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3d-model-new-york-city

FME Workspaces created in the cours of generating a semantic digital 3D city model for the entire city of New York are available for download on this GitHub page.

amundsen

Amundsen is a metadata driven application for improving the productivity of data analysts, data scientists and engineers when interacting with data.

amundsendatabuilder

Data ingestion library for Amundsen to build graph and search index

amundsenfrontendlibrary

Front-end service library for Amundsen

amundsensearchlibrary

Search service library for Amundsen

awesome-data-labeling

A curated list of awesome data labeling tools

awesome-geospatial

Long list of geospatial tools and resources

bestpractice

A Best Practices analysis tool for FME Workspaces

bps

Efficient Learning on Point Clouds with Basis Point Sets

building-finder

A python + postgreSQL model for finding building footprints and heights by implementing DBSCAN on LIDAR data.

building-segmentation-reference-dataset

This is the data set used as the reference for the segmentation of LiDAR building point clouds

building_footprint_extraction

building_footprint_segmentation

Building Footprint Segmentation from Satellite images

buildingdetectors

Winning building footprint detector implementations from the SpaceNet challenges.

buildingfootprints

cartography

Cartography is a Python tool that consolidates infrastructure assets and the relationships between them in an intuitive graph view powered by a Neo4j database.

cookbook-r

Chef Cookbook for R

csf

LiDAR point cloud ground filtering / segmentation (bare earth extraction) method based on cloth simulation

datascience-ml-training

datastandards.directory

The Open Data Standards Directory is an iniative to provide an inventory of information regarding open data standards. This site is operated by the Center for Government Excellence at Johns Hopkins University, in partnership with Geothink, McGill University and members of the open data community.

deeplearningbook

MIT Deep Learning Book in PDF format

deeplidar

Deep Surface Normal Guided Depth Prediction for Outdoor Scene from Sparse LiDAR Data and Single Color Image

dxwg

Data Catalog Vocabulary (DCAT)

fme-workspaces

Collection of workspaces for FME

fmepedia-pointcloud

Demo of point cloud data distribution using FME Server

forestmetrics

Individual tree segmentation from LiDAR-derived point clouds

harvardopendata.github.io

Harvard's first open data catalog

labeled-3d-lidar-ieee_tits_2018

Data used in the following paper: Zhang, Y., Wang, J., Wang, X., & Dolan, J. M. (2018). Road-Segmentation-Based Curb Detection Method for Self-Driving via a 3D-LiDAR Sensor. IEEE Transactions on Intelligent Transportation Systems. https://doi.org/10.1109/TITS.2018.2789462

lastools

efficient tools for LiDAR processing

learning-python

Python notebooks