Low cost method maps vegetation in 3-D

Low cost method maps vegetation in 3-D

Researchers at the Department of Geography and Environmental Systems at the University of Maryland (Baltimore, MD, USA) have proposed an inexpensive way to create 3-D maps of vegetation.

Currently, the standard way to make such high spatial resolution measurements of vegetation has required the use of bulky Light Detection and Ranging (LiDAR) equipment mounted on commercial aircraft.

But the Maryland researchers have demonstrated that it is possible to make high spatial resolution 3-D measurements of the structure of vegetation -- together with associated spectral characteristics -- by applying open-source computer vision algorithms to ordinary digital photographs acquired using inexpensive hobbyist aerial platforms.


Recently, the University of Maryland awarded the researchers a grant to develop a software toolkit called Ecosynth based on the concept.

The open-source 3D Ecosynth toolkit will be offered as an open-source development resource on the Ecotope.org community website here to enable other researchers to also acquire images from the ground and air as well as to rapidly generate high-spatial resolution geo-referenced 3-D scans.

-- by Dave Wilson, Senior Editor, Vision Systems Design




Get All the Vision Systems Design News Delivered to Your Inbox

Subscribe to Vision Systems Design Magazine or email newsletter today at no cost and receive the latest news and information.

 Subscribe Now
RELATED PRODUCTS

SPONSORED CONTENT

Webcasts

How the newest machine vision standards will affect you

How will the latest developments in machine vision standards affect you? This webcast will answer that question by featuring updates on relevant standards by some of the industry’s most knowledgeab...
Date: July 15, 2015

How vision systems are changing automotive manufacturing

How do Ford and General Motors leverage machine vision for powertrain manufacturing? How does traditional vision application development serve today’s needs, and what machine vision capabilities co...
Date: June 24, 2015

Archives

Click here to view archived Vision Systems Design articles