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Service Description: High resolution tree canopy dataset for the Greater Bridgeport, CT area.. This land cover dataset is considered current as of summer 2012 ground conditions. The minimum mapping unit for the delineation of features was set at 16 square feet. The primary remotely sensed sources used to derive this tree canopy layer were: LiDAR data acquired under leaf-off conditions in 2013, 4-band Orthophotgraphy aquired in leaf off conditions in 2013, and National Agricultural Imagery Program (NAIP) 4-band imagery acquired in the summer (leaf-on conditions) of 2010 . Ancillary data sources included planimetric datasets depicting impervious surfaces (buildings, roads, and other paved areas) provided by the Greater Bridgeport Regional Council. Object-based image analysis techniques (OBIA) were employed to extract land cover information using the best available remotely sensed and vector GIS datasets. OBIA systems work by grouping pixels into meaningful objects based on their spectral and spatial properties, while taking into account boundaries imposed by existing vector datasets. Within the OBIA environment a rule-based expert system was designed to effectively mimic the process of manual image analysis by incorporating the elements of image interpretation (color/tone, texture, pattern, location, size, and shape) into the classification process. A series of morphological procedures were employed to insure that the end product is both accurate and cartographically pleasing. The OBIA system developed for this project follows that detailed by MacFaden et al. (2012) and O’Neil-Dunne et al. (2012). No accuracy assessment was conducted, but the dataset was subject to a thorough manual quality control. More than 5000 corrections were made to the classification.

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Service Item Id: f8d0780f10424377bd4d49ed5e21237f

Copyright Text: MetroCOG

Spatial Reference: 102656  (2234)


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Spatial Reference: 102656  (2234)

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Document Info:

Title: Tree Canopy
Author: MetroCOG
Comments: High resolution tree canopy dataset for the Greater Bridgeport, CT area.. This land cover dataset is considered current as of summer 2012 ground conditions. The minimum mapping unit for the delineation of features was set at 16 square feet. The primary remotely sensed sources used to derive this tree canopy layer were: LiDAR data acquired under leaf-off conditions in 2013, 4-band Orthophotgraphy aquired in leaf off conditions in 2013, and National Agricultural Imagery Program (NAIP) 4-band imagery acquired in the summer (leaf-on conditions) of 2010 . Ancillary data sources included planimetric datasets depicting impervious surfaces (buildings, roads, and other paved areas) provided by the Greater Bridgeport Regional Council. Object-based image analysis techniques (OBIA) were employed to extract land cover information using the best available remotely sensed and vector GIS datasets. OBIA systems work by grouping pixels into meaningful objects based on their spectral and spatial properties, while taking into account boundaries imposed by existing vector datasets. Within the OBIA environment a rule-based expert system was designed to effectively mimic the process of manual image analysis by incorporating the elements of image interpretation (color/tone, texture, pattern, location, size, and shape) into the classification process. A series of morphological procedures were employed to insure that the end product is both accurate and cartographically pleasing. The OBIA system developed for this project follows that detailed by MacFaden et al. (2012) and O’Neil-Dunne et al. (2012). No accuracy assessment was conducted, but the dataset was subject to a thorough manual quality control. More than 5000 corrections were made to the classification.
Subject: High resolution tree canopy dataset for the Greater Bridgeport, CT area
Category:
Keywords: MetroCOG,Trees
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