Understanding the assessment
The project to identify the most suitable areas for wind farm development as potential candidate territories, is structured around two main phases: a mapping phase and sensitivity and suitability analysis.
The spatial suitability analysis uses a 25 × 25 m assessment cell (625 m² per cell). The grid is a screening resolution, not a turbine-placement or cadastral survey boundary.
The methodology, criteria tables, and guide are available in English and Ukrainian. The original Word source remains in English.
Визначаються території, непридатні для розміщення вітрових електростанцій через правові, екологічні або технічні обмеження.
Результат: найчутливіші ділянки вилучаються з подальшого аналізу.Перевіряються природні, соціальні та інші ризики для решти території з урахуванням потреби уникнення впливів або пом'якшувальних заходів.
Результат: визначення зон, які слід виключити з подальшого оцінювання.Оцінюються вітровий ресурс, природа, соціально-економічні фактори, інфраструктура та землекористування.
Результат: пріоритезація ділянок для подальшого вивчення.During the mapping phase, exclusion criteria were applied to identify and remove areas where wind farm development could potentially result in significant adverse environmental, social, or other impacts, or where development would be incompatible with existing legal, environmental, or technical restrictions. These areas were excluded from further assessment.
The mapping process was based on the methodology and spatial information developed within the REZOMA project. As part of the preparatory work, the available spatial datasets were reviewed to identify opportunities to incorporate more accurate, up-to-date, or higher-resolution data, thereby improving the reliability and spatial precision of the assessment. In parallel, relevant legislation and regulatory requirements were reviewed to determine whether any additional exclusion criteria or changes to existing restrictions needed to be considered. This process ensured that the mapping approach was based on the best available spatial data, reflected the current regulatory framework, and provided a consistent and reliable basis for the subsequent sensitivity and suitability assessment (Step 2).
Stage 1 mapping criteria from the supplied Excel workbook. Buffer distances and listed data sources describe the methodological reference table; actual run settings are controlled by the selected scenario.
| Data group | Criteria | Excel threshold | Reference | Excel data source |
|---|---|---|---|---|
| Socialeconomic aspects | City zone inc.villages | 1500 m | Rezoma | OSM |
| Socialeconomic aspects | Residential and public buildings | 700 m | UA National standart | OSM |
| Socialeconomic aspects | Churches | 600 m | Rezoma | OSM |
| Socialeconomic aspects | Cultural heritage (National level) | 100 metres within settlements, · 300 metres outside settlements | Law "On Protection of Cultural Heritage" | Ministry of Culture |
| Socialeconomic aspects | UNESCO world heritage | UNESCO definied buferzones | Law "On Protection of Cultural Heritage" | UNESCO |
| Planning constraits and landuse | Slope* | 15 degree | Rezoma | COPERNICUS |
| Planning constraits and landuse | Elevation | > 1000 m | RES Law (1.10.2026) | COPERNICUS |
| Planning constraits and landuse | Rivers and lakes | 400 m | Rezoma | State water cadastre |
| Planning constraits and landuse | Sea (Coastal) | 2 km | Water Code of UA | OSM |
| Planning constraits and landuse | Forest | 0 m | Rezoma | OSM |
| Planning constraits and landuse | Heath | 0 m | Rezoma | OSM |
| Planning constraits and landuse | Meadow | 0 m | Rezoma | OSM |
| Planning constraits and landuse | Scrub | 0 m | Rezoma | OSM |
| Planning constraits and landuse | Natural resource excavation areas | 500 m | Rezoma | OSM |
| Planning constraits and landuse | Border strip | -2km border with Russia and Belarus · - 30-50 m other countries | Law "On the State Border of Ukraine" | PAEW |
| Infrastructure | Roads | 375 m | total h*1,5 | OSM |
| Infrastructure | Railways | 375 m | total h*1,5 | OSM |
| Infrastructure | Energy infrastructure - transmission lines and substations | 375 m | total h*1,5 | OSM |
| Infrastructure | Substations | > 20 km | Rezoma | OSM |
| Infrastructure | Gas and oil pipelines | 400 m | Law ‘On the Legal Status of Land in the Protection Zones of Main Pipeline Facilities’ (Article 11) | OSM |
| Infrastructure | Amonia pipelines | 1000 m | Law ‘On the Legal Status of Land in the Protection Zones of Main Pipeline Facilities’ (Article 11) | OSM |
| Infrastructure | Airports | Large - 15 000 m · Small - 10 000 m | DBN Б.2.2-12:2019 ‘Land-use planning and development’, clause 11.2.9. | ARTŪRS |
| Infrastructure | Television and communication towers | 2000 m | DBN Б.2.2-12:2019 ‘Land-use planning and development’ | OSM |
| Nature values and biodiversity | Nationaly and Internationaly protected areas | 1000 m | Rezoma | WDPA database |
| Wind | Wind potential | <3200 FLH | Rezoma | Global wind atlas |
Areas remaining after mapping were assessed using environmental, social, technical and other relevant criteria to identify locations highly sensitive to wind farm development. Such areas were excluded because of potential environmental constraints.
Reference criteria from STAGE 2 of the supplied Excel workbook. Exclusion 2 removes candidate projects; it does not erase already assessed score cells.
| Data group | Criteria | Excel threshold | Reference | Excel data source | Excel notes | Tool 4.1 default |
|---|---|---|---|---|---|---|
| Socialeconomic aspects | UNESCO world heritage (points, polygons) | < 25 km | UNESCO | UNESCO polygons + points, 25 km | ||
| Planning constraits and landuse | Border strip | < 5 km | PAEW | Inland border + 5,000 m | ||
| Planning constraits and landuse | Areas with a probability of flooding of 1% | 0 m | JRC Data Catalogue | Flooding polygons, 0 m | ||
| Planning constraits and landuse | Suitable area for wind farm construction >= 100 MW | <6,5 km2 | Real-case | Minimum connected project area 6.5 km²; no 100 MW minimum | ||
| Infrastructure | Meteorological radars (C band) | < 20 km | EUMETNET/ WMO recomendation | Kyiv (Boryspil) — Meteor-500 C (C - band) Zaporizhzhia — MRL-5 (X - band) | Radar + 20 km | |
| Infrastructure | Distance to transmission lines | > 15 km | OSM | Exclude beyond 15 km | ||
| Nature values and biodiversity | Areas with high level density of observations of endangered species | 0 m | GBIF | Bird/flora concentration polygons, 0 m | ||
| Nature values and biodiversity | Plant species or plant communities listed in the Red Book or Green Book | 50 m | GBIF | Flora/fungi observation points +50 m; zones 0 m | ||
| Nature values and biodiversity | Forest | 200 m | EUROBAT guidelines | OSM | Prepared forest polygons + 200 m | |
| Nature values and biodiversity | Key Biodiversity Areas (KBA) | 1000 m | Rezoma | Key biodiversity areas | KBA + 1,000 m | |
| Nature values and biodiversity | Important underground sites for bats | 1000 m | Rezoma | EUROBAT | Bat sites + 1,000 m | |
| Wind | Existing wind parks | 1000 m | OSM | Existing turbines + 1,000 m | ||
| Occupied territories | Occupied territories | 0 km | Occupied territories, 0 m |
Following the identification of highly sensitive areas, the remaining locations were evaluated using a predefined assessment scale and a set of suitability criteria. This assessment enabled the comparison and classification of areas according to their suitability for wind farm development, helping to identify and prioritize the most favorable locations for further consideration. Based on the available spatial data inventory, datasets were classified into five thematic groups:
the assessment focuses on identifying areas of high ecological value and sensitivity, including protected areas and species of conservation importance, important bird and bat areas, ecological corridors, and other biodiversity features that may be particularly vulnerable to wind farm development.
the assessment focuses on terrain characteristics, elevation, slope, and land cover to identify physical and land-use conditions that may influence the development potential of areas for wind farm development.
the assessment focuses on the location and proximity of settlements and cultural heritage sites, considering potential constraints and sensitivities associated with wind farm development.
the assessment focuses on the location and proximity of roads, railways, power infrastructure, airports, and existing wind farms, considering both potential constraints and opportunities for wind farm development.
assessment focuses on the spatial distribution and quality of the available wind resource, including wind speed and other relevant wind conditions that influence the technical and economic suitability of areas for wind farm development.
Revised Stage 3 scoring, as supplied on 12 October 2026. Values describe the evaluation criteria; actual calculations follow the selected tool scenario. Blank soil bands remain blank in the supplied revision.
Buildings and residential zones are evaluated separately from heritage, but not added to populated places as a second population score: the tool uses the lower of the buildings/residential score and the cities/villages score for the population component (75% of the socioeconomic group). Cultural heritage contributes the other 25%. The building source covers OSM building footprints and prepared residential zones; hospitals and other public buildings are included only where present in those inputs, not as a separate hospital scoring rule.
| Data group | Layers | Exclusion criteria | Evaluation parameters | Weight |
|---|---|---|---|---|
| Socioeconomic | Cities, villages | 1500 m | 0–1500 m = 0; 1500–3000 m = 50 | |
| Socioeconomic | Buildings and residential zones (including public buildings where mapped) | Footprint + 700 m exclusion (Step 1) | 0–1500 m = 0; >1500–3000 m = 50; >3000 m = 100 | |
| Socioeconomic | Cultural heritage | 100 m within settlements; 300 m outside settlements | 300–1500 m = 0; 1500–3000 m = 50 | |
| Infrastructure | Energy infrastructure – transmission lines | 375 m | 375–5000 m = 100; 5000–10,000 m = 70; 10,000–15,000 m = 40 | |
| Infrastructure | Distance to roads | 375 m | <5000 m = 100; 5000–10,000 m = 66; 10,000–15,000 m = 33 | |
| Infrastructure | Substations | 375 m | 375–2000 m = 100; 2000–5000 m = 80; 5000–10,000 m = 50; 10,000–20,000 m = 20 | |
| Nature | Natural reserves, nationally protected areas (WDPA) | Footprints + 1000 m | 1000–2000 m = 50 | |
| Nature | Key Biodiversity Areas (KBA), including IBA | Footprints + 1000 m | 1000–5000 m = 0; 5000–10,000 m = 50 | |
| Wind | Wind speed | <3200 FLH | <7 m/s = 0; 7–8 m/s = 50; >8 m/s = 100 | |
| Planning constraints and land use | Valuable agricultural land (valuable soils) |
The Excel workbook is a working reference, not a legally certified list of statutory setbacks. Tool defaults were checked against config/criteria/exclusions.yaml, config/criteria/evaluations.yaml, and wind_default.yaml; publication-specific overrides are shown separately above.
The geospatial datasets used for this assessment were based on publicly available information obtained from major open-access databases and data platforms. These datasets provide a useful basis for preliminary spatial screening and identification of potential environmental constraints.
Till now several mapping projects have been conducted in Ukraine, each applying different methodologies and criteria to identify more suitable areas for wind farm development:
Open the map to load the current publication settings.
Run-specific settings are read from the exported publication summary, not assumed from application defaults.
These software settings accompany the methodological description; they do not replace its thematic classification.
A tool for green rebuilding
The project “Renewables Acceleration Areas in Ukraine – a tool for green rebuilding” contributes to Ukraine’s alignment with EU environmental and climate legislation by identifying potential candidate areas through environmentally responsible spatial planning and renewable-energy screening.
The project is implemented with financial support from the Ministry of Foreign Affairs of the Republic of Latvia.
Estonian, Latvian & Lithuanian Environment (ELLE), together with the Professional Association of Environmentalists of the World (PAEW) in Ukraine, is implementing the project with funding from Latvia’s development cooperation programme administered by the Ministry of Foreign Affairs of the Republic of Latvia.
The objective is to support national identification of potential Renewable Acceleration Areas (RAAs), in alignment with the revised Renewable Energy Directive (RED III), environmental protection requirements and sustainable spatial planning.
The identified territories are candidates only. They have not been legally designated as RAAs under this project and do not automatically qualify for accelerated permitting.
The project builds on earlier work, including REZOMA, Ukraine’s renewable energy/hydrogen potential map and the Cross-Border Renewables Acceleration Areas initiative.
ELLE · PAEW · REZOMA · Cross-Border RAAs ·
Start with the study-area total or select an oblast. Published totals come from the model's analytical summary. Selecting an oblast filters the oblast-split candidate polygons when that layer was published; rasters and reference layers stay unchanged.
Use the layer search, five thematic data groups and opacity sliders. Additional archives load on demand. Click a candidate polygon or source feature to view its published attributes. Suitability and area filters apply to candidate polygons, not to source layers.
Candidate territories are preliminary screening outputs, not development approvals. Consult the methodological description, source data limitations and local conditions before using results for project decisions.
The candidate score raster covers final candidate polygons. The grey outside-score raster covers assessed land outside those polygons, including land removed by Exclusion 2 and by area or optional score selection. The two rasters use the same fixed score scale. A missing-data area is not a zero score.
Step 1 mapping exclusions remove constrained land before scoring. Step 2A excludes highly sensitive areas from candidate selection. A dedicated Step 1 mapping-area overlay requires a separately published PMTiles dataset; it is not included in the current source publication.
The oblast-parts layer allocates project area, capacity and generation by polygon-area share. Part score means are inherited from the whole project. Turbines in this layer are fractional equivalents; project counts across oblasts are not additive. Generation is an indicative gross estimate, not a turbine-specific net yield forecast.
Published context layers show original source features selected for the analysis, not the analytical exclusion buffers. Vector tiles simplify display geometry and may split features across tile boundaries. Measurement tools are approximate. Use the original GIS results for precise spatial analysis.
