2016
DOI: 10.3390/su8101011
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Rubber Plantation Expansion Related Land Use Change along the Laos-China Border Region

Abstract: Spatial-temporal changes of land use and land cover in Luang Namtha Province in northern part of Laos was analyzed using Landsat TM (Thematic Mapper)/ETM+ (Enhanced Thematic Mapper) images from 1990 to 2010 since the opening of the Boten border adjacent to China. The results showed that: (1) "forest land-cultivated land-grassland" was the primary landscape structure. Woodland was the major land cover type, while paddy field was the dominant land use type replaced by rubber plantation in 2010; (2) since the ope… Show more

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Cited by 20 publications
(17 citation statements)
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“…To date, Landsat vegetation indices (VIs) and their combinations, such as the Normalized Difference Vegetation Index (NDVI) (Robinson et al, 2017;Tucker et al, 1986), Normalized Difference Vegetation Index (NDMI) (Grogan et al, 2015;Vogelmann and Rock, 1988), Land Surface Water Index (Wang et al, 2018;Xiao et al, 2004), Enhanced Vegetation Index (Dong et al, 2016;Huete, 1988), and Normalized Burn Ratio (NBR) (Frazier et al, 2018;García and Caselles, 1991;Li et al, 2015), have been used to detect and map rubber plantations. The relevant studies have focused on small-scale, regional mapping of rubber plantations in traditional planting regions like Indonesia and Malaysia (Razak and Shariff, 2018;Trisasongko, 2017) as well as emerging rubbergrowing areas such as Xishuangbanna (Fan et al, 2015;Kou et al, 2015;Sun et al, 2017;Xiao et al, 2019c), Hainan Island Dong et al, 2013) in southern China, northeast Thailand (Li and Fox, 2011), and the borders of China, Myanmar, and Laos (Liu et al, 2013(Liu et al, , 2016, the Cambodia-Vietnam border (Ye et al, 2018), and the China-Laos border Tang et al, 2019;Xiao et al, 2020a). However, few studies have been concerned with developing robust algorithms over larger areas, such as the entire MSEA (Chen et al, 2016).…”
Section: Introductionmentioning
confidence: 99%
“…To date, Landsat vegetation indices (VIs) and their combinations, such as the Normalized Difference Vegetation Index (NDVI) (Robinson et al, 2017;Tucker et al, 1986), Normalized Difference Vegetation Index (NDMI) (Grogan et al, 2015;Vogelmann and Rock, 1988), Land Surface Water Index (Wang et al, 2018;Xiao et al, 2004), Enhanced Vegetation Index (Dong et al, 2016;Huete, 1988), and Normalized Burn Ratio (NBR) (Frazier et al, 2018;García and Caselles, 1991;Li et al, 2015), have been used to detect and map rubber plantations. The relevant studies have focused on small-scale, regional mapping of rubber plantations in traditional planting regions like Indonesia and Malaysia (Razak and Shariff, 2018;Trisasongko, 2017) as well as emerging rubbergrowing areas such as Xishuangbanna (Fan et al, 2015;Kou et al, 2015;Sun et al, 2017;Xiao et al, 2019c), Hainan Island Dong et al, 2013) in southern China, northeast Thailand (Li and Fox, 2011), and the borders of China, Myanmar, and Laos (Liu et al, 2013(Liu et al, , 2016, the Cambodia-Vietnam border (Ye et al, 2018), and the China-Laos border Tang et al, 2019;Xiao et al, 2020a). However, few studies have been concerned with developing robust algorithms over larger areas, such as the entire MSEA (Chen et al, 2016).…”
Section: Introductionmentioning
confidence: 99%
“…Four documents used the popular method of supervised classification using the Maximum Likelihood algorithm to investigate rubber expansion [57,64,94,95]. Other supervised algorithms used were Decision Tree [62,[96][97][98] and shapelet based algorithms [99]. Grogan et al [88] used the Landtrendr algorithm to study forest disturbance due to rubber area increment.…”
Section: Change Detectionmentioning
confidence: 99%
“…Fig. local civil society groups speculated that the dam was funded by a Vietnamese loan, which would be paid back through selling its water to cash crop producers in the Muang Sing valley that, given the proliferation of rubber and other cash crops since the early 2000s (Liu et al, 2016), has experienced a significant decrease in surface water flow and groundwater levels (Fig. 17).…”
Section: Concentration Of Labor On Food Production Due To Compromise By Labor Shortagementioning
confidence: 99%