{"query_echo":{"q":"","filters":{"analysis_type":["spatial modelling"]},"warnings":[{"code":"facet_value_not_in_vocabulary","message":"Value 'spatial modelling' for facet 'analysis_type' is not in the controlled vocabulary."}]},"total":{"value":3,"relation":"eq"},"page":1,"page_size":20,"self":"https://climateinsightsdirectory.org/api/v1/search?analysis_type=spatial+modelling","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":"cliinstca-000380","url":"https://climateinsightsdirectory.org/document/cliinstca-000380","title":"Climate Risks Associated With New Housing in Canada","publisher":{"name":"Canadian Climate Institute","organization":"canadian-climate-institute"},"document_type":"report","language":"en","date_published":"2024-09","source_url":"https://climateinstitute.ca/wp-content/uploads/2025/01/climate-risks-new-housing-Canada-technical-report-SSG.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The report details a spatial modelling approach to assess climate risks for new housing in Canada, focusing on flood and wildfire hazards under current and 2030 RCP 4.5 scenarios. It describes the allocation of new units across 5,161 census subdivisions and the specific estimation methods used to determine average annual loss (AAL) for these new developments.","ai_generated":true,"unit":"cliinstca-000380#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Canada Mortgage and Housing Corporation (CMHC) projects a need for 5.8 million new homes between 2023 and 2030, which would increase the country's housing stock by 34 per cent.","ai_generated":true,"unit":"cliinstca-000380#insight-1","date_modified":"2026-10-23"},{"text":"The analysis focused detailed spatial modelling on 943 census subdivisions (CSDs) where 99% of the projected new housing units are expected to be located.","ai_generated":true,"unit":"cliinstca-000380#insight-2","date_modified":"2026-10-23"},{"text":"To estimate flood average annual loss (AAL) for new locations, the study employed a four-tier prioritised methodology: nearest neighbour, contiguous flood susceptibility, sub-regional regression analysis, and regional regression analysis.","ai_generated":true,"unit":"cliinstca-000380#insight-3","date_modified":"2026-10-23"},{"text":"The report identifies risk concentration by calculating 90th and 99th percentile thresholds of normalized AAL per unit to determine the potential flood damage that could be avoided by preventing development in the highest-risk pixels.","ai_generated":true,"unit":"cliinstca-000380#insight-4","date_modified":"2026-10-23"},{"text":"Wildfire risk for 90.1% of projected new units was calculated using a cost-weighted hazard index derived from Canadian Forest Service data and Co-operators AAL data, with future AAL clamped to the maximum experienced by existing dwellings in each CSD.","ai_generated":true,"unit":"cliinstca-000380#insight-5","date_modified":"2026-10-23"}],"climate_tags":["flood risk","land-use planning","climate change adaptation","coastal flood"],"geography_discussed":["British Columbia","Ontario"],"frame_perspective":[],"analysis_type":["risk assessment","spatial modelling"]},{"id":"gclifun-006069","url":"https://climateinsightsdirectory.org/document/gclifun-006069","title":"Strengthening strategic approaches for 30x30 investments in the Democratic Republic of the Congo","publisher":{"name":"Green Climate Fund","organization":"green-climate-fund"},"document_type":"report","language":"en","date_published":"2024-03-28","source_url":"https://www.greenclimate.fund/sites/default/files/document/readiness-proposal-drc-wcs.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The proposal aims to address the lack of coordination between climate, biodiversity, and development strategies in the Democratic Republic of the Congo (DRC). It proposes a 24-month project to create a 30x30 investment strategy that integrates biodiversity conservation with climate mitigation and adaptation, specifically focusing on the rights and engagement of Indigenous Peoples and Local Communities (IPs and LCs). Key activities include spatial modelling to identify priority conservation areas, policy alignment analysis, the development of a business plan for 30x30 implementation, and the submission of a technically sound GCF project concept note.","ai_generated":true,"unit":"gclifun-006069#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"The Democratic Republic of the Congo is identified as the 12th most vulnerable country to climate change and the 5th least ready to address its impacts.","ai_generated":true,"unit":"gclifun-006069#insight-1","date_modified":"2026-10-23"},{"text":"The Land-use, land-use change and forestry (LULUCF) sector is the primary source of greenhouse gas emissions in the DRC, with increasing rates of deforestation and forest degradation in recent years.","ai_generated":true,"unit":"gclifun-006069#insight-2","date_modified":"2026-10-23"},{"text":"Significant sectoral misalignment exists in the DRC, exemplified by the fact that approximately 50% of protected areas overlap with mining concessions, and some forestry concessions and oil blocks overlap with conservation areas.","ai_generated":true,"unit":"gclifun-006069#insight-3","date_modified":"2026-10-23"},{"text":"The DRC government has committed to reducing emissions by 21% by 2030 compared to business-as-usual, with the Forestry and Other Land Use Sector identifying 11 priority actions to achieve this.","ai_generated":true,"unit":"gclifun-006069#insight-4","date_modified":"2026-10-23"},{"text":"The project identifies three primary barriers to achieving 30x30 goals: a lack of alignment between national climate, biodiversity, and development strategies; insufficient human resources and technical capacity for multi-stakeholder engagement and project implementation; and limited capacity to access and integrate financial resources for vulnerable communities.","ai_generated":true,"unit":"gclifun-006069#insight-5","date_modified":"2026-10-23"},{"text":"The proposal targets the empowerment of approximately 600,000 Indigenous Peoples in the DRC, who represent 60% of the IP population in the Congo Basin.","ai_generated":true,"unit":"gclifun-006069#insight-6","date_modified":"2026-10-23"},{"text":"The project will implement a specific set of deliverables, including a spatial plan for priority conservation geographies, a national 30x30 strategy, a costed investment plan, and a GCF project concept note with an environmental and social risk screening report.","ai_generated":true,"unit":"gclifun-006069#insight-7","date_modified":"2026-10-23"}],"climate_tags":["biodiversity conservation","climate change adaptation","climate change mitigation","nature-based solutions","indigenous rights","land-use planning","climate finance","deforestation","forest degradation","Villevocance","peatland"],"geography_discussed":["Congo Basin","Kinshasa","Tshopo","Ituri Province","Bas-Uele","Sud-Ubangi","Tanganyika Province"],"frame_perspective":[],"analysis_type":["policy analysis","strategic planning","financial assessment","spatial modelling"]},{"id":"iisd-001747","url":"https://climateinsightsdirectory.org/document/iisd-001747","title":"MAINSTREAMING CLIMATE CHANGE INTEGRATED LANDSCAPE ASSESSMENT, DECISION-SUPPORT & TOOL KIT","publisher":{"name":"International Institute for Sustainable Development","organization":"international-institute-for-sustainable-development"},"document_type":"briefing","language":"en","date_published":"2015","source_url":"https://www.iisd.org/system/files/publications/mainstreaming-climate-change-toolkit-briefing-note.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The briefing outlines the 'From Farms to Regions' project, which used a participatory framework and the Envision geospatial modelling platform to develop climate adaptation strategies for southeastern Ontario. By engaging stakeholders and analysts, the project identified key drivers of change—climate change, markets, and governance—and created five future scenarios (Business-as-Usual, Targeting foreign markets, Promoting the bioeconomy, Moving towards greener agriculture, and Living locally). These scenarios were used to quantify impacts on land use and environmental indicators, leading to the identification of over 50 adaptation actions clustered into farm-level changes, new insurance mechanisms, ecosystem service support, information tools, and public education. The document concludes with a framework for monitoring the integration of these adaptation measures into cross-sectoral policy and planning.","ai_generated":true,"unit":"iisd-001747#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"The project identified three primary drivers of change for southeastern Ontario: climate change, markets and the economy, and governance and policy, with climate change acting as an overarching driver affecting all others.","ai_generated":true,"unit":"iisd-001747#insight-1","date_modified":"2026-10-23"},{"text":"The project utilized the Envision modelling framework, a dynamic GIS-based spatial engine, to translate qualitative stakeholder scenarios into quantitative measures for landscape characteristics and policy impacts.","ai_generated":true,"unit":"iisd-001747#insight-2","date_modified":"2026-10-23"},{"text":"Five future scenarios were developed to 2035: a Business-as-Usual (BAU) baseline and four alternatives: 'Targeting foreign markets', 'Promoting the bioeconomy', 'Moving towards greener agriculture', and 'Living locally'.","ai_generated":true,"unit":"iisd-001747#insight-3","date_modified":"2026-10-23"},{"text":"Scenario modelling revealed varying environmental outcomes: 'Living locally' provided the highest support for a wide variety of species and the lowest risks to phosphorus loads, while 'Targeting global markets' had negative impacts on habitat.","ai_generated":true,"unit":"iisd-001747#insight-4","date_modified":"2026-10-23"},{"text":"Stakeholders identified over 50 adaptation actions, categorized into five clusters: farm-level production adjustments, new risk-management tools like crop insurance, support for ecosystem goods and services, provision of GIS and forecasting tools, and public awareness/education.","ai_generated":true,"unit":"iisd-001747#insight-5","date_modified":"2026-10-23"},{"text":"The document proposes a monitoring framework to track the mainstreaming of adaptation, using indicators such as the number of municipal plans including adaptation actions and the frequency of cross-sectoral consultations.","ai_generated":true,"unit":"iisd-001747#insight-6","date_modified":"2026-10-23"}],"climate_tags":["climate change adaptation","agriculture","land-use planning","biobased economy","ecosystem service","biodiversity","water quality"],"geography_discussed":["Canada","Prince Edward Island","Quebec","Greater Toronto Area"],"frame_perspective":[],"analysis_type":["scenario analysis","stakeholder engagement","spatial modelling"]}]}