Data Discovery Day 03/06/2008 Jim Jacobi USGS Biological Resource Discipline

1. Very High-resolution
Imagery for Remote
Sensing in Hawai`i
Stephen Ambagis1
Jim Jacobi2
1Hawai`i Cooperative Studies Unit, UH Hilo
2U.S. Geological Survey

2. What happens in a vacuum
• Presently there are no local commercial aerial digital
imagery providers
• Two systems are breaking onto the scene
• Both are focused on research and conservation
• No overlap in base products, complimentary systems
• Both systems are producing new products
This presents the user community with a very unique
situation, one that could progress Hawaii’s
conservation goals more than ever imagined

3. Carnegie Airborne
Observatory
– Hyperspectral imagery,
350 bands, 30 cm
– Full waveform LIDAR
Contact: Greg Asner
email gpa@stanford.edu
website- http://cao.stanford.edu/

4. Resource Mapping
– Very high resolution
multispecral, 4 bands,
20 cm resolution
– Ultra high resolution
natural color, 3 bands,
1 cm resolution
Contact: Dana Slaymaker
Email info@resourcemappinggis.com
Web site http://resourcemappinggis.com/

5. Resource Mapping plane
CAO plane and system and system

6. • Fist contracted through USGS to do pilot research
for TNC, Army, and Fish & Wildlife lands.
• USGS funded development of next generation
system that included image normalization for direct
comparison and dual scale system
• Initial results were promising
• Recently TNCH has taken a leading role in
implementation creating Resource Mapping Hawaii,
local capacity

7. Matching multispectral and
natural color imagery over
the Hakalau National
Wildlife Reserve
This dual-scale approach is
especially helpful with
species like Australian tree
fern which is not
distinguishable from the
native fern species using
any spectral identifiers.
Resource Mappings goal is
usually to find the lowest
resolution adequate to a
specific mapping need to
reduce costs, but the dual
camera set up gives them
several options to meet
these needs.

8. A subsection of the natural color with it’s corresponding multispectral. The multispectral shows better spectral discrimination
between trees while the natural color has more detail. A three times increase in spatial resolution in the natural color was
sufficient to distinguish the tree species needed to map in the the Hakalau National Wildlife Reserve.

9. Example of Ultra High Resolution Image Interpretability
Psidum
cattelianum
Pandanus
Psidum tectorius
cattelianum
Melastoma
candidum Schefflera
actinophylla
Metrosideros
polymorpha
Macaranga
mappa
Cecropia
obtusifolia
Nephrolepis
Melochia multiflora
umbellata
Trema
orentalis
2 cm resolution

10. Range of sub-sampling options, from 7 cm (above) to 1cm per pixel Detail of a single fern at both resolutions

11. Current Status of Systems
• Current product lines
– Resource mapping products are focused on very fine detailed image
interpretation over small to moderate AOI’s.
– CAO data is geared toward large scale, automated, image analysis.
• Availability
– Resource Mapping will be local in June of this year with a dedicated
plane, pilot, and processing facility
– CAO is local but still in research phase of development from a large
scale implementation perspective.
• Cost
– Resource Mapping produces full coverage, 2 scale, ortho-imagery at
less than $2.00 per acre.
– CAO costs requests should be directed to Greg Asner of Carnegie.

12. Summary
• Carnegie Airborne Observatory
– Huge potential for automated large scale mapping of certain species,
vegetation structure, and physiology; high-resolution DEMs.
– True costs still being determined; currently available with conditions;
long term availability being determined.
• Resource Mapping
– Straight forward approach to mapping and monitoring plant
communities and species using image interpretation with ultra high
resolution data
– Known costs, fast and simple tasking ability.

13. Carnegie Airborne Resource Mapping
Observatory – Very high resolution
– Hyperspectral multispecral, 4 bands,
imagery, 350 bands, 20 cm resolution
30 cm resolution – Ultra high resolution
– Full waveform natural color, 3 bands,
LIDAR 1 cm resolution
Contact: Greg Asner Contact: Dana Slaymaker
email gpa@stanford.edu Email info@resourcemappinggis.com
website- http://cao.stanford.edu/ Web site http://resourcemappinggis.com/
Note: Any use of trade, product, or firm names in this presentation is for descriptive
purposes only and does not imply endorsement be the U.S. Government.