{"query_echo":{"q":"","filters":{"analysis_type":["spatial analysis"]},"warnings":[]},"total":{"value":155,"relation":"eq"},"page":8,"page_size":20,"self":"https://climateinsightsdirectory.org/api/v1/search?analysis_type=spatial+analysis&page=8","stability":"beta","ai_marking":{"digital_source_type":{"uri":"http://cv.iptc.org/newscodes/digitalsourcetype/trainedAlgorithmicMedia","name":"Created using Generative AI"},"notice":"Summary and key insights are generated using artificial intelligence."},"results":[{"id":"iai-001792","url":"https://climateinsightsdirectory.org/document/iai-001792","title":"SYNTHESIS REPORT Land Use Change Monitoring and Dynamics in the La Plata River Basin Using Remote Sensing – Methodological Developments","publisher":{"name":"Inter-American Institute for Global Change Research","organization":"inter-american-institute-for-global-change-research"},"document_type":"report","language":"en","date_published":null,"source_url":"https://iai.int/admin/site/sites/default/files/uploads/2014/03/Final_Report_IDRC_Meirelles.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"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.","ai_generated":true,"unit":"iai-001792#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"The La Plata basin faces significant environmental pressure due to its role in international food security, with 22 million hectares of natural land converted to soybean cultivation in Brazil and Argentina over a decade.","ai_generated":true,"unit":"iai-001792#insight-1","date_modified":"2026-10-23"},{"text":"A two-step automatic classification methodology using MODIS multitemporal profiles was developed to first separate agricultural areas from native vegetation and pasture, and then differentiate specific crop classes using agricultural calendars.","ai_generated":true,"unit":"iai-001792#insight-2","date_modified":"2026-10-23"},{"text":"Agricultural frontiers in Mato Grosso evolve through five stages: pre-settlement, occupation, consolidation, intensification, and intensive, marked by three specific frontiers: deforestation, economic, and intensification.","ai_generated":true,"unit":"iai-001792#insight-3","date_modified":"2026-10-23"},{"text":"Agricultural intensification, specifically the adoption of double-cropping systems with two commercial crops, is estimated to have reduced the need for land expansion; without it, an additional 1.68 million hectares would have been required to reach 2006-2007 production levels in Mato Grosso.","ai_generated":true,"unit":"iai-001792#insight-4","date_modified":"2026-10-23"},{"text":"The use of MOD16 global evapotranspiration datasets allows for the detection of seasonal cycles and the differentiation of water loss magnitudes across the Cerrado, Atlantic Forest, Pantanal, and steppes biomes in the Brazilian portion of the basin.","ai_generated":true,"unit":"iai-001792#insight-5","date_modified":"2026-10-23"},{"text":"Land use changes in the basin, particularly the expansion of mechanized agriculture and the conversion of natural lands, act as drivers of deforestation and significantly impact hydrological regimes and the provision of water cycle services.","ai_generated":true,"unit":"iai-001792#insight-6","date_modified":"2026-10-23"}],"climate_tags":["remote sensing","land-use change","deforestation","climate change","greenhouse gas emissions","biodiversity loss"],"geography_discussed":["Brazil","Argentina","Paraguay","Bolivia","Mato Grosso do Sul","Goiás"],"frame_perspective":[],"analysis_type":["methodological assessment","case study","spatial analysis"]},{"id":"napglob-000080","url":"https://climateinsightsdirectory.org/document/napglob-000080","title":"ESTADO DE LA REGIÓN","publisher":{"name":"NAP Global Network","organization":"nap-global-network"},"document_type":"report","language":"es","date_published":null,"source_url":"https://napglobalnetwork.org/wp-content/uploads/2023/06/ERCA-2021-Capitulo_6_Desastres.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"This report provides a spatial analysis of disaster incidence in Central America and the Dominican Republic between 1950 and 2020. It identifies that hydrometeorological events, specifically floods and landslides, are the most recurrent threats, often coinciding with high-density urban areas and coastal zones. The study highlights a significant increase in recorded disasters since 1990, peaking in 2010. It further correlates disaster risk with physical variables, noting that 70.7% of records occur below 1,000 meters above sea level and that a high percentage of critical territories are located in areas with medium to high population density. The analysis also observes a decline in forest cover and an increase in pasture land from 1990 to 2018, linking these land-use changes to increased disaster vulnerability.","ai_generated":true,"unit":"napglob-000080#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Floods and landslides are the most frequent threats in Central America and the Dominican Republic, accounting for 86% of all disaster records between 1950 and 2020.","ai_generated":true,"unit":"napglob-000080#insight-1","date_modified":"2026-10-23"},{"text":"The annual number of recorded disasters rose sharply starting in the 1990s compared to the 1950-1990 period, reaching a peak of 2,544 records in 2010.","ai_generated":true,"unit":"napglob-000080#insight-2","date_modified":"2026-10-23"},{"text":"A majority of disaster records (70.7%) are located at altitudes below 1,000 meters above sea level, which is partly attributed to high population concentrations at these elevations.","ai_generated":true,"unit":"napglob-000080#insight-3","date_modified":"2026-10-23"},{"text":"There is a strong correlation between the timing of precipitation extremes and disaster occurrence, with 54% of droughts, floods, and landslides occurring during the most common drought months (March and April) and surplus precipitation months (October and November).","ai_generated":true,"unit":"napglob-000080#insight-4","date_modified":"2026-10-23"},{"text":"Most critical territories for disaster incidence overlap with areas of medium or high population density (76 or more inhabitants per km2), particularly in capital cities and major urban centers.","ai_generated":true,"unit":"napglob-000080#insight-5","date_modified":"2026-10-23"},{"text":"Between 1990 and 2018, there was a significant decrease in forest cover (a 23.3% reduction) and a corresponding increase in pasture land, which grew from 30% to 50% of the territory.","ai_generated":true,"unit":"napglob-000080#insight-6","date_modified":"2026-10-23"},{"text":"The study identified specific 'multi-hazard' territories where high concentrations of floods, landslides, and droughts coincide, including the canton of Osa in Costa Rica, the municipality of San Pedro Sula in Honduras, and the Distrito Central in the Dominican Republic.","ai_generated":true,"unit":"napglob-000080#insight-7","date_modified":"2026-10-23"}],"climate_tags":["flood","landslide","drought","climate variability","land-use change","deforestation","urbanization","climate change adaptation","disaster risk reduction"],"geography_discussed":["Costa Rica","Guatemala","Honduras","El Salvador","Nicaragua","Panama","Belize","San Pedro Sula","Osa"],"frame_perspective":[],"analysis_type":["spatial analysis","temporal analysis","correlation analysis"]},{"id":"prio-001218","url":"https://climateinsightsdirectory.org/document/prio-001218","title":"Artisanal mining, conflict, and sexual violence in Eastern DRC","publisher":{"name":"Peace Research Institute Oslo","organization":"peace-research-institute-oslo"},"document_type":"research paper","language":"en","date_published":null,"source_url":"https://cdn.cloud.prio.org/files/d9b0068f-c277-41ce-b155-32645b8a8242/Artisanal mining conflict and sexual violence in Eastern DRC.pdf?inline=true","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","geography_discussed","analysis_type"],"summary":{"text":"The study finds that women living near ASM sites in Eastern DRC are more likely to experience both intimate partner sexual violence and sexual violence by others. This risk is particularly acute for women in North Kivu, South Kivu, and Maniema living near mines controlled by armed actors.","ai_generated":true,"unit":"prio-001218#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Women residing in close proximity to artisanal and small-scale mining (ASM) activities in Eastern DRC face a higher likelihood of experiencing sexual violence from both intimate partners and non-partners.","ai_generated":true,"unit":"prio-001218#insight-1","date_modified":"2026-10-23"},{"text":"In the provinces of North Kivu, South Kivu, and Maniema, there is a highly significant correlation between living near ASM sites controlled by armed actors (including government forces, rebels, or militias) and an increased risk of sexual violence by non-partners.","ai_generated":true,"unit":"prio-001218#insight-2","date_modified":"2026-10-23"},{"text":"The risk of sexual violence by non-partners is substantially higher for women living closest to armed actor-controlled mines in the most conflict-affected areas; the risk increases from 5.7% for those furthest away (90th percentile) to 16.2% for those closest (10th percentile).","ai_generated":true,"unit":"prio-001218#insight-3","date_modified":"2026-10-23"},{"text":"The study found no evidence to support the hypothesis that women who both live near ASM sites and work outside the home are more likely to experience sexual violence.","ai_generated":true,"unit":"prio-001218#insight-4","date_modified":"2026-10-23"},{"text":"While proximity to any mine increases risk, the specific link between armed actor-controlled mines and sexual violence was not statistically significant when analyzed across Eastern DRC as a whole, only when restricted to the Kivus and Maniema.","ai_generated":true,"unit":"prio-001218#insight-5","date_modified":"2026-10-23"}],"climate_tags":[],"geography_discussed":["North Kivu","South Kivu","Maniema","Katanga Province","Oriental"],"frame_perspective":[],"analysis_type":["quantitative analysis","spatial analysis","logistic regression"]},{"id":"prio-001297","url":"https://climateinsightsdirectory.org/document/prio-001297","title":"Conflict on the urban fringe: Urbanization, environmental stress, and urban unrest in Africa","publisher":{"name":"Peace Research Institute Oslo","organization":"peace-research-institute-oslo"},"document_type":"research paper","language":"en","date_published":null,"source_url":"https://cdn.cloud.prio.org/files/af66288f-2423-4eab-8298-1e8c830ef693/Conflict on the urban fringe Urbanization environmental stress and urban unrest in Africa.pdf?inline=true","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The study finds that high urban population growth is significantly associated with increased social unrest, but only in peri-urban areas (the urban outskirts). In contrast, population growth in primary urban cores is negatively associated with unrest. The researchers found no evidence that this relationship is driven by environmental push factors such as nearby droughts; in fact, droughts hitting urban areas directly were found to be negatively associated with unrest.","ai_generated":true,"unit":"prio-001297#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"High urban population growth is associated with a higher likelihood of urban social unrest, with the probability of unrest being 64% greater in areas with 5% annual population growth compared to those with no growth.","ai_generated":true,"unit":"prio-001297#insight-1","date_modified":"2026-10-23"},{"text":"The positive relationship between population growth and social unrest is specific to peri-urban areas (the urban outskirts), where the probability of unrest is 58% greater in areas with 5% annual population growth compared to those with no growth.","ai_generated":true,"unit":"prio-001297#insight-2","date_modified":"2026-10-23"},{"text":"In primary urban centers, the relationship is reversed: the rate of grid population growth is negatively associated with social unrest.","ai_generated":true,"unit":"prio-001297#insight-3","date_modified":"2026-10-23"},{"text":"There is no evidence that droughts in nearby rural areas (within 200 km) drive the link between urban population growth and social unrest, rejecting the hypothesis that environmental push factors spur rural-to-urban migration that feeds unrest.","ai_generated":true,"unit":"prio-001297#insight-4","date_modified":"2026-10-23"},{"text":"Droughts that directly affect urban areas are negatively associated with social unrest, contradicting resource scarcity scenarios that assume competition for resources increases tension.","ai_generated":true,"unit":"prio-001297#insight-5","date_modified":"2026-10-23"},{"text":"Other factors significantly associated with increased urban unrest include higher overall population size, proximity to the national capital, and a higher density of infrastructure.","ai_generated":true,"unit":"prio-001297#insight-6","date_modified":"2026-10-23"},{"text":"Higher levels of economic development, measured by GDP per capita within the grid, are associated with lower levels of urban unrest.","ai_generated":true,"unit":"prio-001297#insight-7","date_modified":"2026-10-23"}],"climate_tags":["urbanization","drought","climate change"],"geography_discussed":["Algeria"],"frame_perspective":[],"analysis_type":["quantitative","spatial analysis","econometric modeling"]},{"id":"prio-001318","url":"https://climateinsightsdirectory.org/document/prio-001318","title":"Ethno-nationalist exclusion and civil war","publisher":{"name":"Peace Research Institute Oslo","organization":"peace-research-institute-oslo"},"document_type":"fact sheet","language":"en","date_published":null,"source_url":"https://cdn.cloud.prio.org/files/7b6ff35f-c56d-42d8-a81d-daee7e95bf8c/Debunking Myths about Civil Wars Facts about Ethno-Nationalist Conflict.pdf?inline=true","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","geography_discussed","analysis_type"],"summary":{"text":"The document argues that ethno-nationalist violence is driven by structural relations between ethnic groups and governments rather than simple demographic diversity. Using the Ethnic Power Relations (EPR) and GeoEPR datasets, the research demonstrates that groups excluded from executive power, particularly those who recently lost power, face a significantly higher risk of civil war. Additionally, horizontal inequality—where a group is either significantly poorer or wealthier than the national average—increases the probability of conflict. The text suggests power-sharing or partition as potential solutions to these entrenched conflicts.","ai_generated":true,"unit":"prio-001318#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Ethno-nationalist grievances are not simple individualist phenomena measurable by diversity or polarization; instead, they emerge from the specific relations between ethnic groups and their governments.","ai_generated":true,"unit":"prio-001318#insight-1","date_modified":"2026-10-23"},{"text":"Political exclusion from executive power significantly increases the risk of civil war. Groups excluded from power have an annual conflict probability of 0.71 percent, compared to 0.32 percent for included groups. Those who have experienced a recent loss of power are nearly 18 times more likely to experience civil war, with a conflict probability of 5.7 percent.","ai_generated":true,"unit":"prio-001318#insight-2","date_modified":"2026-10-23"},{"text":"Horizontal inequality, defined as the ratio between a group's per capita income and the national average, drives conflict. Groups that are either significantly poorer or wealthier than the country average are at a higher risk of involvement in civil wars.","ai_generated":true,"unit":"prio-001318#insight-3","date_modified":"2026-10-23"},{"text":"While grievances are a primary driver, the actual outbreak of violent ethno-nationalist challenges depends on additional factors including terrain, geopolitics, political institutions, organizational resources, and transborder intervention.","ai_generated":true,"unit":"prio-001318#insight-4","date_modified":"2026-10-23"},{"text":"Power-sharing is identified as the most apparent solution for ethno-nationalist conflicts, though it is often imperfect and may need to be replaced by partition in highly entrenched cases.","ai_generated":true,"unit":"prio-001318#insight-5","date_modified":"2026-10-23"}],"climate_tags":[],"geography_discussed":["Yugoslavia"],"frame_perspective":[],"analysis_type":["quantitative analysis","spatial analysis"]},{"id":"prio-001323","url":"https://climateinsightsdirectory.org/document/prio-001323","title":"Diffusion Patterns of Violence in Civil Wars","publisher":{"name":"Peace Research Institute Oslo","organization":"peace-research-institute-oslo"},"document_type":"research paper","language":"en","date_published":null,"source_url":"https://cdn.cloud.prio.org/files/001c5f30-1d0c-4456-867a-52998eb64602/Diffusion Patterns of Violence in Civil Wars.pdf?inline=true","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","geography_discussed","analysis_type"],"summary":{"text":"The authors analyze how violence spreads in space and time during civil wars, distinguishing between relocation diffusion (shifting violence) and escalation diffusion (expanding violence). Using a modified joint count statistic and Monte Carlo simulations on ACLED event data from Bosnia, Kosovo, Burundi, and Rwanda, the study finds that violence typically expands in scope, supporting the theory that irregular warfare lacks demarcated front lines.","ai_generated":true,"unit":"prio-001323#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"The authors distinguish between two primary types of conflict diffusion: relocation diffusion, which is a \"shift in the location of violence\" typical of conventional maneuver warfare with clear front lines, and escalation diffusion, which refers to the \"spatial expansion of the conflict site\" typical of mobile guerrilla war.","ai_generated":true,"unit":"prio-001323#insight-1","date_modified":"2026-10-23"},{"text":"The study argues that civil wars should primarily exhibit escalation diffusion because insurgents often establish small bases and expand them, and combatants frequently engage in violence within their own zones of control to extract resources or due to the fragmentation of opposing forces.","ai_generated":true,"unit":"prio-001323#insight-2","date_modified":"2026-10-23"},{"text":"To detect these patterns, the researchers developed a spatial-temporal joint count statistic that observes pairs of neighboring spatial cells over two subsequent time steps, testing observed transitions against a null model created via Monte Carlo simulation.","ai_generated":true,"unit":"prio-001323#insight-3","date_modified":"2026-10-23"},{"text":"Analysis of the Bosnian War (April 1992 to October 1995) revealed a predominance of escalation diffusion, which the authors attribute to the use of irregular units and militias pursuing ethno-territorial goals rather than following clear front lines.","ai_generated":true,"unit":"prio-001323#insight-4","date_modified":"2026-10-23"},{"text":"In the Kosovo conflict (March 1998 to October 1999), the results showed a time-invariant pattern of escalation diffusion occurring at small spatial scales (3 km to 7 km), consistent with the KLA's use of guerrilla tactics.","ai_generated":true,"unit":"prio-001323#insight-5","date_modified":"2026-10-23"},{"text":"The civil war in Burundi (November 1993 to end of 2003) exhibited both escalation and relocation diffusion; the presence of relocation dynamics is attributed to mobile warfare and movements across the border into the Democratic Republic of the Congo.","ai_generated":true,"unit":"prio-001323#insight-6","date_modified":"2026-10-23"},{"text":"Analysis of the Rwandan civil war after 1994 showed a significant number of escalation diffusion instances at spatial scales between 3 km and 8 km, with an almost complete absence of relocation diffusion.","ai_generated":true,"unit":"prio-001323#insight-7","date_modified":"2026-10-23"},{"text":"The overall results across the four cases support the conclusion that violence in civil wars tends to expand in scope once it has occurred at a particular location, fitting a model of irregular warfare without demarcated areas of control.","ai_generated":true,"unit":"prio-001323#insight-8","date_modified":"2026-10-23"}],"climate_tags":[],"geography_discussed":["Democratic Republic of the Congo","Albania"],"frame_perspective":[],"analysis_type":["spatial analysis","temporal analysis","statistical modeling","Monte Carlo simulation"]},{"id":"prio-001350","url":"https://climateinsightsdirectory.org/document/prio-001350","title":"Effectiveness of Aid on Educational Dropout in Post-Genocide Rwanda","publisher":{"name":"Peace Research Institute Oslo","organization":"peace-research-institute-oslo"},"document_type":"research paper","language":"en","date_published":null,"source_url":"https://cdn.cloud.prio.org/files/7cbc9341-df01-492c-afb3-f6df848be88e/Effectiveness of Aid on Educational Dropout.pdf?inline=true","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","geography_discussed","analysis_type"],"summary":{"text":"The research examines the long-term effects of the 1994 Rwandan genocide on primary school dropout rates, specifically analyzing whether living near genocide-targeted areas increases dropout risk and if development aid mitigates this effect. Using a sample of 63,892 respondents and spatial data, the study finds that while proximity to genocide events alone does not significantly increase dropout probability, the presence of aid projects in those areas reduces the likelihood of dropout by 20%. This effect is most pronounced in low-income households, where the probability of dropout decreases by 10.6%. The study also identifies that child-headed households and rural residence are associated with higher dropout rates, while female students and those with educated household heads are less likely to drop out.","ai_generated":true,"unit":"prio-001350#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Geographical proximity to areas targeted during the genocide does not independently increase the probability of primary school dropout.","ai_generated":true,"unit":"prio-001350#insight-1","date_modified":"2026-10-23"},{"text":"Development aid significantly reduces the likelihood of educational dropout for children living in proximity to genocide-targeted areas, with a substantial effect of 20%.","ai_generated":true,"unit":"prio-001350#insight-2","date_modified":"2026-10-23"},{"text":"The mitigating effect of development aid on school dropout is most significant for low-income households, reducing the probability by 10.6%.","ai_generated":true,"unit":"prio-001350#insight-3","date_modified":"2026-10-23"},{"text":"Household head status strongly influences dropout risk, with child-headed households showing the highest probability of dropout.","ai_generated":true,"unit":"prio-001350#insight-4","date_modified":"2026-10-23"},{"text":"The educational level of the household head is a critical factor; children with heads who have not completed primary education have a 31 percentage point higher probability of dropout compared to those with more educated heads.","ai_generated":true,"unit":"prio-001350#insight-5","date_modified":"2026-10-23"},{"text":"Gender and residence play a role in dropout rates, with girls and urban residents being less likely to drop out than boys and rural residents.","ai_generated":true,"unit":"prio-001350#insight-6","date_modified":"2026-10-23"}],"climate_tags":[],"geography_discussed":["Kigali"],"frame_perspective":[],"analysis_type":["quantitative","spatial analysis","longitudinal"]},{"id":"prio-001379","url":"https://climateinsightsdirectory.org/document/prio-001379","title":"Farming or Fighting? Agricultural Price Shocks and Civil War in Africa","publisher":{"name":"Peace Research Institute Oslo","organization":"peace-research-institute-oslo"},"document_type":"research paper","language":"en","date_published":null,"source_url":"https://cdn.cloud.prio.org/files/5f5b87b5-8868-44e0-9f64-090183aa25f5/Farming or Fighting Agricultural Price Shocks and Civil War in Africa.pdf?inline=true","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","geography_discussed","analysis_type"],"summary":{"text":"The study finds a significant negative relationship between local agricultural price indices and the risk of violent conflict in Africa. Using a meso-level approach with a spatial-temporal grid, the author argues that falling agricultural prices lower the opportunity costs for rural populations, thereby facilitating rebel recruitment and civilian support. The results suggest that negative price shocks have a more detrimental effect on conflict risk than positive shocks have a mitigating effect, supporting the 'opportunity cost' mechanism over the 'state capacity' explanation.","ai_generated":true,"unit":"prio-001379#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Negative changes in the local agricultural price index significantly increase the risk of violent conflict events at the local level, while positive changes are associated with a lower risk.","ai_generated":true,"unit":"prio-001379#insight-1","date_modified":"2026-10-23"},{"text":"The impact of negative agricultural price shocks is more severe than the mitigating effect of positive shocks; a 30% decrease in the local agricultural price index increases the annual predicted probability of violence by 4.4% in absolute terms, whereas a 30% increase reduces it by approximately 0.4%.","ai_generated":true,"unit":"prio-001379#insight-2","date_modified":"2026-10-23"},{"text":"The conflict-inducing effects of negative price changes persist over time, with significant impacts observed in the years immediately following a price drop (lags t-1, t-2, and t-3).","ai_generated":true,"unit":"prio-001379#insight-3","date_modified":"2026-10-23"},{"text":"The evidence supports the 'opportunity cost' mechanism—where lower rural income increases incentives to join rebellions—over the 'state capacity' explanation, as the relationship is conditioned on local agricultural production patterns rather than general state revenue.","ai_generated":true,"unit":"prio-001379#insight-4","date_modified":"2026-10-23"},{"text":"The study found no evidence of a 'rapacity effect,' meaning that an increase in the economic value of agricultural output does not precipitate violence.","ai_generated":true,"unit":"prio-001379#insight-5","date_modified":"2026-10-23"},{"text":"Other significant predictors of armed conflict include the presence of politically excluded ethnic groups, higher local population size, and the occurrence of previous violence in the same or neighboring cells (conflict traps).","ai_generated":true,"unit":"prio-001379#insight-6","date_modified":"2026-10-23"}],"climate_tags":[],"geography_discussed":["Ivory Coast"],"frame_perspective":[],"analysis_type":["quantitative","spatial analysis","time-series cross-sectional"]},{"id":"prio-001712","url":"https://climateinsightsdirectory.org/document/prio-001712","title":"Disaggregated determinants of aid: Development aid projects in the Philippines","publisher":{"name":"Peace Research Institute Oslo","organization":"peace-research-institute-oslo"},"document_type":"research paper","language":"en","date_published":null,"source_url":"https://cdn.cloud.prio.org/files/1f616c5b-0e22-444f-9c9a-fe9e0aa31e4c/Rosvold-2019-Development_Policy_Review.pdf?inline=true","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The paper finds that while low Human Development Index (HDI) levels predict aid for excluded group-majority provinces, overall aid distribution is significantly biased in favour of the politically dominant Christian lowlanders. Previous exposure to armed conflict increases the likelihood of new projects only in Christian-majority provinces, and previous disaster exposure is a weak, sometimes negative, predictor of aid across all provinces.","ai_generated":true,"unit":"prio-001712#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Domestic political alliances are a stronger predictor of aid distribution than objective need, with provinces receiving more projects as the share of the population belonging to the politically dominant group, the Christian lowlanders, increases.","ai_generated":true,"unit":"prio-001712#insight-1","date_modified":"2026-10-23"},{"text":"The relationship between development need and aid is conditional on political affiliation; low Human Development Index (HDI) levels significantly predict aid inflow specifically in provinces where excluded groups are the majority.","ai_generated":true,"unit":"prio-001712#insight-2","date_modified":"2026-10-23"},{"text":"Exposure to armed conflict increases the likelihood of receiving new aid projects, but this effect is limited to provinces inhabited by the politically dominant group.","ai_generated":true,"unit":"prio-001712#insight-3","date_modified":"2026-10-23"},{"text":"Previous exposure to rapid-onset natural disasters is not a substantial predictor of aid distribution and may even be weakly associated with a lower likelihood of receiving new projects.","ai_generated":true,"unit":"prio-001712#insight-4","date_modified":"2026-10-23"},{"text":"The findings suggest that the Philippine government exercises significant discretion over the distribution of multilateral aid, often rewarding political supporters regardless of the donor's stated priorities regarding disaster mitigation or conflict-affected populations.","ai_generated":true,"unit":"prio-001712#insight-5","date_modified":"2026-10-23"}],"climate_tags":["natural disaster"],"geography_discussed":["Manila","Mindanao"],"frame_perspective":[],"analysis_type":["quantitative","spatial analysis"]},{"id":"prio-001713","url":"https://climateinsightsdirectory.org/document/prio-001713","title":"Roving Bandits?","publisher":{"name":"Peace Research Institute Oslo","organization":"peace-research-institute-oslo"},"document_type":"research paper","language":"en","date_published":null,"source_url":"https://cdn.cloud.prio.org/files/a357fdc5-9371-46b9-a7e8-9f81d51724d9/Roving Bandits The Geographical Evolution of African Armed Conflicts.pdf?inline=true","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","geography_discussed","analysis_type"],"summary":{"text":"The research analyzes the geographical evolution of African civil wars using the UCDP Georeferenced Event Dataset (GED). It argues that rebel groups with strong ethnic ties or significant military strength tend to maintain stable, localized conflict zones, whereas groups lacking these attributes—or those receiving external military support—are more likely to be 'roving.' The study finds that the greatest mobility occurs when rebels have neither strong local ties nor the strength to compete conventionally with government forces.","ai_generated":true,"unit":"prio-001713#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Rebel groups that make ethnic claims tend to have more stable and localized conflict zones, as they prioritize consolidating control over a specific homeland and can better blend in with local populations.","ai_generated":true,"unit":"prio-001713#insight-1","date_modified":"2026-10-23"},{"text":"External military participation by outside actors is strongly associated with increased movement of conflict zones, as it reduces the rebel group's focus on cultivating local ties and hierarchies.","ai_generated":true,"unit":"prio-001713#insight-2","date_modified":"2026-10-23"},{"text":"Conflict zones exhibit greater mobility when government forces possess dominant military strength, forcing weaker rebel groups to use mobility and guerrilla tactics for survival.","ai_generated":true,"unit":"prio-001713#insight-3","date_modified":"2026-10-23"},{"text":"The highest degree of conflict zone mobility occurs when rebel groups lack both strong local ethnic ties and the military strength to compete with the state.","ai_generated":true,"unit":"prio-001713#insight-4","date_modified":"2026-10-23"},{"text":"Proximity to non-coastal international borders increases the likelihood of conflict stationarity, as governments struggle to project power into peripheral regions.","ai_generated":true,"unit":"prio-001713#insight-5","date_modified":"2026-10-23"},{"text":"Empirical analysis of African conflict polygons shows significant overall movement; less than 45% of conflict areas in a given year overlap by more than 50% with the previous year's area.","ai_generated":true,"unit":"prio-001713#insight-6","date_modified":"2026-10-23"}],"climate_tags":[],"geography_discussed":["Sudan","Uganda","Mali","Libya","Democratic Republic of the Congo","Central African Republic","Sri Lanka"],"frame_perspective":[],"analysis_type":["quantitative analysis","spatial analysis","comparative case study"]},{"id":"wri-000134","url":"https://climateinsightsdirectory.org/document/wri-000134","title":"Predicting Future Forest Loss in the Democratic Republic of the Congo’s CARPE Landscapes","publisher":{"name":"World Resources Institute","organization":"world-resources-institute"},"document_type":"research paper","language":"en","date_published":null,"source_url":"https://www.wri.org/predicting-future-forest-loss-democratic-republic-congos-carpe-landscapes","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The study identifies biophysical conditions, accessibility, and land management as the primary drivers of forest loss in the Democratic Republic of the Congo's CARPE landscapes. Under a business-as-usual scenario, it predicts a loss of approximately 332,200 hectares of forest and 205 million metric tons of CO2 emissions between 2015 and 2025, with the majority of loss occurring in the Ituri-Epulu-Aru and Lac Télé-Lac Tumba landscapes.","ai_generated":true,"unit":"wri-000134#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"The primary drivers of past forest loss across the six CARPE landscapes are biophysical conditions (rainfall and topography), accessibility (distance to rivers, roads, settlements, conflict, and shifting cultivation areas), and land management status (logging concessions and protected areas).","ai_generated":true,"unit":"wri-000134#insight-1","date_modified":"2026-10-23"},{"text":"Under a business-as-usual scenario from 2015 to 2025, approximately 332,200 hectares of forest are projected to be lost, resulting in 205 million metric tons of CO2 emissions, which averages to 20.5 million metric tons per year.","ai_generated":true,"unit":"wri-000134#insight-2","date_modified":"2026-10-23"},{"text":"The majority of projected forest loss (59 percent) is concentrated in two areas: the Ituri-Epulu-Aru Landscape (34 percent) in eastern Orientale Province, and the Lac Télé-Lac Tumba Landscape (25 percent) in Bandundu and Équateur Provinces.","ai_generated":true,"unit":"wri-000134#insight-3","date_modified":"2026-10-23"},{"text":"Preventing all future deforestation in CARPE's forest landscapes could provide climate benefits up to 68 times higher than the carbon sequestration goal of 3 million metric tons of CO2 by 2025 set in the DRC's nationally determined contribution (NDC) under the Paris Agreement.","ai_generated":true,"unit":"wri-000134#insight-4","date_modified":"2026-10-23"},{"text":"Reducing the projected rate of future forest loss by 10 percent would result in emission reductions of 20 million metric tons of CO2 by 2025.","ai_generated":true,"unit":"wri-000134#insight-5","date_modified":"2026-10-23"}],"climate_tags":["carbon dioxide emissions","carbon sequestration","Nationally Determined Contributions","Paris Agreement","climate change mitigation","afforestation","reforestation"],"geography_discussed":["Central Africa","Orientale Province","Équateur","Bandundu Province"],"frame_perspective":[],"analysis_type":["predictive modeling","spatial analysis"]},{"id":"wri-000564","url":"https://climateinsightsdirectory.org/document/wri-000564","title":"Urban Blue-Green Conundrum: A 10-City Study on the Impacts of Urbanization on Natural Infrastructure in India","publisher":{"name":"World Resources Institute","organization":"world-resources-institute"},"document_type":"research paper","language":"en","date_published":null,"source_url":"https://www.wri.org/research/urban-blue-green-conundrum-10-city-study-impacts-urbanization-natural-infrastructure-india","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The study analyzes the impact of urbanization on natural infrastructure in 10 major Indian cities from 2000 to 2015, finding significant increases in built-up areas and a corresponding loss of surface water and groundwater recharge potential. It advocates for an integrated urban blue-green approach to planning to mitigate risks like urban flooding and water scarcity.","ai_generated":true,"unit":"wri-000564#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Between 2000 and 2015, the built-up area in the 10 studied cities grew by an average of 47 percent within 0–20 km of the city center and 134 percent in the periphery (20–50 km).","ai_generated":true,"unit":"wri-000564#insight-1","date_modified":"2026-10-23"},{"text":"The 10 cities experienced an estimated loss of 307 sq. km of surface water between 2000 and 2015, representing a 15 percent decrease.","ai_generated":true,"unit":"wri-000564#insight-2","date_modified":"2026-10-23"},{"text":"Approximately 44 percent (1,177 sq. km) of new development in the 0–50 km urban region of the study cities occurred on areas with very high or high recharge potential between 2000 and 2015.","ai_generated":true,"unit":"wri-000564#insight-3","date_modified":"2026-10-23"},{"text":"Urbanization disconnected from the natural environment leads to negative outcomes including urban flooding, water scarcity, and increased groundwater stress, often because development is sited on vulnerable zones like lake beds, floodplains, and low-lying areas.","ai_generated":true,"unit":"wri-000564#insight-4","date_modified":"2026-10-23"}],"climate_tags":["urbanization","green infrastructure","groundwater recharge","urban flooding","water scarcity","urban planning"],"geography_discussed":["Ahmedabad","Bengaluru","Chennai","Delhi","Hyderabad","Jaipur","Kolkata","Mumbai","Pune","Surat"],"frame_perspective":[],"analysis_type":["correlation study","spatial analysis"]},{"id":"wri-001369","url":"https://climateinsightsdirectory.org/document/wri-001369","title":"REEFS AT RISK","publisher":{"name":"World Resources Institute","organization":"world-resources-institute"},"document_type":"report","language":"en","date_published":null,"source_url":"http://pdf.wri.org/reefs.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The report 'Reefs at Risk' assesses the global status of coral reefs, finding that 58% are potentially threatened by human activities. It identifies overexploitation and coastal development as the primary drivers of risk, with Southeast Asia being the most threatened region. The study utilizes a map-based indicator to flag high-risk areas, particularly biodiversity hot spots, and evaluates the current state of marine protected areas (MPAs).","ai_generated":true,"unit":"wri-001369#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Approximately 58% of the world's coral reefs are potentially threatened by human activity, with 27% classified as high risk and 31% as medium risk.","ai_generated":true,"unit":"wri-001369#insight-1","date_modified":"2026-10-23"},{"text":"Overexploitation of marine resources and coastal development are the most significant threats, each affecting roughly one-third of all reefs globally.","ai_generated":true,"unit":"wri-001369#insight-2","date_modified":"2026-10-23"},{"text":"Southeast Asia is the most threatened region globally, with over 80% of its reefs at risk and more than half (56%) facing high potential threat.","ai_generated":true,"unit":"wri-001369#insight-3","date_modified":"2026-10-23"},{"text":"The Pacific region contains the largest area of coral reefs and is the least threatened, with approximately 60% of its reefs classified as low risk.","ai_generated":true,"unit":"wri-001369#insight-4","date_modified":"2026-10-23"},{"text":"At least 11% of global coral reefs are 'biodiversity hot spots,' defined as areas with high reef fish species richness that are also under high threat; these are concentrated in Southeast Asia and the Caribbean.","ai_generated":true,"unit":"wri-001369#insight-5","date_modified":"2026-10-23"},{"text":"Marine protected areas (MPAs) are insufficient in scale and coverage; at least 40 countries have no formal protection for their reefs, and most existing MPAs are smaller than one square kilometer.","ai_generated":true,"unit":"wri-001369#insight-6","date_modified":"2026-10-23"},{"text":"Destructive fishing practices, specifically the use of cyanide to capture live fish for the aquarium and restaurant trades, are widespread across the Indo-Pacific region.","ai_generated":true,"unit":"wri-001369#insight-7","date_modified":"2026-10-23"}],"climate_tags":["coral reef restoration","biodiversity","coastal management","coral bleaching","climate change"],"geography_discussed":["Southeast Asia","Pacific Ocean","Caribbean","Indian Ocean","Middle East","Philippines","Indonesia","Australia","United States"],"frame_perspective":[],"analysis_type":["global assessment","risk modeling","spatial analysis"]},{"id":"wwf-000284","url":"https://climateinsightsdirectory.org/document/wwf-000284","title":"A GUIDE TO ARCNET: AN ARCTIC OCEAN NETWORK OF PRIORITY AREAS FOR CONSERVATION ARCTIC","publisher":{"name":"WWF International","organization":"wwf-international"},"document_type":"guide","language":"en","date_published":null,"source_url":"https://www.worldwildlife.org/documents/699/20tn3hjotq_report_wwf_arctic_arcnet_introductory_guide_a4_hires_final_webversion.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"WWF has developed ArcNet, a systematic, whole-ocean network of 83 priority areas for conservation (PACs) covering 5,087,000 square kilometres (31% of the study area) in the Arctic Ocean. Using the Marxan tool and a database of over 800 conservation features, ArcNet aims to provide a blueprint for Arctic governments and the Arctic Council to meet the UN Convention on Biological Diversity's target of 30% protection by 2030. The network is designed to be adaptive, allowing for iterative refinement as climate change shifts species distributions and habitats.","ai_generated":true,"unit":"wwf-000284#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"ArcNet has identified a network of 83 priority areas for conservation (PACs) covering 5,087,000 square kilometres, which represents 31 per cent of the study area.","ai_generated":true,"unit":"wwf-000284#insight-1","date_modified":"2026-10-23"},{"text":"The network was developed using a systematic conservation planning approach via the Marxan decision-support software, utilizing a spatial database of more than 800 conservation features including species, habitats, and biological communities.","ai_generated":true,"unit":"wwf-000284#insight-2","date_modified":"2026-10-23"},{"text":"ArcNet is intended to help the international community achieve the United Nations Convention on Biological Diversity (CBD) target to protect and conserve at least 30 per cent of the planet by 2030.","ai_generated":true,"unit":"wwf-000284#insight-3","date_modified":"2026-10-23"},{"text":"The analysis adopted a 'whole-ocean' perspective to capture ocean-scale connectivity and interrelated ecosystems, which the document argues is more effective than the sum of smaller-scale national or regional analyses.","ai_generated":true,"unit":"wwf-000284#insight-4","date_modified":"2026-10-23"},{"text":"The network is designed to protect ecosystems from non-climate, human-induced pressures—such as fishing, resource extraction, and ship strikes—to increase the chances of biodiversity survival as the climate crisis worsens.","ai_generated":true,"unit":"wwf-000284#insight-5","date_modified":"2026-10-23"},{"text":"To support implementation and finer-scale planning, WWF created two web portals: Chikory, for exploring data layers underpinning the PACs, and Accenter, a web-based mini-GIS for querying Marxan outputs.","ai_generated":true,"unit":"wwf-000284#insight-6","date_modified":"2026-10-23"},{"text":"The guide emphasizes an adaptive design approach, noting that the network must be iteratively adjusted to account for climate-driven shifts in the spatial distribution of species and habitats.","ai_generated":true,"unit":"wwf-000284#insight-7","date_modified":"2026-10-23"},{"text":"The geographic scope of the analysis is based on the 18 PAME-defined Large Marine Ecosystems (LMEs) of the Arctic Ocean and adjacent seas, though the Faroe Plateau, Norwegian Sea, and Aleutian Islands LMEs were removed to focus on the Arctic Realm.","ai_generated":true,"unit":"wwf-000284#insight-8","date_modified":"2026-10-23"}],"climate_tags":["biodiversity conservation","climate change"],"geography_discussed":["Pechora Sea","Russia","Canada","Denmark","Norway","United States"],"frame_perspective":[],"analysis_type":["systematic conservation planning","spatial analysis"]},{"id":"wwf-000615","url":"https://climateinsightsdirectory.org/document/wwf-000615","title":"AN AERIAL SURVEY OF ELEPHANTS AND OTHER LARGE HERBIVORES IN THE KAVANGO ZAMBEZI TRANSFRONTIER CONSERVATION AREA","publisher":{"name":"WWF International","organization":"wwf-international"},"document_type":"report","language":"en","date_published":null,"source_url":"https://www.worldwildlife.org/documents/598/5si83x57zx_1._KAZA_Elephant_Survey_Volume_I.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The 2022 KAZA Elephant Survey estimated a total population of 227,900 elephants across the KAZA TFCA, with the majority located in Botswana (58%) and Zimbabwe (29%). The survey also identified 26,641 elephant carcasses, resulting in an all-carcass ratio of 10.47%, which the authors suggest may be a \"warning sign for the health and stability of the elephant population.\" Beyond elephants, the survey estimated populations for various wildlife species and domestic livestock, noting a ratio of 1.16 wild animals to 1 domestic animal in the survey area. The report details the technical execution of the survey, including the use of systematic transect sampling across 179 strata and the implementation of CITES MIKE Aerial Survey Standards.","ai_generated":true,"unit":"wwf-000615#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"The total estimated population of African savanna elephants in the KAZA TFCA survey area is 227,900 (±16,743), achieving a percentage relative precision (PRP) of 7.34%.","ai_generated":true,"unit":"wwf-000615#insight-1","date_modified":"2026-10-23"},{"text":"The survey estimated 26,641 (±1,645) elephant carcasses, leading to an overall all-carcass ratio (CR14) of 10.47%, which is considered a high level of mortality that may signal instability in the population.","ai_generated":true,"unit":"wwf-000615#insight-2","date_modified":"2026-10-23"},{"text":"Elephant distribution is highly uneven across the five partner states: Botswana holds 58% of the population, Zimbabwe 29%, Namibia 9%, and Zambia and Angola combined account for the remaining 4%.","ai_generated":true,"unit":"wwf-000615#insight-3","date_modified":"2026-10-23"},{"text":"The survey estimated populations for several other wildlife species in the KAZA TFCA survey area: impala (100,028), zebra (88,250), buffalo (78,264), red lechwe (137,959), and giraffe (12,771).","ai_generated":true,"unit":"wwf-000615#insight-4","date_modified":"2026-10-23"},{"text":"Domestic livestock in the survey area was estimated at 736,426 animals, consisting of 73% cattle and 24% sheep and goats, creating a ratio of 1.16 wild animals for every 1 domestic animal.","ai_generated":true,"unit":"wwf-000615#insight-5","date_modified":"2026-10-23"},{"text":"Recent mortality, measured by the fresh and recent carcass ratio (CR12), was estimated at 0.51% for the KAZA TFCA, with the highest ratios found in Botswana (0.72%), Angola (0.57%), and the Kavango Zambezi zone (0.49%).","ai_generated":true,"unit":"wwf-000615#insight-6","date_modified":"2026-10-23"},{"text":"The survey observed a pattern of spatial segregation where elephants are generally absent from regions with high densities of human settlements and livestock.","ai_generated":true,"unit":"wwf-000615#insight-7","date_modified":"2026-10-23"},{"text":"The survey covered 60% of the KAZA TFCA (310,865 km²), utilizing 195 flights across 179 strata with an overall sampling intensity of 6.9%.","ai_generated":true,"unit":"wwf-000615#insight-8","date_modified":"2026-10-23"},{"text":"Photo interpretation of observed groups led to a 2.2% increase in the final estimated population of elephants in the KAZA TFCA compared to raw observer data.","ai_generated":true,"unit":"wwf-000615#insight-9","date_modified":"2026-10-23"},{"text":"The survey adhered to CITES MIKE Aerial Survey Standards Version 3.0, with a mean flight height of 91.8 m AGL and a mean ground speed of 171.5 km.hr-1.","ai_generated":true,"unit":"wwf-000615#insight-10","date_modified":"2026-10-23"}],"climate_tags":["biodiversity"],"geography_discussed":["South Africa","France"],"frame_perspective":[],"analysis_type":["population survey","spatial analysis","technical report"]}]}