{ "culture": "en-US", "name": "TREE_CANOPY_2023", "guid": "", "catalogPath": "", "snippet": "Tree Canopy for the urban/suburban areas of the County of Los Angeles developed from information captured in 2023 by the LARIAC program.", "description": "

This layer is a combination of two datasets. One of which is an Normalized Difference Vegetation Index (NDVI) product derived from the LARIAC7 program and the other is a Normalized Digital Surface Model from our County partners at NV5. These two datasets were combined together to produce a new countywide tree canopy layer. The imagery was collected in Winter of 2023 and only includes urban/suburban areas of the County of Los Angeles. <\/span><\/p>

  1. Los Angeles Region Imagery Acquisition Consortium (LARIAC-7) <\/span><\/a>Normalized Difference Vegetation Index (NDVI) tiff tiles. NDVI is a simple numerical indicator that can be used to analyze remote sensing measurements, typically but not necessarily from a space platform, and assess whether the target being observed contains live green vegetation or not. NDVI was developed from the 2023 Color Infrared (CIR) imagery at 4-inch resolution which contains the Red and Near Infrared (NIR) Bands. <\/span>Click here for more information.<\/span><\/a><\/p><\/li>

  2. Normalized Digital Surface Model (NDSM)<\/span><\/a> tiff tiles. NDSM (normalized digital surface model) represents the relative height of features above the surrounding ground surface. It is a valuable elevation product that provides insights into the relative height of features compared to the surrounding ground. In contrast, DSMs (digital surface models) and DTMs (digital terrain models) represent absolute height referenced to a datum, typically the mean sea level.<\/span><\/p><\/li><\/ol>

    Processing Steps:<\/span><\/p>

    1. The NDVI dataset was merged together to form one large county layer.<\/span><\/p><\/li>

    2. The NDSM dataset was merged together to form one large countywide using 6 separate tiles that were all mosaiced together. This processes involved converting the processing bit depth from a unsigned 32-bit to a 32-bit floating point in order to get the correct height pixels. This data uses meters to measure height.<\/span><\/p><\/li>

    3. All areas where the surface height was greater than 1.8288 meters or 6 feet, and the NDVI value was <100 were extracted and assigned the value 1. This is the trees layer. The formula is listed below.<\/span><\/p>

      1. SetNull(\"Mosaic_Height_Float2\", SetNull(\"NDVI_MERGED_Band_1\",1,\"Value <100\"),\"Value < 1.8288\")<\/span><\/p><\/li><\/ol><\/li>

      2. To provide improved symbolization of trees across the County, and to remove a number of artifacts, a set of additional processes were run. The MajorityFilter command was run twice on the trees layer. For the options, I used 8 neighbors with the majority replacement threshold.<\/span><\/p><\/li><\/ol>

        <\/p>

        Important notes<\/span><\/p>

        This trees layer has been validated to provide a true representation of trees. However, the data includes many small processing artifacts, and should not be used for authoritative measuring. There are also known issues with shadows and may result in the software picking up darker shadows as tree canopy. This is a common issue pertaining to using NDVI and NDSM data. <\/span><\/p><\/div><\/div><\/div>", "summary": "Tree Canopy for the urban/suburban areas of the County of Los Angeles developed from information captured in 2023 by the LARIAC program.", "title": "TREE_CANOPY_2023", "tags": [ "LARIAC7", "Tree Canopy", "Trees", "Raster", "NDVI" ], "type": "Image Service", "typeKeywords": [ "Data", "Service", "Image Service", "ArcGIS Server" ], "thumbnail": "thumbnail/thumbnail.png", "url": "https://egisagsimage1.isd.lacounty.gov:6443/arcgis/admin", "minScale": 1091341.3925620534, "maxScale": 34104.41851756417, "spatialReference": "NAD_1983_2011_StatePlane_California_V_FIPS_0405_Ft_US", "accessInformation": "Public Works SMPM, Nathan Shapiro", "licenseInfo": "" }