Agricultural expansion and the ecological marginalization of forest-dependent people

2021 ◽  
Vol 118 (44) ◽  
pp. e2100436118
Author(s):  
Christian Levers ◽  
Alfredo Romero-Muñoz ◽  
Matthias Baumann ◽  
Teresa De Marzo ◽  
Pedro David Fernández ◽  
...  

Agricultural expansion into subtropical and tropical forests causes major environmental damage, but its wider social impacts often remain hidden. Forest-dependent smallholders are particularly strongly impacted, as they crucially rely on forest resources, are typically poor, and often lack institutional support. Our goal was to assess forest-smallholder dynamics in relation to expanding commodity agriculture. Using high-resolution satellite images across the entire South American Gran Chaco, a global deforestation hotspot, we digitize individual forest-smallholder homesteads (n = 23,954) and track their dynamics between 1985 and 2015. Using a Bayesian model, we estimate 28,125 homesteads in 1985 and show that forest smallholders occupy much larger forest areas (>45% of all Chaco forests) than commonly appreciated and increasingly come into conflict with expanding commodity agriculture (18% of homesteads disappeared; n = 5,053). Importantly, we demonstrate an increasing ecological marginalization of forest smallholders, including a substantial forest resource base loss in all Chaco countries and an increasing confinement to drier regions (Argentina and Bolivia) and less accessible regions (Bolivia). Our transferable and scalable methodology puts forest smallholders on the map and can help to uncover the land-use conflicts at play in many deforestation frontiers across the globe. Such knowledge is essential to inform policies aimed at sustainable land use and supply chains.

2020 ◽  
Vol 47 (7) ◽  
pp. 1439-1454
Author(s):  
María Gabriela Názaro ◽  
Daniel A. Dos Santos ◽  
Ricardo Torres ◽  
Matthias Baumann ◽  
Pedro G. Blendinger

2020 ◽  
Vol 12 (24) ◽  
pp. 4158
Author(s):  
Mengmeng Li ◽  
Alfred Stein

Spatial information regarding the arrangement of land cover objects plays an important role in distinguishing the land use types at land parcel or local neighborhood levels. This study investigates the use of graph convolutional networks (GCNs) in order to characterize spatial arrangement features for land use classification from high resolution remote sensing images, with particular interest in comparing land use classifications between different graph-based methods and between different remote sensing images. We examine three kinds of graph-based methods, i.e., feature engineering, graph kernels, and GCNs. Based upon the extracted arrangement features and features regarding the spatial composition of land cover objects, we formulated ten land use classifications. We tested those on two different remote sensing images, which were acquired from GaoFen-2 (with a spatial resolution of 0.8 m) and ZiYuan-3 (of 2.5 m) satellites in 2020 on Fuzhou City, China. Our results showed that land use classifications that are based on the arrangement features derived from GCNs achieved the highest classification accuracy than using graph kernels and handcrafted graph features for both images. We also found that the contribution to separating land use types by arrangement features varies between GaoFen-2 and ZiYuan-3 images, due to the difference in the spatial resolution. This study offers a set of approaches for effectively mapping land use types from (very) high resolution satellite images.


IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 21036-21051
Author(s):  
Zongqian Zhan ◽  
Xiaomeng Zhang ◽  
Yi Liu ◽  
Xiao Sun ◽  
Chao Pang ◽  
...  

2015 ◽  
pp. 77-84
Author(s):  
Sonja Braunović ◽  
Mihailo Ratknić ◽  
Tatjana Ratknić ◽  
Milan Kabiljo

A land use is the sole erosion factor that can be controlled and governed by man. Since an inadequate land use can cause intensification of erosive processes, it is possible to reduce their intensity by its change. The paper presents the changes in land use in the region of Grdelica Gorge in the period between 1963 and 2011 and the impact of the changes on the intensity of erosive processes. The identification of wooded land, arable land, meadows, pastures, orchards, vineyards and infertile land performed in 2011 was based on field works and the analysis of high-resolution satellite images. The comparison of the obtained results with the data for 1963 proved that the categories of barren land, forest, meadow and pasture underwent most intensive changes. The above-mentioned changes, along with performance of biological and technical works, resulted in reduction of intensity of erosive processes in the observed period.


Eos ◽  
2019 ◽  
Vol 100 ◽  
Author(s):  
Kate Wheeling

Researchers use high-resolution satellite images to parse the effects of land use changes on the energy balance between the rain forest and the atmosphere.


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