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This dataset was developed as part of an Urban Tree Canopy (UTC) assessment for Cuyahoga County, Ohio. It shows how tree canopy changed during the period between 2011-2017, highlighting trees that were gained or lost during the six-year period. It is intended for use in monitoring patterns of change in Cuyahoga County, Ohio tree canopy. |
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This dataset was developed as part of an Urban Tree Canopy (UTC) assessment for Cuyahoga County, Ohio. It shows how tree canopy changed during the period between 2011-2017, highlighting trees that were gained or lost during the six-year period. It is intended for use in monitoring patterns of change in Cuyahoga County, Ohio tree canopy. |
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University of Vermont Spatial Analysis Laboratory in collaboration with Cuyahoga County. |
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5000 |
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[] |
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<DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>This layer is a high-resolution tree canopy change-detection layer for Cuyahoga County, Ohio. It contains three tree-canopy classes for the period 2011-2017: (1) No Change; (2) Gain; and (3) Loss. It was created by extracting tree canopy from existing high-resolution land-cover maps for 2011 and 2017 and then comparing the mapped trees directly. Tree canopy that existed during both time periods was assigned to the No Change category while trees removed by development, storms, or disease were assigned to the Loss class. Trees planted during the interval were assigned to the Gain category, as were the edges of existing trees that expanded noticeably. Direct comparison was possible because both the 2011 and 2017 maps were created using object-based image analysis (OBIA) and included similar source datasets (LiDAR-derived surface models, multispectral imagery, and thematic GIS inputs). </SPAN><SPAN>The 2011 land cover dataset was produced by the SAL using 2006 LiDAR, 2011 NAIP and Ortho Imagery. The 2017 dataset was created using Cuyahoga County LiDAR, NAIP, and Ortho imagery from 2017. 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. No accuracy assessment was conducted, but the dataset will be subjected to manual review and correction.</SPAN></P></DIV></DIV></DIV> |
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<DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>None</SPAN></P></DIV></DIV></DIV> |
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| title:
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TreeCanopyChange_2011_2017_Cuyahoga |
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| tags:
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["Tree Canopy","Change Detection","Cuyahoga County"] |
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en-US |
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150000000 |
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