High-resolution urban land cover of Kansas (2015)

Metadata:

Identification_Information:
Citation:
Citation_Information:
Originator: Paull, Darci A.
Originator: Meneguzzo, Dacia M.
Originator: Gonzalez, Ricardo M.
Originator: Garcia, Devon L.
Originator: Marcotte, Abbey L.
Originator: Liknes, Greg C.
Originator: Finney, Tanner N.
Publication_Date: 2019
Title:
High-resolution urban land cover of Kansas (2015)
Geospatial_Data_Presentation_Form: raster digital data
Publication_Information:
Publication_Place: Fort Collins, CO
Publisher: Forest Service Research Data Archive
Other_Citation_Details:
Updated 17 February 2022
Online_Linkage: https://doi.org/10.2737/RDS-2019-0052
Description:
Abstract:
This data publication contains 2015 high-resolution land cover data for each of the 669 communities 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 community. Data are intended for use in cities and towns. Land cover classes (tree cover, other vegetation, bare land, built-up land, and water) were mapped using an object-based image analysis approach and supervised classification.
Purpose:
These data are designed for conducting geospatial analyses and for producing cartographic products. In particular, these data are intended to depict the location of tree cover in communities of all sizes. The mapping procedures were developed specifically for built-up landscapes that are dominated by urban and suburban development where tree cover is often found in small and/or narrow configurations, such as along streets and streams or rivers, or in scattered clusters in yards and parks. Because much of the tree cover in urban and suburban areas of the United States occurs as individual crowns or in small clusters or narrow configurations, many geospatial datasets derived from coarser-resolution satellite data (such as Landsat), do not capture these landscape features. This dataset and others in this series are intended to address this particular data gap.
Supplemental_Information:
This metadata file contains documentation for the entire set of community land cover files. Individual metadata documents containing detailed information specific (e.g. spatial) to each community are included with the data files.

Land cover data for 245 of 669 communities within Kansas were originally published on 12/03/2019. On 02/24/2021 we added data for an additional 200 communities, and a few minor updates were included for the following previously published communities: Abbyville, Ada, Admire, and Agenda. On 02/17/2022 we added data for the remaining 224 communities, and a few minor updates (explained in more detail in the process steps section below) were included for the following previously published communities: Elkhart, Great Bend, Hepler, Lawrence, Leawood, Lenexa, Linn Valley, Logan, and Longton.
Time_Period_of_Content:
Time_Period_Information:
Single_Date/Time:
Calendar_Date: 2015
Currentness_Reference:
Ground condition
Status:
Progress: Complete
Maintenance_and_Update_Frequency: As needed
Spatial_Domain:
Description_of_Geographic_Extent:
Kansas
Bounding_Coordinates:
West_Bounding_Coordinate: -102.045253
East_Bounding_Coordinate: -94.588387
North_Bounding_Coordinate: 40.000958
South_Bounding_Coordinate: 36.993601
Keywords:
Theme:
Theme_Keyword_Thesaurus: ISO 19115 Topic Category
Theme_Keyword: imageryBaseMapsEarthCover
Theme:
Theme_Keyword_Thesaurus: National Research & Development Taxonomy
Theme_Keyword: Inventory, Monitoring, & Analysis
Theme_Keyword: Resource inventory
Theme_Keyword: Natural Resource Management & Use
Theme_Keyword: Agroforestry
Theme_Keyword: Water
Theme:
Theme_Keyword_Thesaurus: None
Theme_Keyword: tree cover
Theme_Keyword: land cover
Theme_Keyword: urban
Place:
Place_Keyword_Thesaurus: None
Place_Keyword: Kansas
Access_Constraints: None
Use_Constraints:
These data were created using funding from the U.S. Government and can be used without additional permissions or fees. If you use these data in a publication, presentation, or other research product please use the following citation:

Paull, Darci A.; Meneguzzo, Dacia M.; Gonzalez, Ricardo M.; Garcia, Devon L.; Marcotte, Abbey L.; Liknes, Greg C.; Finney, Tanner N. 2019. High-resolution urban land cover of Kansas (2015). Updated 17 February 2022. Fort Collins, CO: Forest Service Research Data Archive. https://doi.org/10.2737/RDS-2019-0052

*Appropriate use includes fine-scale assessment of tree cover, total extent of tree cover, community-level summaries of tree cover categories, and construction of cartographic products.
Point_of_Contact:
Contact_Information:
Contact_Person_Primary:
Contact_Person: Darci Paull
Contact_Organization: Kansas Forest Service
Contact_Position: GIS Specialist
Contact_Address:
Address_Type: mailing and physical
Address: 2610 Claflin Road
City: Manhattan
State_or_Province: KS
Postal_Code: 66502
Country: USA
Contact_Voice_Telephone: 785-532-3312
Contact_Electronic_Mail_Address: dpaull@ksu.edu
Contact Instructions: Prefer email contact.
Data_Set_Credit:
This project was funded by the USDA Forest Service, Northern Research Station, Forest Inventory and Analysis as well as Kansas State University - Kansas Forest Service.
Native_Data_Set_Environment:
Microsoft Windows 7 Enterprise Service Pack 1; ESRI ArcMap 10.3.1
Cross_Reference:
Citation_Information:
Originator: Meneguzzo, Dacia M.
Originator: Liknes, Greg C.
Originator: Nelson, Mark D.
Publication_Date: 2013
Title:
Mapping trees outside forests using high-resolution aerial imagery: a comparison of pixel- and object based classification approaches
Geospatial_Data_Presentation_Form: journal article
Series_Information:
Series_Name: Environmental Monitoring and Assessment
Issue_Identification: 185: 6261-6275
Online_Linkage: https://doi.org/10.1007/s10661-012-3022-1
Online_Linkage: https://www.fs.usda.gov/treesearch/pubs/43939
Cross_Reference:
Citation_Information:
Originator: Paull, Darci A.
Originator: Whitson, Jakob W.
Originator: Marcotte, Abbey L.
Originator: Liknes, Greg C.
Originator: Meneguzzo, Dacia M.
Originator: Kellerman, Todd A.
Publication_Date: 2017
Title:
High-resolution land cover of Kansas (2015)
Geospatial_Data_Presentation_Form: raster digital data
Publication_Information:
Publication_Place: Fort Collins, CO
Publisher: Forest Service Research Data Archive
Other_Citation_Details:
Updated 27 November 2017
Online_Linkage: https://doi.org/10.2737/RDS-2017-0025
Analytical_Tool:
Analytical_Tool_Description:
R is a free software environment for statistical computing and graphics.
Tool_Access_Information:
Online_Linkage: https://www.r-project.org/
Tool_Access_Instructions:
R is freely available via the URL provided above. Download instructions available on the website.
Analytical_Tool:
Analytical_Tool_Description:
E-cognition 9.1
Tool_Access_Information:
Online_Linkage: http://www.ecognition.com/
Tool_Access_Instructions:
Access information available via the URL provided above.
Analytical_Tool:
Analytical_Tool_Description:
randomForest: Breiman and Cutler's Random Forests for Classification and Regression Classification and regression based on a forest of trees using random inputs.
Tool_Access_Information:
Online_Linkage: https://cran.r-project.org/web/packages/randomForest/index.html
Tool_Access_Instructions:
Access information available via the URL provided above.
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Data_Quality_Information:
Attribute_Accuracy:
Attribute_Accuracy_Report:
Because of the randomization that occurs in the Random Forests algorithm (Breiman 2001), we created land cover classification models from training data 10 times and averaged the out-of-bag samples in order to produce an estimate of agreement between the training data and the classification model using 10 communities that range in size from small to large. This is not intended to replace an independent assessment of accuracy but provides some information as to how well our classification model was able to separate the land cover classes (see \Supplements\KS_2015_community_accuracy_reports.csv for results, variable descriptions noted below).

Breiman, Leo. 2001. Random Forests. Machine Learning 45(1): 5-32. https://doi.org/10.1023/A:1010933404324
Quantitative_Attribute_Accuracy_Assessment:
Attribute_Accuracy_Value: XX% (Tree Cover class)
Attribute_Accuracy_Explanation:
Mean agreement between out-of-bag samples for 10 runs of a Random Forest (TM) classification model.
Quantitative_Attribute_Accuracy_Assessment:
Attribute_Accuracy_Value: XX% (Other Vegetation class)
Attribute_Accuracy_Explanation:
Mean agreement between out-of-bag samples for 10 runs of a Random Forest (TM) classification model.
Quantitative_Attribute_Accuracy_Assessment:
Attribute_Accuracy_Value: XX% (Bare Land class)
Attribute_Accuracy_Explanation:
Mean agreement between out-of-bag samples for 10 runs of a Random Forest (TM) classification model.
Quantitative_Attribute_Accuracy_Assessment:
Attribute_Accuracy_Value: XX% (Built-up Land class)
Attribute_Accuracy_Explanation:
Mean agreement between out-of-bag samples for 10 runs of a Random Forest (TM) classification model.
Quantitative_Attribute_Accuracy_Assessment:
Attribute_Accuracy_Value: XX% (Water class)
Attribute_Accuracy_Explanation:
Mean agreement between out-of-bag samples for 10 runs of a Random Forest (TM) classification model.
Quantitative_Attribute_Accuracy_Assessment:
Attribute_Accuracy_Value: XX% (Overall agreement)
Attribute_Accuracy_Explanation:
Mean agreement between out-of-bag samples for 10 runs of a Random Forest (TM) classification model.
Logical_Consistency_Report:
not applicable
Completeness_Report:
Communities have been attributed as Tree Cover, Other Vegetation, Bare Land, Built-up Land, or Water. A separate mapping procedure was used to map land cover in the remaining rural areas of the state. Data for all 669 communites have been completed.
Positional_Accuracy:
Horizontal_Positional_Accuracy:
Horizontal_Positional_Accuracy_Report:
We did not compare image segment boundaries to any ground reference data.
Lineage:
Source_Information:
Source_Citation:
Citation_Information:
Originator: U.S. Dept. of Agriculture - Farm Service Agency - Aerial Photography Field Office
Publication_Date: 2015
Title:
Kansas NAIP 2015 imagery
Geospatial_Data_Presentation_Form: raster digital data
Series_Information:
Series_Name: National Agriculture Imagery Program (NAIP) imagery
Publication_Information:
Publication_Place: Salt Lake City, UT
Publisher: U.S. Dept. of Agriculture - Farm Service Agency - Aerial Photography Field Office
Online_Linkage: https://www.fsa.usda.gov/programs-and-services/aerial-photography/imagery-programs/naip-imagery/
Type_of_Source_Media: online
Source_Time_Period_of_Content:
Time_Period_Information:
Single_Date/Time:
Calendar_Date: 2015
Source_Currentness_Reference:
external hard drive
Source_Citation_Abbreviation:
NAIP
Source_Contribution:
Imagery from the U.S. Department of Agriculture's National Agriculture Imagery Program (NAIP) formed the basis for this dataset. We obtained uncompressed (.TIF) DOQQ image tiles via an external hard drive from the Aerial Photography Field Office in Salt Lake City, UT.
Source_Information:
Source_Citation:
Citation_Information:
Originator: U.S. Census Bureau
Publication_Date: 2013
Title:
TIGER Geodatabases
Geospatial_Data_Presentation_Form: vector digital data
Series_Information:
Series_Name: 2013 TIGER Geodatabases
Online_Linkage: https://www.census.gov/geo/maps-data/data/tiger-geodatabases.html
Type_of_Source_Media: online
Source_Time_Period_of_Content:
Time_Period_Information:
Single_Date/Time:
Calendar_Date: 2013
Source_Currentness_Reference:
ground condition
Source_Citation_Abbreviation:
CENSUS
Source_Contribution:
2013 Geodatabase feature class (Incorporated_Place) was used to identify the location of cities and towns. Land cover was mapped for these areas.
Process_Step:
Process_Description:
1. Uncompressed, 4-band (RGB-NIR) NAIP DOQQ image tiles in *.tif format were segmented using the multi-resolution segmentation algorithm in eCognition 9.1. The resulting image segments for each DOQQ image were exported in shapefile format.
Source_Used_Citation_Abbreviation:
NAIP
Process_Date: 2018
Process_Step:
Process_Description:
2. A photo interpreter collected good representative samples of each of five land cover classes (Tree, Other Vegetation, Bare Land, Built-up Land, or Water) as training data from the shapefiles in Step 1 for each community.
Process_Date: 2018
Process_Step:
Process_Description:
3. The training data collected in step 2 were used to train a Random Forest model using R statistical software, and the model was then applied to all of the shapefiles for the community.
Process_Date: 2018
Process_Step:
Process_Description:
4. Each shapefile was clipped to remove sidelap pixels and the clipped results were merged into a community-wide file. Some communities were contained within one image/DOQQ file and clipped to the community boundary.
Process_Date: 2018
Process_Step:
Process_Description:
5. The mosaicked community dataset was reviewed for class label errors, and where possible, those were manually changed to the appropriate class. For areas where the segments were an ambiguous mix of tree and non-tree land or areas where a large amount of manual digitization would be required to correct errors, class labels may have been left unchanged.
Process_Date: 2018
Process_Step:
Process_Description:
6. The resultant community-wide shapefile from step 5 was converted to .tif format.
Process_Date: 2018
Process_Step:
Process_Description:
DATA UPDATES

Data for 9 communities were updated.

Hepler: Corrected the spelling of the name – no changes to any of the pixel values.
Leawood: There was an extra (unnecessary) field in the attribute table that was deleted – no changes to any of the pixel values.
Elkhart: 38 pixels went from class 22 to class 2 (other vegetation)
Great Bend: 100 pixels went from a class 23 to class 2
Lawrence: 158 pixels went from a class 22 to class 2
Lenexa: 6 pixels went from a class 22 to class 2
Linn Valley: 264 pixels went from a class 6 to class 4 (built-up land)
Logan: 601 pixels went from a class 6 to class 4
Longton: 73 pixels went from a class 11 to class 1 (tree cover)
Process_Date: 20220217
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Spatial_Data_Organization_Information:
Direct_Spatial_Reference_Method: Raster
Raster_Object_Information:
Raster_Object_Type: Pixel
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Spatial_Reference_Information:
Horizontal_Coordinate_System_Definition:
Planar:
Grid_Coordinate_System:
Grid_Coordinate_System_Name: Universal Transverse Mercator
Planar_Coordinate_Information:
Planar_Coordinate_Encoding_Method: row and column
Coordinate_Representation:
Abscissa_Resolution: 1
Ordinate_Resolution: 1
Planar_Distance_Units: meters
Geodetic_Model:
Horizontal_Datum_Name: North American Datum of 1983
Ellipsoid_Name: Geodetic Reference System 80
Semi-major_Axis: 6378137
Denominator_of_Flattening_Ratio: 298.25722210088
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Entity_and_Attribute_Information:
Detailed_Description:
Entity_Type:
Entity_Type_Label: Land Cover
Entity_Type_Definition:
map theme
Entity_Type_Definition_Source:
source map legend
Attribute:
Attribute_Label: Land Cover
Attribute_Definition:
A category indicating the land cover.
Attribute_Definition_Source:
source map legend
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: 1
Enumerated_Domain_Value_Definition:
Tree Cover
Enumerated_Domain_Value_Definition_Source:
source map legend
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: 2
Enumerated_Domain_Value_Definition:
Other Vegetation
Enumerated_Domain_Value_Definition_Source:
source map legend
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: 3
Enumerated_Domain_Value_Definition:
Bare Land
Enumerated_Domain_Value_Definition_Source:
source map legend
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: 4
Enumerated_Domain_Value_Definition:
Built-up Land
Enumerated_Domain_Value_Definition_Source:
source map legend
Attribute_Domain_Values:
Enumerated_Domain:
Enumerated_Domain_Value: 5
Enumerated_Domain_Value_Definition:
Water
Enumerated_Domain_Value_Definition_Source:
source map legend
Overview_Description:
Entity_and_Attribute_Overview:
Below is a list and description of the files included in this data publication.

DATA FILES

\Data\COMMUNITY.tif: Georeferenced raster digital TIF files (669) (and associated files) containing 1 meter resolution land cover image for the specified COMMUNITY of Kansas. Land cover categories relate to the presence or absence of tree cover (1), other vegetation (2), bare land (3), built-up land (4), or water (5).

\Data\COMMUNITY.tif.xml: Metadata files (669) containing spatial and other information specific to each COMMUNITY in Kansas, meant to be viewed in conjunction with the associated *.tif file.


SUPPLEMENTAL FILES

\Supplements\KS_2015_community_accuracy_reports.csv: Comma-separated values file containing a table showing how well the classification model was able to separate the land cover classes for ten communities.

Variables include:
COMMUNITY = Name of community.
TREE COVER (%) = Mean agreement between out-of-bag samples for 10 runs of a Random Forest (TM) classification model.
TREE COVER (n) = Sample size for tree cover attribute agreement.
OTHER VEGETATION (%) = Mean agreement between out-of-bag samples for 10 runs of a Random Forest (TM) classification model.
OTHER VEGETATION (n) = Sample size for other vegetation attribute agreement.
BARE LAND (%) = Mean agreement between out-of-bag samples for 10 runs of a Random Forest classification model.
BARE LAND (n) = Sample size for bare land attribute agreement.
BUILT-UP LAND (%) = Mean agreement between out-of-bag samples for 10 runs of a Random Forest classification model.
BUILT-UP LAND (n) = Sample size for built-up land attribute agreement.
WATER (%) = Mean agreement between out-of-bag samples for 10 runs of a Random Forest classification model.
WATER (n) = Sample size for water attribute agreement.
OVERALL AGREEMENT (%) = Mean agreement between out-of-bag samples for 10 runs of a Random Forest classification model.
OVERALL AGREEMENT (n) = Sample size for overall attribute agreement.
NOTES = Additional information.
Entity_and_Attribute_Detail_Citation:
None provided
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Distribution_Information:
Distributor:
Contact_Information:
Contact_Organization_Primary:
Contact_Organization: USDA Forest Service, Research and Development
Contact_Position: Research Data Archivist
Contact_Address:
Address_Type: mailing and physical
Address: 240 West Prospect Road
City: Fort Collins
State_or_Province: CO
Postal_Code: 80526
Country: USA
Contact_Voice_Telephone: see Contact Instructions
Contact Instructions: This contact information was current as of February 2022. For current information see Contact Us page on: https://doi.org/10.2737/RDS.
Resource_Description: RDS-2019-0052
Distribution_Liability:
Metadata documents have been reviewed for accuracy and completeness. Unless otherwise stated, all data and related materials are considered to satisfy the quality standards relative to the purpose for which the data were collected. However, neither the author, the Archive, nor any part of the federal government can assure the reliability or suitability of these data for a particular purpose. The act of distribution shall not constitute any such warranty, and no responsibility is assumed for a user's application of these data or related materials.

The metadata, data, or related materials may be updated without notification. If a user believes errors are present in the metadata, data or related materials, please use the information in (1) Identification Information: Point of Contact, (2) Metadata Reference: Metadata Contact, or (3) Distribution Information: Distributor to notify the author or the Archive of the issues.
Standard_Order_Process:
Digital_Form:
Digital_Transfer_Information:
Format_Name: TIFF
Format_Version_Number: see Format Specification
Format_Specification:
Georeferenced raster digital TIFF file (*.tif)
File_Decompression_Technique: Files zipped with 7-Zip 19.00
Digital_Transfer_Option:
Online_Option:
Computer_Contact_Information:
Network_Address:
Network_Resource_Name: https://doi.org/10.2737/RDS-2019-0052
Digital_Form:
Digital_Transfer_Information:
Format_Name: CSV
Format_Version_Number: see Format Specification
Format_Specification:
Comma-separated values file (*.csv)
File_Decompression_Technique: Files zipped with 7-Zip 19.00
Digital_Transfer_Option:
Online_Option:
Computer_Contact_Information:
Network_Address:
Network_Resource_Name: https://doi.org/10.2737/RDS-2019-0052
Fees: None
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Metadata_Reference_Information:
Metadata_Date: 20220217
Metadata_Contact:
Contact_Information:
Contact_Person_Primary:
Contact_Person: Darci Paull
Contact_Organization: Kansas Forest Service
Contact_Position: GIS Specialist
Contact_Address:
Address_Type: mailing and physical
Address: 2610 Claflin Road
City: Manhattan
State_or_Province: KS
Postal_Code: 66502
Country: USA
Contact_Voice_Telephone: 785-532-3312
Contact_Electronic_Mail_Address: dpaull@ksu.edu
Contact Instructions: Prefer email contact.
Metadata_Standard_Name: FGDC Content Standard for Digital Geospatial Metadata
Metadata_Standard_Version: FGDC-STD-001-1998
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https://www.fs.usda.gov/rds/archive/products/RDS-2019-0052/_metadata_RDS-2019-0052.html