20200918
15453100
1.0
North American Profile of ISO19115 2003
FALSE
gisdb.gisadmin.estimativa_populacional_2019_RS
002
Server=gisdb.pgsql-geo.procergs.reders; Service=sde:postgresql:gisdb.pgsql-geo.procergs.reders; Database=gisdb; User=gisadmin; Version=sde.DEFAULT
ArcSDE Connection
-57.649743
-49.691352
-33.751178
-27.082302
1
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/10.7'><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>8.98315284119521e-09</XYTolerance><ZTolerance>0.001</ZTolerance><MTolerance>0.001</MTolerance><HighPrecision>true</HighPrecision><LeftLongitude>-180</LeftLongitude><WKID>4674</WKID><LatestWKID>4674</LatestWKID></GeographicCoordinateSystem>
FeatureClassToFeatureClass estimativa_pop_2019 "Conexões do Banco de Dados\GISADMIN_ gisdb.pgsql-geo.procergs.reders.sde\gisdb.gisadmin.dee" estimativa_populacional_2019_RS # "codigo "codigo" true true false 4 Long 0 0 ,First,#,estimativa_pop_2019,codigo,-1,-1;nome "nome" true true false 254 Text 0 0 ,First,#,estimativa_pop_2019,nome,-1,-1;regiao_func "regiao_func" true true false 8 Double 0 0 ,First,#,estimativa_pop_2019,regiao_func,-1,-1;Jov_0a14_2019 "Jov_0a14_2019" true true false 4 Long 0 0 ,First,#,estimativa_pop_2019,Jov_0a14_2019,-1,-1;pop_ativa_15a59_2019 "pop_ativa_15a59_2019" true true false 4 Long 0 0 ,First,#,estimativa_pop_2019,pop_ativa_15a59_2019,-1,-1;idoso_60mais_2019 "idoso_60mais_2019" true true false 4 Long 0 0 ,First,#,estimativa_pop_2019,idoso_60mais_2019,-1,-1;idoso_80mais_2019 "idoso_80mais_2019" true true false 4 Long 0 0 ,First,#,estimativa_pop_2019,idoso_80mais_2019,-1,-1;Homens_2019 "Homens_2019" true true false 4 Long 0 0 ,First,#,estimativa_pop_2019,Homens_2019,-1,-1;Mulheres_2019 "Mulheres_2019" true true false 4 Long 0 0 ,First,#,estimativa_pop_2019,Mulheres_2019,-1,-1;pop_Total_2019 "pop_Total_2019" true true false 4 Long 0 0 ,First,#,estimativa_pop_2019,pop_Total_2019,-1,-1;pop_total_2010 "pop_total_2010" true true false 4 Long 0 0 ,First,#,estimativa_pop_2019,pop_total_2010,-1,-1;var_pop_2010_2019 "var_pop_2010_2019" true true false 8 Double 0 0 ,First,#,estimativa_pop_2019,var_pop_2010_2019,-1,-1;perc_jov_0a14_2019 "perc_jov_0a14_2019" true true false 8 Double 0 0 ,First,#,estimativa_pop_2019,perc_jov_0a14_2019,-1,-1;perc_pop_ativa_15a59_2019 "perc_pop_ativa_15a59_2019" true true false 8 Double 0 0 ,First,#,estimativa_pop_2019,perc_pop_ativa_15a59_2019,-1,-1;perc_idoso_60mais_2019 "perc_idoso_60mais_2019" true true false 8 Double 0 0 ,First,#,estimativa_pop_2019,perc_idoso_60mais_2019,-1,-1;shape_Length "shape_Length" false true true 8 Double 0 0 ,First,#,estimativa_pop_2019,shape_Length,-1,-1;shape_Area "shape_Area" false true true 8 Double 0 0 ,First,#,estimativa_pop_2019,shape_Area,-1,-1" #
20201005
16305900
20201005
16352200
150000000
5000
NAP
Microsoft Windows 7 Version 6.1 (Build 7601) Service Pack 1; Esri ArcGIS 10.7.1.11595
Estimativa_populacional_2019_08_Classes
1
-57.649743
-49.691352
-27.082302
-33.751178
Dados relacionados com as estimativas populacionais, para 2019, por município, calculadas pelo IBGE (ver metodologia em https://www.ibge.gov.br/estatisticas/sociais/populacao/9103-estimativas-de-popul?=&t=o-que-e).
<DIV STYLE="text-align:Left;"><DIV><P><SPAN><SPAN>Dados relacionados com as estimativas populacionais, para 2019, por município, calculadas pelo IBGE (ver metodologia em https://www.ibge.gov.br/estatisticas/sociais/populacao/9103-estimativas-de-popul?=&t=o-que-e)</SPAN></SPAN></P></DIV></DIV>
Secretaria de Planejamento, Governança e Gestão/Divisão de Planejamento Territorial e Desenvolvimento Regional
Demografia
Estimativas Populacionais
população
faixa etária
variação populacional
População Potencialmente Ativa
Idosos
Jovens
Classe de Feição SDE
dataset
EPSG
7.8.3(9.2.0)
497
Simple
FALSE
497
TRUE
FALSE
gisdb.gisadmin.estimativa_populacional_2019_RS
Feature Class
497
objectid
objectid
OID
4
10
0
Internal feature number.
Esri
Sequential unique whole numbers that are automatically generated.
codigo
codigo
Integer
4
10
0
nome
nome
String
254
0
0
regiao_func
regiao_func
Double
8
38
8
jov_0a14_2019
Jov_0a14_2019
Integer
4
10
0
pop_ativa_15a59_2019
pop_ativa_15a59_2019
Integer
4
10
0
idoso_60mais_2019
idoso_60mais_2019
Integer
4
10
0
idoso_80mais_2019
idoso_80mais_2019
Integer
4
10
0
homens_2019
Homens_2019
Integer
4
10
0
mulheres_2019
Mulheres_2019
Integer
4
10
0
pop_total_2019
pop_Total_2019
Integer
4
10
0
pop_total_2010
pop_total_2010
Integer
4
10
0
var_pop_2010_2019
var_pop_2010_2019
Double
8
38
8
perc_jov_0a14_2019
perc_jov_0a14_2019
Double
8
38
8
perc_pop_ativa_15a59_2019
perc_pop_ativa_15a59_2019
Double
8
38
8
perc_idoso_60mais_2019
perc_idoso_60mais_2019
Double
8
38
8
shape
shape
Geometry
4
0
0
Feature geometry.
Esri
Coordinates defining the features.
perc_homens_2019
perc_homens_2019
Double
8
38
8
perc_mulheres_2019
perc_mulheres_2019
Double
8
38
8
st_area(shape)
st_area(shape)
Double
0
0
0
st_perimeter(shape)
st_perimeter(shape)
Double
0
0
0
20201005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