451a5fca-d532-47a4-a0c3-5d8b71c009f4 Javier Miranda 2023-07-29T16:44:48 ISO 19115:2003/19139 1.0 EPSG:5641 - SIRGAS 2000 / Brazil Mercator - Projected Deforestation Hotspots in Brazil, 2005-2012 2021-10-29 2012-12-27 Natural land resources in Brazil have been subject to strong pressure from agricultural expansion over the past two decades. This map identifies and classifies deforestation hotspots in the Southern American country. Moreover, it hints to land use change dynamics such as leakage effects in tropical areas. The map represents the period between 2005-2012, and classifies deforestation hotspots in three categories: a) reduced, b) increased, and c) new. Javier Miranda Center for Development Research, Department Economy and Technological Change (ZEF B), University of Bonn Junior Researcher javmi[at]yahoo.com https://daten.zef.de:/geonetwork/srv/api/records/451a5fca-d532-47a4-a0c3-5d8b71c009f4/attachments/thumbnail413843981080159312.png deforestation GEMET - Concepts, version 2.4 2010-01-13 geonetwork.thesaurus.external.theme.gemet deforestation hotspots Brazil Continents, countries, sea regions of the world. 2015-07-17 geonetwork.thesaurus.external.place.regions This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. http://creativecommons.org/licenses/by-sa/4.0/ Citation: Miranda, J. (2021): Deforestation Hotspots in Brazil, 2005-2012 https://daten.zef.de/#/metadata/451a5fca-d532-47a4-a0c3-5d8b71c009f4 40000000 environment 2005-01-01 2012-12-31 -74.018 -28.877 -33.742 5.2672 SOURCE_ EHS_051 ESRI Shapefile 1.0 https://iopscience.iop.org/article/10.1088/1748-9326/ab003a WWW:LINK-1.0-http--link Land speculation and conservation policy leakage in Brazil Publication https://daten.zef.de:/geonetwork/srv/api/records/451a5fca-d532-47a4-a0c3-5d8b71c009f4/attachments/ZEF_econ_deforestation-hotspots_amazon-cerrado_brazil_2005-2012.zip WWW:DOWNLOAD-1.0-http--download ZEF_econ_deforestation-hotspots_amazon-cerrado_brazil_2005-2012.zip Shape File Land cover information from Global Forest Watch (https://data.globalforestwatch.org/) was used to identify deforested pixels per year. ArcGIS 10 was used to create spatial statistics of yearly information. R and RStudio were used to classify each grid cell as a hotspot and its type, and to convert the resulting cover information into a shapefile.