ONS Geospatial have developed a method of creating small area geographies built around record level data using nested grids. The Python package ‘gridgranulator’ allows non-disclosive outputs to be produced using a mixture of 125m x 125m, 250m x 250m, 500m x 500m or 1 kilometre grid cells. Building a geography around the data allows for as spatially detailed outputs as possible, whilst the use of grids means the outputs better integrate with other data sources that are more commonly disseminated as raster layers, such as environmental or climate data
Recent guidance on environmental modeling and global land-cover validation stresses the need for a p...
Clustering Geo-Data Cubes (CGC) is a Python package to perform clustering analysis for multidimensio...
The integration of statistical socioeconomic data and natural resource geospatial data is always a p...
Create structured grids from a spatial distribution of samples (data collection points) obtained at ...
A Discrete Global Grid System (DGGS) is a type of spatial reference system that tessellates the glob...
Open access geospatial data represent a range of metrics relevant to global human population mapping...
International audienceThe increased volume, spatial resolution, and areal coverage of high-resolutio...
Description: These Reference grids have been created for the NaturaConnect project and are based on ...
The increased volume, spatial resolution, and areal coverage of high-resolution images of Mars over ...
The data framework employed in this paper is derived from the PRIO-GRID 2.0 dataset, which is based ...
Researchers use 2D and 3D spatial models of multivariate data of differing resolutions and formats. ...
Recent guidance on environmental modeling and global land-cover validation stresses the need for a p...
Since the emergence of contemporary area classifications, population geography has witnessed a renai...
Discrete Global Grids: A Web Book (2002) was edited by Michael F. Goodchild and A. Jon Kimerling and...
Recent guidance on environmental modeling and global land-cover validation stresses the need for a p...
Clustering Geo-Data Cubes (CGC) is a Python package to perform clustering analysis for multidimensio...
The integration of statistical socioeconomic data and natural resource geospatial data is always a p...
Create structured grids from a spatial distribution of samples (data collection points) obtained at ...
A Discrete Global Grid System (DGGS) is a type of spatial reference system that tessellates the glob...
Open access geospatial data represent a range of metrics relevant to global human population mapping...
International audienceThe increased volume, spatial resolution, and areal coverage of high-resolutio...
Description: These Reference grids have been created for the NaturaConnect project and are based on ...
The increased volume, spatial resolution, and areal coverage of high-resolution images of Mars over ...
The data framework employed in this paper is derived from the PRIO-GRID 2.0 dataset, which is based ...
Researchers use 2D and 3D spatial models of multivariate data of differing resolutions and formats. ...
Recent guidance on environmental modeling and global land-cover validation stresses the need for a p...
Since the emergence of contemporary area classifications, population geography has witnessed a renai...
Discrete Global Grids: A Web Book (2002) was edited by Michael F. Goodchild and A. Jon Kimerling and...
Recent guidance on environmental modeling and global land-cover validation stresses the need for a p...
Clustering Geo-Data Cubes (CGC) is a Python package to perform clustering analysis for multidimensio...
The integration of statistical socioeconomic data and natural resource geospatial data is always a p...