The extracted buildings are compared with the manually digitized buildings. The approach is applied on three different satellite images. Imagine Objective tool of ERDAS 2011 has been used. The cleanup methods are applied to smoothen the extracted buildings and also to increase the accuracy of extraction of buildings. After converting the raster image into vector image, the building objects are extracted on the basis of area. After filtering the segments, the output raster image is converted into vector image. Then different filters are applied on the image to remove the objects which are not of our interest. After that, the high resolution image is segmented by using the split and merge segmentation so that the pixels that are grouped as raster objects have probability attributes. Firstly, Single Feature Classification is applied on the high resolution satellite image. The Massachusetts Elevation Finder uses the combined tile layer for display and the DEM image service for identifying elevation values.In this paper, an object oriented approach for automatic building extraction from high resolution satellite image is developed. The image services give the user more control to adjust the display properties (stretching, color ramps, etc.) compared to tile layers. A tile layer (cache) that combines the two layers uses the ArcGIS Pro symbology and may be accessed in ArcGIS Online and MassMapper. ![]() The DEM is available as an image service from MassGIS' ArcGIS Server. The ArcMap layer file uses a similar custom color ramp for the DEM and a semi-transparent shaded relief image.Īside from the downloads at the top of the page, the shaded relief image is available as a hosted tile layer at ArcGIS Online and as an image service from MassGIS' ArcGIS Server platform. The shaded relief image was displayed atop the DEM with 45% transparency and the Multiply layer blending mode. The ArcGIS Pro layer file included with the download at the top of the page was created using a custom color ramp for the DEM. State Plane Mainland Meters (Fipszone 2001) projection. Once the eastern and western relief images were created in ERDAS IMAGINE, they were merged using ArcGIS Desktop 10.7.1 and the statewide mosaic was converted to a JPEG 2000 format with values from 0 (black) to 255 (white) and saved in the NAD 1983 Mass. Negative numbers and zero values represent shadowed areas, and positive numbers represent sunny areas. The pixel was then assigned a value between -1 and +1 to represent the amount of light reflected. To create the shaded relief image, a 3x3 neighborhood around each pixel in the DEM was analyzed, and a comparison was made between the sun's position and the angle that each pixel faces. > Download the index (shapefile and Arc layer file 18 MB) The index map is based on the LIDAR_PROJ field in the LIDARDEMSOURCES_POLY feature class. ![]() Several very small gaps between the project areas were patched with older lidar data where necessary or with models from recent aerial photo acquisitions. The overlapping lidar projects were adjusted to the same projection and datum and then mosaicked, with the most recent data replacing any older data. Productionĭates of the primary lidar data used in this DEM range from 2010-2015. In MassGIS' VWP Oracle database, the layer is named GISDATA.IMG_SHADEDRELIEF_LIDAR. ![]() It does not show shadows that would be cast by topographic features onto the surrounding surface. The shaded relief image shows areas that are not in direct sunlight as shadowed. In this instance, the position of the sun was assumed to be 45 degrees above the northwest horizon. Based on a specified position of the sun, areas that would be in sunlight are highlighted and areas that would be in shadow are shaded. A shaded relief image provides an illustration of variations in elevation using artificial shadows. This shaded relief image was generated from the lidar-based bare-earth DEM. In MassGIS' VWP Oracle database, the layer is named GISDATA.IMG_ELEV_LIDAR_INT. This DEM is referenced to the WGS_1984_Web_Mercator_Auxiliary_Sphere projection. This version of the DEM stores the elevation values as integers in both feet and meters. ![]() The elevation of each 1-meter square cell (pixel) was linearly interpolated from classified lidar-derived point data. The spatial resolution of the DEM is 1 meter. This bare earth digital elevation model (DEM) represents the elevation of the surface with vegetation and structures removed. The datasets include: Digital elevation model MassGIS has created seamless, statewide imagery layers from the most recent Lidar Terrain Data.
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