Powered by OpenAIRE graph
Found an issue? Give us feedback
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZENODOarrow_drop_down
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2021
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2021
License: CC BY
Data sources: ZENODO
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2021
License: CC BY
Data sources: ZENODO
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2024
License: CC BY
Data sources: ZENODO
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2024
License: CC BY
Data sources: ZENODO
ZENODO
Dataset . 2024
License: CC BY
Data sources: Datacite
versions View all 3 versions
addClaim

This Research product is the result of merged Research products in OpenAIRE.

You have already added 0 works in your ORCID record related to the merged Research product.

LuccME/INLAND land-use scenarios for Brazil 2050

Authors: Bezerra, Francisco Gilney Silva; Von Randow, Celso; Assis, Talita Oliveira; Bezerra, Karine Rocha Aguiar; Tejada, Graciela; Castro, Aline Anderson; Gomes, Diego Melo de Paula; +2 Authors

LuccME/INLAND land-use scenarios for Brazil 2050

Abstract

Land use and land cover change models and scenarios are essential to understand the interconnections between global and regional factors influencing land use and demand changes, especially if we consider population growth and food demand projections in 2050. Understanding the future of changes in land use and land cover in Brazil is fundamental for the future of global climate and biodiversity, given the richness of its five biomes. Thus, the new spatially explicit regional scenarios were developed for Brazil by 2050. Those scenarios are aligned with the Shared Socio-Economic Pathways (SSPs) and Representative Concentration Pathway (RCPs). Aim to detail global models regionally and can be used both regionally to support decision-making and enrich the overall analysis. For the development of these new scenarios, the LuccME spatially explicit land change allocation modeling framework and the INLAND surface model were combined to incorporate climatic variables in water deficit and biophysical, socioeconomic, and institutional factors for Brazil. The scenarios were developed for land use and land cover classes: forest vegetation, grassland vegetation, planted pasture, agriculture, mosaic of occupations, and forestry. The dataset comes in NetCDF format and includes the following products: LUCCMEBR_land_cover_type_100km2_2000.nc: Percentage of land use and land cover for the year 2000 (Observed data). LUCCMEBR_land_cover_type_100km2_2010.nc: Percentage of land use and land cover for the year 2010 (Observed data). LUCCMEBR_land_cover_type_100km2_2012.nc: Percentage of land use and land cover for the year 2012 (Observed data). LUCCMEBR_land_cover_type_100km2_2014.nc: Percentage of land use and land cover for the year 2014 (Observed data). LUCCMEBR_SSP1_RCP19_land_cover_type_100km2_2015_2050.nc: Percentage of land use and land cover for the period 2015-2050 (Simulated data). This scenario considers the combination of SSP1 and RCP1.9. LUCCMEBR_SSP2_RCP45_land_cover_type_100km2_2015_2050.nc: Percentage of land use and land cover for the period 2015-2050 (Simulated data). This scenario considers the combination of SSP2 and RCP4.5. LUCCMEBR_SSP3_RCP70_land_cover_type_100km2_2015_2050.nc: Percentage of land use and land cover for the period 2015-2050 (Simulated data). This scenario considers the combination of SSP3 and RCP7.0. Data Percentage of land use and land cover classes: Forest vegetation (veg), Grassland vegetation (gveg), Planted pasture (pastp), Agriculture (agric), Mosaic of occupation (mosc), Forestry (fores) and Others (others). Spatial resolution The scenarios are available in a spatial resolution of 0.083º x 0.083º (~100 km²) and cover the entire Brazilian territory. Temporal resolution Period of observed data: 2000, 2010, 2012 e 2014 Scenario Period: 2015 – 2050 (each five-year) Coordinate reference system Geographic Coordinate System with Datum WGS84 (EPSG4326) Data format Data is provided as NetCDF. Dataset usage It is free to use, but please make sure to cite the repository and our paper properly if you use this dataset. Publication & further information For additional scenario information, please contact Francisco Gilney Silva Bezerra (franciscogilney@gmail.com). Acknowledgments The authors thank the project “MSA / BNDES (Environmental Monitoring by Satellite in the Amazon biome)” for financing the development of LuccMEBR.

Related Organizations
Keywords

Land cover, regional scenarios, Land use, Modeling, LuccME, INLAND, Brazil

  • BIP!
    Impact byBIP!
    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    1
    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.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
    OpenAIRE UsageCounts
    Usage byUsageCounts
    visibility views 141
    download downloads 64
  • 141
    views
    64
    downloads
    Powered byOpenAIRE UsageCounts
Powered by OpenAIRE graph
Found an issue? Give us feedback
visibility
download
citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
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).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
downloads
OpenAIRE UsageCountsDownloads provided by UsageCounts
1
Average
Average
Average
141
64
Related to Research communities
Italian National Biodiversity Future Center