20190214
11513600
1.0
FGDC CSDGM Metadata
FALSE
20241115
13265000
150000000
5000
FGDC
IrrigatedLands_2009
002
0.000
2396391.017200
2740864.524400
1199411.123400
1519765.119100
1
file://\\dwrboifsvp03\GISData\Spatial\LandCover_Vegetation\SnakePlain\ESPA_IrrigatedLands\IrrigatedLands.gdb
Local Area Network
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>
20241115
13265000
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
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
>
Eastern Snake Plain Aquifer
ESPA
Environment
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></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.
2009 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
2014-06-30T00:00:00
2019-02-14T00:00:00
2019-02-14T00:00:00
First Edition
First Series
Version 6.2 (Build 9200) ; Esri ArcGIS 10.9.1.28388
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
Irrigation status for the 2009 growing season.
-115.311656
-110.952490
41.957893
44.879291
2009-05-01T00:00:00
2009-11-30T00:00:00
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
1
-115.311656
-110.952490
44.879291
41.957893
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
2009-01-01T00:00:00
2009-01-01T00:00:00
https://data-idwr.opendata.arcgis.com/pages/gis-data#IrrigatedLands
0.000
File Geodatabase Feature Class
dataset
EPSG
9.5.1(10.8.0)
222520
Simple
FALSE
222520
TRUE
FALSE
Irrigated Lands Attribute Information
Feature Class
222520
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_2009
STATUS 2009
Irrigation Status in 2009. Values are either "irrigated", "non-irrigated" or "semi-irrigated"
irrigated
Area shows evidence of being irrigated
IDWR
non-irrigated
Area does not show evidence of being irrigated
IDWR
semi-irrigated
Residential area
IDWR
String
25
0
0
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.
20241115
Irrigation status is determined using 2009 Landsat imagery for the following dates:
Path39Row29: 05-28, 06-29, 07-07, 07-23, 08-24, 09-09, 09-17, 10-03
Path39Row30: 05-28, 06-29, 07-07, 07-15, 07-23, 07-31, 08-16, 08-24, 09-01, 09-09, 09-17, 09-25
Path40Row29: 05-27, 06-28, 07-30, 08-15, 09-16
Path40Row30: 05-27, 06-12, 06-28, 07-06, 07-14, 07-22, 07-30, 08-15, 08-31, 09-08, 09-16, 09-24
Path40Row31: 06-04, 07-06, 07-22, 09-08, 09-24.
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.
2013-01-14T00:00:00
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.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