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Market Research Group

Público·81 miembros

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Within this dataset, we also include gold mining as an economic activity. Mining within Brazil is reported to the Brazilian National Department of Mines, DNPM (Departamento Nacional de Produção Mineral). Original shape files depicting all areas of reported mining activity in Brazil were downloaded by state from the DNPM website ( ). For our dataset, we specifically selected the following gold mining categories, as defined by the DNPM: lavra garimpeira (small scale/alluvial mining), licenciamento (mining license), requerimento de lavra (mining authorization), requerimento de licenciamento (license authorization), and concessão de lavra (mining concession). Using ArcGIS, we matched the center of each mining polygon with the corresponding municipality and assigned gold mining presence/absence (1 and 0, respectively) to each municipality, based on the 2010 Brazilian county map.

The Amazon social-ecological database is available as comma-delimited text files (.csv) or as Microsoft Excel (.xlsx) files organized around the following themes: Health (incidence of malaria, dengue fever, cutaneous leishmaniasis, and HIV/AIDS), Environment (mean monthly rainfall and length of dry season, forest cover, and water cover), Socio-economics (including economy, social, education, agriculture, demography, and mining activity), Hydrology (river water level, river discharge/flow, and daily precipitation), and Hydroelectric Dams. All data are stored in the Dryad Digital Repository (Data Citation 1) and are also accessible through the Amazon Dams Network on-line data portal (Data Citation 2). A list of data sources used to build this database, along with data descriptions, spatial and temporal resolutions, and time spans is included in Table 1. The geographic scope of our study encompasses the Brazilian Amazonian states of Acre (AC), Amapá (AP), Amazonas (AM), Maranhão (MA), Mato Grosso (MT), Pará (PA), Rondônia (RO), Roraima (RR), and Tocantins (TO). All information is summarized at the municipality level (n=807), except for point-based hydrology data and hydroelectric dam variables. A summary of field names contained within each dataset is available for download along with the data (see ReadMe files). Covered time period varies by dataset (see Table 1).