Abdullah, M. M., Gholoum, M. M. and Abbas, H. A. (2018). Satellite vs. UAVs remote sensing of arid ecosystems: A review within an eclogical perspective. Environ. Anal. Ecol. Stud. 2: 1–5.
Congedo, L. (2021). Semi-automatic classification plugin: a python tool for the download and processing of remote sensing images in QGIS. J. Open Source Softw. 6: doi:10.21105/ joss.03172.
Duraisamy, V., Bendapudi, R. and Jadhav, A. (2018). Identifying hotspots in land use land cover change and the drivers in a semi-arid region of India. Environ. Monit. Assess. 190: doi:10.1007/s10661-018-6919-5.
Ismail, A. Y., Aminudin, S., Andayani, S. A. and Sumekar, Y. (2021). Analysis of land use patterns in the upper Cimanuk river basin and its relationship with irrigation water discharge in Majalengka Regency, Indonesia. Res. Crop. 22: 836-40.
Khan, Z., Saeed, A. and Bazai, M. H. (2020). Land use/land cover change detection and prediction using the CA-Markov model: A case study of Quetta city, Pakistan. J. Geogr. Soc. Sci. 2: 164-82.
Le, P. D. and Nguyen, T. T. (2022). Evaluation of climate change-related vulnerability for natural resources and environment in Thai Nguyen province. TNU J. Sci. Technol. 227: 71-77. doi.org/10.34238/tnu-jst.5441.
Li, D., Tian, P. P., Luo, H. Y., Hu, T. S., Dong, B., Cui, Y.L., Khan, S. B. and Luo, Y.F. (2020). Impacts of land use and land cover changes on regional climate in the Lhasa River basin, Tibetan Plateau. Sci. Total Environ. 742: doi:10.1016/j.scitotenv.2020.140570.
Liping, C., Yujun, S. and Saeed, S. (2018). Monitoring and predicting land use and land cover changes using remote sensing and GIS techniques—A case study of a hilly area, Jiangle, China. PLoS ONE 13: doi:10.1371/journal.pone.0200493.
Mas, J. F., Kolb, M., Paegelow, M., Olmedo, M. T. C. and Houet, T. (2014). Inductive pattern-based land use/cover change models: A comparison of four software packages. Environ. Modelling Software 51: 94-111. doi:10.1016/j.envsoft.2013.09.010.
MohanRajan, S. N., Loganathan, A. and Manoharan, P. (2020). Survey on land use/land cover (LU/LC) change analysis in remote sensing and GIS environment: Techniques and Challenges. Environ. Sci. Pollut. Res. 27: 29900–926. doi:10.1007/s11356-020-09091-7.
Navin, M. S. and Agilandeeswari, L. (2020). Multispectral and hyperspectral images-based land use/land cover change prediction analysis: An extensive review. Multimed. Tools Appl. 79: 29751-774. doi:10.1007/s11042-020-09531-z.
Nguyen, T. T. H., Tran, T. T., Astarkhanova, T. S., Hoang, T. T., Vu, V. L., Tran, D. D., Dau, K. T., Hoang, A. T., Nguyen, N. T., Phung, T. D., Vo, T. T. H. and Vo, T. N. K. (2023). Potential risks of soil erosion in North-Central Vietnam using remote sensing and GIS. Rev. Bras. Eng. Agríc. Ambient. 27: 910-916. doi:10.1590/1807-1929/agriambi.v27n11.
Ojaghi, S., Ahmadi, F. F. and Ebadi, H. (2016). A new method for semi-automatic classification of remotely sensed images developed based on the cognitive approaches for producing spatial data required in geomatics applications. Arab J. Geosci. 9: doi:10.1007/ s12517-016-2730-1.
Phung, N. T., Le, A. T., Pham, T. B. N. and Nguyen, T. X. T. (2019). Applying assessment approach on livelihood vulnerability index, Including mangroves in the context of climate change in Nga Son and Hau Loc districts, Thanh Hoa province. J. Water Resour. Environ. Eng. 6: 123-30.
Rawat, J. and Kumar, M. (2015). Monitoring land use/cover change using remote sensing and GIS techniques: A case study of Hawalbagh block, district Almora, Uttarakhand, India. Egypt J. Remote Sens. Space Sci. 18: 77-84. doi:10.1016/j.ejrs.2015.02.002.
Séférian, R., Nabat, P., Michou, M., Saint-Martin, D., Voldoire, A. and Colin, et al. (2019). Evaluation of CNRM Earth System Model, CNRM-ESM2-1: Role of Earth System Processes in Present-Day and Future Climate. J. Adv. Model. Earth Syst. 11: 4182-227. doi:10.1029/2019MS001791.
Thakkar, A. K., Desai, V. R., Patel, A. and Potdar, M. B. (2016). An effective hybrid classification approach using tasseled cap transformation (TCT) for improving classification of land use/land cover (LU/LC) in semi-arid region: A case study of Morva-Hadaf watershed, Gujarat, India. Arab. J. Geosci. 9: doi:10.1007/s12517-015-2267-8.
Yulianto, F., Prasasti, I., Pasaribu, J.M., Fitriana, H.L., Haryani, N.S. and Sofan, P. (2016). The dynamics of land use/land cover change modeling and their implication for the flood damage assessment in the Tondano watershed, North Sulawesi, Indonesia. Model Earth Syst. Environ. 2: doi:10.1007/s40808-016-0100-3.
Zhang, T., Su, J., Xu, Z., Luo, Y. and Li, J. (2021). Sentinel-2 satellite imagery for urban land cover classification by optimized random forest classifier. Appl. Sci. 11: doi:10.3390/app11020543.
Congedo, L. (2021). Semi-automatic classification plugin: a python tool for the download and processing of remote sensing images in QGIS. J. Open Source Softw. 6: doi:10.21105/ joss.03172.
Duraisamy, V., Bendapudi, R. and Jadhav, A. (2018). Identifying hotspots in land use land cover change and the drivers in a semi-arid region of India. Environ. Monit. Assess. 190: doi:10.1007/s10661-018-6919-5.
Ismail, A. Y., Aminudin, S., Andayani, S. A. and Sumekar, Y. (2021). Analysis of land use patterns in the upper Cimanuk river basin and its relationship with irrigation water discharge in Majalengka Regency, Indonesia. Res. Crop. 22: 836-40.
Khan, Z., Saeed, A. and Bazai, M. H. (2020). Land use/land cover change detection and prediction using the CA-Markov model: A case study of Quetta city, Pakistan. J. Geogr. Soc. Sci. 2: 164-82.
Le, P. D. and Nguyen, T. T. (2022). Evaluation of climate change-related vulnerability for natural resources and environment in Thai Nguyen province. TNU J. Sci. Technol. 227: 71-77. doi.org/10.34238/tnu-jst.5441.
Li, D., Tian, P. P., Luo, H. Y., Hu, T. S., Dong, B., Cui, Y.L., Khan, S. B. and Luo, Y.F. (2020). Impacts of land use and land cover changes on regional climate in the Lhasa River basin, Tibetan Plateau. Sci. Total Environ. 742: doi:10.1016/j.scitotenv.2020.140570.
Liping, C., Yujun, S. and Saeed, S. (2018). Monitoring and predicting land use and land cover changes using remote sensing and GIS techniques—A case study of a hilly area, Jiangle, China. PLoS ONE 13: doi:10.1371/journal.pone.0200493.
Mas, J. F., Kolb, M., Paegelow, M., Olmedo, M. T. C. and Houet, T. (2014). Inductive pattern-based land use/cover change models: A comparison of four software packages. Environ. Modelling Software 51: 94-111. doi:10.1016/j.envsoft.2013.09.010.
MohanRajan, S. N., Loganathan, A. and Manoharan, P. (2020). Survey on land use/land cover (LU/LC) change analysis in remote sensing and GIS environment: Techniques and Challenges. Environ. Sci. Pollut. Res. 27: 29900–926. doi:10.1007/s11356-020-09091-7.
Navin, M. S. and Agilandeeswari, L. (2020). Multispectral and hyperspectral images-based land use/land cover change prediction analysis: An extensive review. Multimed. Tools Appl. 79: 29751-774. doi:10.1007/s11042-020-09531-z.
Nguyen, T. T. H., Tran, T. T., Astarkhanova, T. S., Hoang, T. T., Vu, V. L., Tran, D. D., Dau, K. T., Hoang, A. T., Nguyen, N. T., Phung, T. D., Vo, T. T. H. and Vo, T. N. K. (2023). Potential risks of soil erosion in North-Central Vietnam using remote sensing and GIS. Rev. Bras. Eng. Agríc. Ambient. 27: 910-916. doi:10.1590/1807-1929/agriambi.v27n11.
Ojaghi, S., Ahmadi, F. F. and Ebadi, H. (2016). A new method for semi-automatic classification of remotely sensed images developed based on the cognitive approaches for producing spatial data required in geomatics applications. Arab J. Geosci. 9: doi:10.1007/ s12517-016-2730-1.
Phung, N. T., Le, A. T., Pham, T. B. N. and Nguyen, T. X. T. (2019). Applying assessment approach on livelihood vulnerability index, Including mangroves in the context of climate change in Nga Son and Hau Loc districts, Thanh Hoa province. J. Water Resour. Environ. Eng. 6: 123-30.
Rawat, J. and Kumar, M. (2015). Monitoring land use/cover change using remote sensing and GIS techniques: A case study of Hawalbagh block, district Almora, Uttarakhand, India. Egypt J. Remote Sens. Space Sci. 18: 77-84. doi:10.1016/j.ejrs.2015.02.002.
Séférian, R., Nabat, P., Michou, M., Saint-Martin, D., Voldoire, A. and Colin, et al. (2019). Evaluation of CNRM Earth System Model, CNRM-ESM2-1: Role of Earth System Processes in Present-Day and Future Climate. J. Adv. Model. Earth Syst. 11: 4182-227. doi:10.1029/2019MS001791.
Thakkar, A. K., Desai, V. R., Patel, A. and Potdar, M. B. (2016). An effective hybrid classification approach using tasseled cap transformation (TCT) for improving classification of land use/land cover (LU/LC) in semi-arid region: A case study of Morva-Hadaf watershed, Gujarat, India. Arab. J. Geosci. 9: doi:10.1007/s12517-015-2267-8.
Yulianto, F., Prasasti, I., Pasaribu, J.M., Fitriana, H.L., Haryani, N.S. and Sofan, P. (2016). The dynamics of land use/land cover change modeling and their implication for the flood damage assessment in the Tondano watershed, North Sulawesi, Indonesia. Model Earth Syst. Environ. 2: doi:10.1007/s40808-016-0100-3.
Zhang, T., Su, J., Xu, Z., Luo, Y. and Li, J. (2021). Sentinel-2 satellite imagery for urban land cover classification by optimized random forest classifier. Appl. Sci. 11: doi:10.3390/app11020543.
