Spatiotemporal changes of economic and social development in Laos based on nighttime light data, 1992-2020

JIANG, Luguang; Yang, Cheng Hui; LIU, Ye

doi:10.18402/resci.2021.12.02

Cited by 2 publications

(2 citation statements)

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“…In recent years, with the continuous improvement of the economic level of Laos, problems, such as increasing urban population pressure, land use degradation and depletion of natural resources, have subsequently emerged. The wanton exploitation of land and forest resources has caused grave water pollution and soil destruction, which has seriously restricted the development of agriculture (Jiang et al, 2021). Cities are also faced with a large amount of domestic garbage and other environmental problems due to population growth.…”

Section: Introductionmentioning

confidence: 99%

Simulation, prediction and driving factor analysis of ecological risk in Savan District, Laos

Peng

Qin³

2023

Front. Environ. Sci.

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Introduction: In recent years, Laos, with its unique geographical advantages, has vigorously developed overseas trade and cultural tourism industry, which has promoted local economic development and introduced numerous ecological and environmental problems.Method: Therefore, this research took Savan District as the research area, built the landscape ecological risk assessment model to reveal the spatiotemporal evolution characteristics of Savan District’s ecological risk from 2000 to 2020. Then, the Geodetector model was utilized to explain the driving forces behind changes in the landscape’s ecological risk. Finally, the Markov-PLUS coupling model was used to simulate and predict the changes in the land use pattern and ecological risk in the Savan District in 2030.Results: The following results are presented. 1) The landscape types in Savan District are mainly cultivated land and forest land, with the lowest degree of landscape fragmentation and loss, and the highest degree of landscape loss in unused land. 2) From 2000 to 2020, the average ecological risk index of the whole study area was low and showed a decreasing trend yearly, with the area of low-risk areas accounting for more than 90%. 3) In 2030, the average ecological risk index of the entire Savan District and the two provinces will rise, meanwhile the low-risk areas in the midwest regions and high-risk areas in the northwest will increase.Discussion: This study can guide the future coordinated development of the social economy and ecological environment in Savan District, Laos, and has good reference significance for ecological construction in similar areas in Southeast Asia.

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Section: Introductionmentioning

confidence: 99%

Simulation, prediction and driving factor analysis of ecological risk in Savan District, Laos

Peng

Qin³

2023

Front. Environ. Sci.

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“…Characterized by high openness, short acquisition cycle and low cost, remote sensing data are extensively applied in various studies. Thereinto, nighttime light images (NTL) are extensively applied to study human social activities (Li and Li, 2015;Li et al, 2019), such as spatial analysis of population (Lo, 2001;Zhou et al, 2005), urban area analysis (Shu et al, 2011;Yu et al, 2018;Zhao et al, 2020;Yu et al, 2021;Jiang et al, 2022), land use management (Rahman et al, 2021), energy consumption and carbon emissions (Su et al, 2013;Ma and Xiao, 2017;Du et al, 2021;Niu et al, 2021), social and economic development analysis (Li et al, 2016;Yang et al, 2019;Li et al, 2019;Li et al, 2021;Peng et al, 2022;Jiang et al, 2021), air quality analysis (Cao, 2016;Wu et al, 2021), physical fitness analysis (Deng et al, 2022;Liao et al, 2022), and disaster monitoring (Du et al, 2020). These studies are closely associated with the sustainable development and sustainable development goals of the human society.…”

Section: Introductionmentioning

confidence: 99%

Study on the substitutability of nighttime light data for SDG indicators: a case study of Yunnan Province

Quan,

Song,

Miao

et al. 2023

Front. Environ. Sci.

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Introdution: One crucial method to attain Sustainable Development Goals (SDGs) involves timely adjustment of development policies, promoting the realization of SDGs through a time-series assessment of the degree of accomplishment. In practical applications, data acquisition is a significant constraint in evaluating the SDGs, not only in China but across the globe. Hence, expanding data channels and exploring the feasibility of various data sources for sustainable development assessment are effective strategies to tackle the challenge of data acquisition.Methods: In light of this issue, this study selected Nighttime Light Data, a remote sensing data source closely linked to human social activities, as an alternative data source. Using Yunnan Province as an example, 16 localized indicators of social, economic, and environmental types were chosen. These indicators were then subjected to a correlation analysis with the Total Nighttime Light Index (TNLI). The relationships between different types of indicators and TNLI were analyzed at both temporal and spatial scales, thus identifying the indicators for which TNLI could serve as a suitable substitute measure.Results: The study indicates that when the SDG indicators are classified into economic, social and environmental categories, the total value of nighttime light presents a significant correlation and substitutability with economic indicators; significantly correlated with some social indicators, it can reveal the weak links in the development of underdeveloped areas; it is not significantly correlated with environmental indicators, while a trend correlation exists, which can provide some reference values.Discussion: This study has demonstrated the feasibility of using Nighttime Light Data for sustainable development assessment. It provides a novel evaluation method for countries that, despite a lack of resources for conducting sustainable development assessments, have a greater need for such assessments due to their lower economic development. Furthermore, a multitude of assessment methods can be developed based on Nighttime Light Data.

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Spatiotemporal changes of economic and social development in Laos based on nighttime light data, 1992-2020

Cited by 2 publications

References 0 publications

Simulation, prediction and driving factor analysis of ecological risk in Savan District, Laos

Simulation, prediction and driving factor analysis of ecological risk in Savan District, Laos

Study on the substitutability of nighttime light data for SDG indicators: a case study of Yunnan Province

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