20190214
11204400
1.0
FGDC CSDGM Metadata
FALSE
20241115
13185400
ItemDescription
IrrigatedLands_1986
0.000
file://\\dwrboifsvp03\GISData\Spatial\LandCover_Vegetation\SnakePlain\ESPA_IrrigatedLands\IrrigatedLands.gdb
Local Area Network
2396391.017200
2740864.524400
1199411.123400
1519765.119100
1
002
Projected
GCS_North_American_1983
Linear Unit: Meter (1.000000)
NAD_1983_Idaho_TM
<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/10.8'><WKT>PROJCS["NAD_1983_Idaho_TM",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",2500000.0],PARAMETER["False_Northing",1200000.0],PARAMETER["Central_Meridian",-114.0],PARAMETER["Scale_Factor",0.9996],PARAMETER["Latitude_Of_Origin",42.0],UNIT["Meter",1.0],AUTHORITY["EPSG",8826]]</WKT><XOrigin>-3120900</XOrigin><YOrigin>-13447900</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>102605</WKID><LatestWKID>8826</LatestWKID></ProjectedCoordinateSystem>
RepairGeometry D:\Topology_Checks\ESPA_check_20180803\ESPA_IrrigatedLands\IrrigatedLands.gdb\EasternSnakePlainAquifer\IrrigatedLands_1986_ESPA DELETE_NULL
RepairGeometry D:\Topology_Checks\ESPA_check_20180803\ESPA_IrrigatedLands\IrrigatedLands.gdb\EasternSnakePlainAquifer\IrrigatedLands_1986_ESPA DELETE_NULL
20241115
13185400
150000000
5000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Geospatial Technology Section
Idaho Department of Water Resources
GIS
Geospatial Technology Section
322 East Front Street
Boise
Idaho
83720
gisinfo@idwr.idaho.gov
(208) 287-4800
(208) 287-6700
8:00 AM - 5:00 PM
Geospatial Technology Section
Idaho Department of Water Resources
GIS
Geospatial Technology Section
322 East Front Street
Boise
Idaho
83720
gisinfo@idwr.idaho.gov
(208) 287-4800
(208) 287-6700
8:00 AM - 5:00 PM
1986-01-01T00:00:00
1986-12-31T00:00:00
https://data-idwr.opendata.arcgis.com/pages/gis-data#IrrigatedLands
File Geodatabase Feature Class
Environment
Groundwater
Human
Hydrology
IDWR GIS Department
Irrigated Areas
Irrigation
Monitoring
Non-Irrigated
Regulatory
Semi-Irrigated
Surface Water
Water
Water Use
>
Eastern Snake Plain Aquifer, ESPA
Idaho, ID
>
Agriculture
Eastern Snake Plain Aquifer
ESPA
Environment
Farming
Groundwater
Human
Hydrology
IDWR GIS Department
Idaho
ID
Irrigated Areas
Irrigation
Monitoring
Non-Irrigated
Regulatory
Semi-Irrigated
Surface Water
Water
Water Use
Idaho Department of Water Resources (IDWR)
<div style='text-align:Left;'><div><div><p><span>Access and Use Constraint: The Idaho Department of Water Resources is making this data available as a public service. The Idaho Department of Water Resources strives to ensure that all technical data and other information made available to the public is accurate, complete and in conformance with the Idaho Public Records Act. Neither the Department of Water Resources nor the State of Idaho, however, assumes any legal responsibility for the accuracy or completeness of the information contained on this site. Persons using information from this site for official purposes, or other purposes, for which accuracy and completeness are required, are hereby notified that they should first verify the information with the public records or other primary sources from which the information was obtained.</span></p><p><span>Please check sources, scale, accuracy, currentness and other available information. Please confirm that you are using the most recent copy of both data and metadata. Acknowledgement of IDWR in any products derived from this dataset is appreciated.</span></p><p><span /></p><p><span /></p></div></div></div>
Distribution Liability: The Idaho Department of Water Resources is making this data available as a public service. The Idaho Department of Water Resources strives to ensure that all technical data and other information made available to the public is accurate, complete and in conformance with the Idaho Public Records Act. Neither the Department of Water Resources nor the State of Idaho, however, assumes any legal responsibility for the accuracy or completeness of the information contained on this site. Persons using information from this site for official purposes, or other purposes, for which accuracy and completeness are required, are hereby notified that they should first verify the information with the public records or other primary sources from which the information was obtained.
Acknowledgment of IDWR would be appreciated in any work derived from this dataset.
1986 Irrigated Lands for the Eastern Snake Plain Aquifer: Hand-Digitized Generated
Geospatial Technology Section
Idaho Department of Water Resources
GIS
Geospatial Technology Section
322 East Front Street
Boise
Idaho
83720
gisinfo@idwr.idaho.gov
(208) 287-4800
(208) 287-6700
8:00 AM - 5:00 PM
Geospatial Technology Section
2019-02-14T00:00:00
First Edition
First Series
This dataset was generated for use in the calculation of recharge and evapotranspiration in order to calibrate the Eastern Snake Plain Aquifer Hydrologic Model.
<div style='text-align:Left;'><div><div><p><span>This layer depicts polygons representing land within the ESPA boundary classified as either "irrigated", "non-irrigated" or "semi-irrigated", where the semi-irrigated classification typically depicts residential land. </span></p><p><span>The creation of this dataset is a multi-year effort. The original line work that was used as a basis to create this dataset, is the Farm Service Agency’s (FSA) 2006 Common Land Unit (CLU) dataset, which is the most recent year the FSA distributed this data to the public. Project time constraints during the development of this dataset required acceptance of "less-than-perfectly-accurate" line work. In essence, line work deemed "close enough" to ground truth is acceptable for Eastern Snake Plain Aquifer (ESPA) modeling purposes. Field boundaries were then further refined using National Agriculture Imagery Program (NAIP) imagery, Digital Ortho Photo Quadrangle (DOQQ) imagery, or other high resolution imagery. </span></p><p><span>Attribute assignments for irrigation status (irrigated, non-irrigated, and semi-irrigated) are determined using available Landsat imagery as background reference. Landsat imagery is typically 30-meter (Landsat5) or 15-meter (Landsat7) resolution. National Agriculture Inventory Program (NAIP) imagery, Digital Ortho Photo Quadrangle (DOQQ) imagery, and other in-house, scanned aerial imagery is used for determining irrigation status and refining the polygon geometry. The interpretation and classification process is described in detail in the report, "2006 Irrigated Land Classification for the Eastern Snake Plain Aquifer" archived on the IDWR website: Legal Actions > Delivery Call Actions > SWC > Archived Matters > Technical Working Group Documents (https://idwr.idaho.gov/legal-actions/delivery-call-actions/SWC/archived-matters.html#twg-documents)</span></p><p><span>While data accuracy is highest inside the Eastern Snake Plain Aquifer Model boundary (ESPAM version 2), the layer does extend beyond the ESPAM2 boundary.</span></p></div></div></div>
10000
Version 6.2 (Build 9200) ; Esri ArcGIS 10.9.1.28388
1
-115.311656
-110.952490
44.879291
41.957893
Ground condition/irrigation status for the 1986 growing season
1986-05-01T00:00:00
1986-11-30T00:00:00
The key attribute is "STATUS_1986". The interpretation and classification process is described in detail in the report titled "2006 Irrigated Land Classification for the Eastern Snake Plain Aquifer" archived on the IDWR website: Legal Actions > Delivery Call Actions > SWC > Archived Matters > Technical Working Group Documents (https://idwr.idaho.gov/legal-actions/delivery-call-actions/SWC/archived-matters.html#twg-documents)
Geospatial Technology Section
Idaho Department of Water Resources
GIS
Geospatial Technology Section
322 East Front Street
Boise
Idaho
83720
gisinfo@idwr.idaho.gov
(208) 287-4800
(208) 287-6700
8:00 AM - 5:00 PM
Geospatial Technology Section
Irrigation status is determined using 1986 Landsat imagery for the following dates:
Path39Row29: 06-06, 06-22, 07-24, 08-09, 09-10, 10-12 and
Path39Row30: 06-06, 06-22, 08-09, 09-10, 10-12 and
Path40Row29: 05-12, 06-13, 06-29, 07-31, 09-01, 09-17, 10-03 and
Path40Row30: 05-12, 05-28, 06-13, 06-29, 07-31, 09-01, 09-17, 10-03, 11-04.
The creation of this dataset is a multi-year effort. Original linework is from the Farm Service Agency's (FSA) Common Land Unit (CLU) dataset of or around 2006. FSA no longer distributes this data to the public. Project time constraints require acceptance of "less-than-perfectly-accurate" linework. In essence, line work deemed "close enough" to ground truth is acceptable for Eastern Snake Plain Aquifer (ESPA) modeling purposes. Attribute assignments for irrigation status (irrigated, non-irrigated, and semi-irrigated) are determined using available Landsat imagery as background reference. Landsat imagery is typically 30-meter (l5) resolution. National Agriculture Inventory Program (NAIP) imagery, Digital Ortho Photo Quadrangle (DOQQ) imagery, and other in-house, scanned aerial imagery is used for determining irrigation status and refining linework geometry. This dataset extends beyond the Eastern Snake Plain Aquifer Model boundary (ESPAM2). Line and attribute correctness is more accurate within ESPAM2 boundary. Landsat imagery available for the 1986 agricultural growing season was sparse due to cloudy conditions. Subsequently, some fields may be misclassified; however, every attempt was made by IDWR staff to minimize classification errors.
2014-07-08T00:00:00
Correct overlapping polygon topology errors *slightly overlapping polygons still exist, typically along pivot edges and/or roads
Check Geometry Tool
Repair Geometry Tool
Delete slivers < 1 m2
Eliminate slivers < 30 m2
2018-08-13T00:00:00
Positional Accuracy requirements are determined by its use in the ESPA modelling process which accepts "less-than-perfectly accurate" horizontal accuracy. However, given any time time constraints, efforts are made to refine positional accuracy based on NAIP and DOQQ imagery.
Attribute assignments for irrigation status (irrigated, non-irrigated, and semi-irrigated) are determined using available Landsat imagery as background reference. Landsat imagery is typically 30-meter (l5) or 15-meter (l7) resolution. National Agriculture Inventory Program (NAIP) imagery, Digital Ortho Photo Quadrangle (DOQQ) imagery, and other in-house, scanned aerial imagery is used for determining irrigation status and refining linework geometry. Hence, attribute accuracy is determined by the scale of those sources.
The data layer consists of polygon features attributed by GIS analysts based on visual interpretation of remote sensing and aerial imagery as well as supplemental information provided in the water rights database.
Concentrated animal feeding operations are identified using Landsat and NAIP imagery in the 2011 and later Irrigated Lands Data layers.
A topology check was performed to repair overlapping polygons and data gaps of consequential size.
The data layer consists of polygon features attributed by GIS analysts based on visual interpretation of remote sensing and aerial imagery as well as supplemental information provided in the water rights database.
Concentrated animal feeding operations are classified as semi-irrigated in the 2011 and later Irrigated Lands Data layers.
Overlapping polygons and data gaps of consequential size were minimized to the best of the analysts ability under existing time constraints.
While data accuracy and completeness is highest inside the Eastern Snake Plain Aquifer Model boundary (ESPAM version 2), the layer does extend beyond the ESPAM2 boundary and may or may not extend to the county line.
While data accuracy and completeness is highest inside the Eastern Snake Plain Aquifer Model boundary (ESPAM version 2), the layer does extend beyond the ESPAM2 boundary and may or may not extend to the county line.
Irrigated Lands Attribute Information
Feature Class
241700
OBJECTID
OBJECTID
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.
ACRES
Acres
Number of acres contained in the the polygon
IDWR
Double
8
0
0
STATUS_1986
Status 1986
Irrigation Status in 1986. Values are either "irrigated", "non-irrigated" or "semi-irrigated"
IDWR
String
25
0
0
irrigated
Area shows evidence of being irrigated
IDWR
non-irrigated
Area does not show evidence of being irrigated
IDWR
semi-irrigated
Residential area
IDWR
Shape_Length
Shape_Length
Double
8
0
0
Length of feature in internal units.
Esri
Positive real numbers that are automatically generated.
Shape_Area
Shape_Area
Double
8
0
0
Area of feature in internal units squared.
Esri
Positive real numbers that are automatically generated.
dataset
EPSG
9.5.1(10.8.0)
241700
Simple
FALSE
241700
TRUE
FALSE
20241115