Roads as drivers of above‐ground biomass loss at tropical forest edges in Xishuangbanna, Southwest China

Dissanayake, Dissanayake Mudiyanselage Naveen Jayalal; Zhai, De‐Li; Dossa, Gbadamassi G.O.; Shi, Jipu; Luo, Qinghui; Xu, Jianchu

doi:10.1002/ldr.3316

Cited by 4 publications

(1 citation statement)

References 48 publications

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“…What then can we deduce about the drivers of deforestation in this region from this remote sensing and GIS analysis? The evidence presented in Figure 7 signals the important role of road building in fragmenting forests that has been noted by other researchers (Davidson et al, 2012; Dissanayake et al, 2019). We can infer from this that the fishbone forest clearance pattern (Figure 5), which has been observed frequently in the Amazon Basin (de Filho & Metzger, 2006; Ewers & Laurance, 2006) is present.…”

Section: Discussionsupporting

confidence: 79%

Spatiotemporal analysis of deforestation in the Chapare region of Bolivia using LANDSAT images

et al. 2020

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The purpose of this study is to quantify (a) spatiotemporal deforestation patterns, and (b) the relationships between changes in the main land-cover types in the Chapare region of Bolivia. We applied subspace classification methods to LANDSAT data from 1986, 1999, and 2018 and used grid cells at scales of 150, 300, 600, and 900 m to measure deforestation trajectories. The 150 m grids provided better detail to determine deforestation trajectories than coarser-scale grid cells. Differences in grid-cell scale did not influence the statistical trends in land-cover changes significantly. Changes in forest area were negatively correlated with changes in cropland (r = −.44), grassland (r = −.34), swamp grassland (r = −.38), and regrowth (r = −.32) areas. Correlations between forest losses in cropland, grassland, and regrowth change analyses were

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Section: Discussionsupporting

confidence: 79%

Spatiotemporal analysis of deforestation in the Chapare region of Bolivia using LANDSAT images

et al. 2020

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Studies of the effectiveness of transport sector interventions in low‐ and middle‐income countries: An evidence and gap map

Malhotra

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Cruz³

et al. 2021

Campbell Systematic Reviews

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Background There are great disparities in the quantity and quality of infrastructure. European countries such as Denmark, Germany, Switzerland, and the UK have close to 200 km of road per 100 km2, and the Netherlands over 300 km per 100 km2. By contrast, Kenya and Indonesia have <30, Laos and Morocco <20, Tanzania and Bolivia <10, and Mauritania only 1 km per 100 km2. As these figures show, there is a significant backlog of transport infrastructure investment in both rural and urban areas, especially in sub‐Saharan Africa. This situation is often exacerbated by weak governance and an inadequate regulatory framework with poor enforcement which lead to high costs and defective construction. The wellbeing of many poor people is constrained by lack of transport, which is called “transport poverty”. Lucas et al. suggest that up to 90% of the world's population are transport poor when defined as meeting at least one of the following criteria: (1) lack of available suitable transport, (2) lack of transport to necessary destinations, (3) cost of necessary transport puts household below the income poverty line, (4) excessive travel time, or (5) unsafe or unhealthy travel conditions. Objectives The aim of this evidence and gap map (EGM) is to identify, map, and describe existing evidence from studies reporting the quantitative effects of transport sector interventions related to all means of transport (roads, rail, trams and monorail, ports, shipping, and inland waterways, and air transport). Methods The intervention framework of this EGM reframes Berg et al's three categories (infrastructure, prices, and regulations) broadly as infrastructure, incentives, and institutions as subcategories for each intervention category which are each mode of transport (road, rail trams and monorail, ports, shipping, and inlands waterways, and air transport). This EGM identifies the area where intervention studies have been conducted as well as the current gaps in the evidence base. This EGM includes ongoing and completed impact evaluations and systematic reviews (SRs) of the effectiveness of transport sector interventions. This is a map of effectiveness studies (impact evaluations). The impact evaluations include experimental designs, nonexperimental designs, and regression designs. We have not included the before versus after studies and qualitative studies in this map. The search strategies included both academic and grey literature search on organisational websites, bibliographic searches and hand search of journals. An EGM is a table or matrix which provides a visual presentation of the evidence in a particular sector or a subsector. The map is presented as a matrix in which rows are intervention categories (e.g., roads) and subcategories (e.g., infrastructure) and the column outcome domains (e.g., environment) and subcategories as (e.g., air quality). Each cell contains studies of the corresponding intervention for the relevant outcome, with links to the available studies. Included studies were coded according to the interve...

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Spatial variation in human disturbances and their effects on forest structure and biodiversity across an Afromontane forest

et al. 2022

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Roads as drivers of above‐ground biomass loss at tropical forest edges in Xishuangbanna, Southwest China

Cited by 4 publications

References 48 publications

Spatiotemporal analysis of deforestation in the Chapare region of Bolivia using LANDSAT images

Spatiotemporal analysis of deforestation in the Chapare region of Bolivia using LANDSAT images

Studies of the effectiveness of transport sector interventions in low‐ and middle‐income countries: An evidence and gap map

Spatial variation in human disturbances and their effects on forest structure and biodiversity across an Afromontane forest

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