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Dataset . 2020
License: CC BY
Data sources: Datacite
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ZENODO
Dataset . 2021
License: CC BY
Data sources: Datacite
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ZENODO
Dataset . 2020
License: CC BY
Data sources: Datacite
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ZENODO
Dataset . 2021
License: CC BY
Data sources: Datacite
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GCAM boundary spatial products from moirai v3.1

Authors: Narayan, Kanishka; Di Vittorio, Alan; Vernon, Chris;

GCAM boundary spatial products from moirai v3.1

Abstract

Summary- These data products present vector files for different representations of land area from the moirai land data system. Vector files are generated at 3 main spatial levels, namely country, region, basin. In addition to this, files are generated for different intersections for the 3 main categories, intersections for country and basin boundaries (country_basin), region and basin boundaries (region_basin) and region and country boundaries (region_country). Since the land data system does not generate land area information for all cells within the above mentioned boundaries (for water bodies for example), the vectors are presented for 3 main classes for each spatial category, land cells, cells with no land and combined. With all of the above mentioned combinations, the data products contain 18 different vector files. Methodology- In generating these vector files, we used the land outputs from moirai as inputs along with separate inputs for the boundaries for the main spatial levels (country, basin and region). Combining the spatial boundaries with land inputs we generated 3 raster outputs (land, no land and combined) for each of the main spatial levels along with all the intersections. A unique key is assigned for each unique spatial boundary. We then converted these rasters to vectors through a process of polygonization where polygons were dissolved using the key and finally added all metadata (basin names, region names, country names) to each of the vector files. We also check and correct geometry errors in the polygons themselves. CONTENTS: gcam_boundaries_moirai_3p1_0p5arcmin_wgs84 folder contains the following, input_files contain the following, moirai_valid_land_area.bsq: raster file containing actual land area by grid cell globally. crs: EPSG:4326 WGS84 - World Geodetic System 1984 resolution: 0.5 arc mins Global235_CLM_5arcmin.bil: raster file containing basin boundaries for all cells output by moirai crs: EPSG:4326 WGS84 - World Geodetic System 1984 resolution: 0.5 arc mins GCAM_32_w_Taiwan.shp – vector file containing boundaries for GCAM regions. GCAM_region_names.csv- Mapping file with details on GCAM region names (Used to fill in metadata) iso_GCAM_regID.csv- Mapping file containing details on individual country names by iso code. (Used to fill in metadata) basin_to_country_mapping.csv – Mapping file containing details on basin names by country and region. (Used to fill in metadata) main_outputs contain the following, Contains files for each spatial boundary (country, region, country_basin etc), for each land category (land cells, no land and combined) <spatial>_boundaries_moirai_<land_category>_3p1_0p5arcmin.shp column names in outputs: key: Unique identifier for feature reg_id: Unique identifier for region (region number) ctry_id: Unique identifier for country (country number) basin_id: Unique identifier for basin (basin number) reg_nm: Region name ctry_nm: Country name basin_nm: Basin name See README in the zipped directory for a full reference.

Related Organizations
Keywords

land, GCAM, spatial data, Moirai, moirai, vector files, GIS

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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