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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.

Object Preview

AGENTS.md — Corine Land Cover 2018 Pilot

Despre date / О данных / About the data

RO. Corine Land Cover 2018, proiect-pilot. Conține 1 845 poligoane extrase din spațiul de lucru corine 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. Corine Land Cover 2018, пилотный проект. Содержит 1 845 полигонов, извлечённых из рабочего пространства corine сервера geodata.gov.md через WFS 2.0.0 от 2026-08-16. Координаты сохранены в исходной системе MOLDREF99 / Moldova TM (EPSG:4026).

EN. Corine Land Cover 2018 Pilot. Holds 1 845 polygons extracted from the corine 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

1,845 features extracted from corine:clc_2018_aggregate_pilot on the geodata.gov.md GeoServer over WFS 2.0.0 on 2026-08-16, and verified against the server's own feature count.

Coordinates are MOLDREF99 / Moldova TM (EPSG:4026): projected, in metres, and the source's own system. They are not reprojected. ST_Area returns square metres directly, and a spatial predicate written against a WGS84 envelope will match nothing without raising an error.

Access

Schema

Column	Type	Notes
`id`	BIGINT	1,845 distinct values
`code`	BIGINT	18 distinct values. The source publishes no code list, so the meaning is unknown
`level_1`	VARCHAR	5 distinct values
`level_2`	VARCHAR	13 distinct values
`level_3`	VARCHAR	18 distinct values
`geometry`	GEOMETRY('EPSG:4026')	EPSG:4026, projected, metres
`bbox`	STRUCT(xmin DOUBLE, ymin DOUBLE, xmax DOUBLE, ymax DOUBLE)	Bounding box struct written by the extractor for spatial pruning

Measured distributions

code, 18 distinct values, most common first:

Value	Rows
`222`	298
`211`	226
`221`	224
`324`	221
`231`	207
`112`	185
`242`	157
`243`	111

level_1, 5 distinct values, most common first:

Value	Rows
`AGRICULTURAL AREAS`	1,223
`FOREST AND SEMI-NATURAL AREAS`	338
`ARTIFICIAL SURFACES`	240
`WATER BODIES`	36
`WETLANDS`	8

level_2, 13 distinct values, most common first:

Value	Rows
`Permanent crops`	522
`Heterogeneous agricultural areas`	268
`Scrub and/or herbaceous associations`	230
`Arable land`	226
`Pastures`	207
`Urban fabric`	185
`Forests`	102
`Industrial, commercial and transport units`	36

level_3, 18 distinct values, most common first:

Value	Rows
`Fruit trees and berry plantations`	298
`Non-irrigated arable land`	226
`Vineyards`	224
`Transitional woodland-scrub`	221
`Pastures`	207
`Discontinuous urban fabric`	185
`Complex cultivation patterns`	157
`Land principally occupied by agriculture, with significant areas of natural vegetation`	111

Data quality

Feature count matches the server's resultType=hits exactly, so nothing was lost to a capped WFS response.
code carry codes the source never defines. They are preserved verbatim without interpretation.
The upstream server answers from several backends that disagree about which layers exist. See the catalog's known-issues page.

Example queries

Row count:

Distribution of code:

Rows carrying geometry. Some layers hold null geometries, so filter before a spatial predicate:

Spatial filtering

This file is Hilbert-ordered and carries a bbox struct with GeoParquet 1.1 covering metadata. That combination makes row groups spatially coherent, so a bounding-box predicate lets the reader skip most of the file unread.

DuckDB does not apply it for you. Writing it yourself is worth 3-7x on a spatial query, measured on this catalog:

Coordinates are metres, so those bounds are a 10 km box.

cadastru_data_uat2 holds the 35 second-level administrative units and is the join target for anything aggregated by raion or municipality. Both sides are EPSG:4026, so a spatial join needs no transform. Prefilter on each raion's bounds so the expensive predicate runs on a fraction of the rows:

The catalog's own AGENTS.md covers the join keys and the quirks that apply across every collection here.

Name: AGENTS.md
Size: 6.08 KB
Content Type: text/markdown; charset=utf-8
Last Modified: 17 Aug 2026
Source URL: https://data.source.coop/nlebovits/moldova-geodata/corine/clc_2018_aggregate_pilot/AGENTS.md
Cloud URI: s3://us-west-2.opendata.source.coop/nlebovits/moldova-geodata/corine/clc_2018_aggregate_pilot/AGENTS.md

Download

AGENTS.md — Corine Land Cover 2018 Pilot

Despre date / О данных / About the data

Overview

1,845 features extracted from corine:clc_2018_aggregate_pilot on the geodata.gov.md GeoServer over WFS 2.0.0 on 2026-08-16, and verified against the server's own feature count.

Access

Schema

Column	Type	Notes
`id`	BIGINT	1,845 distinct values
`code`	BIGINT	18 distinct values. The source publishes no code list, so the meaning is unknown
`level_1`	VARCHAR	5 distinct values
`level_2`	VARCHAR	13 distinct values
`level_3`	VARCHAR	18 distinct values
`geometry`	GEOMETRY('EPSG:4026')	EPSG:4026, projected, metres
`bbox`	STRUCT(xmin DOUBLE, ymin DOUBLE, xmax DOUBLE, ymax DOUBLE)	Bounding box struct written by the extractor for spatial pruning

Measured distributions

code, 18 distinct values, most common first:

Value	Rows
`222`	298
`211`	226
`221`	224
`324`	221
`231`	207
`112`	185
`242`	157
`243`	111

level_1, 5 distinct values, most common first:

Value	Rows
`AGRICULTURAL AREAS`	1,223
`FOREST AND SEMI-NATURAL AREAS`	338
`ARTIFICIAL SURFACES`	240
`WATER BODIES`	36
`WETLANDS`	8

level_2, 13 distinct values, most common first:

Value	Rows
`Permanent crops`	522
`Heterogeneous agricultural areas`	268
`Scrub and/or herbaceous associations`	230
`Arable land`	226
`Pastures`	207
`Urban fabric`	185
`Forests`	102
`Industrial, commercial and transport units`	36

level_3, 18 distinct values, most common first:

Value	Rows
`Fruit trees and berry plantations`	298
`Non-irrigated arable land`	226
`Vineyards`	224
`Transitional woodland-scrub`	221
`Pastures`	207
`Discontinuous urban fabric`	185
`Complex cultivation patterns`	157
`Land principally occupied by agriculture, with significant areas of natural vegetation`	111

Data quality

Feature count matches the server's resultType=hits exactly, so nothing was lost to a capped WFS response.
code carry codes the source never defines. They are preserved verbatim without interpretation.
The upstream server answers from several backends that disagree about which layers exist. See the catalog's known-issues page.

Example queries

Row count:

Distribution of code:

Rows carrying geometry. Some layers hold null geometries, so filter before a spatial predicate:

Spatial filtering

DuckDB does not apply it for you. Writing it yourself is worth 3-7x on a spatial query, measured on this catalog:

Coordinates are metres, so those bounds are a 10 km box.

The catalog's own AGENTS.md covers the join keys and the quirks that apply across every collection here.

1INSTALL spatial; LOAD spatial; INSTALL httpfs; LOAD httpfs;
2
3SELECT *
4FROM read_parquet('https://data.source.coop/nlebovits/moldova-geodata/corine/clc_2018_aggregate_pilot/corine_clc_2018_aggregate_pilot.parquet')
5LIMIT 10;

1INSTALL spatial; LOAD spatial; INSTALL httpfs; LOAD httpfs;
2
3SELECT *
4FROM read_parquet('https://data.source.coop/nlebovits/moldova-geodata/corine/clc_2018_aggregate_pilot/corine_clc_2018_aggregate_pilot.parquet')
5LIMIT 10;

1SELECT count(*) FROM read_parquet('corine/clc_2018_aggregate_pilot/corine_clc_2018_aggregate_pilot.parquet');

1SELECT count(*) FROM read_parquet('corine/clc_2018_aggregate_pilot/corine_clc_2018_aggregate_pilot.parquet');

1SELECT "code", count(*) AS n
2FROM read_parquet('corine/clc_2018_aggregate_pilot/corine_clc_2018_aggregate_pilot.parquet')
3GROUP BY 1 ORDER BY n DESC;

1SELECT "code", count(*) AS n
2FROM read_parquet('corine/clc_2018_aggregate_pilot/corine_clc_2018_aggregate_pilot.parquet')
3GROUP BY 1 ORDER BY n DESC;

1INSTALL spatial; LOAD spatial;
2
3SELECT count(*)
4FROM read_parquet('corine/clc_2018_aggregate_pilot/corine_clc_2018_aggregate_pilot.parquet')
5WHERE geometry IS NOT NULL;

1INSTALL spatial; LOAD spatial;
2
3SELECT count(*)
4FROM read_parquet('corine/clc_2018_aggregate_pilot/corine_clc_2018_aggregate_pilot.parquet')
5WHERE geometry IS NOT NULL;

1INSTALL spatial; LOAD spatial;
2
3-- bbox first, then the exact test on what survives
4SELECT count(*)
5FROM read_parquet('corine/clc_2018_aggregate_pilot/corine_clc_2018_aggregate_pilot.parquet')
6WHERE bbox.xmin >= 200000 AND bbox.xmax <= 210000
7  AND bbox.ymin >= 180000 AND bbox.ymax <= 190000
8  AND ST_Within(geometry, ST_MakeEnvelope(200000, 180000, 210000, 190000));

1INSTALL spatial; LOAD spatial;
2
3-- bbox first, then the exact test on what survives
4SELECT count(*)
5FROM read_parquet('corine/clc_2018_aggregate_pilot/corine_clc_2018_aggregate_pilot.parquet')
6WHERE bbox.xmin >= 200000 AND bbox.xmax <= 210000
7  AND bbox.ymin >= 180000 AND bbox.ymax <= 190000
8  AND ST_Within(geometry, ST_MakeEnvelope(200000, 180000, 210000, 190000));

1INSTALL spatial; LOAD spatial;
2
3WITH units AS (
4  SELECT name, geometry,
5         ST_XMin(geometry) x0, ST_YMin(geometry) y0,
6         ST_XMax(geometry) x1, ST_YMax(geometry) y1
7  FROM read_parquet('cadastru/uat2/cadastru_data_uat2.parquet')
8)
9SELECT u.name, count(*) AS n
10FROM read_parquet('corine/clc_2018_aggregate_pilot/corine_clc_2018_aggregate_pilot.parquet') x
11JOIN units u
12  ON x.bbox.xmin BETWEEN u.x0 AND u.x1
13 AND x.bbox.ymin BETWEEN u.y0 AND u.y1
14 AND ST_Within(ST_Centroid(x.geometry), u.geometry)
15GROUP BY u.name
16ORDER BY n DESC;

1INSTALL spatial; LOAD spatial;
2
3WITH units AS (
4  SELECT name, geometry,
5         ST_XMin(geometry) x0, ST_YMin(geometry) y0,
6         ST_XMax(geometry) x1, ST_YMax(geometry) y1
7  FROM read_parquet('cadastru/uat2/cadastru_data_uat2.parquet')
8)
9SELECT u.name, count(*) AS n
10FROM read_parquet('corine/clc_2018_aggregate_pilot/corine_clc_2018_aggregate_pilot.parquet') x
11JOIN units u
12  ON x.bbox.xmin BETWEEN u.x0 AND u.x1
13 AND x.bbox.ymin BETWEEN u.y0 AND u.y1
14 AND ST_Within(ST_Centroid(x.geometry), u.geometry)
15GROUP BY u.name
16ORDER BY n DESC;

Moldova Geodata

AGENTS.md — Corine Land Cover 2018 Pilot

Despre date / О данных / About the data

Overview

Access

Schema

Measured distributions

Data quality

Example queries

Spatial filtering

Related collections

AGENTS.md — Corine Land Cover 2018 Pilot

Despre date / О данных / About the data

Overview

Access

Schema

Measured distributions

Data quality

Example queries

Spatial filtering

Related collections