LASmoons: Alen Berta

Alen Berta (recipient of three LASmoons)
Department of Terrestrial Ecosystems and Landscape, Faculty of Forestry
University of Zagreb and Oikon Ltd Institute for Applied Ecology, CROATIA

Background:
After becoming the EU member state, Croatia is obliged to fulfill the obligation risen from the Kyoto protocol: National Inventory Report (NIR) of the Green House Gasses according to UNFCCC. One of the most important things during the creation of the NIR is to know how many forested areas there are and their wood stock and increment. This is needed to calculate the size of the existing carbon pool and its potential for sequestration. Since in Croatia, according to legislative, it is not mandatory to calculate the wood stock and yield of the degraded forest areas (shrubbery and thickets) during the creation of the usual forest management plans, this data is missing. So far, only a rough approximation of the wood stock and increment is used during the creation of NIR. However, these areas are expanding every year due to depopulation of the rural areas and the cessation of traditional farming.

very diverse stand structure of degraded forest areas (shrubbery and thickets)

Goal:
This study will focus on two things: (1) Developing regression models for biomass volume estimation in continental shrubberies and thickets based on airborne LiDAR data. To correlate LiDAR data with biomass volume, over 70 field plots with a radius of 12 meters have been established in more than 550 ha of the hilly and lowland shrubberies in Central Croatia and all trees and shrubberies above 1 cm Diameter at Breast Height (DBH) were recorded with information about tree species, DBH and height. Precise locations of the field plots are measured with survey GNNS and biomass is calculated with parameters from literature. For regression modeling, various statistics from the point clouds matching the field plots will be used (i.e. height percentiles, standard deviation, skewness, kurtosis, …). 2) Testing the developed models for different laser pulse densities to find out if there is a significant deviation from results if the LiDAR point cloud is thinner. This will be helpful for planning of the later scanning for the change detection (increment or degradation).

Data:
+
641 square km of discrete returns LiDAR data around the City of Zagreb, the capitol of Croatia (but since it is highly populated area, only the outskirts of the area will be used)
+ raw geo-referenced LAS files with up to 3 returns and an average last return point density of 1 pts/m².

LAStools processing:
1)
extract area of interest [lasclip or las2las]
2) create differently dense versions (for goal no. 2) [lasthin]
3) remove isolated noise points [lasnoise]
4) classify point clouds into ground and non-ground [lasground]
5) create a Digital Terrain Model (DTM) [las2dem]
6) compute height of points above the ground [lasheight]
7) classify point clouds into vegetation and other [lasclassify]
8) normalize height of the vegetation points [lasheight]
9) extract the areas of the field plots [lasclip]
10) compute various metrics for each plot [lascanopy]
11) convert LAZ to TXT for regression modeling in R [las2txt]

Rapidlasso receives “Green Asia Award” at ACRS 2015

PRESS RELEASE (for immediate release)
November 16, 2015
rapidlasso GmbH, Gilching, Germany

At the Asian Conference on Remote Sensing 2015 (ACRS 2015) held in Manila, rapidlasso GmbH was honored with the “Green Asia Award” by the Chinese Society of Photogrammetry and Remote Sensing (CSPRS). This award is given to a paper that directs Asia towards a greener future using remote sensing technology. This year’s award commends rapidlasso GmbH on advancing the area of LiDAR processing through their PulseWaves effort. PulseWaves is a vendor-neutral full waveform LiDAR data exchange format and API that simplifies access to full waveform data and allows researchers to focus on algorithms and share results. In the future this technology may prove valuable to improve biomass estimates for carbon credit programs such as the TREEMAPS project of WWF.

Prof. Kohei Cho and Prof. Peter T. Y. Shih present the award

Prof. Kohei Cho and Prof. Peter T. Y. Shih present the Green Asia Award

The society communicated to Dr. Martin Isenburg, CEO of rapidlasso GmbH, that this award was also meant to honor his many years of teaching and capacity building across the Asian region. Since the beginning of 2013 rapidlasso GmbH has conducted well over 50 seminars, training events, and hands-on workshops at universities, research institutes, and government agencies in Thailand, Malaysia, Myanmar, Vietnam, Indonesia, Singapore, Taiwan, Japan, and the Philippines. The on-going LiDAR teaching efforts of rapidlasso GmbH in Asia and elsewhere can be followed via their event page.

Green Asia Award for CEO of rapidlasso GmbH

Green Asia Award given to the CEO of rapidlasso GmbH

The award certificate that was presented to Dr. Martin Isenburg by Prof Kohei Cho and Prof Peter Shih during the closing ceremony of ACRS 2015 came with a cash reward of USD 300. The award money was donated to the ISPRS summer school that followed the ACRS conference to top off the pre-existing “green sponsorship” by rapidlasso GmbH that was already supporting a “green catering” of summer school lunches and dinners to avoid single-use cups, plastic cutlery and styrofoam containers. The additional award money was used for hosting the main summer school dinner at a sustainable family-run restaurant serving “happy chickens” and “happy pigs” raised organically on a local farm.

during the closing ceremony of ACRS 2015

Award Ceremony held during Closing of ACRS 2015

About rapidlasso GmbH:
Technology powerhouse rapidlasso GmbH specializes in efficient LiDAR processing tools that are widely known for their high productivity. They combine robust algorithms with efficient I/O and clever memory management to achieve high throughput for data sets containing billions of points. The company’s flagship product – the LAStools software suite – has deep market penetration and is heavily used in industry, government agencies, research labs, and educational institutions. Visit http://rapidlasso.com for more information.

Two ASPRS awards for “pit-free” CHM algorithm

PRESS RELEASE (for immediate release)
July 29, 2015
rapidlasso GmbH, Gilching, Germany

The paper “Generating Pit-free Canopy Height Models from Airborne LiDAR” co-authored by rapidlasso GmbH and published in the September 2014 issue of PE&RS (the journal of the ASPRS) was awarded twice at the IGTF 2015 – ASPRS Annual Conference in Tampa, Florida last May. The paper took home the John I. Davidson President’s Award for Practical Papers (2nd Place) as well as the Talbert Abrams Award (2nd Honorable Mention).

The John I. Davidson President’s Award for Practical Papers (2nd Place).

The “pit-free” CHM paper wins the John I. Davidson President’s Award for Practical Papers (2nd Place) and the Talbert Abrams Award (Second Honorable Mention).

The “pit-free” CHM paper is joint work with Anahita Khosravipour, Andrew K. Skidmore, Tiejun Wang, and Yousif A. Hussin of ITC and University of Twente. It describes a technique that can create raster Canopy Height Models (CHMs) without the so called “pits” that tend to hamper subsequent extraction of individual tree attributes such as number, location, height, and crown diameter. The paper uses data measured in the field by ITC researchers to show that “pit-free” CHMs significantly lower the commission and omission errors in single tree detection.

Side-by-side comparison of a "standard" CHM and a "pit-free" CHM.

Visual side-by-side comparison of a “standard” versus a “pit-free” CHM.

The “pit-free” CHM algorithm can easily be implemented with LAStools either by modifying an available batch script or by executing the LAStools Pipelines distributed with the toolboxes for ArcGIS and QGIS. A detailed blog article that compares various different methods for creating CHMs is available via the Web pages of rapidlasso GmbH.

We at rapidlasso GmbH like to especially congratulate the main author, Ms. Anahita Khosravipour, who managed to get two awards with her very first academic publication. Those who like our “pit-free” CHM algorithm will probably also love the new technique that our team will introduce later this year at SilviLaser 2015 in France.

About rapidlasso GmbH:
Technology powerhouse rapidlasso GmbH specializes in efficient LiDAR processing tools that are widely known for their high productivity. They combine robust algorithms with efficient I/O and clever memory management to achieve high throughput for data sets containing billions of points. The company’s flagship product – the LAStools software suite – has deep market penetration and is heavily used in industry, government agencies, research labs, and educational institutions. Visit http://rapidlasso.com for more information.

LASmoons: Andrew Smith

Andrew Smith (recipient of three LASmoons)
Advanced Diploma in GIS Applications
Vancouver Island University, Victoria, CANADA

Background:
Forestry and natural resource development are a large part of British Columbia’s economy and tourism. BC has some of the largest areas of forest-covered land in Canada, and some of the toughest terrain, which makes it a great place for towering trees and nature lovers. With proper resource management we can help ensure that the forestry sector meets its needs for wood while maintaining its obligations to ecosystem management and land use planning.

lasmoons_andrew_smith_0Goal:
The aim of this project is to assess the efficiency of utilising LiDAR data to develop a more spatially
detailed and accurate classification system of tree species. By identifying key tree species, and
tree populations, we can help forestry companies to be more efficient, and cost effective, allowing them
to have better ecosystem management and land use planning. This will help with harvesting profiles,
cutting schedules, opening size, as well as proper habitat analysis and development in line with
BC Forests and Range Practices Act, which spells out forestry obligations for wildlife management and
habitat creation.

Data:
+ 5 square kilometres of LiDAR data covering BC Coastal Forest on Vancouver island, Canada.
+ Average point density: 37 points per square metre.

LAStools processing:
1)
classify the ground points to create a DTM [lasground]
2) normalize the height the trees. the tallest tree in the sample plot is 70 meters tall [lasheight]
3) generate a Canopy Height Model (CHM) using CHM using the pit-free algorithm from (Khosravipour et. al, 2014) with the workflow described here [lasthin, las2dem, lasgrid]
4) overlay the CHM with high-resolution ortho images to first extract tree species, location and canopy diameter and to then derive tree diameter at breast height (DBH) for all identificatied single trees using Taper equations.

Reference:
Khosravipour, A., Skidmore, A.K., Isenburg, M., Wang, T.J., Hussin, Y.A., 2014. Generating pit-free Canopy Height Models from Airborne LiDAR. PE&RS = Photogrammetric Engineering and Remote Sensing 80, 863-872.
BC Forests and Range Practices Act, Forest and Range Evaluation Program Strategic Plan 2011 – 2013 November 8, 2011. http://www.for.gov.bc.ca/ftp/hfp/external/!publish/frep/library/FREP-Strategic-Plan-2011.pdf

Beautiful Full-Waveform LiDAR of a Tropical Rainforest

Scanning forests with LiDAR is done to predict timber yield, estimate biomass, and monitor ecosystems. A detailed Digital Terrain Model (DTM) is needed to accurately compute forestry metrics such as tree height. For generating a DTM it is important to have enough “ground returns” that measure the elevation of the bare-earth for which the laser pulse needs to penetrate through the vegetation down to the forest floor and reflect back to the plane. This can be difficult in a dense tropical forest with tall trees and many layers of canopy as the light of the laser pulse has many opportunities to be reflected or absorbed before reaching the ground. Often none of the light energy will reach the forest floor or the returning ground echo will be too weak to be registered back at the plane.

The "airborne sensors" of  Asian Aerospace Services is equpiied with a RIEGL Q680i airborne LiDAR scanner.

The “airborne sensors” aircraft of Asian Aerospace Services is equipped with a RIEGL Q680i airborne LiDAR scanner.

Asian Aerospace Services Ltd. and rapidlasso GmbH flew a RIEGL LMS Q680i LiDAR system out of a Diamond DA42 “Airborne Sensors” aircraft above dense tropical rainforest in Thailand. We did a short test flight to determine whether the LiDAR would be able to penetrate the canopy of Khao Yai National Forest. The original objective was to demonstrate that the scanner is able to “see through” the canopy in order to produce data for the TREEMAPS project of WWF Thailand funded with EUR 1,730,205 through the International Climate Initiative of the German government. Unfortunately Germany had to pull the funding for TREEMAPS after political tinkering started to interfere with technical objectives, and the LiDAR produced by our “pro-bono flight” has become the only tangible outcome produced by TREEMAPS. We are now making this data available under a Creative Commons Public Domain license (for download see below).

Above Khao Yao National Forest scanning for the pro-bono test flight to investigate the canopy penetration of our LiDAR.

Above Khao Yao National Forest during a test scan to investigate the canopy penetration of the RIEGL Q680i LiDAR scanner.

Low clouds disrupted our original plans but we had one cloud-free stretch during a ferry flight between target locations. We were scanning for 90 seconds at 1200 meters above ground with a speed of 220 km/h. The Q680i was set to operate at a laser pulse rate of 80 kHz with the polygon mirror rotating 10 times per second. The effective scan rate was 240 / 360 * 80,000 = 53,333 shots per second, as each of the 4 mirror facets covers 60 degrees – summing up to 240 degrees – and there are no laser shots leaving the aircraft for the remaining 120 degrees of between facets.

The 53,333 shots per second are reflected over the length of 10 * 4 = 40 mirror facets so that a single scan line contains a sequence of 53,333 / 40 = 1333 shots spaced about 12.4 microseconds apart. After each scan line comes a short pause of 8.3 milliseconds during which the mirror rotates 30 degrees to the next facet. Flying at 220 km/h and 1200 meters above ground means that each second we scanned 62 meters of a 1430 meters wide swath. This resulted in a pulse spacing of 62 / 40 = 1.55 meters between subsequent scan lines and a pulse spacing of 1430 / 1333 = 1.07 meters along each scan line. The 90 second scan resulted in a strip length of about 5.5 km.

The PulseWaves export options available in RIEGL's RiPROCESS.

The PulseWaves export options available in RIEGL’s RiPROCESS.

For each shot the outgoing as well as the returning waveform are digitized and stored to RIEGL’s proprietary SDF format. We used RIEGL’s RiPROCESS software (version 1.5.8) to export the 4,770,152 shots as full waveform LiDAR to PulseWaves and to extract a total of 7,956,587 returns as LASzip-compressed discrete LiDAR to the LAZ format.

The DSM, DTM, and CHM of the 5.5 km long strip scanned above Khao Yai National Forest.

The DSM, DTM, and CHM of the 5.5 km long strip scanned above Khao Yai National Forest.

The Q680i produced sufficiently many ground returns to compute a “plausible” DTM (using lasground and las2dem of LAStools) despite the dense 45 meter tropical canopy during leaf-on season and high humidity. Typical terrain features such as streams and slopes are clearly visible in the hillshading. The corresponding Canopy Height Model (CHM) uses a false coloring that maps vegetation heights of 0 meters to blue and heights of 45 meters to red. There is less vegetation (darker blue) in areas that appear to be in the steeper parts of the DTM.

Only 5 % of pulses emitted produced a discrete return on the ground … this is rather low. It means that the generated DTM will be of much coarser resolution than the number of pulses shot per square meter would typically suggest. Of the 250,473 points classified as ground only 30,931 are single returns where the laser had an unobstructed view of the bare earth. More than half of the ground returns come from laser shots that had already produced two or more vegetation returns and 7,665 of them had their light energy weakened by grazing four or more layers before hitting the forest floor. Scrutinizing the full waveform LiDAR might lead to more ground information to improve the accuracy of the DTM.

We are happy to provide both – the discrete return as well as the full-waveform LiDAR – under a Creative Commons Public Domain license to researchers world-wide. You can download the data here:

You can decompress the pair of compressed PulseWaves files PLZ + WVZ into an pair of uncompressed PulseWaves files PLS + WVS with pulsezip.exe – a recent addition to PulseTools. We would be happy to hear back about your experiences with the data. You could join the PulseWaves user forum at http://pulsewaves.org and share your insights with the group. Below a visualization of a small part of the full waveforms …

Full Waveform LiDAR from Khao Yai National forest.

Full Waveform LiDAR from Khao Yai National forest.

Rapidlasso Teams Up with Carbomap

PRESS RELEASE (for immediate release)
December 4, 2014
rapidlasso GmbH, Gilching, Germany

Just in time for ELMF 2014 in Amsterdam, rapidlasso GmbH and Carbomap Ltd. have teamed up to further the development of tools that better exploit full-waveform LiDAR for the forestry and carbon market. This partnership brings together many years of expertise in processing discrete and full-waveform LiDAR with a wealth of experience in applying this technology within forestry and biomass applications.

The full-waveform tools are built around the PulseWaves format, an open LiDAR format that is the full-waveform sibling of the venerable LAS format, reaffirming a joint committment to support the use of open data formats within the LiDAR industry. Software will be developed both as stand-alone tools as well as for use within the IDL framework.

The use of LiDAR in the forest and carbon industries is expanding rapidly. The new partnership between rapidlasso and Carbomap targets the development of solutions for this growing market. Together the two companies can offer a wider range of tools for vegetation analysis that better exploit the additional information captured by a modern full-waveform scanner, including the newest multispectral instruments.

Antoine Cottin (left), CTO of Carbomap, and Martin Isenburg (right), CEO of rapidlasso, discuss technologie details about their new partnership.

Antoine Cottin (left), CTO of Carbomap, and Martin Isenburg (right), CEO of rapidlasso, discuss technology details about their new partnership.

About rapidlasso GmbH:
Technology start-up rapidlasso GmbH specializes in efficient LiDAR processing tools that are widely known for their high productivity. They combine robust algorithms with efficient I/O and clever memory management to achieve high throughput for data sets containing billions of points. The company’s flagship product – the LAStools software suite – has deep market penetration and is heavily used in industry, government agencies, research labs, and educational institutions. Visit http://rapidlasso.com for more information.

About Carbomap Ltd:
Carbomap is an environmental survey company spun out of the University of Edinburgh. The company takes forward over five years of world-class research in the development of a Multispectral Canopy LiDAR, a revolutionary, patent-pending laser scanning instrument designed to fill a gap in airborne forest survey requirements. The founders are international renown for remote sensing methodologies, satellite radar mapping, forest structure mapping, carbon sequestration and airborne survey. Carbomap is currently the only company with tools for analysing multispectral LiDAR for forest applications. Visit http://carbomap.com for more information.

Worldwide LiDAR of Rainforest Biomass for REDD+

We at rapidlasso have long been big fans of the biomass and biodiversity work done by Greg Asner’s group and their Carnegie Airborne Observatory. They were, in fact, the earliest “power-users” of the BLAST extension of LAStools and helped finding all the bugs when rasterizing billions of LiDAR points collected during large-scale surveys in the Amazon into Digital Elevation Models (DEMs) with blast2dem. Below a video fly-through of some of the LiDAR they collected.

A few days ago, Greg Asner together with his colleagues Joseph Mascaro, Stuart Davies, Alex Dehgan, and Sassan Saatchi published a thought-provoking article called “These are the days of lasers in the jungle” which is essentially a “call for action” to map the world’s tropical forests with a fleet of airplanes outfitted with advanced LiDAR to rapidly and to accurately assess global forest carbon stocks.

Why would anyone want to do this? In order to properly quantify actual emissions savings for REDD+ (Reduced Emissions from Deforestation and Degradation). REDD+ is a tropical forest carbon accounting program of the United Nations Framework Convention on Climate Change that aims to compensate tropical countries for reducing carbon emissions from deforestation and forest degradation that account for roughly 10 percent of global greenhouse gas emissions. The key to implement such a program is the ability to accurately and affordably estimate the actual emissions savings and a worldwide LiDAR inventory of tropical forests will accomplish just that argues the paper. This “call for action” has since been picked up by Mongabay – a site that examines emerging trends in climate, technology, and finance on conservation and development.

Interesting is the price tag that they estimate, which is a fraction of the cost of a typical Earth observation satellite mission, They claim: “Our ambitious plan can be accomplished for far less than what we have already spent on avoided deforestation. Aircraft leasing, data collection and processing costs for 30 days of flying can reasonably be limited to USD 500,000 Using this monthly sampling unit, collecting at an average of 100,000 hectares per day, a fleet of ten aircraft could do the job in four years at USD 250 million, or just 5% of pledged REDD + funding.”

The authors state “The time has come for a brute-force effort to directly assess the carbon stock for all of the world’s tropical forests by 2020” because “airborne LiDAR is uniquely suited for this role because it can be collected, standardized, reported and verified in a simple manner by both a landholder and any third party”. Should such a campaign turn out to be a viable option to implement REDD+ we hope full waveform LiDAR – not just discrete returns – will be collected.

Waveform digitizers have become popular because they can capture the reflection of the emitted laser pulse with much more detail than a discrete return system. The intensity of the signal returning to the plane is digitized up to one billion times per second, giving a vertical resolution of one digitized amplitude each 15 centimeters. As this can capture the interactions between each laser pulse and the vegetation with much greater detail, it would seem that having full waveform instead of discrete returns will prove especially useful for biomass studies. A future blog post will talk about our own experiences of scanning tropical rainforest to produce full waveform LiDAR in PulseWaves format.

Another approach with a similar objective is being taken by NASA with their future GEDI space LiDAR. The Global Ecosystem Dynamics Investigation (GEDI) instrument will be the first to systematically probe the depths of the forests from space to reveal their 3D structure, as depicted in the artist’s concept below, and provide crucial information about the impact that trees have on the amount of carbon in the atmosphere. “One of the most poorly quantified components of the carbon cycle is the net balance between forest disturbance and regrowth”, said Ralph Dubayah, the GEDI principal investigator at the University of Maryland. “GEDI will help scientists fill in this missing piece by revealing the vertical structure of the forest, which is information we really can’t get with sufficient accuracy any other way”. The instrument will be built at NASA’s Goddard Space Flight Center in Greenbelt, Maryland. Not sure about the price tag.

nasa_gedi

Image Credit: NASA’s Goddard Space Flight Center

Until either of these projects become reality, “enjoy” this video by Carnegie Airborne Observatory of a 3D flyover that shows rapidly expanding palm oil plantations in the Peruvian Amazon rainforest that are contributing to deforestation.