5/21/12 1 Lidar analysis in support of the Sierra Nevada Adap�ve Management Project SNAMP Spa�al Team Workshop May 16, 17, 2012 Maggi Kelly, Qinghua Guo Sam Blanchard, Jacob Flanagan, Marek Jakubowski, Wenkai Li, Feng Zhao snamp.cnr.berkeley.edu Sierra Nevada Adap�ve Management Project SNAMP Spa�al Team Workshop Agenda 99:10 Welcome and the day’s overview 9:1010 PART 1: Introduc�on – SNAMP Background – Lidar refresher: Lidar basics, Types; Applica�ons – SNAMP Lidar spec – Ques�ons 1010:15 Break 10:1511:00 PART 2: SNAMP and Lidar – SNAMP Lidar products – SNAMP Lidar research – Lidar + imagery data sources – Ques�ons 11:0011:45 PART 3: Data and So�ware 11:4512:00 – Ques�ons and Evalua�ons 12:00 Adjourn May 16 2012 – Oakhurst, CA May 17, 2012 – Foresthill, CA
24
Embed
SNAMP Spa al Team Workshop Agendasnamp.cnr.berkeley.edu/static/documents/2012/05/21/SNAMP-Spatial... · JFire & Forest Health team works at the scale of the individual tree, to ...
This document is posted to help you gain knowledge. Please leave a comment to let me know what you think about it! Share it to your friends and learn new things together.
Transcript
5/21/12
1
Lidar analysis in support of the Sierra Nevada Adap�ve Management Project
SNAMP Spa�al Team Workshop May 16, 17, 2012 Maggi Kelly, Qinghua Guo Sam Blanchard, Jacob Flanagan, Marek Jakubowski, Wenkai Li, Feng Zhao
snamp.cnr.berkeley.edu Sierra Nevada Adap�ve Management Project
SNAMP Spa�al Team Workshop Agenda
9-‐9:10 -‐ Welcome and the day’s overview 9:10-‐10 -‐ PART 1: Introduc�on
10-‐10:15 -‐ Break 10:15-‐11:00 -‐ PART 2: SNAMP and Lidar
– SNAMP Lidar products – SNAMP Lidar research – Lidar + imagery data sources – Ques�ons
11:00-‐11:45 -‐ PART 3: Data and So�ware 11:45-‐12:00 – Ques�ons and Evalua�ons 12:00 Adjourn
May 16 2012 – Oakhurst, CA
May 17, 2012 – Foresthill, CA
5/21/12
2
snamp.cnr.berkeley.edu Sierra Nevada Adap�ve Management Project
Mee�ng Goals and Desired Outcomes
Goals: To inform stakeholders about SNAMP
spa�al team people and research, with concentra�on on Lidar data.
Desired Outcomes: Increased knowledge of how spa�al data
are integrated into SNAMP. Open communica�on between SNAMP
spa�al team and stakeholders. Par�cipate in the SNAMP adap�ve
management outreach process.
snamp.cnr.berkeley.edu Sierra Nevada Adap�ve Management Project
Sierra Nevada Adap�ve Management Project
What is SNAMP?
A partnership with the goal of learning how to ensure the long-‐term sustainability of the Sierra Nevada forests.
Who is SNAMP?
A collabora�on among federal and state resource agencies. An independent “third-‐party” of University researchers. Public and private stakeholders.
5/21/12
3
snamp.cnr.berkeley.edu Sierra Nevada Adap�ve Management Project
Fire in the Sierra A century of fire suppression management in the Sierra has resulted in build-‐up of fuel, placing millions of hectares of forest at risk of catastrophic fire.
2004 Sierra Nevada Forest Plan Amendment calls for:
the applica�on of strategic fuel management at landscape levels.
There is great uncertainty about treatments impact on fire behavior, wildlife, forest health and water
snamp.cnr.berkeley.edu Sierra Nevada Adap�ve Management Project
Adap�ve Management Common elements to the challenge of stewardship in the era
of global change
1. Drivers of global change operate on the landscape scale.
2. The science is not always available to inform management.
3. Most modern strategies for resource stewardship acknowledges uncertainty.
4. Most modern strategies invokes “adap�ve management” as part of the solu�on.
Broader implica�ons of SNAMP
Sierra Nevada Forest Plan Amendment describes a landscape scale management strategy (SPLATs).
Learning how to do adap�ve management is the explicit goal of SNAMP.
5/21/12
4
snamp.cnr.berkeley.edu Sierra Nevada Adap�ve Management Project
UC Science Team
The UC Science Team’s role as a neutral third party observer: evaluate the efficacy of treatments across four response variables (water, wildlife, fire,
public par�cipa�on), involve the public, feedback into the AM cycle
Public MOUP
UCST/ AES
County/Local CE
Campus CE
snamp.cnr.berkeley.edu Sierra Nevada Adap�ve Management Project
Sierra Nevada Adap�ve Management Project
SNAMP was formed to develop, implement and test Adap�ve Management processes through tes�ng the efficacy of Strategically Placed Landscape Treatments (SPLATs) across four response variables, including:
Public par�cipa�on Wildlife
Pacific Fisher California Spo�ed Owl
Water Fire/forest health
Each of these groups has an associated research team, and all are supported by a spa�al team.
5/21/12
5
snamp.cnr.berkeley.edu Sierra Nevada Adap�ve Management Project
SNAMP Study Areas and Research Teams Two Study Areas:
-‐ Tahoe Na�onal Forest
-‐ Sierra Na�onal Forest
snamp.cnr.berkeley.edu Sierra Nevada Adap�ve Management Project
SNAMP Research Design
Research design BACI – Before, A�er, Control, Implementa�on
Spa�al Scale
Each team will perform their research at a specific scale: Fire & Forest Health team works at the scale of the
individual tree, to the forest stand, to the fireshed… Wildlife teams work at the scale of the individual
tree and its environs to the scale of an animal’s home range…
Water team works at the scale of the watershed… Public Par�cipa�on works at local and na�onal
scales. Spa�al models will be used to integrate across
teams, and extrapolate results in a common spa�al framework
5/21/12
6
snamp.cnr.berkeley.edu Sierra Nevada Adap�ve Management Project
Immediate goal of SNAMP:
Helping to ensure sustainability of Sierra Nevada forests
snamp.cnr.berkeley.edu Sierra Nevada Adap�ve Management Project
Spa�al Scaling in the Research
5/21/12
7
Op�cal Remote Sensing: the View from Overhead MODIS – Landsat – Orthophotography
snamp.cnr.berkeley.edu Sierra Nevada Adap�ve Management Project
Lidar and SNAMP Lidar-‐based forest products as inputs to process-‐based models
Eleva�on, canopy cover, biomass, LAI, all drive fire behavior models and hydrology models…
Forest characteriza�on to understand wildlife habitats
Loca�on and descrip�on of individual trees across a landscape help us understand Pacific fisher or California spo�ed owl behavior…
Novel lidar visualiza�ons
Help describe the poten�al impact of treatments
5/21/12
8
snamp.cnr.berkeley.edu Sierra Nevada Adap�ve Management Project
SNAMP Spa�al Team
Spa�al Team Goals Developed to assist in the GIS and
remote sensing technology that all teams require.
Members of the spa�al team have the responsibility for suppor�ng all other teams’ GIS, remote sensing and spa�al analysis needs.
Conduct applied research in applica�on of spa�al technology to forest science and management
Spa�al Team Ac�vi�es LIDAR data acquisi�on and analysis Field campaign SNAMP team support
Principal Inves�gators:
Qinghua Guo, UC Merced
Maggi Kelly, UC Berkeley
Graduate Students:
Marek Jakubowski, UCB
Wenkai Li, UCM
Jacob Flanagan, UCM
Postdoc:
Feng Zhao, UCB
Staff:
Hong Yu, UCM
Sam Blanchard, UCB
LiDAR = Light Detection And Ranging
5/21/12
9
snamp.cnr.berkeley.edu Sierra Nevada Adap�ve Management Project
Terrestrial Lidar Lasers for terrestrial applica�ons generally have wavelengths in the range of 900–1064 nanometers, where vegeta�on reflectance is high.
One drawback of working in this range of wavelengths is absorp�on by clouds, which impedes the use of these devices during overcast condi�ons.
terrestrial lidar
Bathymetric lidar
how does it work?
amplitude of etected signal
t
laser pulse detector
LiDAR
5/21/12
10
how does it work?
amplitude of etected signal
t
LiDAR
how does it work?
amplitude of etected signal
t
LiDAR
total time traveled
distance = time x speed
total distance traveled = (total time traveled) x (speed of light)
distance to the ground = (total time traveled) x (speed of light) 2 distance
to the ground
5/21/12
11
what about multiple returns? LiDAR
amplitude of etected signal
t
what about multiple returns? LiDAR
amplitude of etected signal
t
last return 1st return
5/21/12
12
what about multiple returns?
LiDAR
GPS IMU
(X, Y, elevation)
(yaw, pitch, roll angles)
roll angle
dist
ance
(X1, Y1, Z1)
(X2, Y2, Z2)
Discrete and Waveform Lidar
Graphics from Bernhard Hoefle, University of Heidelberg
5/21/12
13
snamp.cnr.berkeley.edu Sierra Nevada Adap�ve Management Project
Waveform targets In addi�on to height, we can analyze three other characteris�cs of the lidar return:
1. Echo width: distribu�on of returns, rougher objects give larger widths
2. Amplitude: strength of reflec�on (reflectance and area size of target)
3. Backsca�er cross-‐sec�on (E x A): electromagne�c energy intercepted and reradiated by objects
Graphics from Bernhard Hoefle, University of Heidelberg
Lidar Applications In 2002, Lefsky wrote: “Developments in lidar remote sensing are occurring so rapidly that it is difficult to predict which applications will be dominant in 5 years.” Currently ecological applications of lidar remote sensing: ground topography, 3D structure and function of
Mapping Sea Level Rise Poten�al sea-‐level rise impact to downtown Ft. Lauderdale, FL. Blue indicates impacted areas at two feet above mean higher high water, and orange indicates the associated uncertainty area based on the eleva�on data and water surface calcula�on. From: h�p://www.csc.noaa.gov/digitalcoast
Lidar and wetlands Moeslund, J.E., Arge, L., Burcher, P.K., Nygaard, B., Svenning, J.C., 2011. Geographically Comprehensive Assessment of Salt-‐Meadow Vegeta�on-‐Eleva�on Rela�ons Using LiDAR. Wetlands, 1-‐12.
5/21/12
17
snamp.cnr.berkeley.edu Sierra Nevada Adap�ve Management Project
Mapping carbon Combining field measurements, airborne lidar-‐based observa�ons, and satellite-‐based imagery, we developed a 30-‐meter-‐resolu�on map of aboveground C density spanning 40 vegeta�on types found on the million-‐hectare Island of Hawaii.
Asner, et al. 2011. High-‐resolu�on carbon mapping on the million-‐hectare Island of Hawaii. Fron�ers in Ecology and the Environment 9, 434-‐439.
Lidar + carbon Example LiDAR-based maps of aboveground carbon stocks highlighting: (A) effects of deforestation on humid, low-elevation forests in the northern region, and (B) a natural gradient in elevation and plant available water, from dry forests with low canopy height in the lowlands to humid forests in the uplands. Asner et al. High-resolution Mapping of Forest Carbon Stocks in the Colombian Amazon Biogeosciences Discuss., 9, 2445-2479, 2012 doi:10.1186/1750-0680-7-2
5/21/12
18
Lidar + hyperspectral imagery can map biomass and stress Swatantran, et al. 2011. Mapping biomass and stress in the Sierra Nevada using lidar and hyperspectral data fusion. Remote Sensing of Environment. 115(11): 2917-‐2930
Lidar Applications: Vegetation Canopies From Vierling et al. 2008. Lidar: shedding new light on habitat characterization and modeling. Frontiers in Ecology and Environment. Lidar can provide fine-grained information about the 3-D structure of ecosystems across broad spatial extents. This data can be used to
investigate: Animal-habitat
relationships; Fire behavior; Carbon and energy
balance; Infiltration, canopy
capture and sublimation.
Lidar-‐derived ver�cal distribu�on plots showing the percentage of laser pulse hits that occurred within a par�cular height classifica�on. This kind of analysis helps us more fully understand the 3-‐D structure of vegeta�on.
High: 100
Low: 0
Percent
Canopy
5/21/12
19
Lidar and Habitat LiDAR-derived predictors described between 4.7 and 21.6% of the variability in overall forest songbird species richness and that of several guilds. Lesak, et al. Modeling forest songbird species richness using LiDAR-derived measures of forest structure. Remote Sensing of Environment 115(11): 2823-2835
Lidar and archaeology Chase et al. Airborne LiDAR, archaeology, and the ancient Maya landscape at Caracol, Belize. Journal of Archaeological Science 38(2): 387–398
Photograph and LiDAR imagery of “Caana,” Caracol’s main architectural complex; varying colors in the LiDAR data represent different eleva�ons.
5/21/12
20
Ground-based Lidar Ground-‐based lidar systems are hemispherical scanning laser range finders that fire millions of laser pulses and records detailed structural informa�on at a range of up to 200 m. Data can be used to derive:
canopy height basal area and stem density ver�cal foliage distribu�on leaf area index
Yao et al. Measuring forest structure and biomass in New England forest stands using Echidna ground-‐based lidar. Remote Sensing of Environment, 115(11): 2965–2974.
5/21/12
21
Satellite Lidar: the promise of DESDynI Special Issue: Remote Sensing of Environment. Volume 115, Issue 11, Pages 2751-2974 (15 November 2011) DESDynI VEG-3D Special Issue From Scott Goetz: DESDynI (Deformation, Ecosystem Structure, and Dynamics of Ice) was to provide fundamental information on multiple components of the earth system using a combination of radar and, uniquely, lidar technology. Sadly, on 15 February 2011 the equivalent of a cease and desist order was placed on DESDynI — the very same week that President Obama's science advisor stated, on NPR's Science Friday, that earth observation was the single area he would place most emphasis on were budget priorities not limiting.
Dis
cret
e Li
dar y
ield
s m
ultip
le re
turn
s
first returns
second returns
third returns
last returns
all returns
5/21/12
22
Lidar pulse density depending on flying height, discrete return lidar can yield pulse densities of 1-12 pulses/m2. How much is enough?
Lidar pulse density is important but flying height, flight paths, sensor design can increase costs
5/21/12
23
snamp.cnr.berkeley.edu Sierra Nevada Adap�ve Management Project
SNAMP Lidar Specifica�ons Sugar Pine Area (117km2):
– Lidar data specs: 5-‐10 cm eleva�on accuracy 9-‐20 points per m2 Footprint size: ~0.225m Swath width: 580 m
Contracted with National Center for Airborne Laser Mapping (NCALM;) Both surveys used an Optech GEMINI Airborne Laser Terrain Mapper (ALTM) mounted in a twin-‐engine Cessna Skymaster.
SNAMP Lidar information
5/21/12
24
snamp.cnr.berkeley.edu Sierra Nevada Adap�ve Management Project
Our Lidar Data
Acquired pre-‐treatment. Discrete return (4 returns), contracted with NCALM, 6-‐9 pts per m2