How often do World Bank projects use geospatial data?
Evidence from 2,261 projects, read through 3,791 Project Appraisal and Project Information Documents
In 6 in 10 World Bank projects that use data (1,115 of 1,870, 60%), teams draw on geospatial data, mostly at the level of regions and districts. How reliable is this?
- 2,261projects reviewed: every project with a PAD or PID in the collection
- 1,870use data in the passages read
- 1,115use geospatial data
Used in every sector and region
By approval year, the share runs from 58% (2021) to 61% (2024). 7 years of recent approvals are too few to show a trend.
Among the 109 countries with at least 5 projects, the share runs from 26% in Kyrgyz Republic to 100% in 2 countries.
Projects using geospatial data, by approval year
Under each year: the number of projects counted.
* 2026 counts approvals to 22 September.
Share of projects using geospatial data, by country
- under 20%
- 20–39%
- 40–59%
- 60–79%
- 80% or more
- fewer than 5 projects
- none reviewed
Point at or tap a country to see its figures.
Not on the map: 114 regional or multi-country projects; 62 projects in 24 countries with fewer than 5 are grey. Region, country and approval year come from the World Bank Projects API.
All 109 countries with at least 5 projects
| Country | projects | share | |
|---|---|---|---|
| Guatemala | 8 | 100% | |
| Micronesia, Federated States of | 5 | 100% | |
| Brazil | 60 | 88% | |
| Dominican Republic | 7 | 86% | |
| Afghanistan | 13 | 85% | |
| Pakistan | 40 | 82% | |
| West Bank and Gaza | 27 | 82% | |
| Iraq | 10 | 80% | |
| St. Vincent and the Grenadines | 5 | 80% | |
| Niger | 14 | 79% | |
| Turkiye | 41 | 78% | |
| Sierra Leone | 18 | 78% | |
| Haiti | 17 | 76% | |
| Kenya | 25 | 76% | |
| Bosnia and Herzegovina | 12 | 75% | |
| Myanmar | 8 | 75% | |
| Sudan | 12 | 75% | |
| Burundi | 15 | 73% | |
| Central African Republic | 14 | 71% | |
| El Salvador | 14 | 71% | |
| Tonga | 7 | 71% | |
| Armenia | 10 | 70% | |
| Kiribati | 10 | 70% | |
| Uganda | 19 | 68% | |
| Tanzania | 22 | 68% | |
| Kosovo | 12 | 67% | |
| South Africa | 6 | 67% | |
| Tajikistan | 24 | 67% | |
| Philippines | 26 | 65% | |
| Somalia, Federal Republic of | 28 | 64% | |
| Cameroon | 11 | 64% | |
| Lao People's Democratic Republic | 22 | 64% | |
| Nepal | 22 | 64% | |
| Solomon Islands | 11 | 64% | |
| Bolivia | 8 | 62% | |
| Honduras | 16 | 62% | |
| North Macedonia | 8 | 62% | |
| South Sudan | 21 | 62% | |
| Yemen, Republic of | 21 | 62% | |
| Gambia, The | 13 | 62% | |
| Viet Nam | 13 | 62% | |
| Chad | 18 | 61% | |
| India | 58 | 60% | |
| Belize | 5 | 60% | |
| Congo, Republic of | 15 | 60% | |
| Ecuador | 10 | 60% | |
| Paraguay | 5 | 60% | |
| St. Lucia | 5 | 60% | |
| Timor-Leste | 5 | 60% | |
| Mozambique | 37 | 60% | |
| Ghana | 17 | 59% | |
| Senegal | 17 | 59% | |
| Cambodia | 24 | 58% | |
| Maldives | 12 | 58% | |
| Lebanon | 19 | 58% | |
| Liberia | 19 | 58% | |
| Bangladesh | 40 | 58% | |
| Cabo Verde | 7 | 57% | |
| Lesotho | 7 | 57% | |
| Mali | 14 | 57% | |
| Nicaragua | 7 | 57% | |
| Angola | 16 | 56% | |
| Guinea | 16 | 56% | |
| Indonesia | 25 | 56% | |
| Mongolia | 9 | 56% | |
| Madagascar | 20 | 55% | |
| Zambia | 20 | 55% | |
| Comoros | 11 | 54% | |
| Serbia | 11 | 54% | |
| Mauritania | 13 | 54% | |
| Moldova | 13 | 54% | |
| Peru | 15 | 53% | |
| Malawi | 19 | 53% | |
| Ukraine | 19 | 53% | |
| Ethiopia | 25 | 52% | |
| Argentina | 20 | 50% | |
| Costa Rica | 8 | 50% | |
| Egypt, Arab Republic of | 10 | 50% | |
| Fiji | 6 | 50% | |
| Georgia | 10 | 50% | |
| Marshall Islands | 8 | 50% | |
| Mexico | 6 | 50% | |
| Nigeria | 26 | 50% | |
| Tunisia | 14 | 50% | |
| China | 23 | 48% | |
| Uzbekistan | 23 | 48% | |
| Rwanda | 21 | 48% | |
| Burkina Faso | 19 | 47% | |
| Jordan | 13 | 46% | |
| Sri Lanka | 13 | 46% | |
| Togo | 11 | 46% | |
| Colombia | 9 | 44% | |
| Papua New Guinea | 9 | 44% | |
| Benin | 14 | 43% | |
| Guyana | 7 | 43% | |
| Kazakhstan | 5 | 40% | |
| Tuvalu | 5 | 40% | |
| Djibouti | 18 | 39% | |
| Morocco | 13 | 38% | |
| Sao Tome and Principe | 13 | 38% | |
| Panama | 8 | 38% | |
| Congo, Democratic Republic of | 22 | 36% | |
| Cote d'Ivoire | 17 | 35% | |
| Albania | 9 | 33% | |
| Croatia | 6 | 33% | |
| Eswatini | 6 | 33% | |
| Guinea-Bissau | 9 | 33% | |
| St Maarten | 6 | 33% | |
| Kyrgyz Republic | 19 | 26% |
By sector
From 38% in Financial Sector to 77% in Transportation.
| Primary sector | projects | share | |
|---|---|---|---|
| Transportation | 173 | 77% | |
| Water, Sanitation and Waste Management | 128 | 71% | |
| Education | 177 | 66% | |
| Industry, Trade and Services | 83 | 65% | |
| Agriculture, Fishing and Forestry | 220 | 62% | |
| Social Protection | 193 | 62% | |
| Digital Development | 69 | 61% | |
| Public Administration | 268 | 59% | |
| Energy and Extractives | 164 | 51% | |
| Health | 292 | 45% | |
| Financial Sector | 77 | 38% |
By region
A narrow spread, 56% to 66%.
| Region | projects | share | |
|---|---|---|---|
| Latin America and Caribbean | 276 | 66% | |
| Middle East, North Africa, Afghanistan, and Pakistan | 202 | 65% | |
| East Asia and Pacific | 232 | 60% | |
| South Asia | 151 | 60% | |
| Europe and Central Asia | 248 | 59% | |
| Eastern and Southern Africa | 409 | 57% | |
| Western and Central Africa | 341 | 56% |
Geography mostly stops at the district or region
Each data-using project is placed by the most precise geography in any of its documents. 44% go down to a named area such as a region, district or camp. 16% use exact locations: facilities, stations, parcels. Map- and satellite-derived figures are rare.
| Most precise geography in the project | projects | used mentions | share |
|---|---|---|---|
| Exact locations | 297 | 509 | 16% |
| Administrative or named areas | 814 | 2,448 | 44% |
| Map- or satellite-derived figures | 4 | 17 | <1% |
| Data used, place not stated | 270 | 1,946 | 14% |
| Only national or non-spatial figures | 485 | 3,000 | 26% |
Each project is counted once, under its most precise class. “Used mentions” counts mentions with that exact label across all projects; a project can contribute mentions to more than one row.
What each level looks like in a document
“RGA supports these initiatives by providing information on all land parcels and buildings via ISREC and the Building Register.”Serbia — Public Administration project
“First, the poorest communes in the country will be selected making use of existing poverty maps, hazard exposure maps and climate change vulnerability maps.”Burundi — Social Protection project
“Ground mapping and photography would be supplemented by commercial firms recruited competitively to assist with digital mapping using remote sensing data from satellites and aerial photography.”Tanzania — Digital Development project
“The Logistics Performance Index and the Global Competitiveness Index positioned Ethiopia at the bottom 20 percentile.”Horn of Africa — Transportation project
Censuses and sector records carry the geography; big surveys are quoted as national totals
Uses of population censuses (77%), climate and weather data (67%) and infrastructure records (75%) are usually tied to a place.
Enterprise surveys (5%), Demographic and Health Surveys (16%) and poverty assessments (24%) are cited in many projects, but mostly as national figures, even though their data usually holds regional or district detail.
Maps, GIS and satellite data are almost always tied to a place (97%), but appear in fewer than 7 in 100 projects.
Share of uses tied to a place, by kind of data
| Kind of data | projects | tied to a place | |
|---|---|---|---|
| Maps, GIS and cadastre | 105 | 97% | |
| Satellite and remote sensing | 26 | 96% | |
| Health records (HMIS, DHIS2) | 25 | 79% | |
| Population census | 185 | 77% | |
| Education records (EMIS, school census) | 51 | 76% | |
| Refugee and displacement data | 35 | 76% | |
| Infrastructure and asset records | 74 | 75% | |
| Climate, weather and hydrology | 84 | 67% | |
| Agriculture and land | 65 | 67% | |
| Project monitoring and baseline data | 138 | 45% | |
| Household budget and living-standards surveys | 132 | 37% | |
| Social registries and beneficiary data | 55 | 36% | |
| MICS | 28 | 29% | |
| Labour force surveys | 68 | 27% | |
| Poverty and food-security assessments | 145 | 24% | |
| Demographic and Health Surveys | 87 | 16% | |
| Global indices and country statistics | 761 | 14% | |
| Enterprise and firm surveys | 83 | 5% | |
| Administrative and other records | 1,304 | 42% | |
| Other surveys and assessments | 595 | 31% |
Amber: surveys quoted mostly as national totals. Grey: sources too general to classify.
Named sources teams rely on
Size shows how many projects use the source; colour shows how often it is used with a place. Select a name to read the passages.
- mostly with a place (50%+)
- sometimes (25–49%)
- rarely (under 25%)
In half of reviewed World Bank projects (1,115 of 2,261, 49%), teams draw on geospatial data, mostly at the level of regions and districts. How reliable is this?
- 2,261projects reviewed: every project with a PAD or PID in the collection
- 1,870use data in the passages read
- 1,115use geospatial data
Used in every sector and region
By approval year, the share runs from 45% (2026) to 52% (2023). 7 years of recent approvals are too few to show a trend.
Among the 118 countries with at least 5 projects, the share runs from 0% in Seychelles to 100% in Guatemala.
Projects using geospatial data, by approval year
Under each year: the number of projects counted.
* 2026 counts approvals to 19 November.
Share of projects using geospatial data, by country
- under 20%
- 20–39%
- 40–59%
- 60–79%
- 80% or more
- fewer than 5 projects
- none reviewed
Point at or tap a country to see its figures.
Not on the map: 157 regional or multi-country projects; 42 projects in 19 countries with fewer than 5 are grey. Region, country and approval year come from the World Bank Projects API.
All 118 countries with at least 5 projects
| Country | projects | share | |
|---|---|---|---|
| Guatemala | 8 | 100% | |
| St. Vincent and the Grenadines | 5 | 80% | |
| Haiti | 17 | 76% | |
| Pakistan | 46 | 72% | |
| Micronesia, Federated States of | 7 | 71% | |
| Brazil | 75 | 71% | |
| Kenya | 27 | 70% | |
| Kiribati | 10 | 70% | |
| Sierra Leone | 20 | 70% | |
| El Salvador | 15 | 67% | |
| Myanmar | 9 | 67% | |
| Samoa | 6 | 67% | |
| Turkiye | 48 | 67% | |
| West Bank and Gaza | 33 | 67% | |
| Afghanistan | 17 | 65% | |
| Burundi | 17 | 65% | |
| Armenia | 11 | 64% | |
| Solomon Islands | 11 | 64% | |
| Central African Republic | 16 | 62% | |
| North Macedonia | 8 | 62% | |
| Tonga | 8 | 62% | |
| Tajikistan | 26 | 62% | |
| Niger | 18 | 61% | |
| Belize | 5 | 60% | |
| Bosnia and Herzegovina | 15 | 60% | |
| Dominican Republic | 10 | 60% | |
| Jamaica | 5 | 60% | |
| South Sudan | 22 | 59% | |
| Honduras | 17 | 59% | |
| Cameroon | 12 | 58% | |
| Tanzania | 26 | 58% | |
| Gambia, The | 14 | 57% | |
| Iraq | 14 | 57% | |
| Nicaragua | 7 | 57% | |
| South Africa | 7 | 57% | |
| Philippines | 30 | 57% | |
| Uganda | 23 | 56% | |
| Mozambique | 39 | 56% | |
| Congo, Republic of | 16 | 56% | |
| Lao People's Democratic Republic | 25 | 56% | |
| Bolivia | 9 | 56% | |
| Ghana | 18 | 56% | |
| Chad | 20 | 55% | |
| Kosovo | 15 | 53% | |
| Mali | 15 | 53% | |
| Guinea | 17 | 53% | |
| Sudan | 17 | 53% | |
| Yemen, Republic of | 25 | 52% | |
| Nepal | 27 | 52% | |
| Somalia, Federal Republic of | 35 | 51% | |
| Bangladesh | 45 | 51% | |
| Angola | 18 | 50% | |
| Azerbaijan | 6 | 50% | |
| Cambodia | 28 | 50% | |
| Egypt, Arab Republic of | 10 | 50% | |
| India | 70 | 50% | |
| Liberia | 22 | 50% | |
| Maldives | 14 | 50% | |
| Marshall Islands | 8 | 50% | |
| Senegal | 20 | 50% | |
| Madagascar | 23 | 48% | |
| Comoros | 13 | 46% | |
| Serbia | 13 | 46% | |
| Georgia | 11 | 46% | |
| Indonesia | 31 | 45% | |
| Nigeria | 29 | 45% | |
| Colombia | 9 | 44% | |
| Costa Rica | 9 | 44% | |
| Lesotho | 9 | 44% | |
| Peru | 18 | 44% | |
| Lebanon | 25 | 44% | |
| Zambia | 25 | 44% | |
| Burkina Faso | 21 | 43% | |
| Fiji | 7 | 43% | |
| Guyana | 7 | 43% | |
| Mexico | 7 | 43% | |
| Paraguay | 7 | 43% | |
| St. Lucia | 7 | 43% | |
| Timor-Leste | 7 | 43% | |
| Malawi | 24 | 42% | |
| Mongolia | 12 | 42% | |
| Mauritania | 17 | 41% | |
| China | 27 | 41% | |
| Uzbekistan | 27 | 41% | |
| Argentina | 25 | 40% | |
| Benin | 15 | 40% | |
| Cabo Verde | 10 | 40% | |
| Ecuador | 15 | 40% | |
| Montenegro | 5 | 40% | |
| Viet Nam | 20 | 40% | |
| Ethiopia | 33 | 39% | |
| Moldova | 18 | 39% | |
| Togo | 13 | 38% | |
| Ukraine | 26 | 38% | |
| Bhutan | 8 | 38% | |
| Tunisia | 19 | 37% | |
| Rwanda | 28 | 36% | |
| Sao Tome and Principe | 14 | 36% | |
| Croatia | 6 | 33% | |
| Jordan | 18 | 33% | |
| Panama | 9 | 33% | |
| Papua New Guinea | 12 | 33% | |
| Tuvalu | 6 | 33% | |
| Congo, Democratic Republic of | 25 | 32% | |
| Cote d'Ivoire | 19 | 32% | |
| Sri Lanka | 19 | 32% | |
| Djibouti | 23 | 30% | |
| Guinea-Bissau | 10 | 30% | |
| Kazakhstan | 7 | 29% | |
| Morocco | 18 | 28% | |
| Albania | 11 | 27% | |
| St Maarten | 8 | 25% | |
| Eswatini | 9 | 22% | |
| Kyrgyz Republic | 23 | 22% | |
| Botswana | 5 | 20% | |
| Chile | 5 | 20% | |
| Zimbabwe | 5 | 20% | |
| Seychelles | 6 | 0% |
By sector
From 32% in Financial Sector to 67% in Transportation.
| Primary sector | projects | share | |
|---|---|---|---|
| Transportation | 199 | 67% | |
| Water, Sanitation and Waste Management | 142 | 64% | |
| Education | 196 | 60% | |
| Digital Development | 76 | 55% | |
| Industry, Trade and Services | 101 | 54% | |
| Agriculture, Fishing and Forestry | 264 | 52% | |
| Social Protection | 240 | 50% | |
| Public Administration | 361 | 44% | |
| Energy and Extractives | 214 | 39% | |
| Health | 344 | 38% | |
| Financial Sector | 90 | 32% |
By region
A narrow spread, 47% to 55%.
| Region | projects | share | |
|---|---|---|---|
| Latin America and Caribbean | 328 | 55% | |
| Middle East, North Africa, Afghanistan, and Pakistan | 254 | 52% | |
| Europe and Central Asia | 297 | 49% | |
| Western and Central Africa | 388 | 49% | |
| East Asia and Pacific | 283 | 49% | |
| South Asia | 185 | 49% | |
| Eastern and Southern Africa | 495 | 47% |
Geography mostly stops at the district or region
Each reviewed project is placed by the most precise geography in any of its documents. 36% go down to a named area such as a region, district or camp. 13% use exact locations: facilities, stations, parcels. Map- and satellite-derived figures are rare.
| Most precise geography in the project | projects | used mentions | share |
|---|---|---|---|
| Exact locations | 297 | 509 | 13% |
| Administrative or named areas | 814 | 2,448 | 36% |
| Map- or satellite-derived figures | 4 | 17 | <1% |
| Data used, place not stated | 270 | 1,946 | 12% |
| Only national or non-spatial figures | 485 | 3,000 | 22% |
| No data judged used | 391 | 0 | 17% |
Each project is counted once, under its most precise class. “Used mentions” counts mentions with that exact label across all projects; a project can contribute mentions to more than one row.
What each level looks like in a document
“RGA supports these initiatives by providing information on all land parcels and buildings via ISREC and the Building Register.”Serbia — Public Administration project
“First, the poorest communes in the country will be selected making use of existing poverty maps, hazard exposure maps and climate change vulnerability maps.”Burundi — Social Protection project
“Ground mapping and photography would be supplemented by commercial firms recruited competitively to assist with digital mapping using remote sensing data from satellites and aerial photography.”Tanzania — Digital Development project
“The Logistics Performance Index and the Global Competitiveness Index positioned Ethiopia at the bottom 20 percentile.”Horn of Africa — Transportation project
Censuses and sector records carry the geography; big surveys are quoted as national totals
Uses of population censuses (77%), climate and weather data (67%) and infrastructure records (75%) are usually tied to a place.
Enterprise surveys (5%), Demographic and Health Surveys (16%) and poverty assessments (24%) are cited in many projects, but mostly as national figures, even though their data usually holds regional or district detail.
Maps, GIS and satellite data are almost always tied to a place (97%), but appear in fewer than 6 in 100 projects.
Share of uses tied to a place, by kind of data
| Kind of data | projects | tied to a place | |
|---|---|---|---|
| Maps, GIS and cadastre | 105 | 97% | |
| Satellite and remote sensing | 26 | 96% | |
| Health records (HMIS, DHIS2) | 25 | 79% | |
| Population census | 185 | 77% | |
| Education records (EMIS, school census) | 51 | 76% | |
| Refugee and displacement data | 35 | 76% | |
| Infrastructure and asset records | 74 | 75% | |
| Climate, weather and hydrology | 84 | 67% | |
| Agriculture and land | 65 | 67% | |
| Project monitoring and baseline data | 138 | 45% | |
| Household budget and living-standards surveys | 132 | 37% | |
| Social registries and beneficiary data | 55 | 36% | |
| MICS | 28 | 29% | |
| Labour force surveys | 68 | 27% | |
| Poverty and food-security assessments | 145 | 24% | |
| Demographic and Health Surveys | 87 | 16% | |
| Global indices and country statistics | 761 | 14% | |
| Enterprise and firm surveys | 83 | 5% | |
| Administrative and other records | 1,304 | 42% | |
| Other surveys and assessments | 595 | 31% |
Amber: surveys quoted mostly as national totals. Grey: sources too general to classify.
Named sources teams rely on
Size shows how many projects use the source; colour shows how often it is used with a place. Select a name to read the passages.
- mostly with a place (50%+)
- sometimes (25–49%)
- rarely (under 25%)
In half of PADs and PIDs that use data (1,490 of 2,994, 50%), teams draw on geospatial data, mostly at the level of regions and districts. How reliable is this?
- 3,791PADs and PIDs reviewed, of 4,679 in the collection
- 2,994use data in the passages read
- 1,490use geospatial data
Used in every sector and region
By approval year, the share runs from 45% (2020) to 56% (2026). 7 years of recent approvals are too few to show a trend.
Among the 120 countries with at least 5 documents, the share runs from 17% in Croatia to 84% in Brazil.
Documents using geospatial data, by approval year
Under each year: the number of documents counted.
* 2026 counts approvals to 22 September.
Share of documents using geospatial data, by country
- under 20%
- 20–39%
- 40–59%
- 60–79%
- 80% or more
- fewer than 5 documents
- none reviewed
Point at or tap a country to see its figures.
Not on the map: 181 regional or multi-country documents; 32 documents in 13 countries with fewer than 5 are grey. Region, country and approval year come from the World Bank Projects API.
All 120 countries with at least 5 documents
| Country | documents | share | |
|---|---|---|---|
| Brazil | 84 | 84% | |
| Samoa | 6 | 83% | |
| Bhutan | 5 | 80% | |
| Pakistan | 63 | 76% | |
| Azerbaijan | 7 | 71% | |
| Micronesia, Federated States of | 10 | 70% | |
| Sudan | 16 | 69% | |
| Bosnia and Herzegovina | 18 | 67% | |
| Guatemala | 12 | 67% | |
| Myanmar | 9 | 67% | |
| Sierra Leone | 33 | 67% | |
| Vanuatu | 6 | 67% | |
| Kosovo | 20 | 65% | |
| West Bank and Gaza | 41 | 63% | |
| Gambia, The | 21 | 62% | |
| Afghanistan | 26 | 62% | |
| Iraq | 18 | 61% | |
| Solomon Islands | 20 | 60% | |
| South Africa | 10 | 60% | |
| Kenya | 37 | 60% | |
| Turkiye | 64 | 59% | |
| Niger | 27 | 59% | |
| Bolivia | 12 | 58% | |
| South Sudan | 31 | 58% | |
| Viet Nam | 19 | 58% | |
| India | 89 | 57% | |
| Guyana | 14 | 57% | |
| Timor-Leste | 7 | 57% | |
| El Salvador | 23 | 56% | |
| Nepal | 32 | 56% | |
| Tajikistan | 41 | 56% | |
| Cameroon | 18 | 56% | |
| Romania | 9 | 56% | |
| Serbia | 18 | 56% | |
| Haiti | 29 | 55% | |
| Mali | 20 | 55% | |
| Philippines | 42 | 55% | |
| Colombia | 11 | 54% | |
| Guinea | 24 | 54% | |
| Indonesia | 37 | 54% | |
| Dominican Republic | 13 | 54% | |
| Chad | 28 | 54% | |
| Tanzania | 43 | 54% | |
| Armenia | 15 | 53% | |
| Lebanon | 30 | 53% | |
| Sri Lanka | 15 | 53% | |
| Somalia, Federal Republic of | 38 | 53% | |
| Angola | 23 | 52% | |
| Honduras | 27 | 52% | |
| Malawi | 27 | 52% | |
| Congo, Republic of | 22 | 50% | |
| Georgia | 18 | 50% | |
| Madagascar | 34 | 50% | |
| North Macedonia | 14 | 50% | |
| Peru | 26 | 50% | |
| St. Vincent and the Grenadines | 8 | 50% | |
| Yemen, Republic of | 30 | 50% | |
| Burundi | 29 | 48% | |
| Tunisia | 17 | 47% | |
| Uganda | 34 | 47% | |
| Mozambique | 62 | 47% | |
| Egypt, Arab Republic of | 15 | 47% | |
| Lesotho | 15 | 47% | |
| Ghana | 26 | 46% | |
| Nicaragua | 13 | 46% | |
| Ukraine | 26 | 46% | |
| Eswatini | 11 | 46% | |
| Marshall Islands | 11 | 46% | |
| Senegal | 33 | 46% | |
| Cambodia | 40 | 45% | |
| Lao People's Democratic Republic | 38 | 45% | |
| Argentina | 36 | 44% | |
| Belize | 9 | 44% | |
| Maldives | 18 | 44% | |
| Nigeria | 36 | 44% | |
| Bangladesh | 73 | 44% | |
| Central African Republic | 32 | 44% | |
| Ecuador | 16 | 44% | |
| Liberia | 30 | 43% | |
| Ethiopia | 37 | 43% | |
| Botswana | 7 | 43% | |
| Fiji | 7 | 43% | |
| Mongolia | 14 | 43% | |
| Papua New Guinea | 14 | 43% | |
| Uruguay | 7 | 43% | |
| Zambia | 28 | 43% | |
| Kiribati | 19 | 42% | |
| Tonga | 12 | 42% | |
| Rwanda | 29 | 41% | |
| Cote d'Ivoire | 27 | 41% | |
| China | 32 | 41% | |
| Albania | 15 | 40% | |
| Comoros | 20 | 40% | |
| Grenada | 5 | 40% | |
| Montenegro | 5 | 40% | |
| St. Lucia | 10 | 40% | |
| Tuvalu | 10 | 40% | |
| Cabo Verde | 13 | 38% | |
| Benin | 21 | 38% | |
| Moldova | 21 | 38% | |
| Kazakhstan | 8 | 38% | |
| Burkina Faso | 35 | 37% | |
| Uzbekistan | 39 | 36% | |
| Jordan | 17 | 35% | |
| Morocco | 17 | 35% | |
| Mauritania | 20 | 35% | |
| Congo, Democratic Republic of | 36 | 33% | |
| Mexico | 9 | 33% | |
| Togo | 15 | 33% | |
| Costa Rica | 13 | 31% | |
| Kyrgyz Republic | 30 | 30% | |
| Panama | 10 | 30% | |
| Djibouti | 34 | 29% | |
| Guinea-Bissau | 17 | 29% | |
| St Maarten | 7 | 29% | |
| Paraguay | 11 | 27% | |
| Gabon | 8 | 25% | |
| Sao Tome and Principe | 25 | 24% | |
| Chile | 5 | 20% | |
| Croatia | 12 | 17% |
By sector
From 29% in Financial Sector to 66% in Water, Sanitation and Waste Management.
| Primary sector | documents | share | |
|---|---|---|---|
| Water, Sanitation and Waste Management | 210 | 66% | |
| Transportation | 300 | 63% | |
| Agriculture, Fishing and Forestry | 331 | 54% | |
| Social Protection | 304 | 54% | |
| Education | 315 | 52% | |
| Public Administration | 418 | 51% | |
| Industry, Trade and Services | 132 | 50% | |
| Digital Development | 138 | 42% | |
| Health | 446 | 38% | |
| Energy and Extractives | 249 | 38% | |
| Financial Sector | 122 | 29% |
By region
A narrow spread, 46% to 55%.
| Region | documents | share | |
|---|---|---|---|
| Middle East, North Africa, Afghanistan, and Pakistan | 313 | 55% | |
| Latin America and Caribbean | 446 | 54% | |
| South Asia | 236 | 53% | |
| East Asia and Pacific | 369 | 50% | |
| Europe and Central Asia | 401 | 49% | |
| Eastern and Southern Africa | 655 | 47% | |
| Western and Central Africa | 558 | 46% |
Geography mostly stops at the district or region
Each data-using document is placed by the most precise geography it shows. 39% go down to a named area such as a region, district or camp. 11% use exact locations: facilities, stations, parcels. Map- and satellite-derived figures are rare.
| Most precise geography in the document | documents | used mentions | share |
|---|---|---|---|
| Exact locations | 329 | 508 | 11% |
| Administrative or named areas | 1,157 | 2,463 | 39% |
| Map- or satellite-derived figures | 4 | 17 | <1% |
| Data used, place not stated | 505 | 1,957 | 17% |
| Only national or non-spatial figures | 999 | 3,017 | 33% |
Each document is counted once, under its most precise class. “Used mentions” counts mentions with that exact label across all documents; a document can contribute mentions to more than one row.
What each level looks like in a document
“RGA supports these initiatives by providing information on all land parcels and buildings via ISREC and the Building Register.”Serbia — Public Administration project
“First, the poorest communes in the country will be selected making use of existing poverty maps, hazard exposure maps and climate change vulnerability maps.”Burundi — Social Protection project
“Ground mapping and photography would be supplemented by commercial firms recruited competitively to assist with digital mapping using remote sensing data from satellites and aerial photography.”Tanzania — Digital Development project
“The Logistics Performance Index and the Global Competitiveness Index positioned Ethiopia at the bottom 20 percentile.”Horn of Africa — Transportation project
Censuses and sector records carry the geography; big surveys are quoted as national totals
Uses of population censuses (77%), climate and weather data (67%) and infrastructure records (75%) are usually tied to a place.
Enterprise surveys (5%), Demographic and Health Surveys (16%) and poverty assessments (24%) are cited in many documents, but mostly as national figures, even though their data usually holds regional or district detail.
Maps, GIS and satellite data are almost always tied to a place (97%), but appear in fewer than 5 in 100 documents.
Share of uses tied to a place, by kind of data
| Kind of data | documents | tied to a place | |
|---|---|---|---|
| Maps, GIS and cadastre | 112 | 97% | |
| Satellite and remote sensing | 27 | 96% | |
| Health records (HMIS, DHIS2) | 26 | 78% | |
| Population census | 227 | 77% | |
| Refugee and displacement data | 42 | 76% | |
| Education records (EMIS, school census) | 56 | 75% | |
| Infrastructure and asset records | 78 | 75% | |
| Agriculture and land | 72 | 67% | |
| Climate, weather and hydrology | 91 | 67% | |
| Project monitoring and baseline data | 146 | 44% | |
| Household budget and living-standards surveys | 162 | 37% | |
| Social registries and beneficiary data | 61 | 36% | |
| MICS | 31 | 29% | |
| Labour force surveys | 82 | 27% | |
| Poverty and food-security assessments | 169 | 24% | |
| Demographic and Health Surveys | 103 | 16% | |
| Global indices and country statistics | 1,026 | 14% | |
| Enterprise and firm surveys | 108 | 5% | |
| Administrative and other records | 1,770 | 42% | |
| Other surveys and assessments | 750 | 32% |
Amber: surveys quoted mostly as national totals. Grey: sources too general to classify.
Named sources teams rely on
Size shows how many documents use the source; colour shows how often it is used with a place. Select a name to read the passages.
- mostly with a place (50%+)
- sometimes (25–49%)
- rarely (under 25%)
In 4 in 10 reviewed PADs and PIDs (1,490 of 3,791, 39%), teams draw on geospatial data, mostly at the level of regions and districts. How reliable is this?
- 3,791PADs and PIDs reviewed, of 4,679 in the collection
- 2,994use data in the passages read
- 1,490use geospatial data
Used in every sector and region
By approval year, the share runs from 36% (2020) to 44% (2024). 7 years of recent approvals are too few to show a trend.
Among the 125 countries with at least 5 documents, the share runs from 0% in Seychelles to 67% in Vanuatu.
Documents using geospatial data, by approval year
Under each year: the number of documents counted.
* 2026 counts approvals to 19 November.
Share of documents using geospatial data, by country
- under 20%
- 20–39%
- 40–59%
- 60–79%
- 80% or more
- fewer than 5 documents
- none reviewed
Point at or tap a country to see its figures.
Not on the map: 250 regional or multi-country documents; 22 documents in 12 countries with fewer than 5 are grey. Region, country and approval year come from the World Bank Projects API.
All 125 countries with at least 5 documents
| Country | documents | share | |
|---|---|---|---|
| Vanuatu | 6 | 67% | |
| Brazil | 114 | 62% | |
| Pakistan | 79 | 61% | |
| Myanmar | 10 | 60% | |
| Guatemala | 14 | 57% | |
| Sierra Leone | 39 | 56% | |
| Azerbaijan | 9 | 56% | |
| Romania | 9 | 56% | |
| Colombia | 11 | 54% | |
| Solomon Islands | 22 | 54% | |
| Gambia, The | 24 | 54% | |
| Micronesia, Federated States of | 13 | 54% | |
| Kenya | 41 | 54% | |
| Kosovo | 25 | 52% | |
| Armenia | 16 | 50% | |
| Bosnia and Herzegovina | 24 | 50% | |
| Cameroon | 20 | 50% | |
| Guyana | 16 | 50% | |
| Haiti | 32 | 50% | |
| Jamaica | 6 | 50% | |
| Mali | 22 | 50% | |
| South Africa | 12 | 50% | |
| St. Vincent and the Grenadines | 8 | 50% | |
| West Bank and Gaza | 54 | 48% | |
| Philippines | 48 | 48% | |
| Iraq | 23 | 48% | |
| South Sudan | 38 | 47% | |
| Niger | 34 | 47% | |
| Tanzania | 49 | 47% | |
| Turkiye | 81 | 47% | |
| Bolivia | 15 | 47% | |
| El Salvador | 28 | 46% | |
| Guinea | 28 | 46% | |
| Nicaragua | 13 | 46% | |
| Sudan | 24 | 46% | |
| India | 112 | 46% | |
| Samoa | 11 | 46% | |
| Serbia | 22 | 46% | |
| Afghanistan | 36 | 44% | |
| Bhutan | 9 | 44% | |
| Tajikistan | 52 | 44% | |
| Nepal | 41 | 44% | |
| Honduras | 32 | 44% | |
| Indonesia | 46 | 44% | |
| Chad | 35 | 43% | |
| Georgia | 21 | 43% | |
| Congo, Republic of | 26 | 42% | |
| Ghana | 29 | 41% | |
| Burundi | 34 | 41% | |
| Dominican Republic | 17 | 41% | |
| Uganda | 39 | 41% | |
| Peru | 32 | 41% | |
| Madagascar | 42 | 40% | |
| Mozambique | 72 | 40% | |
| Belize | 10 | 40% | |
| Grenada | 5 | 40% | |
| Malawi | 35 | 40% | |
| Somalia, Federal Republic of | 50 | 40% | |
| Syrian Arab Republic | 5 | 40% | |
| Lebanon | 41 | 39% | |
| Lesotho | 18 | 39% | |
| Bangladesh | 83 | 39% | |
| Kiribati | 21 | 38% | |
| Viet Nam | 29 | 38% | |
| Central African Republic | 37 | 38% | |
| Fiji | 8 | 38% | |
| Senegal | 40 | 38% | |
| Uruguay | 8 | 38% | |
| Nigeria | 43 | 37% | |
| Lao People's Democratic Republic | 46 | 37% | |
| Egypt, Arab Republic of | 19 | 37% | |
| North Macedonia | 19 | 37% | |
| Cambodia | 49 | 37% | |
| Angola | 33 | 36% | |
| Comoros | 22 | 36% | |
| Timor-Leste | 11 | 36% | |
| Benin | 23 | 35% | |
| Sri Lanka | 23 | 35% | |
| Zambia | 35 | 34% | |
| Burkina Faso | 38 | 34% | |
| Liberia | 38 | 34% | |
| Yemen, Republic of | 44 | 34% | |
| Albania | 18 | 33% | |
| Cote d'Ivoire | 33 | 33% | |
| Eswatini | 15 | 33% | |
| Marshall Islands | 15 | 33% | |
| Mongolia | 18 | 33% | |
| Tonga | 15 | 33% | |
| Ethiopia | 49 | 33% | |
| Rwanda | 37 | 32% | |
| Argentina | 50 | 32% | |
| Maldives | 25 | 32% | |
| Ecuador | 22 | 32% | |
| Papua New Guinea | 19 | 32% | |
| Ukraine | 38 | 32% | |
| China | 42 | 31% | |
| Tuvalu | 13 | 31% | |
| Uzbekistan | 46 | 30% | |
| Botswana | 10 | 30% | |
| Kazakhstan | 10 | 30% | |
| Moldova | 27 | 30% | |
| Tunisia | 27 | 30% | |
| Dominica | 7 | 29% | |
| Montenegro | 7 | 29% | |
| St. Lucia | 14 | 29% | |
| Togo | 18 | 28% | |
| Congo, Democratic Republic of | 47 | 26% | |
| Cabo Verde | 20 | 25% | |
| Costa Rica | 16 | 25% | |
| Gabon | 8 | 25% | |
| Mauritania | 29 | 24% | |
| Morocco | 25 | 24% | |
| Guinea-Bissau | 21 | 24% | |
| Mexico | 13 | 23% | |
| Panama | 13 | 23% | |
| Kyrgyz Republic | 40 | 22% | |
| Jordan | 27 | 22% | |
| Sao Tome and Principe | 27 | 22% | |
| Paraguay | 14 | 21% | |
| Djibouti | 48 | 21% | |
| Zimbabwe | 6 | 17% | |
| St Maarten | 13 | 15% | |
| Croatia | 14 | 14% | |
| Chile | 8 | 12% | |
| Seychelles | 7 | 0% |
By sector
From 24% in Financial Sector to 52% in Water, Sanitation and Waste Management.
| Primary sector | documents | share | |
|---|---|---|---|
| Water, Sanitation and Waste Management | 265 | 52% | |
| Transportation | 360 | 52% | |
| Education | 354 | 46% | |
| Agriculture, Fishing and Forestry | 424 | 42% | |
| Social Protection | 412 | 40% | |
| Industry, Trade and Services | 171 | 39% | |
| Public Administration | 576 | 37% | |
| Digital Development | 160 | 36% | |
| Health | 558 | 30% | |
| Energy and Extractives | 322 | 29% | |
| Financial Sector | 148 | 24% |
By region
A narrow spread, 38% to 42%.
| Region | documents | share | |
|---|---|---|---|
| Latin America and Caribbean | 566 | 42% | |
| South Asia | 298 | 42% | |
| East Asia and Pacific | 466 | 40% | |
| Middle East, North Africa, Afghanistan, and Pakistan | 433 | 40% | |
| Europe and Central Asia | 504 | 39% | |
| Western and Central Africa | 671 | 39% | |
| Eastern and Southern Africa | 816 | 38% |
Geography mostly stops at the district or region
Each reviewed document is placed by the most precise geography it shows. 30% go down to a named area such as a region, district or camp. 9% use exact locations: facilities, stations, parcels. Map- and satellite-derived figures are rare.
| Most precise geography in the document | documents | used mentions | share |
|---|---|---|---|
| Exact locations | 329 | 508 | 9% |
| Administrative or named areas | 1,157 | 2,463 | 30% |
| Map- or satellite-derived figures | 4 | 17 | <1% |
| Data used, place not stated | 505 | 1,957 | 13% |
| Only national or non-spatial figures | 999 | 3,017 | 26% |
| No data judged used | 797 | 0 | 21% |
Each document is counted once, under its most precise class. “Used mentions” counts mentions with that exact label across all documents; a document can contribute mentions to more than one row.
What each level looks like in a document
“RGA supports these initiatives by providing information on all land parcels and buildings via ISREC and the Building Register.”Serbia — Public Administration project
“First, the poorest communes in the country will be selected making use of existing poverty maps, hazard exposure maps and climate change vulnerability maps.”Burundi — Social Protection project
“Ground mapping and photography would be supplemented by commercial firms recruited competitively to assist with digital mapping using remote sensing data from satellites and aerial photography.”Tanzania — Digital Development project
“The Logistics Performance Index and the Global Competitiveness Index positioned Ethiopia at the bottom 20 percentile.”Horn of Africa — Transportation project
Censuses and sector records carry the geography; big surveys are quoted as national totals
Uses of population censuses (77%), climate and weather data (67%) and infrastructure records (75%) are usually tied to a place.
Enterprise surveys (5%), Demographic and Health Surveys (16%) and poverty assessments (24%) are cited in many documents, but mostly as national figures, even though their data usually holds regional or district detail.
Maps, GIS and satellite data are almost always tied to a place (97%), but appear in fewer than 4 in 100 documents.
Share of uses tied to a place, by kind of data
| Kind of data | documents | tied to a place | |
|---|---|---|---|
| Maps, GIS and cadastre | 112 | 97% | |
| Satellite and remote sensing | 27 | 96% | |
| Health records (HMIS, DHIS2) | 26 | 78% | |
| Population census | 227 | 77% | |
| Refugee and displacement data | 42 | 76% | |
| Education records (EMIS, school census) | 56 | 75% | |
| Infrastructure and asset records | 78 | 75% | |
| Agriculture and land | 72 | 67% | |
| Climate, weather and hydrology | 91 | 67% | |
| Project monitoring and baseline data | 146 | 44% | |
| Household budget and living-standards surveys | 162 | 37% | |
| Social registries and beneficiary data | 61 | 36% | |
| MICS | 31 | 29% | |
| Labour force surveys | 82 | 27% | |
| Poverty and food-security assessments | 169 | 24% | |
| Demographic and Health Surveys | 103 | 16% | |
| Global indices and country statistics | 1,026 | 14% | |
| Enterprise and firm surveys | 108 | 5% | |
| Administrative and other records | 1,770 | 42% | |
| Other surveys and assessments | 750 | 32% |
Amber: surveys quoted mostly as national totals. Grey: sources too general to classify.
Named sources teams rely on
Size shows how many documents use the source; colour shows how often it is used with a place. Select a name to read the passages.
- mostly with a place (50%+)
- sometimes (25–49%)
- rarely (under 25%)
How this was measured
Out of which projects?
Those that use data (the default) counts projects with at least one data mention judged used. All projects adds the 391 projects that mention data only as plans, bare figures or sources not relied on. Every one of the 2,261 projects in the collection has at least one reviewed passage, so this is every project, not a sample of them.
Projects or documents?
A project usually has more than one PAD or PID. Projects count a project once: it uses geospatial data if any of its reviewed documents does. Documents count each PAD or PID on its own. The project view is the reporting unit, because region, sector and approval year belong to the project. The project share is higher because a project has more text in which geospatial data can appear. The same document sometimes arrives from two collections under two ids; it is counted once, by its World Bank document id, and a passage read twice counts once. 4,708 confirmed document ids are 4,679 distinct documents.
What counts as geospatial data?
Data the document ties to a place: an exact location (a school, a gauge, a village), a named area (a region, district, camp or an urban/rural split; admin level 1 or 2 is enough), or a figure derived from maps or satellite imagery. Coordinates are not required. A topic such as agriculture or displacement does not count on its own.
What counts as using data?
Each data mention was judged for use: does the passage rely on existing data, or only name it, plan to collect it, or cite a bare figure? Only mentions judged as used count.
Why not count datasets?
The same dataset is named many ways (“DHS”, “2016 UDHS”, “Demographic and Health Survey”), so counts of distinct datasets are unreliable. Whether a project or document uses geospatial data is a clear yes or no. Source names are merged across spellings for display only.
How reliable are these figures?
Every number is counted from the records; none is typed in. The figures rest on AI-extracted data-use mentions from a sample of passages: an AI model found each data mention, judged whether the data was used, and labelled its geography against a written rubric, quoting the passage words behind each place label.
Every share is a floor. Each project was judged from a few sampled passages, not its full documents. A passage is an excerpt of a PAD or PID, about a page long, taken where the text mentions data; it is not a data mention, and one passage can hold several. 650 of the 1,870 data-using projects have only one passage read. The more we read, the more we find: of the data-using projects with one passage read, 41% use geospatial data; with five or more, 88% do. Projects with two or more documents reviewed reach 69%, against 50% with one document. Larger, data-heavy projects also had more passages read, so part of the rise reflects the projects themselves. Read in full, more projects would likely count.
Data-using projects with geospatial data, by passages read
650 projects
396 projects
302 projects
209 projects
313 projects
PADs show more than PIDs. Where a PAD was reviewed, 70% of data-using projects use geospatial data (797 of 1,140); counting PADs alone, 63% of data-using documents do (670 of 1,066). A PAD is the full appraisal; PIDs are short and often written at concept stage.
Stricter checks. Under stricter rules the share falls. For projects that use data it is 59% without uncertain labels and 50% when the quoted evidence must also match word for word; for documents, 50% without uncertain labels and 40% when the quoted evidence must also match word for word. The word-for-word rule is harsh, because quotes taken from tables often reorder the cells. A defensible statement is between 50% and 60% of projects.
Coverage and limits
2,261 of 2,261 projects had passages reviewed, through 3,791 of their 4,679 distinct PADs and PIDs. 1,870 of the 1,870 data-using projects were approved in 2020 or later, so this describes recent practice and does not show a trend. Sector and region come from the World Bank Projects API; sectors and regions with fewer than 40 projects or documents are not shown. Kinds of data are grouped from source names; their "tied to a place" share counts individual uses. Review sets used: PAD/PID review — original sample (5,228 passages); PAD/PID review — 500-passage addition (500 passages). A PAD/PID counts only when the World Bank documents catalogue confirms it: the document exists, has the stated type and belongs to the stated project. The same document arriving from two collections is counted once, by its World Bank document id.