20220131
09114700
FALSE
20230918
09471600
20230918
09471600
S_LOMR
497364.314200
978397.099700
4741779.648600
5187754.452600
1
4.794
file://\\DWR305213D\C$\CTP.gdb
Local Area Network
002
Projected
GCS_North_American_1983
Linear Unit: Meter (1.000000)
<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/3.1.0'><WKT>PROJCS["NAD_1983_UTM_Zone_11N",GEOGCS["GCS_North_American_1983",DATUM["D_North_American_1983",SPHEROID["GRS_1980",6378137.0,298.257222101]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Transverse_Mercator"],PARAMETER["False_Easting",500000.0],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",-117.0],PARAMETER["Scale_Factor",0.9996],PARAMETER["Latitude_Of_Origin",0.0],UNIT["Meter",1.0],AUTHORITY["EPSG",26911]]</WKT><XOrigin>-5120900</XOrigin><YOrigin>-9998100</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>26911</WKID><LatestWKID>26911</LatestWKID></ProjectedCoordinateSystem>
NAD_1983_UTM_Zone_11N
Append Updates\S_LOMR "Working Layers\S_LOMR" "Use the field map to reconcile field differences" "DFIRM_ID "DFIRM_ID" true true false 6 Text 0 0,First,#,D:\WorkSpace\IdahoDigitizedFIRM\ID_Idaho_Effective_Various_20251203\ID_Idaho_Effective_Various.gdb\Flood\S_LOMR,DFIRM_ID,0,5;VERSION_ID "VERSION_ID" true true false 11 Text 0 0,First,#,D:\WorkSpace\IdahoDigitizedFIRM\ID_Idaho_Effective_Various_20251203\ID_Idaho_Effective_Various.gdb\Flood\S_LOMR,VERSION_ID,0,10;LOMR_ID "LOMR_ID" true true false 32 Text 0 0,First,#,D:\WorkSpace\IdahoDigitizedFIRM\ID_Idaho_Effective_Various_20251203\ID_Idaho_Effective_Various.gdb\Flood\S_LOMR,LOMR_ID,0,31;EFF_DATE "EFF_DATE" true true false 8 Date 0 0,First,#,D:\WorkSpace\IdahoDigitizedFIRM\ID_Idaho_Effective_Various_20251203\ID_Idaho_Effective_Various.gdb\Flood\S_LOMR,EFF_DATE,-1,-1;CASE_NO "CASE_NO" true true false 13 Text 0 0,First,#,D:\WorkSpace\IdahoDigitizedFIRM\ID_Idaho_Effective_Various_20251203\ID_Idaho_Effective_Various.gdb\Flood\S_LOMR,CASE_NO,0,12;SCALE "SCALE" true true false 5 Text 0 0,First,#,D:\WorkSpace\IdahoDigitizedFIRM\ID_Idaho_Effective_Various_20251203\ID_Idaho_Effective_Various.gdb\Flood\S_LOMR,SCALE,0,4;STATUS "STATUS" true true false 12 Text 0 0,First,#,D:\WorkSpace\IdahoDigitizedFIRM\ID_Idaho_Effective_Various_20251203\ID_Idaho_Effective_Various.gdb\Flood\S_LOMR,STATUS,0,11;SOURCE_CIT "SOURCE_CIT" true true false 21 Text 0 0,First,#,D:\WorkSpace\IdahoDigitizedFIRM\ID_Idaho_Effective_Various_20251203\ID_Idaho_Effective_Various.gdb\Flood\S_LOMR,SOURCE_CIT,0,20;GFID "GFID" true true false 36 Text 0 0,First,#,D:\WorkSpace\IdahoDigitizedFIRM\ID_Idaho_Effective_Various_20251203\ID_Idaho_Effective_Various.gdb\Flood\S_LOMR,GFID,0,35" # # # NOT_UPDATE_GEOMETRY
Append 16001C_LOMC89\S_LOMR "Working Layers\S_LOMR" "Use the field map to reconcile field differences" "DFIRM_ID "DFIRM_ID" true true false 6 Text 0 0,First,#,D:\WorkSpace\Projects\IdahoDigitizedFIRM\24_10_0118P_Final_Shapefiles\24_10_0118P_Final_Shapefiles\S_LOMR.shp,DFIRM_ID,0,5,16001C_LOMC89\S_LOMR,DFIRM_ID,0,5;VERSION_ID "VERSION_ID" true true false 11 Text 0 0,First,#,D:\WorkSpace\Projects\IdahoDigitizedFIRM\24_10_0118P_Final_Shapefiles\24_10_0118P_Final_Shapefiles\S_LOMR.shp,VERSION_ID,0,10,16001C_LOMC89\S_LOMR,VERSION_ID,0,10;LOMR_ID "LOMR_ID" true true false 32 Text 0 0,First,#,D:\WorkSpace\Projects\IdahoDigitizedFIRM\24_10_0118P_Final_Shapefiles\24_10_0118P_Final_Shapefiles\S_LOMR.shp,LOMR_ID,0,24,16001C_LOMC89\S_LOMR,LOMR_ID,0,24;EFF_DATE "EFF_DATE" true true false 8 Date 0 0,First,#,D:\WorkSpace\Projects\IdahoDigitizedFIRM\24_10_0118P_Final_Shapefiles\24_10_0118P_Final_Shapefiles\S_LOMR.shp,EFF_DATE,-1,-1,16001C_LOMC89\S_LOMR,EFF_DATE,-1,-1;CASE_NO "CASE_NO" true true false 13 Text 0 0,First,#,D:\WorkSpace\Projects\IdahoDigitizedFIRM\24_10_0118P_Final_Shapefiles\24_10_0118P_Final_Shapefiles\S_LOMR.shp,CASE_NO,0,12,16001C_LOMC89\S_LOMR,CASE_NO,0,12;SCALE "SCALE" true true false 5 Text 0 0,First,#,D:\WorkSpace\Projects\IdahoDigitizedFIRM\24_10_0118P_Final_Shapefiles\24_10_0118P_Final_Shapefiles\S_LOMR.shp,SCALE,0,4,16001C_LOMC89\S_LOMR,SCALE,0,4;STATUS "STATUS" true true false 12 Text 0 0,First,#,D:\WorkSpace\Projects\IdahoDigitizedFIRM\24_10_0118P_Final_Shapefiles\24_10_0118P_Final_Shapefiles\S_LOMR.shp,STATUS,0,11,16001C_LOMC89\S_LOMR,STATUS,0,11;SOURCE_CIT "SOURCE_CIT" true true false 21 Text 0 0,First,#,D:\WorkSpace\Projects\IdahoDigitizedFIRM\24_10_0118P_Final_Shapefiles\24_10_0118P_Final_Shapefiles\S_LOMR.shp,SOURCE_CIT,0,20,16001C_LOMC89\S_LOMR,SOURCE_CIT,0,20;GFID "GFID" true true false 36 Text 0 0,First,#" # # # NOT_UPDATE_GEOMETRY
1.0
ISO19139
150000000
5000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dataset
GIS Section
Idaho Department of Water Resources
322 East Front Street
Boise
Idaho
83720
gisinfo@idwr.idaho.gov
US
2082874000
2082876700
20230918
ISO 19115 Geographic Information - Metadata
DIS_ESRI1.0
002
withheld
Local Area Network
3.283
File Geodatabase
ArcMap 10.8
File Geodatabase Feature Class
ArcMap 10.8
4.794
Microsoft Windows 10 Version 10.0 (Build 19045) ; Esri ArcGIS 13.1.0.41833
Letter of Map Revision Boundaries
2021-10-01T00:00:00
2021-10-28T00:00:00
2021-10-28T00:00:00
2296229.680052
2340530.827806
1403752.218171
1325534.880506
1
0
0.000000
0.000000
-116.533353
-115.96007
43.817627
43.10313
1
1
-117.034567
-110.744856
46.843332
42.679519
0.000000
0.000000
This is an update of the digital FIRM information in the state of Idaho. This feature class shows areas depicting a Letter of Map Revision (LOMR) boundary.
<div style='text-align:Left;'><p>This is an update of the digital
FIRM information in the state of Idaho.
This feature class shows areas depicting a Letter of Map Revision (LOMR)
boundary. The FIRM is the basis for
floodplain management, mitigation, and insurance activities for the National Flood
Insurance Program (NFIP). Insurance applications include enforcement of the mandatory
purchase requirement of the Flood Disaster Protection Act, which "... requires the
purchase of flood insurance by property owners who are being assisted by Federal programs or by
Federally supervised, regulated or insured agencies or institutions in the acquisition or
improvement of land facilities located or to be located in identified areas having special
flood hazards," Section 2 (b) (4) of the Flood Disaster Protection Act of 1973. In
addition to the identification of Special Flood Hazard Areas (SFHAs), the risk zones shown on
the FIRMs are the basis for the establishment of premium rates for flood coverage
offered through the NFIP.</p>
<p style='margin-bottom:0in;'>This Database presents the flood
risk information depicted on the FIRM in a digital format suitable for use in
electronic mapping applications. This database has been created by digitizing
data from georeferenced paper FIRM maps in the Idaho counties specified by this
project. This data should be used as a
reference layer, not as an authoritative source.</p>
<p style='margin-bottom:0in;'> </p>
<p style='margin-bottom:0in;'>The Flood Insurance Rate Map
(FIRM) depicts flood risk information and supporting data used to develop the
risk data. The primary risk classifications used are the
1-percent-annual-chance flood event (A or AE) and the 0.2-percent-annual-
chance flood event (X). The FIRM data can be derived from Flood Insurance
Studies (FISs) and previously published Flood Insurance Rate Maps (FIRMs). The
FISs and FIRMs are published by the Federal Emergency Management Agency (FEMA).
This database has been created by digitizing data from georeferenced paper FIRM
maps and adding information from FIS where available. All FIRMs were
georeferenced at a 1:4000 scale or finer. This data should be used as a
reference layer, not as an authoritative source. </p>
<p style='margin-bottom:0in;'> </p>
<p style='margin-bottom:0in;'>Section 11 of FEMA's "Flood
Insurance Rate Map (FIRM) Database Technical Reference: Preparing Flood
Insurance Rate Map Databases (Nov. 2022)" document contains a detailed
description of each attribute code and a reference to other relevant information.</p>
<p style='margin-bottom:0in;'> </p>
<p style='margin-bottom:0in;'><a href='https://www.fema.gov/flood-maps/guidance-reports/guidelines-standards/technical-references-flood-risk-analysis-and-mapping' target='_blank'>https://www.fema.gov/flood-maps/guidance-reports/guidelines-standards/technical-references-flood-risk-analysis-and-mapping</a><br /></p>
<p style='margin-bottom:0in;'> </p>
<p style='margin-bottom:0in;'><a href='https://www.fema.gov/sites/default/files/documents/fema_firm-database-technical-reference_112022.pdf' target='_blank'>https://www.fema.gov/sites/default/files/documents/fema_firm-database-technical-reference_112022.pdf</a><br /></p><p><span></span></p></div>
FEMA Flood Hazard Zone
Special Flood Hazard Area
Digital Flood Insurance Rate Map
NFIP
Base Flood Elevation
SFHA
Flood Insurance Rate Map
FIRM
Floodway
<div style='text-align:Left;'><p><p>The hardcopy FIRM and the accompanying FISs are the official
designation of SFHAs and Base Flood Elevations (BFEs) for the NFIP. For the
purposes of the NFIP, changes to the flood risk information published by FEMA
may only be performed by FEMA and through the mechanisms established in the
NFIP regulations (44 CFR Parts 59-78). These digital data are produced in
conjunction with the hardcopy FIRMs and generally match the hardcopy map
exactly. However, the hardcopy flood maps and flood profiles are the
authoritative documents for the NFIP. Acknowledgement of FEMA would be
appreciated in products derived from these data.</p></p></div>
FEMA, IDWR, Custer County, Idaho
Floodplain Unit
Idaho Department of Water Resources
26
Idtm83
EPSG
6.11(3.0.1)
The DFIRM Database is made up of several data themes
containing both spatial and attribute information. These data together represent the current
flood risk for the subject area as identified by FEMA. The attribute tables include SFHA
locations, flood zone designations, BFEs, political entities, cross-section locations, FIRM
panel information, and other data related to the NFIP.
Section 11 of FEMA's "Flood Insurance Rate Map (FIRM) Database Technical Reference: Preparing Flood Insurance
Rate Map Databases (Nov. 2022)" document contains a detailed description of each attribute code and a reference
to other relevant information.
https://www.fema.gov/flood-maps/guidance-reports/guidelines-standards/technical-references-flood-risk-analysis-and-mapping
https://www.fema.gov/sites/default/files/documents/fema_firm-database-technical-reference_112022.pdf
The following tables are included in this data set:
L_Comm_Info
L_Stn_Start
Study_Info
S_bfe
S_firm_pan
S_fld_haz_ar
S_fld_haz_ln
S_gen_struct
S_label_pt
S_perm_bmk
S_plss_ln
S_pol_ar
S_pol_ln
S_quad_index
S_trnsport_ln
S_wtr_ln
S_xs
SOURCE_CIT
SOURCE_CIT
String
21
0
0
OBJECTID
OBJECTID
OID
4
0
0
Internal feature number.
Esri
Sequential unique whole numbers that are automatically generated.
S_LOMR
Feature Class
26
DFIRM_ID
DFIRM_ID
String
6
0
0
VERSION_ID
VERSION_ID
String
11
0
0
Shape
SHAPE
Geometry
0
Feature geometry.
ESRI
Coordinates defining the features.
0
0
Shape_Length
Shape_Length
Double
8
0
0
Length of feature in internal units.
Esri
Positive real numbers that are automatically generated.
LOMR_ID
LOMR_ID
String
32
0
0
EFF_DATE
EFF_DATE
Date
8
0
0
CASE_NO
CASE_NO
String
13
0
0
SCALE
SCALE
String
5
0
0
STATUS
STATUS
String
12
0
0
Shape_Area
Shape_Area
Double
8
0
0
Area of feature in internal units squared.
Esri
Positive real numbers that are automatically generated.
GFID
GFID
String
36
0
0
Simple
FALSE
26
TRUE
FALSE