2022
DOI: 10.3390/land11060927
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Spatio-Temporal Patterns of Land-Use Changes and Conflicts between Cropland and Forest in the Mekong River Basin during 1990–2020

Abstract: The Mekong River Basin (MRB) has experienced drastic and extensive land-use and land-cover changes (LULCCs) since the 1990s, including the conflicts between cropland and forest, yet remain quantitatively uninvestigated. With three decades (1990–2020) of land-use products, here we reveal the characteristics of LULCCs and the conflicts between cropland and forest in the MRB and its three sub-basins, i.e., upstream area (UA), midstream area (MA), and downstream area (DA). The four main results are as follows: (1)… Show more

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Cited by 11 publications
(6 citation statements)
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“…The study of changes in land use has been widespread and beneficial for understanding the evolution of human behavior, whether it involves alterations in land use or forested areas [27,28]. These studies examined changes in the environmental system of forests and the challenges between forested land and agricultural areas.…”
Section: -Discussionmentioning
confidence: 99%
“…The study of changes in land use has been widespread and beneficial for understanding the evolution of human behavior, whether it involves alterations in land use or forested areas [27,28]. These studies examined changes in the environmental system of forests and the challenges between forested land and agricultural areas.…”
Section: -Discussionmentioning
confidence: 99%
“…Regarding the TAFF, it has witnessed various kinds of deforestation pathways and patterns of agrarian transformation (Junquera & Grêt-Regamey, 2019;Morton et al, 2006). There are differences in deforestation ways and land conversion patterns across continents, such as pasture establishment and crop intensification in the Brazilian Amazon (Garrett et al, 2018), small-scale agricultural expansion in the Congo Basin (Tyukavina et al, 2018), cropland and commercialized plantations expansion in Southeast Asia (Xiao et al, 2021;Zeng, Estes, et al, 2018), and woody encroachment in the forest-savanna transitional area of Africa (Brandt et al, 2018;Mitchard et al, 2011); therefore, previous research has greatly enriched our knowledge of FL and agricultural expansion or intensification (Feng et al, 2021;Margono et al, 2014;Stibig et al, 2014;Zhai et al, 2022). Understanding of the advance and retreat of agricultural forests in the TAFF is, however, still poor because the dynamics (including magnitudes and processes) are complex and regionally diverse, let alone the longitudinal and horizontal mechanisms and drivers (Li et al, 2021;Stibig et al, 2014).…”
Section: Introductionmentioning
confidence: 99%
“…Recently, analyses of LUC from different perspectives have been conducted, such as an analysis of landscape patterns (Tscharntke et al, 2005), spatiotemporal variations (Zhai et al, 2022), drivers (Tian et al, 2014), mapping dynamics (Hu et al, 2021), and simulation prediction (Veldkamp and Lambin, 2001). LUC studies have mainly focused on areas with significant human activity (Han et al, 2015), fragile ecological environments (Li et al, 2013), or global impact (Deadman et al, 2004).…”
Section: Introductionmentioning
confidence: 99%
“…To determine how geopolinomical relations impact LUC in border areas, it is necessary to accurately monitor border LUC and understand its spatiotemporal processes, geographical characteristics, and national differences. To date, some studies have focused on regional scales such as provinces, watersheds, or certain cities, such as Bokeo Province in Laos (Boundeth et al, 2012) and the Mekong River Basin (Zhai et al, 2022), lacking systematic and comprehensive LUC studies in border areas (Zhang et al, 2022). Moreover, most studies focused on a single typical land type, such as the recovery of agriculture and fallow vegetation in northern Laos (Liao et al, 2015), the expansion of construction land in the Boten (Laos)-Mohan (China) border port (Li and Xiao, 2022), or the expansion of rubber plantations across national borders in Chinese border (Xiao et al, 2019).…”
Section: Introductionmentioning
confidence: 99%