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Land use/land cover changes in the period of 2015–2020 in AngYai Village, Sikhottabong District, Vientiane Capital, Lao PDR

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
In this study, land use/land cover (LULC) changes were identified in AngYai Village, Sikhottabong District, Vientiane Capital, Laos, from 2015 to 2020 using the Geographic Information System (GIS) and remote sensing (RS). Topographic maps and Google Earth Pro satellite imagery data were used with ArcGIS 10.8 software to map land use fluctuations. The study area was classified into the six main types of LULC (agricultural, builtup, forest, main roads, waste land, and water bodies) based on field research, geographical conditions, and RS data. The results indicated sizeable increases in the built-up, main roads, and especially waste land areas over the study period. The forest and agricultural land areas decreased during the study period, possibly due to increased urbanization rates, nomadic cultivation, and indiscriminate deforestation in the study area. The river area was affected by the construction of hydroelectric dams and by the climate, leading to the drying up of water sources and causing water body areas to decrease to some extent.
Wydawca
Rocznik
Strony
279--286
Opis fizyczny
Bibliogr. 24 poz., rys., tab., wykr.
Twórcy
  • National University of Laos, Faculty of Social Sciences, Vientiane, Lao PDR; Southern Federal University, Rostov-on-Don, Russia
  • National University of Laos, Faculty of Social Sciences, Vientiane, Lao PDR
  • National University of Laos, Faculty of Social Sciences, Vientiane, Lao PDR
  • Hong Duc University, Faculty of Social Sciences, Thanh Hoa, Vietnam
Bibliografia
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  • Aliani H., Malmir M., Sourodi M. & Kafaky S.B., 2019. Change detection and prediction of urban land use changes by CA–Markov model (case study: Talesh County). Environmental Earth Sciences, 78(17), 546. https://doi.org/10.1007/s12665-019-8557-9.
  • Alqurashi A. & Kumar L., 2013. Investigating the use of Remote Sensing and GIS techniques to detect land use and land cover change: A review. Advances in Remote Sensing, 2(2), 193–204. https://doi.org/10.4236/ars.2013.22022.
  • Arshad Z., Robaina M., Shahbaz M. & Veloso A.B., 2020. The effects of deforestation and urbanization on sustainable growth in Asian countries. Environmental Science and Pollution Research, 27(9), 10065–10086. https://doi.org/10.1007/s11356-019-07507-7.
  • 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 pace Science, 18(2), 251–259. https://doi.org/10.1016/j.ejrs.2015.07.003.
  • Buys L. & Miller E., 2011. Conceptualising convenience: Transportation practices and perceptions of inner-urban high density residents in Brisbane, Australia. Transport Policy, 18(1), 289–297. https://doi.org/10.1016/j.tranpol.2010.08.012.
  • Department of Meteorology and Hydrology, 2015. Summary report on hydrometeorological forecasts in 2015, Lao PDR.
  • Department of National Mapping, 2015. General report about the land management nationwide in 2015, Lao PDR.
  • Dolman A.J. & Verhagen A., 2003. Land use and global environmental change. [in:] Dolman A.J., Verhagen A. & Rovers C.A. (eds.), Global Environmental Change and Land Use, Springer, Dordrecht, 3–13. https://doi.org/10.1007/978-94-017-0335-2_1.
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  • Jiyuan L., 2000. Study on the temporal and spatial features of land use change in China-based on the Remote Sensing data. Study of the Quaternary Period, 20(3), 229–239.
  • Lambin E.F., Geist H.J. & Lepers E., 2003. Dynamics of land-use and land-cover change in tropical regions. Annual Review of Environment and Resources, 28(1), 205–241. https://doi.org/10.1146/annurev.energy.28.050302.105459.
  • Liu J.Y., Deng X.Z., Liu M.L. & Zhang S.W., 2002. Study on the spatial patterns of land-use change and analyses of driving forces in Northeastern China during 1990–2000. Chinese Geographical Science, 12(4), 299–308. https://doi.org/10.1007/s11769-002-0033-9.
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  • Xu Y., Yu L., Zhao F.R., Cai X., Zhao J., Lu H. & Gong P., 2018. Tracking annual cropland changes from 1984 to 2016 using time-series Landsat images with a change-detection and post-classification approach: Experiments from three sites in Africa. Remote Sensing of Environment, 218, 13–31. https://doi.org/10.1016/j.rse.2018.09.008.
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Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-b38761a1-da1f-400d-ac86-54f604fa6ba9
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