20160512
10341900
1.0
FALSE
CalculateField HIDRO_GERAL_23.09.2015 CLASSE 4 VB #
CalculateField HIDRO_GERAL_23.09.2015 CLASSE 1 VB #
CalculateField HIDRO_GERAL_23.09.2015 CLASSE 3 VB #
CalculateField HIDRO_GERAL_23.09.2015 CLASSE 1 VB #
CalculateField HIDRO_GERAL_23.09.2015 CLASSE 3 VB #
CalculateField HIDRO_GERAL_23.09.2015 CLASSE 4 VB #
CalculateField HIDRO_GERAL_23.09.2015 CLASSE 4 VB #
CalculateField HIDRO_GERAL_23.09.2015 CLASSE 3 VB #
CalculateField HIDRO_GERAL_23.09.2015 CLASSE 1 VB #
CalculateField HIDRO_GERAL_23.09.2015 CLASSE 2
VB #
CalculateField "HIDRO_GERAL_30.09.2015 selection" CLASSE 1 VB #
CalculateField "HIDRO_GERAL_30.09.2015 selection" CLASSE 0 VB #
CalculateField "HIDRO_GERAL_30.09.2015 selection" CLASSE 1 VB #
CalculateField "HIDRO_GERAL_30.09.2015 selection" CLASSE 2 VB #
CalculateField "HIDRO_GERAL_30.09.2015 selection" CLASSE 2 VB #
CalculateField "HIDRO_GERAL_ selection 3" CLASSE 1 VB #
CalculateField "HIDRO_GERAL_ selection 3" CLASSE 2 VB #
CalculateField "HIDRO_GERAL_ selection" CLASSE 3 VB #
CalculateField "HIDRO_GERAL_ selection" CLASSE 2 VB #
CalculateField "HIDRO_GERAL_ selection" CLASSE 1 VB #
CalculateField "HIDRO_GERAL_01.10.2015 selection" CLASSE 2 VB #
CalculateField "HIDRO_GERAL_ selection" CLASSE 1 VB #
CalculateField "HIDRO_GERAL_ selection" CLASSE 2 VB #
CalculateField "HIDRO_GERAL_ selection" CLASSE 2 VB #
CalculateField "HIDRO_GERAL_ selection" CLASSE 1 VB #
CalculateField "HIDRO_GERAL_ selection" CLASSE 2 VB #
CalculateField "HIDRO_GERAL_02.10.2015 selection" CLASSE 1 VB #
CalculateField "HIDRO_GERAL_02.10.2015 selection" CLASSE 2 VB #
CalculateField "HIDRO_GERAL_02.10.2015 selection" CLASSE 1 VB #
CalculateField "HIDRO_GERAL_02.10.2015 selection" CLASSE 2 VB #
CalculateField "HIDRO_GERAL_02.10.2015 selection" CLASSE 1 VB #
CalculateField "HIDRO_GERAL_02.10.2015 selection" CLASSE 2 VB #
CalculateField "HIDRO_GERAL_02.10.2015 selection" CLASSE 1 VB #
CalculateField "HIDRO_GERAL_02.10.2015 selection" CLASSE 2 VB #
CalculateField "HIDRO_GERAL_02.10.2015 selection" CLASSE 1 VB #
CalculateField "HIDRO_GERAL_02.10.2015 selection" CLASSE 2 VB #
CalculateField "HIDRO_GERAL_02.10.2015 selection" CLASSE 1 VB #
CalculateField "HIDRO_GERAL_02.10.2015 selection" CLASSE 2 VB #
CalculateField "HIDRO_GERAL_05.10.2015 selection" CLASSE 1 VB #
CalculateField "HIDRO_GERAL_05.10.2015 selection" CLASSE 3 VB #
CalculateField "HIDRO_GERAL_05.10.2015 selection" CLASSE 1 VB #
CalculateField "HIDRO_GERAL_05.10.2015 selection" CLASSE 1 VB #
CalculateField "HIDRO_GERAL_05.10.2015 selection" CLASSE 1 VB #
CalculateField "HIDRO_GERAL_05.10.2015 selection" CLASSE 1 VB #
CalculateField "HIDRO_GERAL_05.10.2015 selection" CLASSE 2 VB #
CalculateField "HIDRO_GERAL_05.10.2015 selection" CLASSE 1 VB #
CalculateField "HIDRO_GERAL_06.10.2015 selection" CLASSE 1 VB #
CalculateField "HIDRO_GERAL_06.10.2015 selection" CLASSE 1 VB #
CalculateField "HIDRO_GERAL_06.10.2015 selection" CLASSE 1 VB #
CalculateField "HIDRO_GERAL_06.10.2015 selection" CLASSE 1 VB #
CalculateField "HIDRO_GERAL_06.10.2015 selection" CLASSE 1 VB #
CalculateField "HIDRO_GERAL_06.10.2015 selection" CLASSE 1 VB #
CalculateField "HIDRO_GERAL_06.10.2015 selection" CLASSE 3 VB #
CalculateField "HIDRO_GERAL_06.10.2015 selection" CLASSE 3 VB #
CalculateField "HIDRO_GERAL_06.10.2015 selection" CLASSE 1 VB #
CalculateField "HIDRO_GERAL_06.10.2015 selection" CLASSE 1 VB #
CalculateField "HIDRO_GERAL_06.10.2015 selection" CLASSE 1 VB #
CalculateField "HIDRO_GERAL_06.10.2015 selection" CLASSE 1 VB #
CalculateField "HIDRO_GERAL_06.10.2015 selection" CLASSE 1 VB #
CalculateField "HIDRO_GERAL_07.10.2015 selection" CLASSE 1 VB #
CalculateField "HIDRO_GERAL_07.10.2015 selection" CLASSE 1 VB #
CalculateField "HIDRO_GERAL_07.10.2015 selection selection selection" CodRecepto 02 VB #
CalculateField "HIDRO_GERAL_14.10.2015 selection" CLASSE 1 VB #
CalculateField "HIDRO_GERAL_14.10.2015 selection" CLASSE 1 VB #
CalculateField "HIDRO_GERAL_14.10.2015 selection" CLASSE 1 VB #
CalculateField "HIDRO_GERAL_15.10.2015 selection" CLASSE 1 VB #
CalculateField "HIDRO_GERAL_15.10.2015 selection" CLASSE 1 VB #
CalculateField "HIDRO_GERAL_15.10.2015 selection 2" CLASSE 2 VB #
CalculateField "HIDRO_GERAL_15.10.2015 selection" CLASSE 1 VB #
CalculateField "HIDRO_GERAL_15.10.2015 selection" CLASSE 2 VB #
CalculateField "HIDRO_GERAL_16.10.2015 selection" CLASSE 4 VB #
CalculateField "HIDRO_GERAL_16.10.2015 selection" CLASSE 4 VB #
CalculateField "HIDRO_GERAL_16.10.2015 selection" CLASSE 3 VB #
CalculateField "HIDRO_GERAL_16.10.2015 selection" CLASSE 2 VB #
CalculateField "HIDRO_GERAL_16.10.2015 selection" CLASSE 4 VB #
CalculateField "HIDRO_GERAL_16.10.2015 selection" CLASSE 4 VB #
CalculateField "HIDRO_GERAL_16.10.2015 selection" CLASSE 3 VB #
CalculateField "HIDRO_GERAL_16.10.2015 selection" CLASSE 3 VB #
CalculateField "HIDRO_GERAL_16.10.2015 selection" CLASSE 3 VB #
CalculateField "HIDRO_GERAL_16.10.2015 selection" CLASSE 4 VB #
CalculateField "HIDRO_GERAL_20.10.2015 selection" CLASSE 4 VB #
CalculateField "HIDRO_GERAL_20.10.2015 selection" CLASSE 3 VB #
CalculateField "HIDRO_GERAL_20.10.2015 selection" CLASSE 4 VB #
CalculateField "HIDRO_GERAL_20.10.2015 selection" CLASSE 4
VB #
CalculateField "HIDRO_GERAL_20.10.2015 selection" CLASSE 4 VB #
CalculateField "HIDRO_GERAL_20.10.2015 selection" CLASSE 3 VB #
CalculateField "HIDRO_GERAL_20.10.2015 selection" CLASSE 3 VB #
CalculateField "HIDRO_GERAL_20.10.2015 selection" CLASSE 4 VB #
CalculateField "HIDRO_GERAL_20.10.2015 selection" CLASSE 3 VB #
CalculateField "HIDRO_GERAL_20.10.2015 selection" CLASSE 3 VB #
CalculateField "HIDRO_GERAL_20.10.2015 selection" CLASSE 4 VB #
CalculateField "HIDRO_GERAL_20.10.2015 selection" CLASSE 4 VB #
CalculateField "HIDRO_GERAL_20.10.2015 selection" CLASSE 4 VB #
CalculateField "HIDRO_GERAL_20.10.2015 selection" CLASSE 4 VB #
CalculateField "HIDRO_GERAL_20.10.2015 selection" CLASSE 3 VB #
CalculateField "HIDRO_GERAL_20.10.2015 selection" CLASSE 4 VB #
CalculateField "HIDRO_GERAL_20.10.2015 selection" CLASSE 4 VB #
CalculateField "HIDRO_GERAL_20.10.2015 selection" CLASSE 3
VB #
CalculateField "HIDRO_GERAL_20.10.2015 selection" CLASSE 3 VB #
CalculateField "HIDRO_GERAL_20.10.2015 selection" CLASSE 3 VB #
CalculateField "HIDRO_GERAL_20.10.2015 selection" CLASSE 4 VB #
CalculateField "HIDRO_GERAL_20.10.2015 selection" CLASSE 4 VB #
CalculateField "HIDRO_GERAL_20.10.2015 selection" CLASSE 4 VB #
CalculateField "HIDRO_GERAL_20.10.2015 selection" CLASSE 4 VB #
CalculateField "HIDRO_GERAL_20.10.2015 selection" CLASSE 3 VB #
CalculateField "HIDRO_GERAL_20.10.2015 selection" CLASSE 4 VB #
CalculateField "HIDRO_GERAL_20.10.2015 selection" CLASSE 4 VB #
CalculateField "HIDRO_GERAL_21.10.2015 selection" CLASSE 4 VB #
CalculateField "HIDRO_GERAL_21.10.2015 selection selection" CLASSE 1 VB #
CalculateField "HIDRO_GERAL_21.10.2015 selection selection" CLASSE 1 VB #
CalculateField "HIDRO_GERAL_21.10.2015 selection" CLASSE 2 VB #
CalculateField "HIDRO_GERAL_21.10.2015 selection" CLASSE 1 VB #
CalculateField "HIDRO_GERAL_23.10.2015 selection" CLASSE 1 VB #
CalculateField "HIDRO_GERAL_23.10.2015 selection" CLASSE 1 VB #
CalculateField "HIDRO_GERAL_23.10.2015 selection" CLASSE 1 VB #
CalculateField "HIDRO_GERAL_23.10.2015 selection" CLASSE 1 VB #
CalculateField "HIDRO_GERAL_23.10.2015 selection" CLASSE 1 VB #
CalculateField "HIDRO_GERAL_06.10.2015 selection" CLASSE 2 VB #
CalculateField "HIDRO_GERAL_06.10.2015 selection" CLASSE 1 VB #
CalculateField "HIDRO_GERAL_06.10.2015 selection" CLASSE 1 VB #
CalculateField "HIDRO_GERAL_30.10.2015 selection" CLASSE 2 VB #
CalculateField "HIDRO_GERAL_06.10.2015 selection" CLASSE 3 VB #
CalculateField "HIDRO_GERAL_06.10.2015 selection" CLASSE 3 VB #
CalculateField "HIDRO_GERAL_04.11.2015 selection" CLASSE 1 VB #
CalculateField "HIDRO_GERAL_04.11.2015 selection" CLASSE 1 VB #
CalculateField "HIDRO_GERAL_04.11.2015 selection" CLASSE 1 VB #
CalculateField "HIDRO_GERAL_04.11.2015 selection" CLASSE 1 VB #
CalculateField "HIDRO_GERAL_05.11.2015 selection" CLASSE 4 VB #
CalculateField "HIDRO_GERAL_05.11.2015 selection" CLASSE 1 VB #
CalculateField "HIDRO_GERAL_05.11.2015 selection" CLASSE 1 VB #
CalculateField "HIDRO_GERAL_05.11.2015 selection" CLASSE 1 VB #
CalculateField "HIDRO_GERAL_05.11.2015 selection" CLASSE 1 VB #
CalculateField "HIDRO_GERAL_05.11.2015 selection" CLASSE 1 VB #
CalculateField "HIDRO_GERAL_05.11.2015 selection" CLASSE 1 VB #
CalculateField "HIDRO_GERAL_05.11.2015 selection" CLASSE 1 VB #
CalculateField "HIDRO_GERAL_05.11.2015 selection" CLASSE 1 VB #
CalculateField "HIDRO_GERAL_05.11.2015 selection" CLASSE 1 VB #
CalculateField "HIDRO_GERAL_05.11.2015 selection" CLASSE 1 VB #
CalculateField "HIDRO_GERAL_05.11.2015 selection" CLASSE 1 VB #
CalculateField "HIDRO_GERAL_05.11.2015 selection" CLASSE 1 VB #
CalculateField "HIDRO_GERAL_05.11.2015 selection" CLASSE 1 VB #
CalculateField "HIDRO_GERAL_05.11.2015 selection" CLASSE 1 VB #
CalculateField "HIDRO_GERAL_06.10.2015 selection 2" CLASSE 2 VB #
CalculateField "HIDRO_GERAL_06.10.2015 selection" CLASSE 4 VB #
CalculateField "HIDRO_GERAL_06.10.2015 selection" CLASSE 4 VB #
CalculateField "HIDRO_GERAL_06.10.2015 selection 2" CLASSE 4 VB #
CalculateField "HIDRO_GERAL_06.10.2015 selection 2" CLASSE 4 VB #
CalculateField "HIDRO_GERAL_06.10.2015 selection 2" CLASSE 4 VB #
CalculateField "10.11.2015 selection" CLASSE 4 VB #
CalculateField "10.11.2015 selection" CLASSE 4
VB #
CalculateField "10.11.2015 selection" CLASSE 4 VB #
CalculateField "10.11.2015 selection 2" CLASSE 3 VB #
CalculateField "10.11.2015 selection 2" CLASSE 3 VB #
CalculateField "10.11.2015 selection 2" CLASSE 3 VB #
CalculateField "10.11.2015 selection 2" CLASSE 1 VB #
CalculateField "10.11.2015 selection 2" CLASSE 1 VB #
CalculateField "10.11.2015 selection" CLASSE 3 VB #
CalculateField "10.11.2015 selection" CLASSE 4 VB #
CalculateField "10.11.2015 selection" CLASSE 3 VB #
CalculateField "10.11.2015 selection" CLASSE 1 VB #
CalculateField "10.11.2015 selection" CLASSE 1 VB #
CalculateField "10.11.2015 selection" CLASSE 1
VB #
CalculateField "10.11.2015 selection" CLASSE 3 VB #
CalculateField "10.11.2015 selection" CLASSE 1 VB #
CalculateField "10.11.2015 selection" CLASSE 3 VB #
CalculateField "10.11.2015 selection" CLASSE 3 VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" CLASSE 1 VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" CLASSE 2 VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" CLASSE 2 VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" CLASSE 2 VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" CLASSE 2 VB #
CalculateField 2015_11_17_CLASSIFICACAO2 CLASSE 1 VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" CLASSE 2 VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" CLASSE 2 VB #
CalculateField 2015_11_17_CLASSIFICACAO2 CLASSE 1 VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" CLASSE 2 VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" CLASSE 2 VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" CLASSE 2 VB #
CalculateField 2015_11_17_CLASSIFICACAO2 CLASSE 2 VB #
CalculateField 2015_11_17_CLASSIFICACAO2 OBSERVACAO "NASCENTES EM UNIDADES DE CONSERVACAO INTEGRAL" VB #
CalculateField 2015_11_17_CLASSIFICACAO2 CLASSE 2 VB #
CalculateField 2015_11_17_CLASSIFICACAO2 OBSERVACAO "" VB #
CalculateField 2015_11_17_CLASSIFICACAO2 OBSERVACAO "AFLUENTE RIO BAQUIVURU-GUACU" VB #
CalculateField 2015_11_17_CLASSIFICACAO2 CLASSE 3 VB #
CalculateField 2015_11_17_CLASSIFICACAO2 OBSERVACAO "AFLUENTE RIO BOTUJURU" VB #
CalculateField 2015_11_17_CLASSIFICACAO2 CLASSE 3 VB #
CalculateField 2015_11_17_CLASSIFICACAO2 OBSERVACAO "AFLUENTES DA MARGEM ESQUERDA DO RIO TIETÊ" VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" CLASSE 1 VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" OBSERVACAO "AFLUENTES DO RIO TAIACUPEBA ATE A BARRAGEM DO RESERVATORIO" VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" OBSERVACAO "AFLUENTES DO RIO TAIACUPEBA ATE A BARRAGEM" VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" CLASSE 1 VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" OBSERVACAO "AFLUENTES DO RIO TAIACUPEBA ATE A BARRAGEM" VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" CLASSE 1 VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" OBSERVACAO "AFLUENTES DO RIO JUNDIAI ATE A BARRAGEM" VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" CLASSE 1 VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" OBSERVACAO "AFLUENTES DO RIO BIRITIBA-MIRIM ATE A BARRAGEM" VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" CLASSE 1 VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" OBSERVACAO "AFLUENTES DO RIO PARAITINGA ATE A BARRAGEM" VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" CLASSE 1 VB #
CalculateField 2015_11_17_CLASSIFICACAO2 OBSERVACAO "AFLUENTES DO RIO TIETE ATE BARRAGEM PONTE NOVA" VB #
CalculateField 2015_11_17_CLASSIFICACAO2 CLASSE 1 VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" CLASSE 4 VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" CLASSE 3 VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" OBSERVACAO "AFLUENTES DO RIO TIETÊ NA MARGEM ESQUERDA" VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" CLASSE 3 VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" OBSERVACAO "AFLUENTES DO RIO TIETE NA MARGEM ESQUERDA" VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" CLASSE 3 VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" CLASSE 4 VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" OBSERVACAO "AFLUENTES DO RIO TRES PONTES" VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" CLASSE 3 VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" OBSERVACAO "AFLUENTES DO RIO TIETE NA MARGEM ESQUERDA" VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" CLASSE 4 VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" OBSERVACAO "AFLUENTES DO RIBEIRAO ITAIM" VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" CLASSE 4 VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" OBSERVACAO "AFLUENTES DO RIBEIRAO LAJEADO" VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" CLASSE 3 VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" OBSERVACAO "AFLUENTES DO RIO TIETE NA MARGEM ESQUERDA" VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" CLASSE 3 VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" CLASSE 2 VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" OBSERVACAO "NASCENTES EM UNIDADE DE CONSERVACAO INTEGRAL" VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" CLASSE 1 VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" CLASSE 3 VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" OBSERVACAO "AFLUENTES DO RIO GUARARA" VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" OBSERVACAO "NASCENTES EM UNIDADE DE CONSERVAÇÃO INTEGRAL" VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" CLASSE 1 VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" CLASSE 3 VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" OBSERVACAO "AFLUENTE RIO TIETE" VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" CLASSE 4 VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection selection" OBSERVACAO "AFLUENTES DO RIO COTIA ATE A BARRAGEM" VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection selection" CLASSE 1 VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection selection" OBSERVACAO "AFLUENTES DA REPRESA DO GUARAPIRANGA" VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection selection" CLASSE 1 VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection selection" OBSERVACAO "AFLUENTES DO RIO COTIA ENTRE AS BARRAGENS" VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection selection" CLASSE 3 VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" CLASSE 1 VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" OBSERVACAO "AFLUENTES DA REPRESA DO GUARAPIRANGA" VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" OBSERVACAO "" VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" CLASSE 2 VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" OBSERVACAO "CONFORME ITEM 1.2 - A DO DECRETO 10.755 DE 1.977" VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" CLASSE 1 VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" CLASSE 1 VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" OBSERVACAO "" VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" CLASSE 2 VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" OBSERVACAO "CONFORME ITEM 1.2 - A DO DECRETO 10.755 DE 1.977" VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" CLASSE 1 VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" OBSERVACAO "CONFORME ITEM 1.2 - B, DO DECRETO 10.755 DE 1.977" VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" CLASSE 1 VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" OBSERVACAO "NASCENTES EM UNIDADE DE CONSERVACAO INTEGRAL" VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" CLASSE 4 VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" OBSERVACAO "AFLUENTE RIO TIETE" VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" OBSERVACAO "AFLUENTE RIO TIETE" VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" CLASSE 4 VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" OBSERVACAO "AFLUENTE RIO SAPIANTA" VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" CLASSE 3 VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" OBSERVACAO "AFLUENTE RIO SAPIANTA" VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" CLASSE 3 VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" OBSERVACAO "AFLUENTE RIO TIETE" VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" CLASSE 4 VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" OBSERVACAO "AFLUENTES DA REPRESA DO GUARAPIRANGA" VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" CLASSE 1 VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" NomeCursoA "" VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" CodRecepto "" VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" CodCurso_1 "" VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" hid_cd "" VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" CLASSE 2 VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" OBSERVACAO "" VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" OBSERVACAO "AFLUENTES DO RIO TIETE NA MARGEM ESQUERDA" VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" CLASSE 3 VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" CLASSE 2 VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" OBSERVACAO "" VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" CLASSE 1 VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" CLASSE 3 VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" OBSERVACAO "AFLUENTES DO RIO TIETÊ NA MARGEM ESQUERDA" VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" CLASSE 3 VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" OBSERVACAO "AFLUENTE RIO TIETE" VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" CLASSE 4 VB #
CalculateField 2015_11_17_CLASSIFICACAO2 CLASSE 2 VB #
CalculateField 2015_11_17_CLASSIFICACAO2 CLASSE 3 VB #
CalculateField 2015_11_17_CLASSIFICACAO2 CLASSE 4 VB #
CalculateField 2015_11_17_CLASSIFICACAO2 OBSERVACAO "CLASSE ALTERADA COM A DELIBERAÇÃO CRH 168, de 9/12/2014" VB #
CalculateField 2015_11_17_CLASSIFICACAO2 OBSERVACAO "ALTERADA COM A DELIBERAÇÃO CRH 168 de 9/12/2014" VB #
CalculateField 2015_11_17_CLASSIFICACAO2 CLASSE 4 VB #
CalculateField 2015_11_17_CLASSIFICACAO2 CLASSE 4 VB #
CalculateField 2015_11_17_CLASSIFICACAO2 OBSERVACAO "CONFORME DECRETO 10.755 ITEM 4.5 d)" VB #
CalculateField 2015_11_17_CLASSIFICACAO2 CLASSE 3 VB #
CalculateField 2015_11_17_CLASSIFICACAO2 CLASSE 3 VB #
CalculateField 2015_11_17_CLASSIFICACAO2 CLASSE 3 VB #
CalculateField 2015_11_17_CLASSIFICACAO2 CLASSE 4 VB #
CalculateField 2015_11_17_CLASSIFICACAO2 CLASSE 4 VB #
CalculateField 2015_11_17_CLASSIFICACAO2 CLASSE 4 VB #
CalculateField 2015_11_17_CLASSIFICACAO2 CLASSE 4 VB #
CalculateField 2015_11_17_CLASSIFICACAO2 CLASSE 2 VB #
CalculateField 2015_11_17_CLASSIFICACAO2 OBSERVACAO "CONFORME DELIBERAÇÃO CRH Nº 162, DE 09/09/2014" VB #
CalculateField 2015_11_17_CLASSIFICACAO2 OBSERVACAO "CONFORME DELIBERAÇÃO CRH Nº 162, DE 09/09/2014" VB #
CalculateField 2015_11_17_CLASSIFICACAO2 CLASSE 3 VB #
CalculateField 2015_11_17_CLASSIFICACAO2 CLASSE 4 VB #
CalculateField "2015_11_17_CLASSIFICACAO2 selection" OBSERVACAO "NASCENTES EM UNIDADE DE CONSERVACAO INTEGRAL" VB #
CalculateField 2015_11_17_CLASSIFICACAO2 CLASSE 1 VB #
CalculateField 2015_11_17_CLASSIFICACAO2 OBSERVACAO "CONFORME DEC. 10.755/77 - ITEM 1.6 - S" VB #
CalculateField 2015_11_17_CLASSIFICACAO2 OBSERVACAO "CONFORME DECRETO 10.755, ITEM 4.5 - d)" VB #
CalculateField 2015_11_17_CLASSIFICACAO2 OBSERVACAO "CONFORME DECRETO 10.755/77, ITEM 1.1 - i)" VB #
CalculateField 2015_11_17_CLASSIFICACAO2 OBSERVACAO "CONFORME DECRETO 10.755/77, ITEM 1.6 - d)" VB #
CalculateField 2015_11_17_CLASSIFICACAO2 OBSERVACAO "CONFORME DECRETO 10.755/77, ITEM 1.6 - s)" VB #
CalculateField 2015_11_17_CLASSIFICACAO2 OBSERVACAO "CONFORME DECRETO 10.755/77, ITEM 4.5 - d)" VB #
CalculateField 2015_11_17_CLASSIFICACAO2 OBSERVACAO "CONFORME DECRETO 10.755/77, ITEM 1.2 - a)" VB #
CalculateField 2015_11_17_CLASSIFICACAO2 OBSERVACAO "CONFORME DECRETO 10.755/77, ITEM 1.2 - b)" VB #
CalculateField 2015_11_17_CLASSIFICACAO2 OBSERVACAO "CONFORME DECRETO 10.755/77, ITEM 1.7 - s)" VB #
CalculateField HIDROGRAFIA NomeCursoA "SERIMBURA,COR(SENHORIA,COR)" VB #
CalculateField HIDROGRAFIA CLASSE 2 VB #
CalculateField HIDROGRAFIA CodRecepto 0224 VB #
CalculateField HIDROGRAFIA CodCurso_1 0224001 VB #
CalculateField HIDROGRAFIA CLASSE 4 VB #
CalculateField HIDROGRAFIA CLASSE 2 VB #
CalculateField HIDROGRAFIA OBSERVACAO "" VB #
CalculateField HIDROGRAFIA CLASSE 2 VB #
CalculateField HIDROGRAFIA OBSERVACAO "" VB #
CalculateField HIDROGRAFIA CLASSE 4 VB #
CalculateField HIDROGRAFIA NomeCursoA "CHACARA, RIB" VB #
CalculateField HIDROGRAFIA CodCurso_1 0274 VB #
CalculateField HIDROGRAFIA CodRecepto "02" VB #
CalculateField "HIDROGRAFIA - CLASSE 3 E 4" CLASSE 2 VB #
CalculateField "HIDROGRAFIA - CLASSE 3 E 4" CLASSE 2 VB #
CalculateField "HIDROGRAFIA - ENQUADRAMENTO" CLASSE 0 VB #
CalculateField "HIDROGRAFIA - ENQUADRAMENTO" CLASSE 2 VB #
CalculateField "HIDROGRAFIA - ENQUADRAMENTO" CodRecepto "010100740" VB #
CalculateField "HIDROGRAFIA - ENQUADRAMENTO" NomeCursoA "PEIXE,R DO/CORRENTE,R DA" VB #
CalculateField "HIDROGRAFIA - ENQUADRAMENTO" CodCurso_1 "01010074019" VB #
CalculateField "HIDROGRAFIA - ENQUADRAMENTO" hid_cd "01010074019" VB #
CalculateField "HIDROGRAFIA - ENQUADRAMENTO" hid_tp_el "Eixos de Rios MD" VB #
CalculateField "HIDROGRAFIA - ENQUADRAMENTO" hid_ft "IGC" VB #
CalculateField "HIDROGRAFIA - ENQUADRAMENTO" hid_es "1:50.000" VB #
CalculateField "HIDROGRAFIA - ENQUADRAMENTO" hid_mi "2708-3" VB #
CalculateField "HIDROGRAFIA - ENQUADRAMENTO" hid_ni 55 VB #
CalculateField "HIDROGRAFIA - ENQUADRAMENTO" NomeCursoA " " VB #
CalculateField "HIDROGRAFIA - ENQUADRAMENTO" CodRecepto " " VB #
CalculateField "HIDROGRAFIA - ENQUADRAMENTO" CodCurso_1 " " VB #
CalculateField "HIDROGRAFIA - ENQUADRAMENTO" hid_cd " " VB #
CalculateField "HIDROGRAFIA - ENQUADRAMENTO" hid_cd "010100740" VB #
CalculateField "HIDROGRAFIA - ENQUADRAMENTO" CodCurso_1 "010100740" VB #
CalculateField "HIDROGRAFIA - ENQUADRAMENTO" CodRecepto "0101007" VB #
CalculateField "HIDROGRAFIA - ENQUADRAMENTO" NomeCursoA "MOJI-GUACU,R/CORISCO,COR DO" VB #
CalculateField "HIDROGRAFIA - ENQUADRAMENTO" hid_tp_el "Rio Permanente" VB #
CalculateField "HIDROGRAFIA - ENQUADRAMENTO" hid_ft "IGC" VB #
CalculateField "HIDROGRAFIA - ENQUADRAMENTO" hid_es "1:50.000" VB #
CalculateField "HIDROGRAFIA - ENQUADRAMENTO" hid_mi "2708-2" VB #
CalculateField "HIDROGRAFIA - ENQUADRAMENTO" CLASSE 2 VB #
CalculateField "HIDROGRAFIA - ENQUADRAMENTO" CLASSE 2 VB #
CalculateField "HIDROGRAFIA - ENQUADRAMENTO" CLASSE 1 VB #
CalculateField "HIDROGRAFIA - ENQUADRAMENTO" OBSERVACAO "NASCENTES EM UNIDADE DE CONSERVACAO INTEGRAL" VB #
CalculateField 2015_11_17_CLASSIFICACAO2 CLASSE 4 VB #
CalculateField 2015_11_17_CLASSIFICACAO2 CLASSE 4 VB #
CalculateField "HIDROGRAFIA - ENQUADRAMENTO" CLASSE 3 VB #
CalculateField 2015_11_17_CLASSIFICACAO2 CLASSE 4 VB #
CalculateField "HIDROGRAFIA - ENQUADRAMENTO" CLASSE 2 VB #
CalculateField "HIDROGRAFIA - ENQUADRAMENTO" OBSERVACAO "" VB #
CalculateField "HIDROGRAFIA - ENQUADRAMENTO" NomeCursoA "GUAIO,R/GUAIO,RIB" VB #
CalculateField "HIDROGRAFIA - ENQUADRAMENTO" OBSERVACAO "" VB #
CalculateField "HIDROGRAFIA - ENQUADRAMENTO" CLASSE 2 VB #
Merge UGRHI_3;Ughri22_hidrografia;Ughri21_hidrografia;Ughri20_hidrografia;Ughri19_hidrografia;Ughri18_hidrografia;Ughri17_hidrografia;Ughri16_hidrografia;Ughri15_hidrografia;Ughri14_hidrografia;Ughri13_hidrografia;Ughri12_hidrografia;Ughri11_hidrografia;Ughri10_hidrografia;Ughri09_hidrografia;Ughri08_hidrografia;Ughri07_hidrografia;Ughri06_hidrografia;Ughri05_hidrografia;Ughri04_hidrografia;UGRHI_2;Ughri01_hidrografia "C:\Users\Arklok\OneDrive - PRODESP\Documentos\Projetos\GE Fast\MyProject\MyProject.gdb\HidrografiaSP" "OBJECTID "OBJECTID" true true false 10 Long 0 10,First,#,UGRHI_3,OBJECTID,-1,-1,Ughri22_hidrografia,OBJECTID,-1,-1,Ughri21_hidrografia,OBJECTID,-1,-1,Ughri20_hidrografia,OBJECTID,-1,-1,Ughri19_hidrografia,OBJECTID,-1,-1,Ughri18_hidrografia,OBJECTID,-1,-1,Ughri17_hidrografia,OBJECTID,-1,-1,Ughri16_hidrografia,OBJECTID,-1,-1,Ughri15_hidrografia,OBJECTID,-1,-1,Ughri14_hidrografia,OBJECTID,-1,-1,Ughri13_hidrografia,OBJECTID,-1,-1,Ughri12_hidrografia,OBJECTID,-1,-1,Ughri11_hidrografia,OBJECTID,-1,-1,Ughri10_hidrografia,OBJECTID,-1,-1,Ughri09_hidrografia,OBJECTID,-1,-1,Ughri08_hidrografia,OBJECTID,-1,-1,Ughri07_hidrografia,OBJECTID,-1,-1,Ughri06_hidrografia,OBJECTID,-1,-1,Ughri04_hidrografia,OBJECTID,-1,-1,UGRHI_2,OBJECTID,-1,-1,Ughri01_hidrografia,OBJECTID,-1,-1;hid_cd "hid_cd" true true false 200 Text 0 0,First,#,UGRHI_3,hid_cd,0,199,Ughri17_hidrografia,hid_cd,0,199,Ughri11_hidrografia,hid_cd,0,199,Ughri06_hidrografia,hid_cd,0,199,UGRHI_2,hid_cd,0,199;hid_tp_el "hid_tp_el" true true false 150 Text 0 0,First,#,UGRHI_3,hid_tp_el,0,149,Ughri17_hidrografia,hid_tp_el,0,149,Ughri11_hidrografia,hid_tp_el,0,149,Ughri06_hidrografia,hid_tp_el,0,149,UGRHI_2,hid_tp_el,0,149;hid_ft "hid_ft" true true false 50 Text 0 0,First,#,UGRHI_3,hid_ft,0,49,Ughri17_hidrografia,hid_ft,0,49,Ughri11_hidrografia,hid_ft,0,49,Ughri06_hidrografia,hid_ft,0,49,UGRHI_2,hid_ft,0,49;hid_es "hid_es" true true false 20 Text 0 0,First,#,UGRHI_3,hid_es,0,19,Ughri17_hidrografia,hid_es,0,19,Ughri11_hidrografia,hid_es,0,19,Ughri06_hidrografia,hid_es,0,19,UGRHI_2,hid_es,0,19;hid_mi "hid_mi" true true false 20 Text 0 0,First,#,UGRHI_3,hid_mi,0,19,Ughri17_hidrografia,hid_mi,0,19,Ughri11_hidrografia,hid_mi,0,19,Ughri06_hidrografia,hid_mi,0,19,UGRHI_2,hid_mi,0,19;hid_ni "hid_ni" true true false 19 Double 0 0,First,#,UGRHI_3,hid_ni,-1,-1,Ughri17_hidrografia,hid_ni,-1,-1,Ughri11_hidrografia,hid_ni,-1,-1,Ughri06_hidrografia,hid_ni,-1,-1,UGRHI_2,hid_ni,-1,-1;Shape_Leng "Shape_Leng" true true false 19 Double 0 0,First,#,UGRHI_3,Shape_Leng,-1,-1,Ughri17_hidrografia,Shape_Leng,-1,-1,Ughri11_hidrografia,Shape_Leng,-1,-1,Ughri06_hidrografia,Shape_Leng,-1,-1,UGRHI_2,Shape_Leng,-1,-1;Enabled "Enabled" true true false 5 Long 0 5,First,#,UGRHI_3,Enabled,-1,-1,Ughri17_hidrografia,Enabled,-1,-1,Ughri11_hidrografia,Enabled,-1,-1,Ughri06_hidrografia,Enabled,-1,-1,UGRHI_2,Enabled,-1,-1;STATUS "STATUS" true true false 5 Long 0 5,First,#,UGRHI_3,STATUS,-1,-1,Ughri17_hidrografia,STATUS,-1,-1,Ughri11_hidrografia,STATUS,-1,-1,Ughri06_hidrografia,STATUS,-1,-1,UGRHI_2,STATUS,-1,-1;CODCURSOAG "CODCURSOAG" true true false 19 Text 0 0,First,#,UGRHI_3,CODCURSOAG,0,18,Ughri17_hidrografia,CODCURSOAG,0,18,Ughri11_hidrografia,CODCURSOAG,0,18,Ughri06_hidrografia,CODCURSOAG,0,18,UGRHI_2,CODCURSOAG,0,18;Nome "Nome" true true false 200 Text 0 0,First,#,UGRHI_3,Nome,0,199,Ughri17_hidrografia,Nome,0,199,Ughri11_hidrografia,Nome,0,199,Ughri06_hidrografia,Nome,0,199,UGRHI_2,Nome,0,199;Shape_Le_1 "Shape_Le_1" true true false 19 Double 0 0,First,#,UGRHI_3,Shape_Le_1,-1,-1,Ughri17_hidrografia,Shape_Le_1,-1,-1,Ughri11_hidrografia,Shape_Le_1,-1,-1,Ughri06_hidrografia,Shape_Le_1,-1,-1,UGRHI_2,Shape_Le_1,-1,-1;CodCurso_1 "CodCurso_1" true true false 254 Text 0 0,First,#,UGRHI_3,CodCurso_1,0,253,Ughri17_hidrografia,CodCurso_1,0,253,Ughri11_hidrografia,CodCurso_1,0,253,Ughri06_hidrografia,CodCurso_1,0,253,UGRHI_2,CodCurso_1,0,253;NomeCursoA "NomeCursoA" true true false 254 Text 0 0,First,#,UGRHI_3,NomeCursoA,0,253,Ughri22_hidrografia,NomeCursoA,0,253,Ughri21_hidrografia,NomeCursoA,0,253,Ughri20_hidrografia,NomeCursoA,0,253,Ughri19_hidrografia,NomeCursoA,0,253,Ughri18_hidrografia,NomeCursoA,0,253,Ughri17_hidrografia,NomeCursoA,0,253,Ughri16_hidrografia,NomeCursoA,0,253,Ughri15_hidrografia,NomeCursoA,0,253,Ughri14_hidrografia,NomeCursoA,0,253,Ughri13_hidrografia,NomeCursoA,0,253,Ughri12_hidrografia,NomeCursoA,0,253,Ughri11_hidrografia,NomeCursoA,0,253,Ughri10_hidrografia,NomeCursoA,0,253,Ughri09_hidrografia,NomeCursoA,0,253,Ughri08_hidrografia,NomeCursoA,0,253,Ughri07_hidrografia,NomeCursoA,0,253,Ughri06_hidrografia,NomeCursoA,0,253,Ughri05_hidrografia,NomeCursoA,0,253,Ughri04_hidrografia,NomeCursoA,0,253,UGRHI_2,NomeCursoA,0,253,Ughri01_hidrografia,NomeCursoA,0,253;CodRecepto "CodRecepto" true true false 254 Text 0 0,First,#,UGRHI_3,CodRecepto,0,253,Ughri17_hidrografia,CodRecepto,0,253,Ughri11_hidrografia,CodRecepto,0,253,Ughri06_hidrografia,CodRecepto,0,253,UGRHI_2,CodRecepto,0,253;CLASSE "CLASSE" true true false 19 Double 0 19,First,#,UGRHI_3,CLASSE,-1,-1,Ughri22_hidrografia,CLASSE,-1,-1,Ughri21_hidrografia,CLASSE,-1,-1,Ughri20_hidrografia,CLASSE,-1,-1,Ughri19_hidrografia,CLASSE,-1,-1,Ughri18_hidrografia,CLASSE,-1,-1,Ughri17_hidrografia,CLASSE,-1,-1,Ughri16_hidrografia,CLASSE,-1,-1,Ughri15_hidrografia,CLASSE,-1,-1,Ughri14_hidrografia,CLASSE,-1,-1,Ughri13_hidrografia,CLASSE,-1,-1,Ughri12_hidrografia,CLASSE,-1,-1,Ughri11_hidrografia,CLASSE,-1,-1,Ughri10_hidrografia,CLASSE,-1,-1,Ughri09_hidrografia,CLASSE,-1,-1,Ughri08_hidrografia,CLASSE,-1,-1,Ughri07_hidrografia,CLASSE,-1,-1,Ughri06_hidrografia,CLASSE,-1,-1,Ughri05_hidrografia,CLASSE,-1,-1,Ughri04_hidrografia,CLASSE,-1,-1,UGRHI_2,CLASSE,-1,-1,Ughri01_hidrografia,CLASSE,-1,-1;OBSERVACAO "OBSERVACAO" true true false 50 Text 0 0,First,#,UGRHI_3,OBSERVACAO,0,49,Ughri22_hidrografia,OBSERVACAO,0,49,Ughri21_hidrografia,OBSERVACAO,0,49,Ughri20_hidrografia,OBSERVACAO,0,49,Ughri19_hidrografia,OBSERVACAO,0,49,Ughri18_hidrografia,OBSERVACAO,0,49,Ughri17_hidrografia,OBSERVACAO,0,49,Ughri16_hidrografia,OBSERVACAO,0,49,Ughri15_hidrografia,OBSERVACAO,0,49,Ughri14_hidrografia,OBSERVACAO,0,49,Ughri13_hidrografia,OBSERVACAO,0,49,Ughri12_hidrografia,OBSERVACAO,0,49,Ughri11_hidrografia,OBSERVACAO,0,49,Ughri10_hidrografia,OBSERVACAO,0,49,Ughri09_hidrografia,OBSERVACAO,0,49,Ughri08_hidrografia,OBSERVACAO,0,49,Ughri07_hidrografia,OBSERVACAO,0,49,Ughri06_hidrografia,OBSERVACAO,0,49,Ughri05_hidrografia,OBSERVACAO,0,49,Ughri04_hidrografia,OBSERVACAO,0,49,UGRHI_2,OBSERVACAO,0,49,Ughri01_hidrografia,OBSERVACAO,0,49" NO_SOURCE_INFO MANUAL_EDIT
HidrografiaSP
002
file://\\ARK400865\C$\Users\Arklok\OneDrive - PRODESP\Documentos\Projetos\GE Fast\MyProject\MyProject.gdb
Local Area Network
Projected
GCS_South_American_1969
Linear Unit: Meter (1.000000)
SAD_1969_UTM_Zone_23S
<ProjectedCoordinateSystem xsi:type='typens:ProjectedCoordinateSystem' 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/3.4.0'><WKT>PROJCS["SAD_1969_UTM_Zone_23S",GEOGCS["GCS_South_American_1969",DATUM["D_South_American_1969",SPHEROID["GRS_1967_Truncated",6378160.0,298.25]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Transverse_Mercator"],PARAMETER["False_Easting",500000.0],PARAMETER["False_Northing",10000000.0],PARAMETER["Central_Meridian",-45.0],PARAMETER["Scale_Factor",0.9996],PARAMETER["Latitude_Of_Origin",0.0],UNIT["Meter",1.0],AUTHORITY["EPSG",29193]]</WKT><XOrigin>-5120900</XOrigin><YOrigin>1800</YOrigin><XYScale>10000</XYScale><ZOrigin>-100000</ZOrigin><ZScale>10000</ZScale><MOrigin>-100000</MOrigin><MScale>10000</MScale><XYTolerance>0.001</XYTolerance><ZTolerance>0.001</ZTolerance><MTolerance>0.001</MTolerance><HighPrecision>true</HighPrecision><WKID>29183</WKID><LatestWKID>29193</LatestWKID></ProjectedCoordinateSystem>
20250414
15331500
20250414
15331500
Microsoft Windows 10 Version 10.0 (Build 22631) ; Esri ArcGIS 13.4.0.55405
HidrografiaSP
File Geodatabase Feature Class
dataset
EPSG
7.6.8(9.2.0)
0
Simple
FALSE
0
TRUE
FALSE
HidrografiaSP
Feature Class
0
OBJECTID_1
OBJECTID_1
OID
4
0
0
Internal feature number.
Esri
Sequential unique whole numbers that are automatically generated.
Shape
Shape
Geometry
0
0
0
Feature geometry.
Esri
Coordinates defining the features.
OBJECTID
OBJECTID
Integer
4
0
0
hid_cd
hid_cd
String
200
0
0
hid_tp_el
hid_tp_el
String
150
0
0
hid_ft
hid_ft
String
50
0
0
hid_es
hid_es
String
20
0
0
hid_mi
hid_mi
String
20
0
0
hid_ni
hid_ni
Double
8
0
0
Shape_Leng
Shape_Leng
Double
8
0
0
Enabled
Enabled
Integer
4
0
0
STATUS
STATUS
Integer
4
0
0
CODCURSOAG
CODCURSOAG
String
19
0
0
Nome
Nome
String
200
0
0
Shape_Le_1
Shape_Le_1
Double
8
0
0
CodCurso_1
CodCurso_1
String
254
0
0
NomeCursoA
NomeCursoA
String
254
0
0
CodRecepto
CodRecepto
String
254
0
0
CLASSE
CLASSE
Double
8
0
0
OBSERVACAO
OBSERVACAO
String
50
0
0
Shape_Length
Shape_Length
Double
8
0
0
Length of feature in internal units.
Esri
Positive real numbers that are automatically generated.
20250414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