Introduction:This project will attempt to (1) identify suspected mowed grass areas in the Hinckley Lake region of Medina County, Ohio, by applying a threshold to a NDVI product derived from a color infrared image, and (2) attempt to filter those suspected mowed grass areas with a canopy layer derived from classified LIDAR return data to remove areas that are not grass but rather are suspected to be evergreen vegetation that are errors of commission in the NDVI product.

Data:Data for the project was obtained from the Ohio Statewide Imagery Program website at http://gis3.oit.ohio.gov/geodata/ . The 2006 OSIP digital color infrared orthophotography was collected during the months of March and April (leaf-off conditions) at a minimum resolution of 3-foot statewide. Horizontal accuracy is based upon NMAS Standards, with the 1"=1,000' scale (3-foot imagery) based upon an accuracy of +/- 25.0-feet. Imagery was collected with Leica ADS40 digital cameras and rectified using LiDAR data. The 2006 OSIP digital LiDAR data was collected during the months of March and May (leaf-off conditions). LiDAR was collected with Leica ALS50 digital LiDAR Systems. Additional data was obtained from Medina County at http://www.gisdata.co.medina.oh.us/ and from ESRI at http://arcdata.esri.com/data/tiger2000/tiger_download.

Methods:A subset of the County-wide CIR image was created for the study area. A NDVI layer was produced using the Image Analyst extension of ESRI’s ArcGIS software package. A threshold of .05 was then applied to the resulting layer to separate areas suspected to be mowed grass (above .05) from areas suspected to not be mowed grass, and a shapefile representing the suspected mowed grass was produced.

LIDAR data points classified as vegetation (class 5) were selected and imported to a geodatabase using ArcCatalogand the LAS Reader for ArcGIS 9 utility developed by GeoCue. A canopy raster layer was then produced from the data using the Point Statistics tool in the ArcGIStoolbox. The raster was then converted to vector format so that the suspected mowed grass polygons residing completely within the canopy layer (and therefore suspected of being in fact evergreen vegetation) could be selected by their location and removed .

Conclusions:The technique reduced the number of suspected mowed grass polygons in the study area from 104,342 to 43, 859, and should reduce the time spent manually cleaning the suspected mowed grass layer.

Note:This technique was developed by Stephen Mather, GIS Manager for the Cleveland Metroparks, in conjunction with my Internship at Cleveland Metroparks. The process represents the initial stages of an effort to quantify and classify maintained areas within the Metroparks.

Layer Creation and Selection Processes

Mowed Grass Identification and Filtering Operation Using LIDAR Derived Canopy DataProject by: Paul Boehnlein, The University of Akron Department of Geography and Planning

Advanced Remote Sensing 3350:449-001, Dr. Linda Barrett, Instructor

ArcSceneVisualization of

CIR,Suspected Grass, and

Canopy Layers