Forest Type Classification, 2010-2011, Delaware River Basin, Northern Section 2014

High resolution land cover dataset for the Delaware River Basin, an area comprised of parts of six counties in the state of New York and four counties in Pennsylvania. Seven land cover classes were mapped: (1) tree canopy, (2) grass/shrub, (3) bare earth, (4) water, (5) buildings, (6) roads, and (7) other paved surfaces. The minimum mapping unit for the delineation of features was set at six square meters. The primary sources used to derive this land cover layer were 2008 LiDAR data and 2010 - 2011 NAIP imagery. LiDAR coverage was complete for the Pennsylvaia portion of the AOI, however, LiDAR was unavailable for large portions of the New York portion. Where LiDAR was not available, imagery was the primary data source. Ancillary data sources included GIS data (eg. such as hydrology, breakline and buildings) provided by the counties of Lackawana, Monroe, Pike and Wayne, PA, as well as the New York State GIS Clearinghouse. Some of these vector datasets were edited by the UVM Spatial Analysis lab through manual interpretation. Other datasets, such as bare soil, were created by the UVM Spatial Anyslsis Lab in order to assist in landcover creation. This land cover dataset is considered current for Pennsylvania portion of the study area as of summer 2010. The dataset is current as of summer 2011 for the New York counties of Chenango, Delaware, Orange and Sullivan. Broome County, NY, is considered current as of summer 2010. Ulster County, NY, employed data from both summer 2010 and summer 2011, therefore currentness varies throughout the county. 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. No accuracy assessment was conducted, but the dataset was subject to a thorough manual quality control.

This data is hosted at, and may be downloaded or accessed from PASDA, the Pennsylvania Spatial Data Access Geospatial Data Clearinghouse http://www.pasda.psu.edu/uci/DataSummary.aspx?dataset=3169

该数据集为特拉华河流域高分辨率土地覆盖数据集，覆盖范围包括纽约州六个县的部分地区以及宾夕法尼亚州四个县。数据中划分为七种土地覆盖类别：（1）树冠，（2）草地/灌木，（3）裸地，（4）水域，（5）建筑物，（6）道路，以及（7）其他铺装表面。特征划分的最小单位为六平方米。构建该土地覆盖层的主要数据源为2008年LiDAR数据和2010-2011年NAIP影像。LiDAR数据在研究区域宾夕法尼亚州部分完全覆盖，但在纽约州部分大部分地区LiDAR数据不可用。在LiDAR数据不可用的情况下，影像数据成为主要数据源。辅助数据源包括来自宾夕法尼亚州拉克瓦纳、门罗、派克和韦恩县的GIS数据（例如水文、断线以及建筑物），以及纽约州GIS数据中心提供的数据。部分矢量数据集由佛蒙特大学空间分析实验室通过人工解释进行编辑。其他数据集，如裸土数据，由佛蒙特大学空间分析实验室创建，以辅助土地覆盖的生成。截至2010年夏季，该土地覆盖数据集在研究区域宾夕法尼亚州部分被认为是现行的。至于纽约州的切南戈、特拉华、奥兰奇和萨利文县，数据集的现行性截至2011年夏季。纽约州的布罗姆县则截至2010年夏季被认为是现行的。纽约州的乌尔斯特县使用了2010年和2011年夏季的数据，因此该县的数据现行性存在差异。在提取土地覆盖信息时，采用了基于对象的光学图像分析技术（OBIA），结合了最佳可用的遥感数据和矢量GIS数据集。OBIA系统通过基于光谱和空间属性将像素分组为有意义的对象，同时考虑现有矢量数据集所施加的边界。在OBIA环境中，设计了一个基于规则的专家系统，以有效地模拟人工图像分析过程，通过将图像解释的元素（颜色/色调、纹理、模式、位置、尺寸和形状）纳入分类过程。采取了一系列形态学过程，以确保最终产品既准确又符合地图制图的美观标准。未进行精度评估，但数据集已接受彻底的人工质量检查。该数据集可在宾夕法尼亚空间数据访问网（PASDA）上托管、下载或访问，即宾夕法尼亚空间数据访问地理空间数据清点中心（http://www.pasda.psu.edu/uci/DataSummary.aspx?dataset=3169）。