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Visibility: Public
Owner: Nissim Lebovits
Created: 17 Aug 2026
Last Updated: 17 Aug 2026

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25 Aug 2026

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Moldova Geodata

RO. Catalog cloud-native cu date selectate din geoportalul național geodata.gov.md. Româna este limba de referință. Textele în rusă și engleză sunt traduceri. Catalogul nu este o publicație oficială a AGCC.

RU. Облачный каталог избранных данных национального геопортала geodata.gov.md. Румынский текст является основным; русский и английский тексты — переводы. Каталог не является официальной публикацией AGCC.

EN. A cloud-native catalog of selected data from Moldova’s national geoportal, geodata.gov.md. Romanian is authoritative; Russian and English are translations. This is not an official AGCC publication.

Name: AGENTS.md
Size: 4.68 KB
Content Type: text/markdown; charset=utf-8
Last Modified: 17 Aug 2026
Source URL: https://data.source.coop/nlebovits/moldova-geodata/cadastru/cladiri/AGENTS.md
Cloud URI: s3://us-west-2.opendata.source.coop/nlebovits/moldova-geodata/cadastru/cladiri/AGENTS.md

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AGENTS.md — Cladiri (constructii)

Despre date / О данных / About the data

RO. Cladiri (constructii). Conține 1 838 203 poligoane extrase din spațiul de lucru cadastru_data al serverului geodata.gov.md prin WFS 2.0.0 la data de 2026-08-16. Coordonatele sunt păstrate în sistemul sursă MOLDREF99 / Moldova TM (EPSG:4026).

RU. Здания (сооружения). Содержит 1 838 203 полигонов, извлечённых из рабочего пространства cadastru_data сервера geodata.gov.md через WFS 2.0.0 от 2026-08-16. Координаты сохранены в исходной системе MOLDREF99 / Moldova TM (EPSG:4026).

EN. Buildings (structures). Holds 1 838 203 polygons extracted from the cadastru_data workspace of geodata.gov.md over WFS 2.0.0 on 2026-08-16. Coordinates are kept in the source system, MOLDREF99 / Moldova TM (EPSG:4026).

Overview

Extracted from cadastru_data:cladiri over WFS 2.0.0 on 2026-08-16.

Coordinates are MOLDREF99 / Moldova TM (EPSG:4026): projected, metric, unreprojected. ST_Area returns square metres directly. A predicate against a WGS84 envelope returns no matches without an error.

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Schema

Column	Type	Notes
`codcadastral`	VARCHAR	Cadastral code of the parcel the building sits on. 1,828,765 distinct across 1,838,203 rows and null on 4,214, so neither unique nor complete
`nr_constructiei`	VARCHAR	Building number within its parcel. 100 distinct values, null on the same 4,214 rows
`aria`	VARCHAR	Area as text with units, e.g. `19461 m2`. Not a number, and note the unit differs from the parcel layer, which uses hectares
`geometry`	GEOMETRY(EPSG:4026)	Building footprint polygons in metres
`bbox`	STRUCT	Bounding box written by the extractor for spatial pruning

There is no stable per-building identifier. codcadastral plus nr_constructiei together come closest to one, and 4,214 rows have neither.

Data quality

Footprints span an implausible range. The median is 61 m², which is a reasonable house, but the maximum is 2,385,222 m² — a single building of 2.4 km². 4,998 buildings exceed 10,000 m². Some are genuine industrial or agricultural structures and some are certainly errors; the source does not distinguish them and neither does this catalog. Filter before any statistic.
aria is text. 19461 m2 will not sum or compare. Use ST_Area(geometry).
Units are inconsistent across the cadastre. Buildings are labelled in m², parcels in ha, administrative units in ha. A pipeline that parses aria generically across collections will produce numbers wrong by four orders of magnitude.
4,214 buildings carry no cadastral code at all, so they cannot be tied to a parcel by attribute. They still carry geometry.

Example queries

Footprint distribution, excluding the extreme tail:

Buildings per raion, joined spatially in the native CRS:

cadastru_data_terenuri holds the 5,206,686 parcels these buildings sit on. Both carry codcadastral, which is tempting as a join key and is not one: it repeats in both collections and is null on some rows in each. Joining spatially and treating the result as an inference is more honest than joining on a code the source never documents as a key.

cadastru_data_adresa_point holds 855,851 addresses, roughly one for every two buildings.

The catalog's AGENTS.md covers what applies everywhere here.

AGENTS.md — Cladiri (constructii)

Despre date / О данных / About the data

Overview

Extracted from cadastru_data:cladiri over WFS 2.0.0 on 2026-08-16.

Access

Schema

Column	Type	Notes
`codcadastral`	VARCHAR	Cadastral code of the parcel the building sits on. 1,828,765 distinct across 1,838,203 rows and null on 4,214, so neither unique nor complete
`nr_constructiei`	VARCHAR	Building number within its parcel. 100 distinct values, null on the same 4,214 rows
`aria`	VARCHAR	Area as text with units, e.g. `19461 m2`. Not a number, and note the unit differs from the parcel layer, which uses hectares
`geometry`	GEOMETRY(EPSG:4026)	Building footprint polygons in metres
`bbox`	STRUCT	Bounding box written by the extractor for spatial pruning

There is no stable per-building identifier. codcadastral plus nr_constructiei together come closest to one, and 4,214 rows have neither.

Data quality

Footprints span an implausible range. The median is 61 m², which is a reasonable house, but the maximum is 2,385,222 m² — a single building of 2.4 km². 4,998 buildings exceed 10,000 m². Some are genuine industrial or agricultural structures and some are certainly errors; the source does not distinguish them and neither does this catalog. Filter before any statistic.
aria is text. 19461 m2 will not sum or compare. Use ST_Area(geometry).
Units are inconsistent across the cadastre. Buildings are labelled in m², parcels in ha, administrative units in ha. A pipeline that parses aria generically across collections will produce numbers wrong by four orders of magnitude.
4,214 buildings carry no cadastral code at all, so they cannot be tied to a parcel by attribute. They still carry geometry.

Example queries

Footprint distribution, excluding the extreme tail:

Buildings per raion, joined spatially in the native CRS:

cadastru_data_adresa_point holds 855,851 addresses, roughly one for every two buildings.

The catalog's AGENTS.md covers what applies everywhere here.

1INSTALL spatial; LOAD spatial; INSTALL httpfs; LOAD httpfs;
2
3SELECT codcadastral, aria, ST_Area(geometry) AS footprint_m2
4FROM read_parquet(
5  'https://data.source.coop/nlebovits/moldova-geodata/'
6  || 'cadastru/cladiri/cadastru_data_cladiri.parquet')
7LIMIT 10;

1INSTALL spatial; LOAD spatial; INSTALL httpfs; LOAD httpfs;
2
3SELECT codcadastral, aria, ST_Area(geometry) AS footprint_m2
4FROM read_parquet(
5  'https://data.source.coop/nlebovits/moldova-geodata/'
6  || 'cadastru/cladiri/cadastru_data_cladiri.parquet')
7LIMIT 10;

1INSTALL spatial; LOAD spatial;
2
3SELECT round(median(ST_Area(geometry))) AS median_m2,
4       count(*) AS buildings
5FROM read_parquet('cadastru/cladiri/cadastru_data_cladiri.parquet')
6WHERE ST_Area(geometry) BETWEEN 1 AND 10000;

1INSTALL spatial; LOAD spatial;
2
3SELECT round(median(ST_Area(geometry))) AS median_m2,
4       count(*) AS buildings
5FROM read_parquet('cadastru/cladiri/cadastru_data_cladiri.parquet')
6WHERE ST_Area(geometry) BETWEEN 1 AND 10000;

1INSTALL spatial; LOAD spatial;
2
3SELECT u.name, count(*) AS buildings
4FROM read_parquet('cadastru/cladiri/cadastru_data_cladiri.parquet') b
5JOIN read_parquet('cadastru/uat2/cadastru_data_uat2.parquet') u
6  ON ST_Within(ST_Centroid(b.geometry), u.geometry)
7GROUP BY u.name
8ORDER BY buildings DESC;

1INSTALL spatial; LOAD spatial;
2
3SELECT u.name, count(*) AS buildings
4FROM read_parquet('cadastru/cladiri/cadastru_data_cladiri.parquet') b
5JOIN read_parquet('cadastru/uat2/cadastru_data_uat2.parquet') u
6  ON ST_Within(ST_Centroid(b.geometry), u.geometry)
7GROUP BY u.name
8ORDER BY buildings DESC;

1-- Buildings to their parcel, spatially rather than by code
2INSTALL spatial; LOAD spatial;
3
4SELECT b.codcadastral AS building_code,
5       p.id AS parcel_id,
6       p.landuse
7FROM read_parquet('cadastru/cladiri/cadastru_data_cladiri.parquet') b
8JOIN read_parquet('cadastru/terenuri/cadastru_data_terenuri.parquet') p
9  ON ST_Within(ST_Centroid(b.geometry), p.geometry)
10LIMIT 100;

1-- Buildings to their parcel, spatially rather than by code
2INSTALL spatial; LOAD spatial;
3
4SELECT b.codcadastral AS building_code,
5       p.id AS parcel_id,
6       p.landuse
7FROM read_parquet('cadastru/cladiri/cadastru_data_cladiri.parquet') b
8JOIN read_parquet('cadastru/terenuri/cadastru_data_terenuri.parquet') p
9  ON ST_Within(ST_Centroid(b.geometry), p.geometry)
10LIMIT 100;

Moldova Geodata

AGENTS.md — Cladiri (constructii)

Despre date / О данных / About the data

Overview

Access

Schema

Data quality

Example queries

Related collections

AGENTS.md — Cladiri (constructii)

Despre date / О данных / About the data

Overview

Access

Schema

Data quality

Example queries

Related collections