Population Density : This vector dataset provides the population density by commune in Cambodia, as provided by Cambodian Demographic Census 2008 (Ministry of Planning, National Institute of Statistics). Dataset were provided to Open Development Cambodia (ODC) in vector format by Save Cambodia's Wildlife's Atlas Working Group.Urban Density in Cambodia (2011) : This vector dataset provides the urban density in Cambodia, as given by the United Nations Population Fund (UNFPA). Dataset were provided to Open Development Cambodia (ODC) by Save Cambodia's Wildlife's Atlas Working Group.Population Projections for 2030 in Cambodia (2010) : This dataset provides projected population of 2030, projected annual growth rate in each province in Cambodia, given by National Institute of Statistics and the United Nations. Data were provided to Open Development Cambodia (ODC) in vector format by Save Cambodia's Wildlife's Atlas Working Group.River networks of Cambodia : Vector polyline data of river networks in Cambodia. Attributes include: name of river, name of basin, name of sub-basin, Strahler number.Canals in Cambodia (2008) : This dataset is included geographical locations of canals and types of canal such as earthen, levee and masonry. The data is released by Department of Geography of Ministry of Land Management, Urban Planning, and Construction of Cambodia, and then it is contributed by Office for the Coordination of Humanitarian Affairs (OCHA) and shared on Humanitarian Data Exchange (HDX). ODC's map and data team has collected the data from HDX website in Shapefile format and re-published it on ODC's website.Special economic zone in Cambodia (2006-2019) : This dataset describes the information of special economic zone (SEZ) in Cambodia from 2006 to 2019. The total number of 42 SEZ is recorded. The data was collected from many sources by ODC’s mappers such as the royal gazette of Cambodia's government, and reports of the governmental ministries in hard and soft copies of pdf format. Geographic data is encoded in the WGS 84, Zone 48 North coordinate reference system.Road and railway networks in Cambodia (2012- 2019) : Road networks are produced by Open Street Map. ODC's map and data team extracted the data in vector format. Moreover, the polyline data of railway​ given by Save Cambodia's Wildlife's Atlas Working Group in Cambodia for two statuses such as existing, proposed new lines in Cambodia.Forest cover in Cambodia (2015-2018) : This forest cover is extracted from the Forest Monitoring System (https://rlcms-servir.adpc.net/en/forest-monitor/) which is developed by SERVIR-Mekong and the Global Land Analysis and Discovery Lab (GLAD) from University of Maryland. The definition of forest for this dataset is the tree canopy greater than 10% with height more than 5 meters.Schools in flood-prone area 2013 (information 2012-2014) : This dataset is created by clipping between Cambodia flood-prone areas in 2013 dataset and Basic information of school dataset to identify schools are under the flood extend in 2013. The basic information of school contains the spatial location of school, the attribute information in 2014, and total enrollment in 2012.Basic map of Cambodia (2014) : These datasets contain three different types of administrative boundary levels: provincial, district and commune which were contributed by Office for the Coordination of Humanitarian Affairs (OCHA) to Humanitarian Data Exchange (HDX). The datasets were obtained from the Department of Geography of Ministry of Land Management, Urban Planning and Construction (MLMUPC) in 2008 and then unofficially updated in 2014 by referring to Sub-decrees on administrative modifications. Most Recent Changes: New province added (Tbong Khmum), with underlying districts and communes.Land cover in Cambodia (2012- 2016) : The land cover is extracted from the Regional Land Cover Monitoring System (https://rlcms-servir.adpc.net/en/landcover/) which is developed by SERVIR-Mekong. The primitives are calculated from remote sensing indices which were made from yearly Landsat surface reflectance composites. The training data were collected by combining field information with high-resolution satellite imagery.Cropland in Cambodia : This dataset contains information of cropland and location of croplands in Cambodia which was downloaded from World Food Programme GeoNode (WFPGeoNode) using data in 2013 from​ the Department of Land and Geography of the Ministry of Land Management, Urban Planning and Construction.Community Fisheries Map for Cambodia (2011) : This dataset provides 2011 geographic boundaries, size and the number of villages covered by each community fishery for which coordinates are available in Cambodia, as given by the Fisheries Administration. For those community fisheries sites without coordinates, locations are given as the center points of communes and metrics are taken from the Commune Database of 2011. Geographic data is encoded in the WGS 84 coordinate reference system. Data were provided to ODC in vector format by Save Cambodia's Wildlife's Atlas Working Group.Digital Elevation Model (DEM 12.5 m) in 2010 : This raster dataset provides the Digital Elevation Model in the world. Dataset were provided to ASF Data Search Vertex by EarthData. This dataset has high resolution terrain at 12.5 meter. Alaska Satellite Facility (ASF) : making remote-sensing data accessible. ASF operates the NASA archive of synthetic aperture radar (SAR) data from a variety of satellites and aircraft, providing these data and associated specialty support services to researchers in support of NASA’s Earth Science Data and Information System (ESDIS) project.Function Area : This dataset are produced by Open Street Map. The data extracted the data in vector format (point feature).Tourism area (Museum, Attraction) : This dataset are produced by Open Street Map. The data extracted the data in vector format (point feature).Entity : Royal Government of Cambodia, Ministry of Planning, National Institute of Statistics; Cambodian Demographic Census 2008. Phnom Penh, 2008; Save Cambodia's Wildlife; In Atlas of Cambodia: maps on socio-economic development and environment;Time period : 2006-2018Frequency of update : Always up-to-dateGeo-coverage() : NationalGeo-coverage: National() : Cambodia

Region of Interest (ROI) is comprised of the Belgium, the Netherlands and Luxembourg

We use the communes adminitrative division which is standardized across Europe by EUROSTAT at: https://ec.europa.eu/eurostat/web/gisco/geodata/reference-data/administrative-units-statistical-units This is roughly equivalent to the notion municipalities in most countries.

From the link above, communes definition are taken from COMM_RG_01M_2016_4326.shp and country borders are taken from NUTS_RG_01M_2021_3035.shp.

images: Sentinel2 RGB from 2020-01-01 to 2020-31-12 filtered out pixels with clouds acoording to QA60 band following the example given in GEE dataset info page at: see https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S2_SR_HARMONIZED

  see also https://github.com/rramosp/geetiles/blob/main/geetiles/defs/sentinel2rgbmedian2020.py

labels: Global Human Settlement Layers, Population Grid 2015

  labels range from 0 to 31, with the following meaning:
    label value   original value in GEE dataset
    0        0
    1        1-10
    2        11-20
    3        21-30
    ...
    31       >=291 


  see https://developers.google.com/earth-engine/datasets/catalog/JRC_GHSL_P2016_POP_GPW_GLOBE_V1


  see also https://github.com/rramosp/geetiles/blob/main/geetiles/defs/humanpop2015.py

_aschips.geojson the image chips geometries along with label proportions for easy visualization with QGIS, GeoPandas, etc.

_communes.geojson the communes geometries with their label prortions for easy visualization with QGIS, GeoPandas, etc.

splits.csv contains two splits of image chips in train, test, val - with geographical bands at 45° angles in nw-se direction - the same as above reorganized to that all chips within the same commune fall within the same split.

data/ a pickle file for each image chip containing a dict with - the 100x100 RGB sentinel 2 chip image - the 100x100 chip level lavels - the label proportions of the chip - the aggregated label proportions of the commune the chip belongs to

The catchment area of a city is a group of municipalities, of a single enclave and enclave, which defines the extent of the influence of a cluster of population and employment on the surrounding municipalities, this influence being measured by the intensity of commuting to work. Urban area zoning follows the zoning into urban areas in 2010. An area consists of a pole and a crown. — Poles are determined mainly on the basis of density and total population criteria, using a methodology consistent with that of the municipal density grid. A threshold of jobs is added in order to prevent essentially residential municipalities with few jobs from being considered poles. Within the pole, the most populous commune is called the center commune. If a pole sends at least 15 % of its assets to work in another pole of the same level, the two poles are associated and together form the heart of a catchment area. — Municipalities that send at least 15 % of their assets to work in the pole are the crown of the area. The definition of the largest catchment areas of cities is consistent with the definition of “cities” and “functional urban areas” used by Eurostat and the OECD to analyse the functioning of cities. Zoning into catchment areas thus facilitates international comparisons and makes it possible to visualise the influence in France of major foreign cities. For example, seven areas have a town located abroad (Bâle, Charleroi, Geneva, Lausanne, Luxembourg, Monaco and Saarbrücken). The areas are classified according to the total number of inhabitants of the area in 2017. The main thresholds selected are: Paris, 700,000 inhabitants, 200,000 inhabitants and 50,000 inhabitants. Areas whose pole is located abroad are classified in the category corresponding to their total population (French and foreign). Urban catchment areas, dated 2020, were constructed with reference to commuting known in the 2016 Census. Downloadable files provide the characteristics of the city’s catchment areas (size slice, number of municipalities) and the municipal composition of the city’s catchment areas.

RHAs/Health Regions are geographic areas which are used to define populations and catchment areas for the administration and delivery of health services. This file provides RHA boundaries for cartographic and analytical purposes. Within Manitoba there are five Regional Health Authorities (or "RHAs") responsible for the delivery of health services in five specific areas of the province described in the legislation as "health regions." (In practice, the terms "health region" and "RHA" are often used interchangeably to describe these geographic areas.). This file contains boundaries for the health regions for each Regional Health Authority in Manitoba. Fields included (Alias (Field Name): Field description.) RHA Code (RHACODE): Two-digit numeric code which uniquely identifies a specific legislatively defined RHA RHA Name (RHAName): This field contains a simple name for each RHA, suitable for use as a label, in English. Nom de l'office régionale de la santé (RHANomFr): This field contains a simple name for each RHA, suitable for use as a label, in French. RHA Area - total (sq km) (RHAArea): The calculated geodesic area, in square kilometres, of the area within a given RHA's boundaries. RHA Area - excludes major lakes (sq km) (LandArea): The calculated geodesic area, in square kilometres, of the area within a given RHA's boundaries, with the area of major lakes excluded. For population density calculations, we recommend the use of this area value. The following major lakes have been excluded: Lake Winnipeg, Lake Manitoba, Lake Winnipegosis, and Cedar Lake.

L_AIRE_ATT_VILLE_2020_ZSUP_FLA_000 Attractions of cities in 2020 in Corrèze and neighbouring departments. Objects located on the outskirts of neighbouring departments may not be complete if they overflow on the neighbouring deparetment. Sources: INSEE + GeoFLA IGN https://www.insee.fr/fr/information/4803954 The catchment area of a city is a group of municipalities, of a single enclave and enclave, which defines the extent of the influence of a cluster of population and employment on the surrounding municipalities, this influence being measured by the intensity of commuting to work. Urban area zoning follows the zoning into urban areas in 2010. An area consists of a pole and a crown. * Poles are determined mainly on the basis of density and total population criteria, using a methodology consistent with that of the municipal density grid. A threshold of jobs is added in order to prevent essentially residential municipalities with few jobs from being considered poles. Within the pole, the most populous commune is called the center commune. If a pole sends at least 15 % of its assets to work in another pole of the same level, the two poles are associated and together form the heart of a catchment area. * Municipalities that send at least 15 % of their assets work in the pole are the crown of the area. The definition of the largest catchment areas of cities is consistent with the definition of “cities” and “functional urban areas” used by Eurostat and the OECD to analyse the functioning of cities. Zoning into catchment areas thus facilitates international comparisons and makes it possible to visualise the influence in France of major foreign cities. For example, seven areas have a town located abroad (Bâle, Charleroi, Geneva, Lausanne, Luxembourg, Monaco and Saarbrücken). The areas are classified according to the total number of inhabitants of the area in 2017. The main thresholds selected are: Paris, 700,000 inhabitants, 200,000 inhabitants and 50,000 inhabitants. Areas whose pole is located abroad are classified in the category corresponding to their total population (French and foreign). Urban catchment areas, dated 2020, were constructed with reference to commuting known in the 2016 Census. Downloadable files provide the characteristics of the city’s catchment areas (size slice, number of municipalities) and the municipal composition of the city’s catchment areas.

Refer to the current geographies boundaries table for a list of all current geographies and recent updates.

This dataset is the definitive version of the annually released urban rural (UR) boundaries as at 1 January 2025 as defined by Stats NZ. This version contains 689 UR areas, including 195 urban areas and 402 rural settlements.

Urban rural (UR) is an output geography that classifies New Zealand into areas that share common urban or rural characteristics and is used to disseminate a broad range of Stats NZ’s social, demographic and economic statistics.

The UR separately identifies urban areas, rural settlements, other rural areas, and water areas. Urban areas and rural settlements are form-based geographies delineated by the inspection of aerial imagery, local government land designations on district plan maps, address registers, property title data, and any other available information. However, because the underlying meshblock pattern is used to define the geographies, boundaries may not align exactly with local government land designations or what can be seen in aerial images. Other rural areas, and bodies of water represent areas not included within an urban area.

Urban areas are built from the statistical area 2 (SA2) geography, while rural and water areas are built from the statistical area 1 (SA1) geography.

Urban areas

Urban areas are statistically defined areas with no administrative or legal basis. They are characterised by high population density with many built environment features where people and buildings are located close together for residential, cultural, productive, trade and social purposes.

Urban areas are delineated using the following criteria. They:

form a contiguous cluster of one or more SA2s,

contain an estimated resident population of more than 1,000 people and usually have a population density of more than 400 residents or 200 address points per square kilometre,

have a high coverage of built physical structures and artificial landscapes such as:

• residential dwellings and apartments,
• commercial structures, such as factories, office complexes, and shopping centres,
• transport and communication facilities, such as airports, ports and port facilities, railway stations, bus stations and similar transport hubs, and communications infrastructure,
• medical, education, and community facilities,
• tourist attractions and accommodation facilities,
• waste disposal and sewerage facilities,
• cemeteries,
• sports and recreation facilities, such as stadiums, golf courses, racecourses, showgrounds, and fitness centres,
• green spaces, such as community parks, gardens, and reserves,

have strong economic ties where people gather together to work, and for social, cultural, and recreational interaction,

have planned development within the next 5–8 years.

Urban boundaries are independent of local government and other administrative boundaries. However, the Richmond urban area, which is mainly in the Tasman District, is the only urban area that crosses territorial authority boundaries

Rural areas

Rural areas are classified as rural settlements or other rural.

Rural settlements

Rural settlements are statistically defined areas with no administrative or legal basis. A rural settlement is a cluster of residential dwellings about a place that usually contains at least one community or public building.

Rural settlements are delineated using the following criteria. They:

form a contiguous cluster of one or more SA1s,

contain an estimated resident population of 200–1,000, or at least 40 residential dwellings,

represent a reasonably compact area or have a visible centre of population with a population density of at least 200 residents per square kilometre or 100 address points per square kilometre,

contain at least one community or public building, such as a church, school, or shop.

To reach the target SA2 population size of more than 1,000 residents, rural settlements are usually included with other rural SA1s to form an SA2. In some instances, the settlement and the SA2 have the same name, for example, Kirwee rural settlement is part of the Kirwee SA2.

Some rural settlements whose populations are just under 1,000 are a single SA2. Creating separate SA2s for these rural settlements allows for easy reclassification to urban areas if their populations grow beyond 1,000.

Other rural

Other rural areas are the mainland areas and islands located outside urban areas or rural settlements. Other rural areas include land used for agriculture and forestry, conservation areas, and regional and national parks. Other rural areas are defined by territorial authority.

Water

Bodies of water are classified separately, using the land/water demarcation classification described in the Statistical standard for meshblock. These water areas are not named and are defined by territorial authority or regional council.

The water classes include:

inland water – non-contiguous, defined by territorial authority,

inlets (which also includes tidal areas and harbours) – non-contiguous, defined by territorial authority,

oceanic – non-contiguous, defined by regional council.

To minimise suppression of population data, separate meshblocks have been created for marinas. These meshblocks are attached to adjacent land in the UR geography.

Non-digitised

The following 4 non-digitised UR areas have been aggregated from the 16 non-digitised meshblocks/SA2s.

6901; Oceanic outside region, 6902; Oceanic oil rigs, 6903; Islands outside region, 6904; Ross Dependency outside region.

UR numbering and naming

Each urban area and rural settlement is a single geographic entity with a name and a numeric code.

Other rural areas, inland water areas, and inlets are defined by territorial authority; oceanic areas are defined by regional council; and each have a name and a numeric code.

Urban rural codes have four digits. North Island locations start with a 1, South Island codes start with a 2, oceanic codes start with a 6 and non-digitised codes start with 69.

Urban rural indicator (IUR)

The accompanying urban rural indicator (IUR) classifies the urban, rural, and water areas by type. Urban areas are further classified by the size of their estimated resident population:

• major urban area – 100,000 or more residents,
• large urban area – 30,000–99,999 residents,
• medium urban area – 10,000–29,999 residents,
• small urban area – 1,000–9,999 residents.

This was based on 2018 Census data and 2021 population estimates. Their IUR status (urban area size/rural settlement) may change if the 2025 Census population count moves them up or down a category.

The indicators, by name, with their codes in brackets, are:

urban area – major urban (11), large urban (12), medium urban (13), small urban (14),

rural area – rural settlement (21), rural other (22),

water – inland water (31), inlet (32), oceanic (33).

​

High definition version

This high definition (HD) version is the most detailed geometry, suitable for use in GIS for geometric analysis operations and for the computation of areas, centroids and other metrics. The HD version is aligned to the LINZ cadastre.

​

Macrons

Names are provided with and without tohutō/macrons. The column name for those without macrons is suffixed ‘ascii’.

​

Digital data

Digital boundary data became freely available on 1 July 2007.

​

Further information

To download geographic classifications in table formats such as CSV please use Ariā

For more information please refer to the Statistical standard for geographic areas 2023.

Contact: geography@stats.govt.nz

The development of the ecosystem approach and models for the management of ocean marine resources requires easy access to standard validated datasets of historical catch data for the main exploited species, together with the model estimates achieved from these data, allowing models inter-comparison and evaluation of model skills. North Atlantic albacore tuna is exploited all year round by longline and in summer and autumn by surface fisheries and fishery statistics compiled by the International Commission for the Conservation of Atlantic Tunas (ICCAT). Catch and effort with geographical coordinates at monthly spatial resolution of 1° or 5° squares were extracted for this species with a careful definition of fisheries and data screening. Length frequencies of catch were also extracted according to the definition of fisheries for the period 1956-2010. Using these data, an application of the spatial ecosystem and population dynamics model (SEAPODYM) was developed for the North Atlantic albacore population and fisheries and provided the first spatially explicit estimate of albacore density in the North Atlantic by life stage. These densities by life stage (larval recruits, young immature fish adult mature fish and total biomass) are provided in gridded file (Netcdf) at resolution of 2° x 2° x month.