20241021
15170600
1.0
FALSE
biomas_5000
002
Geographic
GCS_SIRGAS_2000
Angular Unit: Degree (0.017453)
<GeographicCoordinateSystem xsi:type='typens:GeographicCoordinateSystem' xmlns:xsi='http://www.w3.org/2001/XMLSchema-instance' xmlns:xs='http://www.w3.org/2001/XMLSchema' xmlns:typens='http://www.esri.com/schemas/ArcGIS/3.3.0'><WKT>GEOGCS["GCS_SIRGAS_2000",DATUM["D_SIRGAS_2000",SPHEROID["GRS_1980",6378137.0,298.257222101]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433],AUTHORITY["EPSG",4674]]</WKT><XOrigin>-400</XOrigin><YOrigin>-400</YOrigin><XYScale>999999999.99999988</XYScale><ZOrigin>-100000</ZOrigin><ZScale>10000</ZScale><MOrigin>-100000</MOrigin><MScale>10000</MScale><XYTolerance>8.983152841195215e-09</XYTolerance><ZTolerance>0.001</ZTolerance><MTolerance>0.001</MTolerance><HighPrecision>true</HighPrecision><LeftLongitude>-180</LeftLongitude><WKID>4674</WKID><LatestWKID>4674</LatestWKID></GeographicCoordinateSystem>
20241021
15474500
20250506
11073400
50000000
500000
ItemDescription
Esri ArcGIS 13.3.0.52636
Biomas e Sistema Costeiro-Marinho do Brasil
O Mapa de Biomas e Sistema Costeiro-Marinho do Brasil, compatível com a escala 1:5.000.000, traz os limites entre os seis Biomas brasileiros, Amazônia, Mata Atlântica, Caatinga, Cerrado, Pantanal, Pampa e introduz o Sistema Costeiro-Marinho, cuja parte continental se sobrepõe aos Biomas limitantes à costa brasileira. De forma geral foi elaborado tendo por base as fitofisionomias do Mapa de Vegetação do Brasil na mesma escala, com exceção do Bioma Pantanal, que respeita características hidrogeomorfológicas referente às áreas de inundação . O Sistema Costeiro-Marinho, em sua parte continental, é fruto da análise ponderada dos mapeamentos geológicos, geomorfológicos e de vegetação em suas classes com influência marinha e fluviomarinha; a parte marítima respeita os Grandes Ecossistemas Marinhos do Brasil, que considera os fatores batimetria, hidrografia, produtividade e interações trófica.
<DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>Os dados provém dos mapas temáticos do território brasileiro: Vegetação, Geologia, Geomorfologia e Solos (IBGE de 1998 a 2017),</SPAN><SPAN> </SPAN><SPAN>no escopo dos Projetos SIVAM e Mapeamento de Recursos Naturais da Coordenação de Recursos Naturais e Estudos Ambientais,</SPAN><SPAN> </SPAN><SPAN>disponíveis no Banco de Dados de Informações Ambientais (www.bdiaweb.ibge.gov.br). Além de consultas a mapeamentos</SPAN><SPAN> </SPAN><SPAN>preexistentes, revisões bibliográficas e verificações em campo. Os limites foram traçados por equipes multidisciplinares distribuídas</SPAN><SPAN> </SPAN><SPAN>em diferentes partes do território. O projeto contribuiu na atualização do mapeamento da vegetação.</SPAN></P><P><SPAN><https://geoservicos.ibge.gov.br/geoserver/ows?service=WFS&version=1.0.0&request=GetFeature&typeName=CREN:bioma_vazado&outputFormat=SHAPE-ZIP></SPAN></P><P><SPAN /></P><P><SPAN>Publicado em </SPAN><SPAN>2019-10-30</SPAN></P></DIV></DIV></DIV>
Diretoria de Geociências(DGC)- Coordenação de Recursos Naturais e Estudos Ambientais(CREN) - Instituto Brasileiro de Geografia e Estatística - IBGE
Rio de Janeiro , 20031-170 , BR
(21) 2142-4578
Biomas
Amazônia
Caatinga
Cerrado
Pantanal
Pampa
Costeiro-Marinho
IBGE
Enterprise Geodatabase Feature Class
dataset
EPSG
6.11(9.2.0)
0
Simple
FALSE
0
TRUE
FALSE
biomas_5000
Feature Class
0
objectid
objectid
OID
4
10
0
Internal feature number.
Esri
Sequential unique whole numbers that are automatically generated.
cod_bioma
cod_bioma
String
254
0
0
nom_bioma
nom_bioma
String
254
0
0
shape
shape
Geometry
8
0
0
Feature geometry.
Esri
Coordinates defining the features.
st_area(shape)
st_area(shape)
Double
0
0
0
st_length(shape)
st_length(shape)
Double
0
0
0
20250506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