Trees sustain livelihoods and mitigate climate change but a predominance of trees outside forests and limited resources make it difficult for many tropical countries to conduct automated nation-wide inventories. Here, we propose an approach to map the carbon stock of each individual overstory tree at the national scale of Rwanda using aerial imagery from 2008 and deep learning. We show that 72% of the mapped trees are located in farmlands and savannas and 17% in plantations, accounting for 48.6% of the national aboveground carbon stocks. Natural forests cover 11% of the total tree count and 51.4% of the national carbon stocks, with an overall carbon stock uncertainty of 16.9%. The mapping of all trees allows partitioning to any landscapes classification and is urgently needed for effective planning and monitoring of restoration activities as well as for optimization of carbon sequestration, biodiversity and economic benefits of trees.

The problem of soil erosion in Rwanda has been highlighted in previous studies. They have shown that half of the country’s farmland suffers moderate to severe erosion, with the highest soil loss rates found in the steeper and highly rainy northern and western highlands of the country. The purpose of this study was to estimate soil loss in Satinskyi, one of the catchments located in Ngororero District of Western Rwanda. This has been achieved using the Revised Universal Soil Loss Equation (RUSLE) model, which has been implemented in a Geographic Information Systems (GIS) environment. The methods consisted of preparing a set of input factor layers including Slope Length and Steepness (LS) factor, Rainfall Erosivity (R) factor, Soil Erodibility (K) factor, Support Practice (P) factor, and Land Surface Cover Management Factor (C) factor, for the model. The input factors have been integrated for soil loss estimates computation using RUSLE model, and this has enabled to quantitatively assess variations in the mean of the total estimated soil loss per annum in relation to topography and land-use patterns of the studied catchment. The findings showed that the average soil loss in Satinskyi catchment is estimated at 38.4 t/ha/year. It was however found that about 91% of the study area consists of areas with slope angle exceeding 15°, a situation which exposes the land to severe soil loss rates ranging between 31 t/ha/year and 41 t/ha/year. Apart from the steep slope, changes in land use also contribute to high rates of soil loss in the catchment. Keywords: Soil Erosion Estimation, GIS, RUSLE, Satinskyi Catchment, Rwanda

Trees sustain livelihoods and mitigate climate change, but a predominance of trees outside forests and limited resources make it difficult for many developing countries to conduct frequent nation-wide inventories. Here, we propose a rapid and accurate approach to map the carbon stock of each individual tree and shrub at the national scale of Rwanda using aerial imagery and deep learning. We show that 72% of the mapped trees are located in farmlands and savannas, and 15% in plantations. These non-forest trees account for 41% of the national carbon stocks. Natural forests cover 5% of the country and 11% of the total tree count, but comprise 59% of the national carbon stocks. The mapping of all trees facilitates any landscape stratification and is urgently needed for effective planning and monitoring of landscape restoration activities as well as for optimization of carbon sequestration, biodiversity and economic benefits of trees.

No abstract

This paper highlights the importance of transforming Artisanal and Small-scale Mining (ASM) sector into a more sustainable enterprise and shows  the reclamation of despoiled mined sites as an opportunity to return land to beneficial uses which do not compromise future development of the sites. It presents some of environmental impacts produced by ASM and the contribution of a geomorphological approach to alleviate them. The methodology consisted of the review supported by field survey in small-scale mining areas to summarize the most relevant scientific findings and the importance of stabilizing the land that will support sustainably reclamation structures. The impacts include haphazard excavations with no land reclamation plan, pits, trenches inadequately protected, siltation of open water bodies, soil and rock wastes, negative change of soil properties, and accelerated erosion of the mine sites. To transform the sector into a more responsible industry, ASM has to be placed within two integrated perspectives: (i) building the capacity of ASM sector, and (ii) promoting restoration approach by building a critical knowledge mass through collaboration of relevant stakeholders, with emphasis on multidisciplinary approach.The study opens a relevant new research field and emphasises on the collaboration of mining stakeholders including local communities to develop an integrated approach to address challenges that ASM industry is facing in developing countries. This review highlights the impacts of small-scale mining sector on land use potentials and it is essentialcontribution towards the sustainability of ASM industry and reclamation of despoiled mined lands. Key Words: small-scale mining sector, environmental impact, geomorphologic approach, sustainability