The release of carbon into the atmosphere from forest conversion and exploitation is estimated to be 18% of global carbon dioxide emissions, and thus a significant contributor to the increase of atmospheric CO 2 (and other greenhouse gas) concentrations that is linked to global climate change (IPCC, 2007); • If the recent estimates of total emissions of 3 Giga ton per year for Indonesia are true, per capita emissions are twice that in France and 30% above those in the UK or Germany; • The Clean Development Mechanism (CDM) of the Kyoto Protocol supports some forms of affores- tation and reforestation, but no projects have been approved for Indonesia; it excludes activities that protect existing carbon stocks and forms of ‘avoided deforestation’; • There probably is a large potential in Indonesia to reduce emissions from agriculture, forestry and other land uses (AFOLU) and to generate both local and global benefits; the scope for Reducing Emissions from Deforestation and Degradation (REDD) will depend on the definitions used; • Indonesia has an institutional and a vegetation concept of forest, and therefore includes “forests without trees” and “non-forests with trees”; mixed and multristrata agroforestry (intermediate land uses) can store significant quantities of carbon, maintain flows of ecosystem services, generate good economic returns and reduce pressure on remaining forest resources; • Mechanisms for reducing carbon emissions through avoi ded deforestat ion will have to maintain national sovereignty, and to balance between fairness (incentives for long term protection) and effectiveness (demonstrated reductions of emissions on the short term); • Before the institutional challenges of REDD mechanisms are tackled, we need to know the potential cost effectiveness; if current emissions would lead to large economic benefits, emission reduction would be difficult, if not, incentive systems will be feasible.
Tag: Land cover
Avoided Deforestation with Sustainable Benefits: East Kalimantan Land Cover Changes 1990’s – 2005
Abstract not found
Avoided Deforestation with Sustainable Benefits: Jambi Land Cover Changes 1990’s – 2005
Trees and forests play important roles in global climate change mitigation. On the one hand, trees growing in forests and on farms are one of the world’s greatest sinks of carbon. Afforestation in Europe now offsets significant amounts of global emissions and there are many unexploited opportunities for afforestation and reforestation in the developing world. On the other hand, tropical deforestation is one of the largest sources of greenhouse gas emissions. The Intergovernmental Panel on Climate Change estimate that in 2004, the forest sector was responsible for 17.4% of global greenhouse gas emissions. Global-level studies of the economics of climate change mitigation indicate that afforestation and avoided deforestation are among the most attractive investments for reducing net greenhouse gas emissions (total emissions less total sequestration). The ASB Partnership for the Tropical Forest Margins has conducted biophysical, socioeconomic and institutional research on the tradeoffs associated with alternative land uses in the humid tropics. Building on previous research at the ASB benchmark sites, this paper presents spatially-explicit analyses of the trade offs between carbon and economic returns in three sites in Indonesia, and one site in each of Peru and Cameroon. Located in the humid forest zones of Southeast Asia, the Amazon basin, and Central Africa, these sites represent a range of the conditions that shape tree and forest management across the humid tropics. Indonesia is particularly distinguished by having the world’s highest levels of land-based emissions of greenhouse gases and largest CO2 emissions from conversion of peat lands.
Soil nutrient maps of Sub-Saharan Africa: assessment of soil nutrient content at 250 m spatial resolution using machine learning
Spatial predictions of soil macro and micro-nutrient content across Sub-Saharan Africa at 250 m spatial resolution and for 0–30 cm depth interval are presented. Predictions were produced for 15 target nutrients: organic carbon (C) and total (organic) nitrogen (N), total phosphorus (P), and extractable—phosphorus (P), potassium (K), calcium (Ca), magnesium (Mg), sulfur (S), sodium (Na), iron (Fe), manganese (Mn), zinc (Zn), copper (Cu), aluminum (Al) and boron (B). Model training was performed using soil samples from ca. 59,000 locations (a compilation of soil samples from the AfSIS, EthioSIS, One Acre Fund, VitalSigns and legacy soil data) and an extensive stack of remote sensing covariates in addition to landform, lithologic and land cover maps. An ensemble model was then created for each nutrient from two machine learning algorithms—random forest and gradient boosting, as implemented in R packages ranger and xgboost—and then used to generate predictions in a fully-optimized computing system. Cross-validation revealed that apart from S, P and B, significant models can be produced for most targeted nutrients (R-square between 40–85%). Further comparison with OFRA field trial database shows that soil nutrients are indeed critical for agricultural development, with Mn, Zn, Al, B and Na, appearing as the most important nutrients for predicting crop yield. A limiting factor for mapping nutrients using the existing point data in Africa appears to be (1) the high spatial clustering of sampling locations, and (2) missing more detailed parent material/geological maps. Logical steps towards improving prediction accuracies include: further collection of input (training) point samples, further harmonization of measurement methods, addition of more detailed covariates specific to Africa, and implementation of a full spatio-temporal statistical modeling framework.
REDD Abacus SP
REDD Abacus SP is a public domain software developed by World Agroforestry (ICRAF) to estimate emission from land use and land cover changes allowing for dynamic heterogeneity of soil types, elevations, climate and other biophysical characteristics in the landscapes, Analyze trade-offs between emissions and financial gain (opportunity cost analysis) and produce abatement cost curves Project ex-ante emissions and financial gain of business-as-usual scenarios for setting Reference Emission Level (REL), Simulate zone-specific policies and other emission reduction scenarios within the landscapes, and estimate the potential emission reductions and opportunity costs of them.
Annual litter fall of nitrogen-fixing tree species in rotational woodlots at Tumbi (Tabora), western Tanzania
A rotational woodlot is a method involving growing trees with crops up to 2-3 years until trees start competing with crops. Thereafter the woodlot is left as a source of fuel wood, building poles or fodder while restoring soil fertility until farmers start cutting down the trees and growing crops between the stumps 4 to 5 years later. The method was designed and developed by the South African Development Countries (SADC) and the World Agroforestry Centre(ICRAF) and their partners to alleviate rural farmers from the problems of fuelwood scarcity and poor soil fertility in the tobacco cereal land use system. The method is currently being practised at farmers’ fields in Tabora rural district in western Tanzania involving a large number of farmers. This study reports an assessment of litter production and seasonal pattern of Acacia crassicarpa , A. julifera , A. leptocarpa, Leucaena pallida and Senna siamea grown in rotational woodlots at five years of age.
Socio-economic determinants of land use and land cover change in South-Kivu wetlands, eastern D.R. Congo: Case study of Hogola and Chisheke wetlands
In the South-Kivu province, wetlands are mainly converted into farmlands to ensure food and income security among rural populations. This study aimed at assessing the land use and land cover (LULC) change for the last three decades (1990–2020) in South-Kivu wetlands; mainly the Hogola and Chisheke, in Walungu territory, eastern Democratic Republic of Congo (DRC). Socio-economic determinants of LULC in the two wetlands were also assessed. Google earth (CNI/airbus) and airborne images were used for LULC while socio-economic data were collected through a survey questionnaire from 369 households. The Chi-squared Automatic Interaction Detector (CHAID) model allowed assessing factors determining conversion of wetlands’ use. For the last three decades, there were 30 and 40% decreases in the acreage covered by Hogola and Chisheke wetlands, respectively, as a result of rapid farmland expansion and brick making. Farmers perceived wetlands as wastelands and thus unfit for agriculture and brick making activities. These two human activities provided significant monetary benefits to wetland users though the profitability of agriculture was dependent on practiced crops. The conversion of wetlands into farmlands was driven by annual household income, wetland utilization patterns, households’ main activity and the seniority in exploiting wetlands. The perception of wetlands as degraded and wastelands, the exploited acreage and the farmer gender had also influenced significantly wetland conversions. On the other hand, perceiving wetlands as wastelands depended on the age of the household head, the inclination to brick making activities, the household’s main activity and crop, and the wetland traditional/cultural values in the South-Kivu province. Though generating significantly higher annual incomes than any other land use in target wetlands, the conversion of wetlands for agriculture and brick making, under the current practices, is unsuitable for their sustainable management (use), as recommended to achieve the RAMSAR objectives of “wise use” of wetlands.
Understanding the states and dynamics of mangrove forests in land cover transitions of The Gambia using a Fourier transformation of Landsat and MODIS time series in Google Earth Engine
Mangroves are resilient forests of transitional zones between land, ocean and freshwater for they are tolerant to salinity. In The Gambia, mangrove forests are found along the coast of Atlantic Ocean and River Gambia where they support the livelihoods of millions through multiple ecosystems services. Despite their importance in The Gambia, consistent country-wide information on their coverage, dynamics and change hotspots are lacking. Thus far, it remains unclear whether the coverage of mangroves has decreased or increased over the last few decades. Often, the existing estimates vary strongly across sources and the methodologies in the available literature are not always reproducible. This study attempts to fill these gaps by providing up-to-date spatial information on mangrove forests in The Gambia.
Scrutinizing Urbanization in Kathmandu Using Google Earth Engine Together with Proximity-Based Scenario Modelling
‘Urbanization’ refers to the expansion of built-up areas caused by several factors. This study focuses on the urbanization process in Kathmandu, the capital of Nepal. Supervised classification was conducted in Google Earth Engine by using Landsat data for years 2001, 2011 and 2021. The random forest classifier with 250 trees was used for classification to generate land-cover map. A land-cover map of 2021 was used as base map in the InVEST tool for scenario modelling. An accuracy assessment with 20% of sample points was conducted with different metrics, such as overall accuracy, kappa coefficient, producer accuracy, and consumer accuracy. The results show an increment of built-up areas by around 67 km2 over 20 years in a centrifugal pattern from the core district, converting agricultural and forest land. ‘Forest’ is still dominant land-use class, with an area of 177.97 km2. Agricultural land was highly converted to urban area. The overall accuracy of this classification process ranged 0.96–1.00 for different years. The scenario modelling further elaborated an amiability of drastic shift in land-use classes to ‘built-up’, especially forest and agriculture, by around 33 km2 and 66 km2, respectively. This study recommends the consideration of ecological approaches during the planning process.
Paddy Rice Phenological Mapping throughout 30-Years Satellite Images in the Honghe Hani Rice Terraces
The Honghe Hani Rice Terraces represent the coexistence between natural and cultural systems. Despite being listed as a World Heritage Site in 2013, certain natural and anthropogenic factors have changed land use/land cover, which has led to a reduction in the size of the paddy rice area. It is difficult to accurately assess these changes due to the lack of historical maps of paddy rice croplands with fine spatial resolution. Therefore, we integrated a random forest classifier and phenological information to improve mapping accuracy and stability. We then mapped the historical distribution of land use/land cover in the Honghe Hani Rice Terraces from 1989–1991 to 2019–2021 using the Google Earth Engine. Finally, we analyzed the driving forces of land use types in the Honghe Hani Rice Terraces. We found that: (1) forests, shrubs or grasslands, and other croplands could be discriminated from paddy rice during the flooding and transplanting period, and water bodies and buildings could also be discriminated from paddy rice during the growing and harvesting period. (2) Inputting phenological feature data improved mapping accuracy and stability compared with single phenological periods. (3) In the past thirty years, 10.651%, 8.810%, and 5.711% of paddy rice were respectively converted to forests, shrubs or grasslands, and other croplands in the Honghe Hani Rice Terraces. (4) Lower agricultural profits and drought led to problems in identifying the driving mechanisms behind paddy rice distribution changes. This study demonstrates that phenological information can improve the mapping accuracy of rice terraces. It also provides evidence for the change in the size of the rice terrace area and associated driving forces in Southwest China.