Vol. 5, No. 2
August 2004
In this Issue
|
Basics |
 |
Using remote sensing to measure and monitor impervious surfaces |
|
Image Data
Corner |
|
NOAA National Geophysical Data Center |
|
Tech
Tip |
|
Tips for using IMAGINE Subpixel Classifier on images containing extreme topography |
|
New
Advancements |
|
Detecting significant change over time |
|
Hot
Sites |
|
Web sites related to impervious surfaces and remote sensing |
|
AAI
News |
|
Announcing
|
AAI Home
From the Editor
Welcome to a new issue of The Spectral Explorer!This issue examines the use of remote sensing for locating and measuring the areal extent of impervious surfaces, which include parking lots, roads, driveways and rooftops. Such surfaces prevent the infiltration of precipitation and snowmelt into the soil, thereby generating an increase in stormwater runoff. As the percent of impervious surface area increases within a watershed, environmental degradation, including impacts to water quantity and quality as well as habitat loss, also increases.
As urban and suburban areas continue to expand, impervious surfaces are being examined more closely from both a land-use planning and an environmental perspective. Remote sensing has proven to be a key tool in facilitating this effort by providing a cost-effective way to monitor and measure impervious surfaces. The availability of multi-temporal satellite imagery, including historical data, allows for the timely and accurate assessment of impervious surfaces over time.
We welcome your comments, ideas, and suggestions! We are always
looking to learn of new remote sensing applications with which our readers
have been involved. Please send email to Brenda at bberasi@discover-aai.com.
Basics
USA's Built-up Surfaces Equal Ohio in Area
June 16, 2004
The following article was a press release from
SpatialNews.com on June 16, 2004. To learn more go to: http://spatialnews.geocomm.com/dailynews/2004/jun/16/news5.html
WASHINGTON - If all the highways, streets, buildings, parking lots and other solid structures in the 48 contiguous United States were pieced together like a giant jigsaw puzzle, they would almost cover the state of Ohio. That is the result of a study by Christopher Elvidge of the National Oceanic and Atmospheric Administration's (NOAA) National Geophysical Data Center in Boulder, Colorado, who along with colleagues from several universities and agencies produced the first national map and inventory of impervious surface areas (ISA) in the United States.
As calculated by the researchers, the total impervious surface area of the 48 states and District of Columbia is approximately 112,610 square kilometers [43,480 square miles], and, for comparison, the total area of the state of Ohio is 116,534 square kilometers [44,994 square miles].
The new map is important, because impervious surface areas affect the environment. The qualities of impervious materials that make them ideal for construction also create urban heat islands, by reducing heat transfer from Earth's surface to the atmosphere. The replacement of heavily vegetated areas by ISA reduces sequestration of carbon, which plants absorb from the atmosphere, Elvidge says in the 15 June issue of Eos, published by the American Geophysical Union. Both of these effects can play a role in climate change.
In watersheds, impervious surface areas alter the shape of stream channels, raise the water temperature, and sweep urban debris and pollutants into aquatic environments. These effects are measurable once ten percent of a watershed's surface area is covered by ISA, Elvidge writes. The consequences of increased ISA include fewer fish and fewer species of fish and aquatic insects, as well as a general degradation of wetlands and river valleys. The impervious surface area of the contiguous United States is already slightly larger than that of its wetlands, which is 98,460 square kilometers [38,020 square miles].
Elvidge notes that few areas have ISA maps, because they are difficult and expensive to create. He used a variety of data sources to produce the map accompanying his article, including nighttime lights observed by satellite, Landsat images, and data on roads from the US Census Bureau, along with aerial photography. He anticipates that this map will be useful to scientists and planners managing conservation and resource allocation, as well as those working on issues of water quality, biodiversity, habitat loss and fragmentation, and climate change.
The population of the United States is increasing by three million persons annually, Elvidge writes. New impervious surface areas are rapidly covering vegetated surfaces, including one million new single family homes and 20,000 kilometers [10,000 miles] of new roads per year. Given these trends, he says, ISA will likely become a more prominent issue in coming years.
The study was funded in part by NASA.
Image Data Corner
NOAA National Geophysical Data Center
http://www.ngdc.noaa.gov/ngdcinfo/onlineaccess.html
This
website provided by the NOAA National Geophysical Data Center provides a
wide variety of downloadable data ranging from bathymetry and coastlines
to geology and geophysics. In addition, access to the NOAA server is
provided to allow users to search for data other than that directly
available through the NGDC website. Whether you are just browsing data
sources or searching for a particular data type, be sure to bookmark this
site as a great resource!
Subpixel Classifier Tech Tip
Tips for Using IMAGINE Subpixel Classifier on Images Containing Extreme Topography
Images with extreme topography can often pose a challenge to detecting a particular material of interest (MOI) with IMAGINE Subpixel Classifier but there are strategies that can be utilized to overcome these challenges. The key is to recognize that the higher elevation terrain in the image has different environmental characteristics than that of the lower elevation terrain. The Environmental Correction process generates a single pair of calibration spectra that apply to each pixel. Therefore, depending upon where your MOI is likely to be found, the user must tailor the Environmental Correction process accordingly as follows:If the MOI is primarily in low elevation terrain:
• One can use the
cross-hair tool labeled “Pick cloud pixel” to mask out pixels comprising
the darker (deep shadow) and brighter (snow and/or bright rock/soil)
materials in the high elevation terrain.
If the MOI is primarily in high elevation terrain:
• Use the
cross-hair tool labeled “Pick cloud pixel” to exclude any obvious low
elevation contributors.
If you are looking for the MOI in both elevation regimes:
• It may
be advantageous to use two separate .corenv files and process the image
twice; once focusing on the MOI in high elevation terrain and once
focusing on the MOI in the low elevation terrain.
• Generally you can tell if a material is the major dark or bright material contributor to the Environmental Correction process by whether it is at or near the bottom or top (exclusive of the cloud classes), respectively, of the histogram counterpart to the cross-hair tool labeled “Pick cloud pixel.” When masking out classes you may find that it is only the deep shadows that contribute meaningfully from the high elevation terrain, and that (unless there is snow) the brightest contributors are only in the lower terrain.
• Once you have a .corenv file for the high elevation terrain, the next
step is to get a signature for the material in its shadowed state. The
signature for the illuminated material of interest will be different than
that of a shadowed occurrence. If the shadow is too deep, however, it may
not be reasonable to expect to get an adequate signature or to detect the
material with 8-bit data such as Landsat Thematic Mapper. In that case,
you could either choose another image with shadows that are less intense
or use higher precision (e.g., 11-bit IKONOS) imagery. To determine if the
shadows are too deep, use the Inquire Cursor to obtain pixel spectra from
the shadows and compare to the atmospheric correction factor (ACF)
spectrum in the .corenv file. If the pixel spectra in the shadows are
brighter than the ACF, then the material may be detectable with a shadowed
version of the material signature. If the pixel spectra have comparable or
lower DN values than the ACF, then you are likely to be more successful
with an alternative image.
New Advancements in Remote Sensing at AAI
Detecting Significant Change over Time
Adaptive Terrain Change Analysis (ATCA) was developed by AAI to allow one to use satellite imagery to detect significant changes between two dates at the same location. Change is identified based on the spectral properties of each image pixel once the two images have been properly aligned (registered) and calibrated to remove atmospheric effects. ATCA is typically used for wide area surveillance. For example, ATCA works extremely well with Landsat Thematic Mapper (TM) images, which exist for many parts of the world from 1984 to present and cover 10,000 sq. miles each. The type of change that can be detected varies greatly and the analysis can be targeted to detect a particular type of change that is of interest to the user. For example, some users may be focused on deforestation whereas others may be interested in urban expansion.The ATCA software package is a set of processing steps built into a
workflow. The workflow is completely implemented from within ERDAS IMAGINE
software, the premier geographic imaging software package that
incorporates the functions of both image processing and geographic
information systems (GIS).
For more information about AAI’s Adaptive Terrain Change Analysis
(ATCA), feel free to contact us at 978-663-6828 or visit http://www.discover-aai.com/company/contact.htm
Top
of Page
Success Stories
Users of IMAGINE Subpixel Classifier vary widely from private firms and universities to non-profit organizations and government agencies resulting in a diverse array of applications. If you have an interesting application utilizing IMAGINE Subpixel Classifier that you would like to share, we’d love to hear about it and highlight it in our newsletter. Feel free to contact Brenda at 978-663-6828 or bberasi@discover-aai.com.
Hot Sites
Impervious Surfaces and the Quality of Natural and Built
Environments
http://chesapeake.towson.edu/landscape/impervious/download/Impervious.pdf
This paper provides an overview of the environmental effects of an
increased percentage of impervious surfaces within a watershed, as
exemplified by the Chesapeake Bay. An excellent bibliography is included.
Impervious Surface Mapping using Multi-Resolution Imagery
http://www.geog.umd.edu/resac/impervious.htm
The
Mid-Atlantic Regional Earth Science Applications Center at the University
of Maryland has conducted research on the use of multi-spectral and
hyper-spectral imagery to discern man-made impervious surfaces within the
Chesapeake Bay Watershed. Comparisons were made from four data sets: a
planimetric map interpreted from aerial photos, 2 meter resolution imagery
from the Airborne Imaging Spectrometer (AISA), 30 meter resolution Landsat
TM imagery, and 4 meter resolution IKONOS imagery. Assessing Spatial Growth of the Washington Metropolitan Area Using
Thematic Mapper Data
http://www.nasm.si.edu/research/ceps/research/wash/washdc1.htm
This
study used three Landsat TM images from 1982, 1989 and 1993 to analyze
urban grown patterns in the Washington metropolitan area. Effectiveness of Subpixel Analysis in Detecting and Quantifying
Urban Imperviousness from Landsat Thematic Mapper Imagery
http://www.geocarto.com.hk/cgi-bin/protect.pl?file=dec99&id=BAFmEGCBlBAHAH2162
This
paper from the December 1999 issue of Geocarto International examines the
use of remotely sensed spectral data for the quantification of urban
imperviousness. IMAGINE Subpixel
Classifier was used to determine the spectral fraction of
impervious components of each pixel in a Landsat TM image of Charleston,
South Carolina. Quantifying and Describing Urbanizing Landscapes in the Northeast
United States
http://resac.uconn.edu/publications/tech_papers/pdf_paper/Civco_et_al_PERS_Oct2002.pdf
This
paper provides an overview of recent research using remote sensing
technology to detect impervious surfaces, forest fragmentation and urban
growth. Temporal Characterization of Connecticut's Landscape
http://resac.uconn.edu/publications/tech_papers/pdf_paper/Hurd_at_al_ASPRS2003.pdf
This
study used Landsat imagery to identify and quanitfy impervious surfaces,
urban growth, and forest fragmentation for the purpose of assisting local
land use decision makers in Connecticut. Subpixel classification was used
to derive estimates of percent impervious surfaces for four dates over a
17-year period. Subpixel Impervious Surface Mapping
http://resac.uconn.edu/publications/tech_papers/pdf_paper/Flanagan_and_Civco_ASPRS_2001.pdf
This
study compared the use of IMAGINE Subpixel Classifier versus artificial
neural networks to
characterize and quantify impervious surfaces for four Connecticut towns
using Landsat imagery. IMAGINE Subpixel Classifier
Version 8.4: Software Review
http://resac.uconn.edu/publications/tech_papers/pdf_paper/ERDAS_Subpixel_Classifier_Software_Review.pdf
This
review of IMAGINE Subpixel
Classifier provides a detailed example of the use of this tool to
quanitfy the subpixel percent impervious surface cover for a Landsat TM
image of Waterford, Connecticut.
AAI News
AAI Celebrates 20
Years!
Applied Analysis Inc. (AAI) was founded in 1984 by Dr. Robert Huguenin and is a privately held small business that combines innovation with proven technology to advance the science and practice of remote sensing. For the last 20 years, the company has provided expertise and technology to solve problems for an ever-widening range of customers. Building on our long history of developing leading edge algorithms, software products, and information technologies, we continue to specialize in two primary markets - military intelligence and environmental monitoring for businesses and government agencies. In addition, we produce commercial software products for general-purpose and specialized use in conjunction with other satellite image processing packages. By providing total solutions that are creative, practical, and affordable, we seek to be a market leader in the field of remote sensing services and products. As we celebrate this 20 year anniversary, we look forward to the advancements yet to be made during the next twenty years and beyond.
New Hires at AAI
John Colorusso joined AAI in July as the new Director of Finance and Administration. John received a B.S. from Northeastern University and an M.B.A. from Babson College. He has 25 years of financial management experience with technology organizations in defense and commercial industries, including Sanders Associates in Nashua NH (now BAE Systems), Computervision Inc. in Bedford, MA; Cognition Corp. in Bedford, MA; Technical Communications Corp. in Concord, MA; Avici Systems in N. Billerica, MA and most recently The Info Group in Framingham, MA.Anthony Ryan has joined the AAI team as a Software Quality Assurance Specialist. Anthony received a B.A. in Earth and Geographic Science and a certificate in Geographic Information Technologies from the University of Massachusetts at Boston. Previously, he worked as a GIS Technician for KeySpan Energy and as a Test Technician for MJ Research, Inc. His responsibilities at AAI include the development and implementation of the software QA processes involving multi- and hyperspectral imagery on multiple software products, both commercial and in-house.
Roger Schane has joined the company as AAI’s Director of
Environmental Business Development. Roger earned an MSEE from Marquette
University, a BS in Systems Engineering from the University of Illinois,
and has completed five MBA courses. He has over 30 years experience in
marketing, proposing, planning, directing, and performing life-cycle
development/support of computer-based systems for government and
commercial clients, including the Environmental Protection Agency,
Department of Energy, Department of Transportation, National Aeronautics
and Space Administration, the Department of Defense, and federal
intelligence agencies. His position at AAI focuses on applying AAI’s
state-of-the-art remote sensing technology to solve environmental problems
related to water quality assessment and land cover analysis.
Upcoming Presentations by AAI
Join AAI at the North American Lakes Management Society (NALMS) Conference to be held November 3-5, 2004 in Victoria, British Columbia. The theme for the 2004 conference is "Lakes - habitat for fish, habitat for people." In addition to the challenges associated with the co-existence of people and wildlife, the program will also address a wide range of topics such as introduced aquatic plants and animals, lake assessment and restoration techniques, government policies and new scientific methods. Dr. Scott Stoodley, AAI’s Director of Environmental Programs, is planning to present “The Use of Remote Sensing to Locate and Characterize Areas of Dense Growth of Eurasian watermilfoil” at NALMS 2004. We hope to see you there!http://www.nalms.org/symposia/victoria/
Recent Presentations by AAI
Four presentations were delivered by AAI at the government’s Spectral Analyst Exchange Forum (SAEF) held in Lexington, MA this past April. Dr. Ahmed Fahsi presented “Detection of Disturbed Soil Using IMAGINE Subpixel Classifier.” Steve Newman presented “ATCA Change Detection for Military Targets.” Dr. Robert Huguenin presented “Self-Calibrating Spectral Change Detection” and “Signature Transformer.”
Dr. Scott Stoodley, AAI’s Director of Environmental Programs, recently presented at two conferences addressing non-point source pollution.
- This past February, the Environmental Protection Agency (EPA) and the Association of State and Interstate Water Pollution Control Administrators (ASIWPCA) brought together state and EPA non-point source (NPS) program managers for a conference entitled “Implementation at the Watershed Level" held in Austin, TX. One aspect of the conference focused on the use of new assessment tools to increase the effectiveness of best management practices. As part of this theme, Dr. Stoodley presented “Utilization of Remotely Sensed Data for Targeting BMP Implementation – Case Study: Fort Cobb Basin, Oklahoma.” To view this presentation, click on the following link:
http://www.discover-aai.com/presentations/EPA-ASIWPCA.htm
- EPA Region VI, which includes the states of Arkansas, Louisiana, New Mexico, Oklahoma, and Texas, as well as 66 Indian Tribes, held a Non-point Source Pollution Conference in Oklahoma City this past June. Dr. Stoodley delivered a presentation entitled “Utilization of Remotely Sensed Data for Targeting BMP Implementation.” To view this presentation, click on the following link: http://www.discover-aai.com/presentations/REGVI-OSE-Stoodley.htm
New Projects at AAI
Remote Sensing Survey of Water Quality in China
On 16 July
2004, Applied Analysis, Inc. (AAI) was awarded a subcontract from
D’Appolonia S.P.A.,an engineering and environmental consulting firm
located in Genoa, Italy, to support their remote sensing survey of water
quality for three large areas in China. The project will use three
Landsat Thematic Mapper (TM) satellite images each covering 10,000 square
miles.
AAI will use its Quantitative Shoreline Characterization 2 (QSC2) software tool to process the Landsat imagery and derive five water quality parameters for each pixel in each image:
1. Chlorophyll (Chl)QSC2 uses AAI’s Image Calibrator software to accurately and autonomously calibrate satellite spectral imagery without the need for ground truth data.
2. Suspended Minerals (SM)
3. Colored Dissolved Organic Carbon (CDOC)
4. Turbidity (total attenuation coefficient)
5. Vertical Subsurface Sighting Distances (equivalent to Secchi Depth)
AAI's contract was awarded as part of a larger Memorandum of Agreement between the two companies, where D'Appalonia will market AAI's QSC2 software and other services in China. D'Appalonia is in a unique posiiton to continue to access the Chinese Market as a bilateral partnership exists between China and Italy.
Remote Sensing Survey of Water Quality in Maryland
In July
2004, AAI received a contract with the National Oceanic and Atmospheric
Administration (NOAA) to conduct a pilot project on the use of remotely
sensed data for water quality monitoring on the Patuxent River, Maryland.
The project will take place this August and will involve the comparison of
several water quality parameters as measured via an IKONOS satellite
sensor to temporally coincident ground truth data collected by NOAA.
Results from this study will be presented by AAI at NOAA’s Annual
GeoSpatial Tools Conference in the Spring of 2005.
Employment Opportunities at AAI
AAI currently has an employment position available for a Remote Sensing/Image Processing Specialist. For more information about this position and instructions on how to apply, please visit AAI Jobs .
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