C., Elnashar, A., Bashir, B., Wang, G., Li, L., Naeem, S., Arshad, A., & Wang, D. (2020). Modeling Spatio-Temporal Land Transformation and Its Associated Impacts on land Surface Temperature (LST). Remote Sensing, 12(18), 2987. https://doi.org/10.3390/rs12182987
Neteler, M. (2010). Estimating daily land surface temperatures in mountainous environments by reconstructed MODIS LST data. Remote Sensing, 2(1), 333–351. https://doi.org/10.3390/rs1020333
Nghia, B. P. Q., Pal, I., Chollacoop, N., & Mukhopadhyay, A. (2022). Applying Google earth engine for flood mapping and monitoring in the downstream provinces of Mekong river. Progress in Disaster Science, 14, 100235. https://doi.org/10.1016/j.pdisas.2022.100235
Nguyen, H., Pham, V. P., & Nguyen, T. H. D. (2022a). Monitoring 15-year land use/land cover change in the Vietnamese Mekong Delta. Dong Thap University Journal of Science, 11(5), 93–103. https://doi.org/10.52714/dthu.11.5.2022.985
Nguyen, H., Trung, T. H., Phan, D. C., Anh Tran, T., Thi Hai Ly, N., Nasahara, K. N., Prishchepov, A. V., & Hölzel, N. (2022b). Transformation of rural landscapes in the Vietnamese Mekong Delta from 1990 to 2019: A spatio-temporal analysis. Geocarto International, 37(26), 13881–13903. https://doi.org/10.1080/10106049.2022.2086623
Pham-Duc, B., Nguyen, H., Phan, H., & Tran-Anh, Q. (2023). Trends and applications of google earth engine in remote sensing and earth science research: A bibliometric analysis using scopus database. Earth Science Informatics, 16(3), 2355–2371. https://doi.org/10.1007/s12145-023-01035-2
Rebecca, L. (ngày 12/01/2011). 2010 Ties 2005 As the Warmest Year on Record. Climate.gov. Truy cập từ: https://www.climate.gov/news-features/featured-images/2010-ties-2005-warmest-year-record
Roy, B., & Bari, E. (2022). Examining the relationship between land surface temperature and landscape features using spectral indices with Google Earth Engine. Heliyon, 8(9), e10668. https://doi.org/10.1016/j.heliyon.2022.e10668
Sajan, N. B., Kanga, N. S., Singh, N. S. K., Mishra, N. V. N., & Durin, N. B. (2023). Spatial variations of LST and NDVI in Muzaffarpur district, Bihar using Google earth engine (GEE) during 1990-2020. Journal of Agrometeorology, 25(2), 262–267. https://doi.org/10.54386/jam.v25i2.2155
Sở Tài nguyên và Môi trường tỉnh Kiên Giang. (2023). Báo cáo kết quả quan trắc chất lượng môi trường tỉnh Kiên Giang đợt 3 (tháng 4) năm 2023. Truy cập từ: https://stnmt.kiengiang.gov.vn/trang/TinTuc/166/2180/Bao-cao-ket-qua-quan-trac-chat-luong-moi-truong-tinh-Kien-Giang-dot-3--thang-4--nam-2023.html
Sơn, L. (ngày 20/06/2017). Kiên Lương đang đối diện với sự tàn phá khủng khiếp. Tuổi Trẻ. Truy cập từ: https://tuoitre.vn/kien-luong-dang-doi-dien-voi-su-tan-pha-khung-khiep-1334511.htm
Tiwari, A. K., & Kanchan, R. (2024). Analytical study on the relationship among land surface temperature, land use/land cover and spectral indices using geospatial techniques. Discover Environment, 2(1). https://doi.org/10.1007/s44274-023-00021-1
Vân, T. T. (2006). Ứng dụng viễn thám nhiệt khảo sát đặc trưng nhiệt độ bề mặt đô thị với sự phân bố các kiểu thảm phủ ở Thành phố Hồ Chí Minh. Tạp chí Phát triển Khoa học và Công nghệ, 09, 70–74.
Vu, H. T. D., Tran, D. D., Schenk, A., Nguyen, C. P., Vu, H. L., Oberle, P., Trinh, V. C., & Nestmann, F. (2022). Land use change in the Vietnamese Mekong Delta: New evidence from remote sensing. Science of The Total Environment, 813, 151918. https://doi.org/10.1016/j.scitotenv.2021.151918
Wang, X., Zhong, L., & Ma, Y. (2022). Estimation of 30 m land surface temperatures over the entire Tibetan Plateau based on Landsat-7 ETM+ data and machine learning methods. International Journal of Digital Earth, 15(1), 1038–1055. https://doi.org/10.1080/17538947.2022.2088873
Yu, W., Ma, M., Wang, X., Song, Y., & Tan, J. (2011). Validation of MODIS land surface temperature products using ground measurements in the Heihe River Basin, China. SPIE Proceedings, Vol. 8174, Remote Sensing for Agriculture, Ecosystems, and Hydrology XIII, 817423. https://doi.org/10.1117/12.897571
Zhang, P., Bounoua, L., Imhoff, M. L., Wolfe, R. E., & Thome, K. (2014). Comparison of MODIS Land Surface Temperature and Air Temperature over the Continental USA Meteorological Stations. Canadian Journal of Remote Sensing, 40(2), 110–122. https://doi.org/10.1080/07038992.2014.935934
Zhenming, W. (2019). MODIS Land Surface Temperature Products Users’ Guide. The Land Processes Distributed Active Archive Center (LP DAAC). Truy cập từ: https://lpdaac.usgs.gov/documents/715/MOD11_User_Guide_V61.pdf
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