Tools tagged with "point-clouds"

Lidar is a specialized Python package designed for analyzing high-resolution topographic data, particularly Digital Elevation Models (DEMs) derived from LiDAR. It enables the delineation of the nested hierarchy of surface depressions, offering crucial insights for hydrological and geomorphological studies. The tool is openly available and supported by comprehensive documentation.

Open3D is an open-source library designed for the rapid development of software involving 3D data. It provides a highly optimized backend for parallelization and exposes a curated set of data structures and algorithms in both C++ and Python. The library supports various 3D data processing tasks, including scene reconstruction, surface alignment, and advanced visualization with physically based rendering.

Cesium provides an end-to-end platform for streaming and visualizing massive 3D geospatial content. It leverages open standards and an open-source ecosystem to facilitate advanced 3D mapping and digital twin applications. The platform includes cloud services for tiling, hosting, and global 3D content.

The Puget Sound LIDAR Consortium (PSLC) website provides access to historical LiDAR data for the Puget Sound area. While no longer actively maintained, it served as an important early resource for researchers and the public. Users are now directed to the more current Washington Department of Natural Resources LiDAR portal for up-to-date information and data.

The 3D Elevation Program (3DEP) is a U.S. Geological Survey (USGS) initiative to systematically collect enhanced elevation data nationwide. It aims to generate high-resolution topographic data, primarily using lidar technology, to support a wide range of applications. This program provides critical foundational data for mapping, natural resource management, infrastructure planning, and hazard mitigation across the United States.

Potree is an open-source WebGL-based point cloud viewer, enabling users to interactively explore extensive 3D point cloud datasets directly within a web browser. It provides a robust solution for visualizing remotely sensed data, supporting various applications from urban planning to environmental monitoring.

This resource details the lidar data collection methods employed by NSF NEON to map vegetation height, density, and other surface characteristics over large regions. Using airborne sensors, lidar provides detailed 3D pictures of forest structure, crucial for ecological research. It highlights the advantages of active sensors like lidar for comprehensive ecosystem parameter mapping.

PDAL is an open-source C++ library and suite of applications designed for the translation and processing of point cloud data. It provides a common abstraction layer for various point cloud formats, enabling users to read, write, filter, and manipulate large geospatial datasets efficiently.

OpenTopography provides easy, centralized access to a diverse collection of high-resolution topographic data. This platform strives to simplify data discovery by integrating data from various sources, including the USGS 3D Elevation Program. It also offers a suite of tools for processing and analyzing these datasets.

LiDAR and Aerial Archaeology offers free LiDAR and aerial photography maps from various global regions. It also provides access to other related archaeological resources, including training materials and geological data.

This platform offers comprehensive access to LIDAR datasets for New York State, including options for individual tile downloads via an application and bulk downloads through an FTP site. It also tracks the status of in-progress, planned, latest, and historic LIDAR collections across the state. Users can explore various projects and access associated metadata.

DASC serves as the official State of Kansas GIS data clearinghouse, archiving and distributing authoritative geospatial data from trusted sources. It offers a comprehensive GeoPortal Hub for downloading GIS and map data, including LiDAR and imagery, alongside various geospatial technical services and application hosting for state agencies and partners.

pgpointcloud is a PostgreSQL extension designed to efficiently store and manage point cloud data, specifically LIDAR data. It provides robust capabilities for handling large datasets, enabling geospatial professionals to integrate high-density spatial information directly within their database infrastructure.

The TxGIO DataHub serves as a central repository for geospatial data pertaining to Texas. It offers various data categories including imagery, elevation, hydrography, and transportation, accessible through multiple delivery methods. Users can download, access external links, or order specific datasets.

displaz is an open-source, hackable lidar viewer designed for visualizing point cloud data. Hosted on GitHub, it encourages community contributions for its development and enhancement, providing a flexible platform for geospatial professionals and enthusiasts.

HELIOS++ is developed and maintained by the 3DGeo Research Group at Heidelberg University. This C++11-written package provides robust capabilities for simulating various LiDAR operations, making it a valuable resource for researchers and practitioners in geospatial science. It supports detailed simulations of laser scanning surveys, essential for planning and analysis in 3D geographic data acquisition.

point-cloud-utils is a Python library designed for efficient processing and manipulation of 3D point clouds and meshes. It offers a straightforward interface for common operations, making it accessible for developers and researchers working with 3D geospatial data. The library aims to simplify complex tasks related to 3D data handling.

OpenDroneMap/ODM is an open-source command-line tool designed for processing aerial imagery. It transforms images captured by drones, balloons, or kites into valuable geospatial products. This toolkit is essential for users needing to create detailed maps, reconstruct 3D environments, and generate elevation models.

OpenDroneMap is a suite of open-source tools designed for processing aerial images from drones. It enables users to create high-quality geospatial products like orthomosaics, point clouds, 3D models, and digital elevation models, supporting various camera types and image orientations. The project fosters a sustainable ecosystem for aerial data collection, processing, analysis, and display, backed by a collaborative community.

This guide introduces the lidR package, an open-source R tool for processing and visualizing airborne laser scanning (ALS) data. It emphasizes research and development applications in forestry and ecology, offering functions for reading/writing LiDAR files, point cloud processing, and individual tree segmentation.

The Computer Vision Group at TUM offers a variety of datasets for researchers in computer vision, image processing, and pattern recognition. These datasets are shared to foster academic collaboration, with a request to cite the relevant publications when utilized.

Probreg is an open-source Python package designed for aligning point clouds through advanced probabilistic models. It offers implementations of several registration algorithms, including Coherent Point Drift, GMMReg, SVR, GMMTree, FilterReg, and Bayesian CPD. This tool is essential for tasks requiring precise spatial alignment of 3D data.

This open-source JavaScript library provides a robust renderer implementation for the 3D Tiles format, leveraging the three.js library for efficient visualization. Developed by NASA-AMMOS, it supports most features of the 3D Tiles specification and includes various examples for different use cases. It allows for rendering complex geospatial 3D data directly in web applications.

This metadata catalog documents UAV flight activities conducted by the IN SITU.MLUGEO drone team, publishing all flight operations. It provides high-quality geospatial data derived from RGB, thermal, multispectral, and LiDAR sensor technology, supporting numerous research projects and study areas. Users can explore datasets via interactive search filters and submit data requests through a contact form.

Hexagon is a global leader in measurement technologies, providing confidence to vital industries. It focuses on enabling customers to build, navigate, and innovate through its comprehensive solutions. The company's offerings span from precision measurement to autonomous solutions, transforming various sectors.

Flash Point Classifier is a powerful and user-friendly software tool designed for rapid classification of airborne lidar point clouds. It transforms raw lidar data into actionable insights, offering custom classification options and the ability to manage data locally without cloud uploads. The software is cross-platform, available for Windows and macOS, and enhances productivity through streamlined workflows and parallel processing.

This resource provides NOAA Coastal Lidar Data, a collection of lidar projects focused on U.S. coastal areas. The data, measuring 3D object locations from airborne platforms, is available in Entwine Point Tiles (EPT) and LAZ formats. It includes point clouds attributed with object type, reflection intensity, and other metadata, organized by original projects with specific coordinate reference systems.

WhiteboxTools is an advanced geospatial data analysis platform designed for environmental applications, offering a comprehensive suite of tools for processing and analyzing various types of geospatial data. It serves as a powerful resource for researchers, students, and professionals in the field of geospatial science.

LGB (Landesvermessung und Geobasisinformation Brandenburg) serves as the state agency responsible for official land surveying and providing fundamental geoinformation for Brandenburg, Germany. It offers a wide array of geospatial data, applications, and services to the public and professional users.

OpenSfM is an open-source Structure-from-Motion (SfM) pipeline developed by Mapillary. It provides tools and algorithms for reconstructing 3D models from collections of unordered images, serving as a foundational component for various geospatial and computer vision applications. The project is hosted on GitHub, encouraging community contributions and development.

Entwine is a powerful data organization library specifically built for managing massive point cloud datasets, including those with trillions of points. It can index anything readable by PDAL, supporting various sources like S3 and Dropbox. The library ensures completely lossless builds, preserving all points, metadata, and precision.

This GitHub repository provides tools and methods for performing road corrections and measurements using Airborne Laser Scanning (ALS) data. It focuses on extracting valuable information about road infrastructure from high-resolution LiDAR scans. The project aims to facilitate accurate analysis and management of road networks.

Connecticut Environmental Conditions Online (CT ECO) provides access to a wealth of geospatial information focusing on Connecticut's environment. Users can explore various map viewers, browse a catalog of static PDF maps by town, and connect to map services using GIS software. The platform also offers direct downloads of GIS files for further analysis and integration.

SensatUrban is a large-scale photogrammetric point cloud dataset designed for urban semantic segmentation research. It features nearly three billion richly annotated points, covering approximately 6 km² across two UK cities. This dataset provides essential benchmarks and challenges for advancing 3D point cloud analysis and deep learning applications.

This dataset provides access to the USGS 3D Elevation Program (3DEP) LiDAR point cloud data covering the conterminous United States, Hawaii, and U.S. territories. It offers two data realizations: public access Entwine Point Tiles (EPT) and Requester Pays access to the original Raw LAZ format. The data is periodically updated and available under a US Government Public Domain license.

Cartographer is an open-source software system designed to provide robust real-time simultaneous localization and mapping (SLAM) capabilities. It supports both 2D and 3D environments, enabling precise navigation and mapping across various platforms and sensor configurations. This system is crucial for applications requiring accurate self-localization and environmental modeling.