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<idPurp>This land-cover change extract (Time Period 2) is intended to facilitate analysis of landscape change in the Chesapeake Bay Watershed of Delaware, District of Columbia, Maryland, New York, Pennsylvania, Virginia, and West Virginia. It will permit identification of specific areas of land-cover conversion during the analysis period and also serve as a baseline for future change-detection analyses.</idPurp>
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<idAbs>&lt;DIV STYLE="text-align:Left;"&gt;&lt;DIV&gt;&lt;DIV&gt;&lt;P&gt;&lt;SPAN&gt;This map shows 12-class land cover in the Chesapeake Bay Watershed. It was extracted from a map showing land-cover conversion in the Chesapeake Bay Watershed during the period 2013/2014-2017/2018. It was modeled with an existing 2013/2014 (Time Period 1, or T1) land-cover map containing the following classes: Water, Emergent Wetlands, Tree Canopy, Scrub\Shrub, Low Vegetation, Barren, Impervious Structures, Other Impervious, Impervious Roads, Tree Canopy Over Impervious Structures, Tree Canopy Over Other Impervious, and Tree Canopy Over Impervious Roads. Using object-based image analysis mapping techniques, the T1 map was first refined, where necessary, using all remote-sensing imagery and GIS datasets available for 2013\2014, including LiDAR, multispectral imagery, and thematic layers (e.g., roads, building footprints). The refined T1 map was then compared to imagery and GIS data corresponding to the period 2017/2018 (Time Period 1, or T2), identifying features that had changed during the analysis interval. Each change combination was assigned to a unique category that indicated both the "from" and "to" classes, enabling monitoring of specific types of change. Features that had not changed during the analysis interval were also incorporated into the change map, making it possible to reconstitute full land cover for either T1 or T2. Draft output was manually reviewed and edited to eliminate obvious errors of omission and commission, focusing on the most important types of landscape change: 1) tree-canopy loss; and 2) impervious-surfaces gain. The final map contained 79 change classes plus the original 12 classes for features that had not changed. The specific analysis periods for the watershed's 7 states\districts were: Delaware, 2013-2018; District of Columbia, 2013-2017; Maryland, 2013-2018; New York, 2013-2017; Pennsylvania, 2013-2017; Virginia, 2014-2018; and West Virginia, 2014-2018. The 12-class extract of the change-detection map was created by reassigning all change classes to their T2 status.&lt;/SPAN&gt;&lt;/P&gt;&lt;/DIV&gt;&lt;/DIV&gt;&lt;/DIV&gt;</idAbs>
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<statement>This map was based on a 12-class land-cover map for the Chesapeake Bay Watershed, previously developed for 2013\2014 (Time Period 1, or T1). The T1 map was first refined as necessary using LiDAR, multispectral imagery, and thematic GIS data, where available, that corresponded to the same 2013\2014 time period. Landscape that had occurred since T1 were then identified using LiDAR, multispectral imagery, and thematic GIS data, where available, that corresponded to 2017\2018 (Time Period 2, or T2). Each combination of land-cover change was coded into the output map, making it possible to reconstitute land cover for either T1 or T2. All modeling was performed in eCognition, state-of-the-art mapping software that uses object-based image analysis to segment and classify source data into meaningful landscape features.</statement>
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<srcDesc>LiDAR, 2017/2018 (Time Period 2, or T2), Resolution Dependent on Location. Where available, original LiDAR point clouds were converted into derivatives that facilitate landscape analysis, including a digital elevation model (DEM) and a digital surface model (DSM). The DEM was subtracted from the DSM to produce a normalized digital surface model (nDSM) that indicates the height of aboveground features such as buildings and trees. NOTE: T2 LiDAR was not available for every county in the Chesapeake Bay Watershed. In such cases, modeling relied more on other input datasets and subsequent manual review.</srcDesc>
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<srcDesc>Thematic GIS Datasets, Various Dates. Thematic datasets representing building footprints, roads, road centerlines, sidewalks, driveways, parking lots, alleys, county boundaries, and other datasets were used to augment change detection. NOTE: Because datasets varied widely in availability, quality, and chronology, they were not used in all Chesapeake Bay counties.</srcDesc>
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<stepDateTm>2020-03-01T00:00:00</stepDateTm>
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<stepDateTm>2020-05-01T00:00:00</stepDateTm>
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<stepDesc>The manually-reviewed and edited vector polygons representing changes to tree canopy, impervious surfaces, and barren features were incorporated into the draft classification using eCognition. This review draft was then submitted to project stakeholders for further review and comment.</stepDesc>
<stepDateTm>2020-07-01T00:00:00</stepDateTm>
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<stepDateTm>2021-11-30T00:00:00</stepDateTm>
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<stepDesc>To update the dataset, the manually-reviewed and edited vector polygons representing corrections from all rounds of review were incorporated into the draft classification using eCognition.</stepDesc>
<stepDateTm>2022-01-19T00:00:00</stepDateTm>
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<stepDesc>To create the T2 extract of the final change-detection map, each change class was converted to its T2 status, reducing the number of classes to 12.</stepDesc>
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<udom Sync="TRUE">Sequential unique whole numbers that are automatically generated.</udom>
</attrdomv>
</attr>
<attr>
<attrlabl Sync="TRUE">Value</attrlabl>
<attalias Sync="TRUE">Value</attalias>
<attrtype Sync="TRUE">Integer</attrtype>
<attwidth Sync="TRUE">10</attwidth>
<atprecis Sync="TRUE">10</atprecis>
<attscale Sync="TRUE">0</attscale>
</attr>
<attr>
<attrlabl Sync="TRUE">Count</attrlabl>
<attalias Sync="TRUE">Count</attalias>
<attrtype Sync="TRUE">Double</attrtype>
<attwidth Sync="TRUE">19</attwidth>
<atprecis Sync="TRUE">0</atprecis>
<attscale Sync="TRUE">0</attscale>
</attr>
</detailed>
<detailed>
<attr>
<attrlabl>Value</attrlabl>
<attrdef>Numeric identifier for each Time Period 2 land-cover class</attrdef>
<attrdefs>University of Vermont Spatial Analysis Laboratory</attrdefs>
<attrdomv>
<edom>
<edomv>1</edomv>
<edomvd>Water</edomvd>
</edom>
<edom>
<edomv>2</edomv>
<edomvd>Emergent Wetlands</edomvd>
</edom>
<edom>
<edomv>3</edomv>
<edomvd>Tree Canopy</edomvd>
</edom>
<edom>
<edomv>4</edomv>
<edomvd>Scrub\Shrub</edomvd>
</edom>
<edom>
<edomv>5</edomv>
<edomvd>Low Vegetation</edomvd>
</edom>
<edom>
<edomv>6</edomv>
<edomvd>Barren</edomvd>
</edom>
<edom>
<edomv>7</edomv>
<edomvd>Impervious Structures</edomvd>
</edom>
<edom>
<edomv>8</edomv>
<edomvd>Other Impervious</edomvd>
</edom>
<edom>
<edomv>9</edomv>
<edomvd>Impervious Roads</edomvd>
</edom>
<edom>
<edomv>10</edomv>
<edomvd>Tree Canopy Over Impervious Structures</edomvd>
</edom>
<edom>
<edomv>11</edomv>
<edomvd>Tree Canopy Over Other Impervious</edomvd>
</edom>
<edom>
<edomv>12</edomv>
<edomvd>Tree Canopy Over Impervious Roads</edomvd>
</edom>
<edom>
<edomv>254</edomv>
<edomvd>Aberdeen Proving Ground. Land-cover mapping was not performed for this military installation, which is located in Harford County, Maryland</edomvd>
</edom>
</attrdomv>
</attr>
</detailed>
</eainfo>
<mdLang>
<languageCode Sync="TRUE" value="eng"/>
<countryCode Sync="TRUE" value="USA"/>
</mdLang>
<distInfo>
<distFormat>
<formatName Sync="TRUE">Raster Dataset</formatName>
</distFormat>
</distInfo>
<mdHrLv>
<ScopeCd Sync="TRUE" value="005"/>
</mdHrLv>
<mdHrLvName Sync="TRUE">dataset</mdHrLvName>
<refSysInfo>
<RefSystem>
<refSysID>
<identCode Sync="TRUE" code="102039"/>
<idCodeSpace Sync="TRUE">Esri</idCodeSpace>
<idVersion Sync="TRUE">8.1.2</idVersion>
</refSysID>
</RefSystem>
</refSysInfo>
<mdDateSt Sync="TRUE">20220307</mdDateSt>
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