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The document details the application of MODIS satellite imagery and automated algorithms to track land use dynamics in the La Plata River Basin. It focuses on the transition of agricultural frontiers—from deforestation to intensification—and the use of remote sensing to estimate evapotranspiration and water balance. A case study in Mato Grosso demonstrates how these tools can map the expansion of soybean and sugarcane, the adoption of double-cropping systems, and the resulting impacts on natural biomes like the Cerrado and Amazon forest.

The report argues that the ITES sector has missed previous opportunities to drive sustainable development and must now adopt an 'Outsourcing 3.0' model. This framework moves beyond simple cost-cutting (Outsourcing 1.0) and high-value job relocation (Outsourcing 2.0) toward a model where companies, cities, and countries compete responsibly. The authors identify six drivers for this transition: creating a responsible business climate, smart philanthropy at the base-of-the-pyramid, building talent, improving business standards and compliance, fostering product and service innovation (such as 'tribesourcing'), and contributing to low-carbon prosperity. The report emphasizes that the 2009 economic downturn provides a critical window to reset the industry's approach to corporate social responsibility and environmental impact.

The text outlines the methodological toolkit of human geographers, distinguishing between quantitative and qualitative approaches. It explains the use of text analysis (from social media to archives), quantitative data for causal inference and pattern recognition, GIS for spatial analysis, and qualitative tools such as semi-structured interviews and focus groups. Additionally, it covers the role of visual data (remote sensing and photography) and the importance of field presence through ethnography and observation.

The CHAPOSA project investigated charcoal production systems around Lusaka, Dar es Salaam, and Maputo between 1989 and 1998. Findings indicate a significant reduction in closed forest cover in all three areas, with the most severe depletion around Maputo. Charcoal serves as a critical income source for rural poor and a stable, affordable energy source for urban poor, creating a socio-economic dependency that complicates regulation. The report argues that current fiscal and licensing systems are inadequately enforced, treating forests as open-access resources. To mitigate deforestation, the authors recommend a coordinated approach: enforcing licensing to increase prices and fund forest management, while simultaneously providing rural income alternatives (e.g., improved agriculture) and urban energy substitutes (e.g., expanded electricity access).

The World Resources Institute developed a baseline water risk model for Ethiopia using 2015 data to help decision-makers incorporate water-related climate risk into sectoral planning. The model utilizes geospatially-explicit estimates for irrigation, livestock, domestic, and industrial water use, combined with 36 years of remotely-sensed renewable water resources data. It generates four key indicators: baseline water stress, months of water scarcity, seasonal variability, and interannual variability. The model is intended for national-level scenario analysis and monitoring of Sustainable Development Goal target 6.4.2, though it excludes water storage infrastructure, environmental flow requirements, and transboundary water obligations.

The Land Disturbance Alert Classification System (LDACS) is a global data set that enhances NASA's 30-meter resolution DIST-ALERT system by integrating fire, water, cropland, and natural ecosystem data. It classifies vegetation disturbances into four categories: potential land conversion, fire-related, water-related, and cropland dynamics. This system specifically addresses monitoring gaps for non-forest ecosystems like grasslands, savannas, shrublands, and wetlands. Global 2023 data indicates that cropland dynamics represent one-third of classified disturbances, while potential land conversion accounts for 4%. Initial validation in Brazil's Cerrado biome demonstrated an 87% accuracy rate for classified alerts.

The paper presents a wildfire prediction and loss assessment framework designed for the financial sector, using a case study of five crops in Yunnan Province. It finds that historical annual losses for these crops ranged from US$135.8 million to $254.8 million between 2011 and 2020, with extreme events causing 15 to 30 percent of annual losses. Future projections indicate a shift in the peak Fire Weather Index (FWI) from March/April to February/March, with the SSP2-45 scenario showing the highest mean FWI. The study notes that financial institutions in Yunnan lack the capacity to manage these risks, though insurance companies and banks show interest in integrating physical climate risk analysis for parametric insurance and credit risk management.

The World Resources Institute, in partnership with the World Cocoa Foundation and Climate Focus, developed two tools to support deforestation-free cocoa commitments in West Africa. The West Africa Cocoa Dataset aggregates data from 19 companies, identifying 840,000 unique plots covering approximately 1.5 million hectares. To protect farmer privacy, this dataset is shared as a heat map rather than raw plot data. The Cocoa Deforestation Risk Assessment provides a harmonized method to prioritize deforestation prevention; it found that recent forest loss significantly influences risk levels, while legal protections in areas like Taï National Park and Bia National Park correlate with lower priority rankings due to a lack of recent loss.

The World Resources Institute introduces a framework for planning passive cooling infrastructure in cities using OpenUrban, a 1-meter resolution urban land-use and land-cover dataset. By combining OpenUrban with remotely sensed data on albedo, tree canopy, and temperature, the framework generates three implementation scenarios—technical, achievable, and program—for trees, cool roofs, reflective pavements, and shade structures. The tool is designed to be city-agnostic and low-burden, requiring no local data inputs and providing both area-wide potential indicators and spatial simulation maps to support policy and planning.

The document details the creation of a dataset identifying 11,309 school bus depots in the U.S. using remote sensing and aerial imagery from the National Agriculture Imagery Program (NAIP). The dataset is intended to support environmental justice analysis regarding air pollution hotspots in underserved communities, as well as electricity grid planning for school bus electrification and climate hazard risk assessment. Findings show that 51% of depots are located within 350 meters of a school, with North Carolina having the highest number of depots (841).

The document highlights the increasing demand for credible forest monitoring to meet climate and sustainable development goals, noting that while satellite and remote sensing technologies have advanced, a gap remains between research capabilities and actual implementation in tropical forest countries. It warns that the proliferation of diverse monitoring systems may lead to redundancy and confusion.

The World Resources Institute (WRI) conducted a scoping exercise to develop a list of indicators to measure the environmental sustainability of agriculture, defined as minimizing its environmental impacts. The process involved analyzing existing datasets, selecting five thematic areas (water, climate change, land conversion, soil health, and pollution), and mapping indicators across a three-stage causal chain: public policy, farmer practice, and biophysical performance. Candidate indicators were evaluated against seven screening criteria, including data availability, accuracy, and consistency, to produce a 'short list'. The paper argues that increasing demand for these indicators from governments and the private sector is necessary to drive the supply of required data, which could be supported by remote sensing and crowd-sourcing.

The document estimates that agricultural soil carbon management in the United States could remove 100–200 MtCO2 per year by 2050 at a cost of approximately $40 per ton of CO2. It advocates for a hybrid federal policy approach combining financial subsidies, technical assistance, and expanded research and monitoring to overcome farmer risk-aversion and scientific uncertainty.

The document identifies critical infrastructure and policy needs for scaling carbon removal in the United States, including the requirement for low-carbon energy to power direct air capture, the need for independent life-cycle assessments, and the expansion of geologic storage and CO2 pipeline networks. It emphasizes the importance of improving monitoring systems for natural carbon capture and increasing land use efficiency to balance food production with ecosystem restoration.

The briefing outlines potential U.S.-China collaborations to mitigate methane emissions, highlighting research and development in enteric fermentation and rice cultivation, knowledge sharing on biodigesters and remote sensing, and the application of economic and regulatory incentives. It emphasizes the role of subnational engagement, particularly through California, while noting that trade tensions and intellectual property concerns may impede progress.