We are pleased to share that the AUC Geographica was awarded an Impact Factor of 0.6 in the 2022 Journal Citation Reports™ released by Clarivate in June 2023. AUC Geographica ranks (JCI) in Q3 in Geography.
AUC Geographica (Acta Universitatis Carolinae Geographica) is a scholarly academic journal continuously published since 1966 that publishes research in the broadly defined field of geography: physical geography, geo-ecology, regional, social, political and economic geography, regional development, cartography, geoinformatics, demography and geo-demography.
AUC Geographica also publishes articles that contribute to advances in geographic theory and methodology and address the questions of regional, socio-economic and population policy-making in Czechia.
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Release dates: June 30, December 31
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Journal metrics 2022
Web of Science
Impact factor (JCR®): 0.6
Journal Citation Indicator (JCI): 0.24
Rank (JCI): Q3 in Geography
Cite Score: 1.1
Rank (ASJC): Q3 in Geography, Planning and Development; Q3 in General Earth and Planetary Sciences
The journal is archived in Portico.
AUC GEOGRAPHICA, 172–186
Assessment of forest cover and forest loss using satellite images in Thua Thien Hue province, Vietnam
Bui B. Thien, Vu T. Phuong, Akinola A. Komolafe
zveřejněno: 01. 11. 2023
Deforestation in the tropics continues inexorably with severe implications for biodiversity conservation, climate regulation and ecosystem services. This study investigated variation in forest cover in Thua Thien Hue province, Vietnam, using the Landsat Thematic Mapper and Operational Land Imager satellite images over the period 1989–2021. Imageries were classified using the maximum likelihood classification technique for the years 1989, 2006, and 2021 and were evaluated for accuracy using the kappa coefficient for each year. Furthermore, forest cover losses and gains were evaluated using the Normalized Difference Vegetation Index and Soil Adjusted Vegetation Index, which were compared with the output of the supervised classification. Results showed that the forest cover of Thua Thien Hue province has drastically declined over the years. The forest cover, which was estimated at 68.88% (3461.46 km2) of the total land area in 1989, increased to 69.04% (3469.51 km2) in 2006 and subsequently decreased to 57.55% (2891.81 km2) in 2021. Severely reduced forest cover is often associated with the expansion of agriculture on the forest edge; other contributing factors include logging, illegal production land, and forest fires. Overall, our results show the necessity of forest management, rational land-use planning policy, and increased community awareness of conservation and sustainable development of forest resources in the study area in the future.
klíčová slova: forest cover; vegetation index; remote sensing; GIS; Thua Thien Hue province
1. Agarwal, M., Fatima, T., Freedman, H. I. (2010): Depletion of forestry resource biomass due to industrialization pressure: A ratio-dependent mathematical model. Journal of Biological Dynamics 4(4), 381-396. CrossRef
2. Ahammad, R., Stacey, N., Eddy, I. M., Tomscha, S. A., Sunderland, T. C. (2019): Recent trends of forest cover change and ecosystem services in eastern upland region of Bangladesh. Science of the Total Environment 647, 379-389. CrossRef
3. Alongi, D. M. (2008): Mangrove forests: resilience, protection from tsunamis, and responses to global climate change. Estuarine, Coastal and Shelf Science 76(1), 1-13. CrossRef
4. Anderson, J. R., Hardy, E. E., Roach, J. T., Witmer, R. E. (1976): A land use and land cover classification system for use with remote sensor data. Geological survey professional paper, U.S. government printing office. Washington DC 964, 1-28. CrossRef
5. Atmiş, E., Özden, S., Lise, W. (2007): Urbanization pressures on the natural forests in Turkey: An overview. Urban Forestry & Urban Greening 6(2), 83-92. CrossRef
6. Bakr, N., Weindorf, D. C., Bahnassy, M. H., Marei, S. M., El-Badawi, M. M. (2010): Monitoring land cover changes in a newly reclaimed area of Egypt using multi-temporal Landsat data. Applied Geography 30(4), 592-605. CrossRef
7. Butt, A., Shabbir, R., Ahmad, S. S., Aziz, N. (2015): Land use change mapping and analysis using Remote Sensing and GIS: A case study of Simly watershed, Islamabad, Pakistan. The Egyptian Journal of Remote Sensing and Space Science 18(2), 251-259. CrossRef
8. Chakraborty, A., Seshasai, M. V. R., Reddy, C. S., Dadhwal, V. K. (2018): Persistent negative changes in seasonal greenness over different forest types of India using MODIS time series NDVI data (2001-2014). Ecological Indicators 85, 887-903. CrossRef
9. Chowdhury, M., Hasan, M. E., Abdullah-Al-Mamun, M. M. (2020): Land use/land cover change assessment of Halda watershed using remote sensing and GIS. The Egyptian Journal of Remote Sensing and Space Science 23(1), 63-75. CrossRef
10. Dan, K. O., David, P. K., Pierre, N. L. J., Chérif, A. Y. (2018): Analysis of the Causes of Deforestation and Degradation of the Forest of Katako Village. Environment and Forestry 123(2018), 51945-51948.
11. Dien, V. T. (2004): Susceptibility to forest degradation a case study of the application of remote sensing and GIS in Bach Ma National Park, ThuaThien Hue Province-Vietnam. International Institution for Geo-Information and Earth Observation, Enschede.
12. Dimyati, R. D., Danoedoro, P., Dimyati, M. (2018): Digital interpretability of annual tile-based mosaic of landsat-8 OLI for time-series land cover analysis in the Central Part of Sumatra. Indonesian Journal of Geography 50(2), 168-183. CrossRef
13. Disperati, L., Virdis, S. G. P. (2015): Assessment of land-use and land-cover changes from 1965 to 2014 in Tam Giang-Cau Hai Lagoon, central Vietnam. Applied Geography 58, 48-64. CrossRef
14. Faruque, M. J., Vekerdy, Z., Hasan, M. Y., Islam, K. Z., Young, B., Ahmed, M. T., Monir, M. U., Shovon, S. M., Kakon, J. F., Kundu, P. (2022): Monitoring of land use and land cover changes by using remote sensing and GIS techniques at human-induced mangrove forests areas in Bangladesh. Remote Sensing Applications: Society and Environment 25, 100699. CrossRef
15. Forget, Y., Linard, C., Gilbert, M. (2018): Supervised classification of built-up areas in sub-Saharan African cities using Landsat imagery and OpenStreetMap. Remote Sensing 10(7), 1145. CrossRef
16. Harris, P. M., Ventura, S. J. (1995): The integration of geographic data with remotely sensed imagery to improve classification in an urban area. Photogrammetric Engineering and Remote Sensing 61(8), 993-998.
17. Hasan, M. E., Nath, B., Sarker, A. R., Wang, Z., Zhang, L., Yang, X., Nobi, M. N., Røskaft, E., Chivers, D. J., Suza, M. (2020): Applying multi-temporal Landsat satellite data and markov-cellular automata to predict forest cover change and forest degradation of Sundarban reserve forest, Bangladesh. Forests 11(9), 1016. CrossRef
18. Hor, S., Saizen, I., Tsutsumida, N., Watanabe, T., Kobayashi, S. (2014): The impact of agricultural expansion on forest cover in Ratanakiri Province, Cambodia. Journal of Agricultural Science 6(9), 46. CrossRef
19. Huang, S., Tang, L., Hupy, J. P., Wang, Y., Shao, G. (2021): A commentary review on the use of normalized difference vegetation index (NDVI) in the era of popular remote sensing. Journal of Forestry Research 32(1), 1-6. CrossRef
20. Huete, A. R. (1988): A soil-adjusted vegetation index (SAVI). Remote Sensing of Environment 25(3), 295-309. CrossRef
21. Huete, A. R. (2012): Vegetation indices, remote sensing and forest monitoring. Geography Compass 6(9), 513-532. CrossRef
22. Islam, M. S. (2021): Assessing the dynamics of land cover and shoreline changes of Nijhum Dwip (Island) of Bangladesh using remote sensing and GIS techniques. Regional Studies in Marine Science 41, 101578. CrossRef
23. Jadin, I., Vanacker, V., Hoang, H. T. T. (2013): Drivers of forest cover dynamics in smallholder farming systems: the case of northwestern Vietnam. Ambio 42, 344-356. CrossRef
24. JICA, VNFOREST (2012): The study on Potential Forests and Land Related to ''Climate Change and Forests" in The Socialist Republic of Viet Nam. Final report.
25. Lea, C., Curtis, A. C. (2010): Thematic accuracy assessment procedures: National Park Service vegetation inventory, version 2.0. Natural resource report NPS/2010/NRR-2010/204. National Park Service, Fort Collins, Colorado.
26. Liang, L., Chen, F., Shi, L., Niu, S. (2018): NDVI-derived forest area change and its driving factors in China. PloS One 13(10), e0205885. CrossRef
27. Lu, D., Moran, E., Hetrick, S., Li, G. (2011): Land-use and land-cover change detection. Advances in environmental remote sensing sensors, algorithms, and applications. CRC Press Taylor & Francis Group, New York, pp 273-290. CrossRef
28. Manandhar, R., Odeh, I. O., Ancev, T. (2009): Improving the accuracy of land use and land cover classification of Landsat data using post-classification enhancement. Remote Sensing 1(3), 330-344. CrossRef
29. Matsushita, B., Yang, W., Chen, J., Onda, Y., Qiu, G. (2007): Sensitivity of the enhanced vegetation index (EVI) and normalized difference vegetation index (NDVI) to topographic effects: a case study in high-density cypress forest. Sensors 7(11), 2636-2651. CrossRef
30. Mermoz, S., Bouvet, A., Koleck, T., Ballère, M., Toan, T. L. (2021): Continuous Detection of Forest Loss in Vietnam, Laos, and Cambodia Using Sentinel-1 Data. Remote Sensing 13(23), 4877. CrossRef
31. Meyfroidt, P., Lambin, E. F. (2008): The causes of the reforestation in Vietnam. Land Use Policy 25(2), 182-197. CrossRef
32. Mubako, S., Belhaj, O., Heyman, J., Hargrove, W., Reyes, C. (2018): Monitoring of land use/land-cover changes in the arid transboundary middle Rio grande basin using remote sensing. Remote Sensing 10(12), 2005. CrossRef
33. Muhati, G. L., Olago, D., Olaka, L. (2018): Land use and land cover changes in a sub-humid Montane forest in an arid setting: A case study of the Marsabit forest reserve in northern Kenya. Global Ecology and Conservation 16, e00512. CrossRef
34. Osio, A., Lefèvre, S., Ogao, P., Ayugi, S. (2018): OBIA-based Monitoring of Riparian Vegetation Applied to the Identification of Degraded Acacia Xanthophloea along Lake Nakuru, Kenya. In GEOBIA 2018-From pixels to ecosystems and global sustainability hal-01960341, version 1, 1--22.
35. Owojori, A., Xie, H. (2005, March): Landsat image-based LULC changes of San Antonio, Texas using advanced atmospheric correction and object-oriented image analysis approaches. In 5th international symposium on remote sensing of urban areas, Tempe, AZ.
36. Pendrill, F., Gardner, T. A., Meyfroidt, P., Persson, U. M., Adams, J., Azevedo, T., Lima, M. G. B., Baumann, M., Curtis, P. G., Sy, V. D., Garrett, R., Godar, J., Goldman, E. D., Hansen, M. C., Heilmayr, R., Herold, M., Kuemmerle, T., Lathuillière, M. J., Ribeiro, V., Tyukavina, A., Weisse, M. J., West, C. (2022): Disentangling the numbers behind agriculture-driven tropical deforestation. Science 377(6611), eabm9267. CrossRef
37. People's Committee of Thua Thien Hue Province (2005): Thua Thien hue chorography - part nature. Social Sciences Publishing House.
38. People's Committee of Thua Thien Hue Province (2021): Decision to announce the forest status of Thua Thien Hue province in 2020. Available at: https://stnmt.thuathienhue.gov.vn/UploadFiles/TinTuc/2021/3/3/00.00.h57439qdubnd2021pl2_signed_1.pdf.
39. Pesaresi, S., Mancini, A., Quattrini, G., Casavecchia, S. (2020): Mapping mediterranean forest plant associations and habitats with functional principal component analysis using Landsat 8 NDVI time series. Remote Sensing 12(7), 1132. CrossRef
40. Pham, T. T., Moeliono, M., Nguyen, T. H., Nguyen, H. T., Vu, T. H. (2012): The context of REDD+ in Vietnam: drivers, agents and institutions. CIFOR Occasional, pp 75. CrossRef
41. Pham, T. T., Ngo, H. C., Dao, T. L. C., Hoang, T. L., Moeliono, M. (2021): Participation and influence of REDD+ actors in Vietnam, 2011-2019. Global Environmental Change 68, 102249. CrossRef
42. Phuong, V. T., Thien, B. B. (2023): Using Landsat Satellite Images to Detect Forest Cover Changes in the Northeast Region of Vietnam. Bulletin of the Transilvania University of Brasov. Series II: Forestry - Wood Industry - Agricultural Food Engineering 16(1), 19-36. CrossRef
43. Ranjan, R. (2019): Assessing the impact of mining on deforestation in India. Resources Policy 60, 23-35. CrossRef
44. Shivakumar, B. R., Rajashekararadhya, S. V. (2018): Investigation on land cover mapping capability of maximum likelihood classifier: a case study on North Canara, India. Procedia Computer Science 143, 579-586. CrossRef
45. Spadoni, G. L., Cavalli, A., Congedo, L., Munafò, M. (2020): Analysis of Normalized Difference Vegetation Index (NDVI) multi-temporal series for the production of forest cartography. Remote Sensing Applications: Society and Environment 20, 100419. CrossRef
46. Thakur, S., Maity, D., Mondal, I., Basumatary, G., Ghosh, P. B., Das, P., De, T. K. (2021): Assessment of changes in land use, land cover, and land surface temperature in the mangrove forest of Sundarbans, northeast coast of India. Environment, Development and Sustainability 23(2), 1917-1943. CrossRef
47. Thien, B. B., Phuong, V. T. (2023): Using Landsat satellite imagery for assessment and monitoring of long-term forest cover changes in Dak Nong province, Vietnam. Geographica Pannonica 27(1), 69-82. CrossRef
48. Thien, B. B., Sosamphanh, B., Yachongtou, B., Phuong, V. T. (2022): Land use/land cover changes in the period of 2015-2020 in AngYai Village, Sikhottabong District, Vientiane Capital, Lao PDR. Geology, Geophysics and Environment 48(3), 279-286. CrossRef
49. Thien, B. B., Yachongtou, B., Phuong, V. T. (2023): Long-term monitoring of forest cover change resulting in forest loss in the capital of Luang Prabang province, Lao PDR. Environmental Monitoring and Assessment 195(8), 1-17. CrossRef
50. Thua Thien Hue General Statistical Office (2019): Statistical yearbook 2018. Thuan Hoa Publishing House.
51. Tran, D. X., Tran, T. V., Pearson, D., Myint, S. W., Lowry, J., Nguyen, T. T. (2022): Spatiotemporal analysis of forest cover change and associated environmental challenges: a case study in the Central Highlands of Vietnam. Geocarto International 37(25), 9277-9297. CrossRef
52. Truong, N. C. Q., Nguyen, H. Q., Kondoh, A. (2018): Land use and land cover changes and their effect on the flow regime in the upstream Dong Nai River Basin, Vietnam. Water 10(9), 1206. CrossRef
53. Tsutsumida, N., Comber, A. J. (2015): Measures of spatio-temporal accuracy for time series land cover data. International Journal of Applied Earth Observation and Geoinformation 41, 46-55. CrossRef
54. Yen, P., Ziegler, S., Huettmann, F., Onyeahialam, A. I. (2005): Change detection of forest and habitat resources from 1973 to 2001 in Bach Ma National Park, Vietnam, using remote sensing imagery. International Forestry Review 7(1), 1-8. CrossRef
Assessment of forest cover and forest loss using satellite images in Thua Thien Hue province, Vietnam is licensed under a Creative Commons Attribution 4.0 International License.
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