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Latthachack P, Llopis JC, Heinimann A, Thongmanivong S, Vongvisouk T, Messerli P, Zaehringer JG. Agricultural commercialization in borderlands: Capturing the transformation of a tropical forest frontier through participatory mapping. FRONTIERS IN SUSTAINABLE FOOD SYSTEMS 2023. [DOI: 10.3389/fsufs.2022.1048470] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/15/2023] Open
Abstract
Forest-frontier landscapes in the humid tropics display distinct land use change dynamics compared to other world regions, providing useful examples of current global environmental and development challenges. In northwestern Laos, part of the former Golden Triangle region, investments in value chains for commercial crops—mainly to fulfill Chinese market demands—have triggered various land use changes and put increasing pressure on remaining biodiverse forest areas. Capturing the existing land use change trajectories is a key initial step toward further studies assessing land use change impacts. However, methodological challenges arise when conducting spatially-explicit change assessments in these regions, given the high temporal variability of land use at the plot level, compounded by the paucity of good quality satellite imagery. Thus, we applied a novel approach combining analysis of very high-resolution (VHR) satellite imagery with participatory mapping. This enabled joint collection of annual land use information for the last 17 years together with local land users, shedding light on temporally dense land system dynamics. For decades, the government of Laos has sought to halt shifting cultivation, labeling it environmentally degrading, and to reduce poverty through promotion of permanent commodity-oriented commercial agriculture. Among other things, this gave rise to a boom in banana and rubber investments in Luang Namtha province in order to satisfy growing Chinese demand for these commodities. The present paper investigates the impact of these cash crop booms on land use transitions and whether they reduced pressure on forest-frontier areas, as ostensibly desired by government authorities. Our study is among the first to demonstrate in a spatially-explicit manner that subsistence agriculture—in less than two decades—has virtually disappeared in northern Laos due to diverse cash-crop production and agricultural commercialization initiatives linked to Chinese investments. As subsistence-focused cultivation systems are being replaced by land uses solely aimed at commercial production for export, a telecoupled land system is being developed in northwestern Laos with potentially manifold impacts for sustainable development.
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Chen A, Yang X, Guo J, Zhang M, Xing X, Yang D, Xu B, Jiang L. Dynamic of land use, landscape, and their impact on ecological quality in the northern sand-prevention belt of China. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2022; 317:115351. [PMID: 35642818 DOI: 10.1016/j.jenvman.2022.115351] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/28/2022] [Revised: 05/05/2022] [Accepted: 05/17/2022] [Indexed: 06/15/2023]
Abstract
Changes in land use and landscapes have a direct impact on the regional eco-environment. It is of great importance to understand the change pattern of land use, landscapes, and their mechanism on the ecological quality, especially ecologically fragile areas. The northern sand-prevention belt (NSPB) is an important ecologically fragile area in China, which has a large influence on the ecological security of the entire country. Based on the land use data of the NSPB in 2000, 2010, and 2018, we studied the spatio-temporal characteristics of land-use change and change in landscape patterns. The ecological quality represented by the remote sensing-based desertification index (RSDI) was calculated using satellite images. The effects of land use and landscape patterns on RSDI were analyzed by geographic detector and geographically weighted regression. Important results include the following: (1) Land-use change in the study area was high during 2000-2010 but slower in 2010-2018. Grassland was the largest land-use type in the NSPB, and varied greatly in terms of total change and spatial location. The major change was the conversion between dense and moderate grass, with 64,860 km2 of dense grass turning into moderate grass, and 48,505 km2 changing the other way. (2) Among the four landscape metrics, patch density, area-weighted mean fractal dimension, and edge density increased, whereas the aggregation index decreased, which indicated that the landscape was developing towards heterogeneity, fragmentation, complexity, and aggregation. Spatially, the landscape metrics presented a strip distribution in the east of the NSPB. (3) The effects of various land-use types on ecological quality, from high to low, were unused land, woodland, dense grass, cropland, moderate grass, built-up land, sparse grass, and waterbody. The areas where the ecological quality was greatly affected by the landscape patterns were concentrated in the agro-pastoral ecotone and the forest-steppe ecotone. The results of this study reveal the trends of land use and landscape patterns in the NSPB over 18 years and can help to understand their mechanism on ecological quality, which is of significance for the management of this area.
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Affiliation(s)
- Ang Chen
- School of Grassland Science, Beijing Forestry University, Beijing, 100083, China
| | - Xiuchun Yang
- School of Grassland Science, Beijing Forestry University, Beijing, 100083, China.
| | - Jian Guo
- State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, Beijing, 100875, China
| | - Min Zhang
- School of Grassland Science, Beijing Forestry University, Beijing, 100083, China
| | - Xiaoyu Xing
- Key Laboratory of Agri-informatics, Ministry of Agriculture/Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Dong Yang
- Key Laboratory of Agri-informatics, Ministry of Agriculture/Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Bin Xu
- Key Laboratory of Agri-informatics, Ministry of Agriculture/Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Liwei Jiang
- Academy of Forestry Inventory and Planning, National Forestry and Grassland Administration, Beijing, 100714, China
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Abstract
Frequent land use change has generally been considered as a consequence of human activities. Here, we revealed the land use volatility process in northern Southeast Asia (including parts of Myanmar, Thailand, Laos, Vietnam, and China) from 2000 to 2018 with LandTrendr in the Google Earth Engine (GEE) platform based on the Normalized Burning Index (NBR). The result showed that land use volatility with similar degrees had very obvious aggregation characteristics in time and space in the study area, and the time for the occurrence of land use volatility in adjacent areas was often relatively close. This trend will become more obvious with the intensity of land use volatility. At the same time, land use volatility also has obvious spillover effects, and strong land use volatility will drive changes in the surrounding land. If combined with the land use/cover types, which are closely related to human activities that could have more severe land use volatility, and with the increase of the volatility intensity, the proportion of the land use type with strong land use volatility will gradually increase. Revealing the land use volatility process has a possibility to deepen the understanding of land use change and to help formulate land use policy.
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Yang Y, Chen J, Lan Y, Zhou G, You H, Han X, Wang Y, Shi X. Landscape Pattern and Ecological Risk Assessment in Guangxi Based on Land Use Change. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:ijerph19031595. [PMID: 35162617 PMCID: PMC8835525 DOI: 10.3390/ijerph19031595] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/21/2021] [Revised: 01/26/2022] [Accepted: 01/28/2022] [Indexed: 12/10/2022]
Abstract
Due to ecological environmental fragility and soil erosion in Guangxi, studies of landscape patterns and associated ecological risks are needed to guide sustainable land development and ecologically sensitive land management. This study assesses dynamic spatial and temporal change patterns in land use and ecological risks based on 30 m land-use data, analyzes spatial correlations with ecological risks, and explores natural and socio-economic factor impacts on ecological risks. The results reveal: (1) A rapid and sizeable construction land increase in Guangxi from 2000 to 2018 associated mainly with loss of woodland and grassland. (2) Guangxi had the highest number of arable land patches from 2000 to 2018, and the distribution tended to be fragmented; moreover, the construction land gradually expanded outward from concentrated areas to form larger aggregates with increasing internal stability each year. (3) Guangxi ecological risk levels were low, low–medium, and medium, with significantly different spatial distributions observed for areas possessing different ecological risk levels. Regional ecological risk gradually decreased from the middle Guangxi regions to the surrounding areas and was positively correlated with spatial distribution. (4) Socio-economic factor impacts on ecological risk exceeded natural factor impacts. These results provide guidance toward achieving ecologically sensitive regional land-use management and ecological risk reduction and control, it can also provide a reference for ecological risk research in other similar regions in the world.
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Affiliation(s)
- Yanping Yang
- College of Geomatics and Geoinformation, Guilin University of Technology, Guilin 541004, China; (Y.Y.); (Y.L.); (G.Z.); (H.Y.); (X.H.); (Y.W.); (X.S.)
| | - Jianjun Chen
- College of Geomatics and Geoinformation, Guilin University of Technology, Guilin 541004, China; (Y.Y.); (Y.L.); (G.Z.); (H.Y.); (X.H.); (Y.W.); (X.S.)
- Guangxi Key Laboratory of Spatial Information and Geomatics, Guilin University of Technology, Guilin 541004, China
- Correspondence:
| | - Yanping Lan
- College of Geomatics and Geoinformation, Guilin University of Technology, Guilin 541004, China; (Y.Y.); (Y.L.); (G.Z.); (H.Y.); (X.H.); (Y.W.); (X.S.)
- Guangxi Key Laboratory of Spatial Information and Geomatics, Guilin University of Technology, Guilin 541004, China
| | - Guoqing Zhou
- College of Geomatics and Geoinformation, Guilin University of Technology, Guilin 541004, China; (Y.Y.); (Y.L.); (G.Z.); (H.Y.); (X.H.); (Y.W.); (X.S.)
- Guangxi Key Laboratory of Spatial Information and Geomatics, Guilin University of Technology, Guilin 541004, China
| | - Haotian You
- College of Geomatics and Geoinformation, Guilin University of Technology, Guilin 541004, China; (Y.Y.); (Y.L.); (G.Z.); (H.Y.); (X.H.); (Y.W.); (X.S.)
- Guangxi Key Laboratory of Spatial Information and Geomatics, Guilin University of Technology, Guilin 541004, China
| | - Xiaowen Han
- College of Geomatics and Geoinformation, Guilin University of Technology, Guilin 541004, China; (Y.Y.); (Y.L.); (G.Z.); (H.Y.); (X.H.); (Y.W.); (X.S.)
- Guangxi Key Laboratory of Spatial Information and Geomatics, Guilin University of Technology, Guilin 541004, China
| | - Yu Wang
- College of Geomatics and Geoinformation, Guilin University of Technology, Guilin 541004, China; (Y.Y.); (Y.L.); (G.Z.); (H.Y.); (X.H.); (Y.W.); (X.S.)
- Guangxi Key Laboratory of Spatial Information and Geomatics, Guilin University of Technology, Guilin 541004, China
| | - Xue Shi
- College of Geomatics and Geoinformation, Guilin University of Technology, Guilin 541004, China; (Y.Y.); (Y.L.); (G.Z.); (H.Y.); (X.H.); (Y.W.); (X.S.)
- Guangxi Key Laboratory of Spatial Information and Geomatics, Guilin University of Technology, Guilin 541004, China
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Mapping Abandoned Cropland Changes in the Hilly and Gully Region of the Loess Plateau in China. LAND 2021. [DOI: 10.3390/land10121341] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
As a form of land marginalization, abandoned cropland has an important impact on food security and the effective supply of agricultural products. With rapid urbanization across the world, large areas of cropland are abandoned in some regions, especially in mountainous and hilly areas with poor terrain. Due to the fine fragmentation and scattered distribution of abandoned cropland, and considering differences in the abandoned and fallow time of cropland, it is difficult to extract information using remote sensing technology. Therefore, this paper proposes a change in the detection method for extracting abandoned cropland information based on identifying the annual land use trajectory. Based on Landsat satellite data, annual land use was mapped from 2011 to 2020 in Gaolan County, which is located in the hilly and gully region of the Loess Plateau of China, using the random forest classification method. Subsequently, abandoned cropland information in Gaolan County was extracted, based on the land use change trajectory and analysis of the influencing factors of abandoned land. The results showed that: (1) The overall accuracy of land use interpretation in Gaolan County ranged from 86.44% to 95.45%, from 2011 to 2020, with a kappa coefficient of up to 0.93, and the classification results were ideal. (2) The recall of extracted abandoned cropland was 81%, the extraction accuracy of which was relatively high. (3) From 2013 to 2020, the cropland abandonment rate in Gaolan County ranged from 8.41% to 19.65%, with an average of 14.55%, which increased and then decreased. The abandonment rate was highest in 2015 but it then decreased year by year. The average period of abandoned cropland was 4.2 years. (4) The influence factors of the plot scale explain the difference in the spatial distribution of cultivated land abandonment. The higher the slope condition, the lower the soil nutrient content and the greater the possibility of abandonment.
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