[Crack Para Global Mapper 14 154
Tilo Chopin
I export as *.dem from global mapper and use that to build the surface. Make sure your projection matches the one used in C3D. Create the surface and add the dem to it instead of creating one from a dem.
Sanet,
Civil 3D has a little problem with DEM data. It uses the lower left of pixel instead of center. DEM is derivative data. Better to use the original LiDAR point cloud data.
Location? I'd try first to find state or county elevation data.
Dave
@Pointdump
Hi,
Thank you very much for the information you sent. I got the lidar data. The coordinate system of my cad drawing is NAD83 Georgia State Planes, West Zone, US Foot (GA83-WF). But when .laz is converted to .rcp through autocad recap and imported into civil 3d, it is displayed in a different place. (When importing to civil 3d, I also imported according to "use geographic location".)
please help.
Hi, @Pointdump
Thank you very much for the information you sent. I got the lidar data. The coordinate system of my cad drawing is NAD83 Georgia State Planes, West Zone, US Foot (GA83-WF). But when .laz is converted to .rcp through autocad recap and imported into civil 3d, it is displayed in a different place. (When importing to civil 3d, I also imported according to "use geographic location".)
please help.
Sanet,
What did "Current" and "Target" look like when you brought the point cloud into ReCap?
The LAZ file I grabbed was horizontal degree units and vertical Meters. ReCap read the header information as "LL-HPGN".
Dave
Sanet,
Horizontal transformation worked well on the LAZ file I grabbed. You'll need to check vertical units to see if they are OK.
Attached are drawing, ReCap files, and the original LAZ file. I filtered ground points in ReCap.
Dave
Civil 3D inserts the DEM the same way it inserts all rasters, i.e. the lower left of each pixel. However, if you add the DEM as an FDO connection, then it inserts properly. (It treats the raster as an entity, not as a collective bunch of pixels.) As long as the raster is a rectangle and not an IRREGULAR shaped image, such as one with zig-zag edged(s), an FDO will insert correctly.
Global Mapper is more than just a utility; it offers a surprisingly extensive collection of analysis and data processing tools in a truly affordable package. Providing support for virtually every known spatial file format as well as direct access to common spatial databases, this remarkable application can read, write, and analyze virtually all spatial data.
Complementing these powerful analysis tools is Global Mapper includes a complete suite of raster and vector data creation and editing functions offering everything from simple and intuitive drawing to image rectification and vectorization. Global Mapper The software also includes numerous attribute editing functions as well as intuitive data display and thematic mapping capabilities.
When the time comes to share map data, Global Mapper offers numerous options including eye-catching page layout and printing tools, geospatial PDF creation, and direct web publishing to MangoMap, an affordable and easy-to-use online map service.
Offering access to an unparalleled variety of spatial datasets, Global mapper provides a high level of functionality to satisfy both the experienced GIS professionals and beginning users. Global mapper can be used as a standalone spatial data management tool or as an integral component of an enterprise-wide GIS.
Using an array of overlapping images, such as those collected using a drone, the Pixels to Points tool generates a high-density point cloud based on user-selectable parameters. Employing the principles of photogrammetry in which measurements are derived from photographs, the Pixels to Points tool analyzes the relationship between recognizable objects in adjacent images to determine the three-dimensional coordinates of the corresponding surface. As a by-product of the point cloud generation capability, the Pixels to Points tool also offers the option of creating an orthorectified image by gridding the RGB values in each point, as well as a 3D Mesh, complete with photorealistic textures.
The processing of creating the point cloud begins with a simple loading of the images into the Pixels to Points dialog box. For optimal results, at least 60% overlap and evenly distributed photos taken from varying angles are recommended. Individual images can be previewed and those not needed for the final point cloud can be removed. Various settings can then be applied to determine the output quality, analysis method, etc. Finally, ground control points may optionally be added to adjust the horizontal and vertical positioning of the point cloud. After processing is complete, the point cloud will be automatically added to the current workspace. It can be further processed or edited before exporting to any of the supported point cloud formats including LAS and LAZ.
The Pixels to Points process is memory intensive and may take several hours to process depending on the input data and quality setting. It is recommended that this process is performed on a dedicated computer with at least 16GB of RAM. The Pixels to Points tool also requires a 64-bit operating system.
Using a selected group of lidar points, this process uses the inherent 3D geometry of the points along with the associated colors if present and creates a 3D mesh or model. When viewed in 3D, this model displays as a multifaceted photo-realistic 3D representation of the corresponding feature. This process produces a similar output to the model creation option in the Pixels to Points tool.
The Lidar Module offers a tool for verifying the vertical accuracy of a point cloud. Using surveyed ground control points, the elevation values throughout the layer can be checked and adjusted if necessary.
Points can be filtered using a variety of criteria and at various stages during the point cloud processing workflow. During import, points can be filtered based on classification, return count, sample count, or based on their geographic distribution. The same filtering options can be used to filter the display of points in the map view. When creating a gridded surface or a DEM, a further level of filtering is available which can be used to remove points based on elevation range, classification, intensity, color, or on many other point cloud characteristics.
Addressing a major concern among lidar users, Global Mapper Lidar Module provides an efficient and effective way to remove noise from point cloud data. This powerful filtering tool can reclassify or automatically delete any points that are beyond a prescribed elevation or height above the ground threshold within a local area.
The Lidar Module includes numerous tools for querying points based on both the point cloud attributes and on their geographic distribution. The Search function can be used to create a multi-level query of point classification, elevation range, intensity, or any of the other variables. Spatial querying options include identifying points contained within a selected polygon or points that are within a defined distance of a certain type of point type or line feature. This function is ideally suited for encroachment detection.
Using a set of customizable parameters, this tool reduces the number of points in a point cloud resulting in a more manageable file size while eliminating redundancy. This thinning process can be applied consistently across the 2D extent of the layer or it can vary to reflect the 3D distribution of points.
The Lidar Module provides numerous options for creating a surface model. Supplementing the simple triangulation (TIN) process, binning offers a more efficient and customizable way to create DTM or DSM of a specific resolution. Hydro-flattening allows the inherent elevation values associated with 3D vector lines or polygons to override the point-based elevations when modeling water bodies or streams.
The module enables the display of a section of a point cloud in the Path Profile view. This lateral perspective is initially created by establishing a swath width to ensure that sufficient points are displayed for the area of interest. The lateral perspective is ideally suited for manual point selection and editing as it clearly distinguishes points that are vertically offset from those in the surrounding area.
The specific version of Global Mapper you license from Blue Marble may be used indefinitely as the license file delivered is perpetual. Once the license file has been delivered to activate the software on the target machine, there are restrictions on the frequency in which you may move the software to additional machines. For the first year after purchase, upgrade, or renewal of maintenance and support, this perpetual license entitles the customer to download all released versions of the software and to receive technical support. After one year has passed since the last purchase, upgrade, or renewal of maintenance and support, the license may be upgraded by purchasing maintenance and support. Please contact our sales team for more information on the latest upgrade rates.
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Analyses were performed at a 1-km resolution for terrestrial lands defined as cells containing one or more 300-m pixels of terrestrial land cover types based on ESA CCI dataset67. We projected input data to the equal-area Mollweide projection and applied bilinear resampling method for continuous raster data and nearest-neighbor method for discrete data (vector data were first projected and then converted to raster datasets). Unless otherwise specified, analyses were conducted using ArcGIS 10.5 (www.esri.com) with the Spatial Analyst 10.5 extension.
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