A subset of the Wyandotte County, Kansas tax map parcel polygon feature dataset in ESRI GIS format in Kansas North State Plane NAD83 coordinates, units feet, suitable for use at 1:1200 map scale or smaller. This subset contains only parcels owned by the Wyandotte County Land Bank. The goal of the Wyandotte County Land Bank is to return tax delinquent property to productive use that benefits the community. This layer may include properties in all parts of Wyandotte County, including the cities of Kansas City Kansas, Bonner Springs, Edwardsville, and that portion of City of Lake Quivira in Wyandotte Co. Attributes include the county parcel number (PARCEL and PARCEL_NBR) and Acres (ACRE). Multifarious property and ownership information in separate county taxroll and CAMA databases have been joined to the county parcel number for more complete attribution. Line features represent ownership boundaries per source materials (deed, plat, legal description, etc.) and are approximations of true ownership lines. Not included in this dataset are plat lot and block # designations, subdivision boundaries across ROW, ROW polys, easements, multi-story condominium property boundaries, or lot dimensions.

The 2005 Kansas Land Cover Patterns (KLCP) Mapping Initiative was a two-phase mapping endeavor that occurred over a three-year period (2007-2009). Note that while the processing occurred during the 2207-2009 period, all satellite data used in the project was acquired in 2005. Concurrent with mapping the state of Kansas, the Kansas River Watershed was also mapped. The Kansas River Watershed extends into southern Nebraska and includes a portion of eastern Colorado. During Phase I a Modified Level I map was produced. In Phase II a series of maps, Modified Level II through IV, were produced. All KLCP 2005 map products were produced at four spatial extents: the state of Kansas plus a 300 meter buffer, a DEM-derived watershed boundary of the Kansas River, the Kansas River watershed boundary plus a 1,000 meter buffer, and a combined dataset of the state of Kansas plus 300 meter buffer and the watershed plus 1,000 meter buffer.These extents are annotated in the file names with the extentions k, w, wb, and kwb respectively.

The goal of Phase II was to map subclasses for grassland and cropland, classes which were mapped during Phase I. For the Level II map, cool- and warm-season grasslands were mapped along with Spring Crop, Summer Crop, Alfalfa, Fallow, and Double-Crop classes. For the Level III map, the Summer Crop subclasses Corn, Soybean, and Sorghum were mapped, and the Spring Crop class was reassigned to Winter Wheat. In the Level IV map, irrigation status was mapped and added to the Level III crop type map.The Kansas Land Cover Patterns Level IV map contains twenty-four land use/land cover classes and has a positional accuracy and spatial resolution appropriate for producing 1:50,000 scale maps. The minimum map unit (MMU) varies by land cover class and ranges from 0.22 to 5.12 acres.

In general, the mapping methodology used a hybrid, hierarchical classification of multi-temporal, multi-resolution imagery to develop modified Anderson Level II through Anderson Level IV land cover maps of the Kansas River Watershed and the State of Kansas. More specifically, multi-seasonal Landsat Thematic Mapper (TM) imagery from the 2004 and 2005 growing season was used to map the grassland subclasses (cool- and warm-season grasslands). while MODIS NDVI time-series imagery from the 2005 growing season was used to map cropland subclasses.

The land use/land cover classes in the Level IV map are coded hierarchically to allow aggregation of land use and land cover classes as needed by the end-user. For example, a user can aggregate the Level IV map classes to a Level III classification by ignoring or eliminating the last digit of each land use/land cover class. Likewise, a Level II and Level I map can be created from the Level IV map by eliminating the last two and three digits, respectively, from each Level IV land use/land cover class.

A formal accuracy assessment found the Level II, Level III, and Level IV maps to have overall accuracy levels of 86.3%, 82.0%, and 74.3%, respectively. User and Producer (per-class errors of commission and omission) accuracies vary by land cover class and users are encouraged to reference the reported accuracy levels in the final report and/or metadata when using the Kansas Land Cover Patterns map series. Digital versions of the map, metadata, and accuracy assessment can be accessed from the Data Access Support Center (http://www.kansasgis.org/) or the Kansas Applied Remote Sensing Program (http://www.kars.ku.edu/).

This database was developed as part of the Core Database for the State of Kansas. It is suited for county-level and watershed-level analysis that involve land use and land cover.

[Summary provided by the Kansas Applied Remote Sensing, KARS, at the Kansas Biological Survey.]

Land Parcels mapped with Parcel Number and Acreage.By using this dataset you acknowledge the following:Kansas Open Records Act StatementThe Kansas Open Records Act provides in K.S.A. 45-230 that "no person shall knowingly sell, give or receive, for the purpose of selling or offering for sale, any property or service to persons listed therein, any list of names and addresses contained in, or derived from public records..." Violation of this law may subject the violator to a civil penalty of $500.00 for each violation. Violators will be reported for prosecution.By accessing this site, the user makes the following certification pursuant to K.S.A. 45-220(c)(2): "The requester does not intend to, and will not: (A) Use any list of names or addresses contained in or derived from the records or information for the purpose of selling or offering for sale any property or service to any person listed or to any person who resides at any address listed; or (B) sell, give or otherwise make available to any person any list of names or addresses contained in or derived from the records or information for the purpose of allowing that person to sell or offer for sale any property or service to any person listed or to any person who resides at any address listed."

Shows links to Kansas county websites, GIS websites, and parcel search websites where available. Some parcel search websites are password protected. Data is updated as new or corrected information is found or reported. Please report any updated or erroneous links to DASC at kgs.ku.edu.The full Kansas geospatial catalog is administered by the Kansas Data Access & Support Center (DASC) and can be found at the following URL: https://hub.kansasgis.org/

description: The 2005 Kansas Land Cover Patterns map represents Phase 1 of a two-phase mapping initiative occurring over a three-year period. The map is designed to be explicitly comparable to the 1990 Kansas Land Cover Patterns map. Using a similar methodology to produce the 2005 Kansas Land Cover Patterns map provides opportunities to identify and examine how the Kansas landscape has changed over a 15-year period. The map contains eleven land use/land cover classes. The positional accuracy and spatial resolution of the map are appropriate for producing 1:50,000 scale maps. The map is not intended to define precise boundaries between landscape features and while the source data has a spatial resolution of 30 m x 30 m, the minimum map unit varies by land cover class and ranges between 0.22 to 5.12 acres (see below). The formal accuracy assessment reports the map to have an overall accuracy level of 90.72%. User and Producer accuracies vary by land cover class and rural classes have higher accuracy levels (88-95%) than urban classes (48-78%). Users are encouraged to reference the reported accuracy levels in this report and/or metadata when using the 2005 Kansas Land Cover Patterns map. Digital versions of the map, metadata, and accuracy assessment can be accessed from the Data Access Support Center (DASC) website of the Kansas Geological Survey (http://www.kansasgis.org/) or the website of the Kansas Applied Remote Sensing Program (http://kars.ku.edu/).; abstract: The 2005 Kansas Land Cover Patterns map represents Phase 1 of a two-phase mapping initiative occurring over a three-year period. The map is designed to be explicitly comparable to the 1990 Kansas Land Cover Patterns map. Using a similar methodology to produce the 2005 Kansas Land Cover Patterns map provides opportunities to identify and examine how the Kansas landscape has changed over a 15-year period. The map contains eleven land use/land cover classes. The positional accuracy and spatial resolution of the map are appropriate for producing 1:50,000 scale maps. The map is not intended to define precise boundaries between landscape features and while the source data has a spatial resolution of 30 m x 30 m, the minimum map unit varies by land cover class and ranges between 0.22 to 5.12 acres (see below). The formal accuracy assessment reports the map to have an overall accuracy level of 90.72%. User and Producer accuracies vary by land cover class and rural classes have higher accuracy levels (88-95%) than urban classes (48-78%). Users are encouraged to reference the reported accuracy levels in this report and/or metadata when using the 2005 Kansas Land Cover Patterns map. Digital versions of the map, metadata, and accuracy assessment can be accessed from the Data Access Support Center (DASC) website of the Kansas Geological Survey (http://www.kansasgis.org/) or the website of the Kansas Applied Remote Sensing Program (http://kars.ku.edu/).

Kansas Senate District boundary lines within Wyandotte County, Kansas, including Kansas City, KS, Bonner Springs, KS, Edwardsville, KS that portion of Lake Quivira, KS within Wyandotte County, and the unincorporated remnant of Delaware Township. Also includes portions of District 6 and 10 that extend into Johnson County, Kansas In addition to District 7 that extends into Leavenworth County, Kansas. GIS polygon feature layer dataset derived from ward and precinct data. Represents present-day boundaries.By using this dataset you acknowledge the following:Kansas Open Records Act StatementThe Kansas Open Records Act provides in K.S.A. 45-230 that "no person shall knowingly sell, give or receive, for the purpose of selling or offering for sale, any property or service to persons listed therein, any list of names and addresses contained in, or derived from public records..." Violation of this law may subject the violator to a civil penalty of $500.00 for each violation. Violators will be reported for prosecution.By accessing this site, the user makes the following certification pursuant to K.S.A. 45-220(c)(2): "The requester does not intend to, and will not: (A) Use any list of names or addresses contained in or derived from the records or information for the purpose of selling or offering for sale any property or service to any person listed or to any person who resides at any address listed; or (B) sell, give or otherwise make available to any person any list of names or addresses contained in or derived from the records or information for the purpose of allowing that person to sell or offer for sale any property or service to any person listed or to any person who resides at any address listed."

The USGS Protected Areas Database of the United States (PAD-US) is the nation's inventory of protected areas, including public open space and voluntarily provided, private protected areas, identified as an A-16 National Geospatial Data Asset in the Cadastral Theme (http://www.fgdc.gov/ngda-reports/NGDA_Datasets.html). PAD-US is an ongoing project with several published versions of a spatial database of areas dedicated to the preservation of biological diversity, and other natural, recreational or cultural uses, managed for these purposes through legal or other effective means. The geodatabase maps and describes public open space and other protected areas. Most areas are public lands owned in fee; however, long-term easements, leases, and agreements or administrative designations documented in agency management plans may be included. The PAD-US database strives to be a complete “best available” inventory of protected areas (lands and waters) including data provided by managing agencies and organizations. The dataset is built in collaboration with several partners and data providers (http://gapanalysis.usgs.gov/padus/stewards/). See Supplemental Information Section of this metadata record for more information on partnerships and links to major partner organizations. As this dataset is a compilation of many data sets; data completeness, accuracy, and scale may vary. Federal and state data are generally complete, while local government and private protected area coverage is about 50% complete, and depends on data management capacity in the state. For completeness estimates by state: http://www.protectedlands.net/partners. As the federal and state data are reasonably complete; focus is shifting to completing the inventory of local gov and voluntarily provided, private protected areas. The PAD-US geodatabase contains over twenty-five attributes and four feature classes to support data management, queries, web mapping services and analyses: Marine Protected Areas (MPA), Fee, Easements and Combined. The data contained in the MPA Feature class are provided directly by the National Oceanic and Atmospheric Administration (NOAA) Marine Protected Areas Center (MPA, http://marineprotectedareas.noaa.gov ) tracking the National Marine Protected Areas System. The Easements feature class contains data provided directly from the National Conservation Easement Database (NCED, http://conservationeasement.us ) The MPA and Easement feature classes contain some attributes unique to the sole source databases tracking them (e.g. Easement Holder Name from NCED, Protection Level from NOAA MPA Inventory). The "Combined" feature class integrates all fee, easement and MPA features as the best available national inventory of protected areas in the standard PAD-US framework. In addition to geographic boundaries, PAD-US describes the protection mechanism category (e.g. fee, easement, designation, other), owner and managing agency, designation type, unit name, area, public access and state name in a suite of standardized fields. An informative set of references (i.e. Aggregator Source, GIS Source, GIS Source Date) and "local" or source data fields provide a transparent link between standardized PAD-US fields and information from authoritative data sources. The areas in PAD-US are also assigned conservation measures that assess management intent to permanently protect biological diversity: the nationally relevant "GAP Status Code" and global "IUCN Category" standard. A wealth of attributes facilitates a wide variety of data analyses and creates a context for data to be used at local, regional, state, national and international scales. More information about specific updates and changes to this PAD-US version can be found in the Data Quality Information section of this metadata record as well as on the PAD-US website, http://gapanalysis.usgs.gov/padus/data/history/.) Due to the completeness and complexity of these data, it is highly recommended to review the Supplemental Information Section of the metadata record as well as the Data Use Constraints, to better understand data partnerships as well as see tips and ideas of appropriate uses of the data and how to parse out the data that you are looking for. For more information regarding the PAD-US dataset please visit, http://gapanalysis.usgs.gov/padus/. To find more data resources as well as view example analysis performed using PAD-US data visit, http://gapanalysis.usgs.gov/padus/resources/. The PAD-US dataset and data standard are compiled and maintained by the USGS Gap Analysis Program, http://gapanalysis.usgs.gov/ . For more information about data standards and how the data are aggregated please review the “Standards and Methods Manual for PAD-US,” http://gapanalysis.usgs.gov/padus/data/standards/ .

Download this data or get more information. This data publication contains 2015 high-resolution land cover data for each of the 105 counties within Kansas. These data are a digital representation of land cover derived from 1-meter aerial imagery from the National Agriculture Imagery Program (NAIP). There is a separate file for each county. Data are intended for use in rural areas and therefore do not include land cover in cities and towns. Land cover classes (tree cover, other land cover, water, or city/town) were mapped using an object-based image analysis approach and supervised classification.This record was taken from the USDA Enterprise Data Inventory that feeds into the https://data.gov catalog. Data for this record includes the following resources: ISO-19139 metadata ArcGIS Hub Dataset ArcGIS GeoService For complete information, please visit https://data.gov.

The information and data included on the Shawnee County GIS Web Mapping Service has been created and compiled by County staff from a variety of sources, and are subject to change without notice. Shawnee County makes no warranties or representations whatsoever regarding the quality, content, completeness, or adequacy of such information and data. SHAWNEE COUNTY DIGITAL INFORMATION IS PREPARED FOR REFERENCE PURPOSES OR COUNTY TAX ASSESSMENT PURPOSES ONLY AND SHOULD NOT BE USED, AND IS NOT INTENDED FOR SURVEY OR ENGINEERING PURPOSES, OR TO SERVE AS ANY SORT OF LEGAL FORM OF CONVEYANCE OR BOUNDARY SURVEY. By use of these map products, map applications, or data the user accepts data with all faults, and assumes all responsibility for the use thereof, and further covenants and agrees to hold Shawnee County, its employees and officials, harmless from and against all damages, loss, or liability arising from any use of this map product, in consideration of Shawnee County’s effort to make this information available. All Data are projected in NAD 83 Kansas State Plane North Coordinates.

This map is from the 1954 Preliminary appraisal report for the Great Salt Marsh National Wildlife Refuge, known today as Quivira National Wildlife Refuge, in Stafford and Reno counties, Kansas. This map shows ownership and cover type of the proposed refuge. The original map was georeferenced against Stafford County NAIP (2012) imagery. Fifteen points were used in the georeferencing process, and large landmarks such as intersections were used a reference points. It represents the refuge landuse and ownership 3 years prior to the establishment of Quivira National Wildlife Refuge. This image allows a great look back in time to interpret habitat types and land use patterns. Pixel resolution of this image is 3 meters. This image and map should be used for resource-level interpretation only. This reference contains a PDF of the preliminary appraisal landuse map, and a georeferenced map.

Dickinson County KS Parcel Search containing various layers to find and view property within the county.

This dataset combines the work of several different projects to create a seamless data set for the contiguous United States. Data from four regional Gap Analysis Projects and the LANDFIRE project were combined to make this dataset. In the northwestern United States (Idaho, Oregon, Montana, Washington and Wyoming) data in this map came from the Northwest Gap Analysis Project. In the southwestern United States (Colorado, Arizona, Nevada, New Mexico, and Utah) data used in this map came from the Southwest Gap Analysis Project. The data for Alabama, Florida, Georgia, Kentucky, North Carolina, South Carolina, Mississippi, Tennessee, and Virginia came from the Southeast Gap Analysis Project and the California data was generated by the updated California Gap land cover project. The Hawaii Gap Analysis project provided the data for Hawaii. In areas of the county (central U.S., Northeast, Alaska) that have not yet been covered by a regional Gap Analysis Project, data from the Landfire project was used. Similarities in the methods used by these projects made possible the combining of the data they derived into one seamless coverage. They all used multi-season satellite imagery (Landsat ETM+) from 1999-2001 in conjunction with digital elevation model (DEM) derived datasets (e.g. elevation, landform) to model natural and semi-natural vegetation. Vegetation classes were drawn from NatureServe's Ecological System Classification (Comer et al. 2003) or classes developed by the Hawaii Gap project. Additionally, all of the projects included land use classes that were employed to describe areas where natural vegetation has been altered. In many areas of the country these classes were derived from the National Land Cover Dataset (NLCD). For the majority of classes and, in most areas of the country, a decision tree classifier was used to discriminate ecological system types. In some areas of the country, more manual techniques were used to discriminate small patch systems and systems not distinguishable through topography. The data contains multiple levels of thematic detail. At the most detailed level natural vegetation is represented by NatureServe's Ecological System classification (or in Hawaii the Hawaii GAP classification). These most detailed classifications have been crosswalked to the five highest levels of the National Vegetation Classification (NVC), Class, Subclass, Formation, Division and Macrogroup. This crosswalk allows users to display and analyze the data at different levels of thematic resolution. Developed areas, or areas dominated by introduced species, timber harvest, or water are represented by other classes, collectively refered to as land use classes; these land use classes occur at each of the thematic levels. Raster data in both ArcGIS Grid and ERDAS Imagine format is available for download at http://gis1.usgs.gov/csas/gap/viewer/land_cover/Map.aspx Six layer files are included in the download packages to assist the user in displaying the data at each of the Thematic levels in ArcGIS. In adition to the raster datasets the data is available in Web Mapping Services (WMS) format for each of the six NVC classification levels (Class, Subclass, Formation, Division, Macrogroup, Ecological System) at the following links. http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Class_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Subclass_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Formation_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Division_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Macrogroup_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_Ecological_Systems_Landuse/MapServer

By using this dataset you acknowledge the following:Kansas Open Records Act StatementThe Kansas Open Records Act provides in K.S.A. 45-230 that "no person shall knowingly sell, give or receive, for the purpose of selling or offering for sale, any property or service to persons listed therein, any list of names and addresses contained in, or derived from public records..." Violation of this law may subject the violator to a civil penalty of $500.00 for each violation. Violators will be reported for prosecution.By accessing this site, the user makes the following certification pursuant to K.S.A. 45-220(c)(2): "The requester does not intend to, and will not: (A) Use any list of names or addresses contained in or derived from the records or information for the purpose of selling or offering for sale any property or service to any person listed or to any person who resides at any address listed; or (B) sell, give or otherwise make available to any person any list of names or addresses contained in or derived from the records or information for the purpose of allowing that person to sell or offer for sale any property or service to any person listed or to any person who resides at any address listed."

Summary: This dataset serves as a core reference layer in support of the Unified Government's Enterprise GIS (E-GIS). It is used for visualization, query, analysis, and address matching/geocoding of road network. It is also used by the Unified Government's CAD (Computer Aided Dispatch) 9-1-1 system as geographic location aid, and is also shared with Kansas City area's Mid America Regional Council regional E9-1-1 emergency response system.Description: Best cartographic rendering at map scale 1:6000 or smaller. Contains federal, state, county, and city roads, park drives, cemetery drives, plus private roads, ramps, service roads, alleys, and some private drives. Includes street name directional prefix, street name proper, and street type attribution, along with theoretical block address range information. Roads are depicted as a single line in center of pavement (not double-line, edge of pavement).By using this dataset you acknowledge the following:Kansas Open Records Act StatementThe Kansas Open Records Act provides in K.S.A. 45-230 that "no person shall knowingly sell, give or receive, for the purpose of selling or offering for sale, any property or service to persons listed therein, any list of names and addresses contained in, or derived from public records..." Violation of this law may subject the violator to a civil penalty of $500.00 for each violation. Violators will be reported for prosecution.By accessing this site, the user makes the following certification pursuant to K.S.A. 45-220(c)(2): "The requester does not intend to, and will not: (A) Use any list of names or addresses contained in or derived from the records or information for the purpose of selling or offering for sale any property or service to any person listed or to any person who resides at any address listed; or (B) sell, give or otherwise make available to any person any list of names or addresses contained in or derived from the records or information for the purpose of allowing that person to sell or offer for sale any property or service to any person listed or to any person who resides at any address listed."

City limits (corporate) boundary lines for municipalities within Wyandotte County, Kansas, including cities of Kansas City, KS, Bonner Springs, Ks, Edwardsville, KS, that portion of City of Lake Quivira within Wyandotte County, and unincorporated remnant of Delaware Township. This dataset also contains city boundaries for Bonner Springs, KS and Lake Quivira, KS, that continue across Wyandotte Co. corporate boundary and into neighboring Johnson and Leavenworth Counties. GIS polygon feature layer dataset derived from source document legal boundary and annexation documents using reference map information at 1:1200 scale. Represents present-day boundary.By using this dataset you acknowledge the following:Kansas Open Records Act StatementThe Kansas Open Records Act provides in K.S.A. 45-230 that "no person shall knowingly sell, give or receive, for the purpose of selling or offering for sale, any property or service to persons listed therein, any list of names and addresses contained in, or derived from public records..." Violation of this law may subject the violator to a civil penalty of $500.00 for each violation. Violators will be reported for prosecution.By accessing this site, the user makes the following certification pursuant to K.S.A. 45-220(c)(2): "The requester does not intend to, and will not: (A) Use any list of names or addresses contained in or derived from the records or information for the purpose of selling or offering for sale any property or service to any person listed or to any person who resides at any address listed; or (B) sell, give or otherwise make available to any person any list of names or addresses contained in or derived from the records or information for the purpose of allowing that person to sell or offer for sale any property or service to any person listed or to any person who resides at any address listed."

This data represents an effort by Shawnee County to assist local Rural Water Districts in their ascertainment of properties within their boundaries built before 1988. Data from the State appraisal system for Year Built was merged with properties located in each water district within Shawnee County. This data is provided as a courtesy to the water districts, and as such, is deemed reliable but no guarantees or warranties are made as to the accuracy of the information. Shawnee County makes no assertions as to the correctness of such information; however, and by accepting this map and/or data you absolve Shawnee County from any liability related to its use for any purpose. Rural Water District boundaries as shown on KRWA and from the source https://services.kgs.ku.edu/arcgis15/rest/services/admin_boundaries/KS_RuralWaterDistricts/MapServer were used to determine which district a property falls within.

This data represents the GIS Version of the Public Land Survey System including both rectangular and non-rectangular survey data. The rectangular survey data are a reference system for land tenure based upon meridian, township/range, section, section subdivision and government lots. The non-rectangular survey data represent surveys that were largely performed to protect and/or convey title on specific parcels of land such as mineral surveys and tracts. The data are largely complete in reference to the rectangular survey data at the level of first division. However, the data varies in terms of granularity of its spatial representation as well as its content below the first division. Therefore, depending upon the data source and steward, accurate subdivision of the rectangular data may not be available below the first division and the non-rectangular minerals surveys may not be present. At times, the complexity of surveys rendered the collection of data cost prohibitive such as in areas characterized by numerous, overlapping mineral surveys. In these situations, the data were often not abstracted or were only partially abstracted and incorporated into the data set. These PLSS data were compiled from a broad spectrum or sources including federal, county, and private survey records such as field notes and plats as well as map sources such as USGS 7 ½ minute quadrangles. The metadata in each data set describes the production methods for the data content. This data is optimized for data publication and sharing rather than for specific "production" or operation and maintenance. A complete PLSS data set includes the following: PLSS Townships, First Divisions and Second Divisions (the hierarchical break down of the PLSS Rectangular surveys) PLSS Special surveys (non-rectangular components of the PLSS) Meandered Water, Corners, Metadata at a Glance (which identified last revised date and data steward) and Conflicted Areas (known areas of gaps or overlaps or inconsistencies). The Entity-Attribute section of this metadata describes these components in greater detail. The PLSS First Division is commonly the section. This is the first set of divisions for a PLSS Township. This fully intersected data is the atomic level of the PLSS that is similar to the coverage or the smallest pieces used to build the PLSS. Polygons may overlap in this feature class.

While seasonal maximum vegetation index values from general cropland have been found to have some utility for identifying irrigated locations, the diverse agricultural landscape and pronounced climatic gradients across Kansas undermine the general effectiveness of approaches based solely on this information. Consequently, we developed an alternative procedure for creating a binary irrigated lands map for Kansas focused on 2007 but applicable to the 2003-2012 time period and which utilizes multiple datasets and methods facilitative of this task. Five crop types (alfalfa, corn, sorghum, soybeans, and winter wheat) dominate the Kansas agricultural landscape, and these crop types were considered for this exercise. The mapping effort is summarized in the following steps.

“Place of Use” (POU) spatial information provided by the Division of Water Resources – Kansas Department of Agriculture, which indicates where high-volume irrigation is permissible in Kansas, was used to restrict the mapping exercise to locations contained therein. All irrigated locations in the final dataset fall within POU boundaries.Based on spatial variability in agricultural management tendencies, crop-specific MODIS NDVI profile distributions, and irrigation use extensiveness, we split the state into two regions, west-central (WC) and east (E), following Agricultural Statistics District (ASD) boundaries. Region-specific boosted decision tree models developed using MODIS NDVI time series were used to provide initial annual estimates for irrigated locations. Models were trained using ground reference data consisting of USDA Farm Service Agency (FSA) annual cropping records from 2003-2007 that were spatially linkable to FSA Common Land Unit (CLU) polygons (c.2007). Models for 2003-2005 were constructed to simultaneously map both crop type and irrigation status, whereas models for 2006-2012 were constructed to map crop-specific irrigation status. For the latter period, USDA National Agricultural Statistics Service (NASS) Cropland Data Layer (CDL) spatial information was used to map individual crop types prior to irrigation status model development. Classified raster data were generalized to field boundaries. Field boundaries were created by combining multi-year CLU data and manual delineations using heads-up digitizing and NAIP imagery.Initializing the irrigated locations map using model output from 2007, land use/land cover (LULC) trajectories were examined for 2007 non-irrigated cropland locations within the POU. A rule set was developed based on mapped irrigation frequency during 2003-2012 that was used to “flip” irrigation status from non-irrigated to irrigated for fields in the 2007 layer that met particular criteria.Statewide irrigated area, by crop, was computed for the 2007 map and compared to USDA NASS irrigated cropland area estimates from 2007. Mapped irrigated area for alfalfa and corn were found to exceed the USDA numbers (by 14% and 3%, respectively), so no further irrigation status changes were applied to locations mapped to those crop types in 2007. It was determined that 2007 total mapped soybean area within the POU fell 15% short of the 2007 USDA estimate for irrigated soybean area in Kansas, so all soybeans within the POU were assigned a status of irrigated, and no further irrigation status changes were applied to fields mapped to this crop in 2007. Mapped irrigated area for 2007 sorghum and winter wheat were found to fall short of 2007 USDA irrigated area estimates (by 44% and 26%, respectively), and non-irrigated areas for these crops were sufficiently prevalent within the POU to consider further irrigation status changes.Non-irrigated 2007 sorghum and winter wheat parcels were ranked according to 10 size classes reasoned to be decreasingly reflective of field sizes commonly associated with center pivot irrigation. The same fields were then ranked according to 2007 maximum MODIS NDVI, and then again by mapped irrigation frequency during 2003-2012. A crop-specific weighted sum of these three rankings was calculated to provide each parcel with a score reasoned to reflect its likelihood of being irrigated. For each crop, county-level NASS irrigated area estimates from 2007 were compared with respective county specific, mapped irrigated area totals from 2007. For each county whereby the mapped irrigated area exceeded the NASS irrigated area, no action was taken. For each county whereby the mapped total area within the POU fell short of the NASS irrigated area, all relevant parcels within the POU were assigned a status of irrigated. For the final case, whereby mapped irrigated area fell short of NASS irrigated area but total mapped area within the POU exceeded NASS irrigated area, one by one, the highest ranked parcels were reassigned to irrigated status until NASS totals were met or exceeded. The irrigated location map obtained at the end of this step is the final map. Processing was completed on 28-April-2014.

NSF BACC-FLUD Kansas Land Cover 2003-2012 (ZIP download)

REFERENCES

Gao, J., A.Y. Sheshukov, H. Yen, J.H. Kastens, and D.L. Peterson (2017). Impacts of Incorporating Dominant Crop Rotation Patterns as Primary Land Use Change on Hydrologic Model Performance. Agriculture, Ecosystems and Environment, 247: 33-42. DOI: 10.1016/j.agee.2017.06.019

MardanDoost, B., A.E. Brookfield, J. Feddema, B. Sturm, J. Kastens, D. Peterson, and C. Bishop (2019). Estimating irrigation demand with geospatial and in-situ data: Application to the High Plains Aquifer, Kansas, USA. Agriculture Water Management, 223(2019): 105675. DOI: 10.1016/j.agwat.2019.06.010

This data represents the GIS Version of the Public Land Survey System including both rectangular and non-rectangular survey data. The rectangular survey data are a reference system for land tenure based upon meridian, township/range, section, section subdivision and government lots. The non-rectangular survey data represent surveys that were largely performed to protect and/or convey title on specific parcels of land such as mineral surveys and tracts. The data are largely complete in reference to the rectangular survey data at the level of first division. However, the data varies in terms of granularity of its spatial representation as well as its content below the first division. Therefore, depending upon the data source and steward, accurate subdivision of the rectangular data may not be available below the first division and the non-rectangular minerals surveys may not be present. At times, the complexity of surveys rendered the collection of data cost prohibitive such as in areas characterized by numerous, overlapping mineral surveys. In these situations, the data were often not abstracted or were only partially abstracted and incorporated into the data set. These PLSS data were compiled from a broad spectrum or sources including federal, county, and private survey records such as field notes and plats as well as map sources such as USGS 7 ½ minute quadrangles. The metadata in each data set describes the production methods for the data content. This data is optimized for data publication and sharing rather than for specific "production" or operation and maintenance. A complete PLSS data set includes the following: PLSS Townships, First Divisions and Second Divisions (the hierarchical break down of the PLSS Rectangular surveys) PLSS Special surveys (non-rectangular components of the PLSS) Meandered Water, Corners, Metadata at a Glance (which identified last revised date and data steward) and Conflicted Areas (known areas of gaps or overlaps or inconsistencies). The Entity-Attribute section of this metadata describes these components in greater detail. The PLSS First Division is commonly the section. This is the first set of divisions for a PLSS Township.

This data represents the GIS Version of the Public Land Survey System including both rectangular and non-rectangular survey data. The rectangular survey data are a reference system for land tenure based upon meridian, township/range, section, section subdivision and government lots. The non-rectangular survey data represent surveys that were largely performed to protect and/or convey title on specific parcels of land such as mineral surveys and tracts. The data are largely complete in reference to the rectangular survey data at the level of first division. However, the data varies in terms of granularity of its spatial representation as well as its content below the first division. Therefore, depending upon the data source and steward, accurate subdivision of the rectangular data may not be available below the first division and the non-rectangular minerals surveys may not be present. At times, the complexity of surveys rendered the collection of data cost prohibitive such as in areas characterized by numerous, overlapping mineral surveys. In these situations, the data were often not abstracted or were only partially abstracted and incorporated into the data set. These PLSS data were compiled from a broad spectrum or sources including federal, county, and private survey records such as field notes and plats as well as map sources such as USGS 7 ½ minute quadrangles. The metadata in each data set describes the production methods for the data content. This data is optimized for data publication and sharing rather than for specific "production" or operation and maintenance. A complete PLSS data set includes the following: PLSS Townships, First Divisions and Second Divisions (the hierarchical break down of the PLSS Rectangular surveys) PLSS Special surveys (non-rectangular components of the PLSS) Meandered Water, Corners, Metadata at a Glance (which identified last revised date and data steward) and Conflicted Areas (known areas of gaps or overlaps or inconsistencies). The Entity-Attribute section of this metadata describes these components in greater detail. The second division of the PLSS is quarter, quarter-quarter, sixteenth or government lot division of the PLSS. The second and third divisions are combined into this feature class as an intentional de-normalization of the PLSS hierarchical data. The polygons in this feature class represent the smallest division to the sixteenth that has been defined for the first division. For example In some cases sections have only been divided to the quarter. Divisions below the sixteenth are in the Special Survey or Parcel Feature Class. The second division of the PLSS is quarter, quarter-quarter, sixteenth or government lot division of the PLSS. The second and third divisions are combined into this feature class as an intentional de-normalization of the PLSS hierarchical data. The polygons in this feature class represent the smallest division to the sixteenth that has been defined for the first division. For example In some cases sections have only been divided to the quarter. Divisions below the sixteenth are in the Special Survey or Parcel Feature Class.