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Analysis of Land Use Change and Driving Mechanisms in Vietnam during the Period 2000–2020

Remote sensing (Basel, Switzerland), 2022-04, Vol.14 (7), p.1600 [Peer Reviewed Journal]

2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 2072-4292 ;EISSN: 2072-4292 ;DOI: 10.3390/rs14071600

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  • Title:
    Analysis of Land Use Change and Driving Mechanisms in Vietnam during the Period 2000–2020
  • Author: Guo, Xuan ; Ye, Junzhi ; Hu, Yunfeng
  • Subjects: Accuracy ; Agricultural land ; Algorithms ; Classification ; Climate change ; Datasets ; driving mechanisms ; dynamic change ; Economic development ; Land classification ; Land cover ; Land use ; Landsat ; Landsat satellites ; Mapping ; Principal components analysis ; random forest ; Regional development ; Remote sensing ; Satellite imagery ; Satellites ; spatial pattern ; Sustainability ; Time series ; time-series analysis ; Vegetation ; Woodlands
  • Is Part Of: Remote sensing (Basel, Switzerland), 2022-04, Vol.14 (7), p.1600
  • Description: High-accuracy, long-time-series and large-scale land classification mapping are essential for assessing the evolutionary patterns of land systems and developing sustainability studies. In this paper, using Google Earth Engine (GEE) and Landsat satellite remote sensing images, based on the Random Forest (RF) algorithm, we carried out remote sensing classification to obtain a year-by-year land use/cover data set in Vietnam over the past 21 years (2000–2020). Further applying principal component analysis and multiple linear regression methods, we examined the spatio-temporal characteristics, dynamic changes and driving mechanisms of land use change. The results show the following: (1) The RF classification algorithm supported by the GEE can quickly and accurately obtain a land use/cover data set. The overall classification accuracy is 0.91 ± 0.01. (2) The land cover types in Vietnam are dominated by woodland and cropland, with an area share of 54.62% and 37.90%, respectively. In the past 20 years, the area of built-up land has increased the most (+93.49%), followed by the area of water bodies (+54.19%), while the area of woodland has remained almost unchanged. (3) The expansion of built-up land is driven by regional economic development; the area changes in cropland, water bodies and woodland are influenced by both national economic development and climate change. The results of the study provide a basis for assessing land use policies in Vietnam and a reference methodological framework for rapid land mapping and analysis in other countries in the China–Indochina Peninsula.
  • Publisher: Basel: MDPI AG
  • Language: English
  • Identifier: ISSN: 2072-4292
    EISSN: 2072-4292
    DOI: 10.3390/rs14071600
  • Source: ROAD: Directory of Open Access Scholarly Resources
    ProQuest Central
    DOAJ Directory of Open Access Journals
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