Hurricane Katrina hit southwestern Mississippi on August 29, 2005, at 10 a.m. CDT as a category 3 event with storm surges up to approximately 9 m and sustained winds of approximately 120 mph. The hurricane ravaged several coastal towns, destroying or severely damaging hundreds of homes. Hurricand Katrina deposited millions of tons of debris and caused severe damage to coastal forests. In response, several Federal agencies have been using a broad range of remotely sensed data (e.g., IKONOS) to aid damage assessment and disaster recovery efforts. This presentation discusses an effort to use IKONOS data for damage assessment, based on data collected over southwestern coastal Mississippi on September 2, 2005

McKellip, Rodney

Spruce, Joseph P.

NASA Technical Reports Server

Stennis Space Center
Assessing Hurricane Katrina Damage 
to the Mississippi Gulf Coast Using 
IKONOS Imagery
Joseph P. Spruce
Science Systems and Applications, Inc.
John C. Stennis Space Center, MS 39529
Rodney McKellip
NASA Project Integration Office
John C. Stennis Space Center, MS 39529
JACIE Civil Commercial Imagery Evaluation Workshop
Laurel, Maryland, USA
March 14–16, 2006
https://ntrs.nasa.gov/search.jsp?R=20070038244 2019-08-29T18:36:51+00:00Z
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Stennis Space Center
JACIE Civil Commercial Imagery Evaluation Workshop, Laurel, MD
Discussion Items
• Project Background
• Research Objectives
• Remote Sensing Data Acquisition and Processing Methods
• Results
• Concluding Remarks
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Stennis Space Center
JACIE Civil Commercial Imagery Evaluation Workshop, Laurel, MD
Project Background
• Hurricane Katrina hit southwestern Mississippi on August 
29, 2005, at 10 a.m. CDT as a category 3 event with storm 
surges up to ~9 m and sustained winds of ~120 mph
• The hurricane ravaged several coastal towns, destroying or 
severely damaging hundreds of homes
• Hurricane Katrina deposited millions of tons of debris and 
caused severe damage to coastal forests
• In response, several Federal agencies have been using a 
broad range of remotely sensed data (e.g., IKONOS) to aid 
damage assessment and disaster recovery efforts
• This presentation discusses an effort to use IKONOS data 
for damage assessment, based on data collected over 
southwestern coastal Mississippi on September 2, 2005
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Hurricane Katrina’s Swath
MS
AL
LA
FL Hurricane Force Winds
Tropical Force Winds
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Katrina’s Approach of Mississippi 
Shown on GOES-12 Satellite Imagery
Image Shown Below Acquired at 9:02 a.m. CDT
Red – Relative Location 
of Hurricane Eye
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Location of Study Area in 
Southwestern Mississippi Gulf Coast
IKONOS Data
Acquired 9/2/2005
Landsat 7 Mosaic from NASA Scientific Data Purchase in Background
Waveland and 
Bay St. Louis
Pass
Christian
Includes material © Space Imaging LLC
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IKONOS Data Used in Study
IKONOS Color Composite – Bands 4,3,1 Loaded into RGB 
Includes material © Space Imaging LLC
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Federal Efforts to Assess Katrina 
Damage with IKONOS Data
• Several Federal agencies have been using IKONOS and 
other commercial remote sensing data for assessing 
damage from Hurricane Katrina, including NOAA, USGS, 
NASA, NGA, and FEMA
– NOAA Coastal Services Center (CSC) used IKONOS data and Feature 
Analyst software for mapping storm debris in Gulfport, MS
– DHS/NGA/FEMA used heads-up digitizing to map debris zones apparent on 
high resolution satellite (e.g., IKONOS) and aerial data
– The USGS, NOAA, FEMA, and others are using mid- to high-resolution 
remote sensing data to map and assess flood extent, coastal land loss, and 
vegetation condition; IKONOS imagery is being used to support these efforts
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JACIE Civil Commercial Imagery Evaluation Workshop, Laurel, MD
Example Debris Map from IKONOS Data 
Source: NOAA Coastal Services Center
Data Acquired 9/2/2005
Location – Gulfport, Mississippi
Includes material © Space Imaging LLC
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Objectives of Study
• Assess pan-sharpened multispectral IKONOS data for 
visualization of Hurricane Katrina storm damage
– Damaged buildings, wood-dominated debris, denuded forest, and mud 
covered open areas
• Assess traditional image classification techniques for 
classifying storm damage types from pan-sharpened 
IKONOS data
– ISODATA unsupervised clustering and/or Maximum Likelihood supervised 
classification 
• Longer term: Assess hurricane damage using change 
detection techniques in conjunction with before and after 
storm IKONOS data
– Damage to residential and industrial areas, forests, and marsh land
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Examples of Hurricane Damage in 
Waveland, Mississippi
Saint Clare's Catholic Church
Looking North from Coast
Acquired 9/4/2006
Waveland Coast - East View 
from Saint Clare’s Church
Acquired 9/4/2006
Tree Damage at Former Home
0.4 km from Waveland Coast 
Acquired 9/4/2006
House and Forest Damage
1.2 km from Waveland Coast
Acquired 11/25/2006
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Preparing IKONOS Data for 
Classification
• Acquired IKONOS data from a USGS Katrina Web site in GeoTIFF 
format for subsequent processing with ERDAS Imagine software
• Stacked visible and NIR multispectral band tiffs into multiband image
• Applied “bootstrap” haze correction to individual bands as needed
– Used minimum value subtract technique (Jensen, 1996)
• Ran pan-sharpening algorithm to produce 1-meter pan-sharpened 
multispectral image
– Used Local Mean and Variance Matching (LMVM) filtering technique
described by de Béthune et al. (1998), as implemented in ERDAS 
IMAGINE® via the Spatial Modeler toolbox
• Developed and applied appropriate look-up table stretch to visually 
enhance storm damage features of interest
Sources:
de Béthune, S., F. Muller, and J.-P. Donnay, 1998. Fusion of multispectral and panchromatic images by local mean and variance matching filtering 
techniques. Proceedings of the Second International Conference: Fusion of Earth Data: Merging Point Measurements, Raster Maps and Remotely 
Sensed Images. Sophia Antipolis, France, 28–30 January, (Thierry Ranchin and Lucien Wald, eds. published by SEE/URISCA, Nice, France), pp. 31–
36.
Jensen, J.R., 1996. Introductory Digital Image Processing: A Remote Sensing Perspective. 2nd ed. Upper Saddle River, New Jersey: Prentice Hall.
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IKONOS Data Used in Study
Location of 
Subsequent Slides
IKONOS Color Composite – Bands 4,3,1 Loaded into RGB
Imagery Enhanced with Gamma LUT Stretch 
Includes material © Space Imaging LLC
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IKONOS Panchromatic Data – 9/2/2006
Zooms of Waveland, MS
Includes material © Space Imaging LLC
St. Clare’s Church on Left
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IKONOS Multispectral Data – 9/2/2006
Includes material © Space Imaging LLC
Zooms of Waveland, MS
St. Clare’s Church on Left
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IKONOS Pan-Sharpened
Multispectral Data – 9/2/2006
Includes material © Space Imaging LLC
St. Clare’s Church on Left
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IKONOS Image Classification
Methodology
• Ran series of ISODATA unsupervised classifications to 
collect signatures needed for supervised classification
• Appended signatures from 10 individual unsupervised 
classifications into master signature file
• Subjected master signature file of 191 cluster classes and 
pan-sharpened data to supervised classification with the 
maximum likelihood (ML) algorithm
• Applied contrast-enhanced color look-up table to 
classification results to resemble an enhanced 431 RGB 
composite of the pan-sharpened data
• Evaluated preliminary results of ML classification, refining as 
needed to produce final classification product
• Assessed classification results compared to reference data
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Selection of Training Areas for 
Collecting Classification Signatures
Urban
Forest
Water
Non-Green
Marsh
Green Marsh
Debris
Beach Sand
Independent Unsupervised Classifications were Produced for 10 Subset Areas
Includes material © Space Imaging LLC
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Example IKONOS Classification Results
vs. Bands 4,3,1 RGB Color Composite
ML Classification – Pseudo Color LUT IKONOS 4,3,1 RGB
Includes material © Space Imaging LLC
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Select IKONOS Classification Results
vs. Bands 4,3,1 RGB Color Composite
ML Classification – Select Classes Colored
Other Classes – Bands 3,4,1 RGB LUT
IKONOS 4,3,1 RGB
Includes material © Space Imaging LLC
Water
Sand
Woody Storm Debris
Brown Grass with Mud
Exposed Pavement
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NOAA NGS 0.5-Meter Digital Aerial Data
Storm
Debris
Flooded
Marsh
Exposed
Concrete
Slabs
Data Acquired 8/30/2005 Before Road Clearing
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JACIE Civil Commercial Imagery Evaluation Workshop, Laurel, MD
IKONOS Classification Result
Includes material © Space Imaging LLC
Water
Sand
Woody Storm Debris
Brown Grass with Mud
Exposed Pavement
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IKONOS Data Acquired 9/2/2005
Includes material © Space Imaging LLC
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JACIE Civil Commercial Imagery Evaluation Workshop, Laurel, MD
Visualization of Hurricane Damage
on the IKONOS RGBs
• Several flood and wind damage effects can be viewed on IKONOS 
RGBs, including green vegetation loss and dieback, multi-tree blow 
downs, flood water, house damage or loss, flood-deposited mud, and 
debris in coastal water.
• Deciduous forests were largely defoliated by the storm, whereas the 
pine-dominated evergreens were green although greatly reduced by 
storm damage. The 1-meter spatial resolution was insufficient to show 
single-tree blow down on a consistent basis, although mass tree blow 
downs were evident in some cases.
• Flooded, defoliated wetland forests and marshes can be clearly seen.
• Several marsh conditions were evident, apparently because of variability 
in greenness and saltwater conditions.
• Mud-covered surfaces were evident, such as mud on lawns and paved 
surfaces.
• The September 2nd acquisition date of the IKONOS data was close in 
time to the hurricane’s landfall and does not necessarily show vegetation 
stress effects that take a longer period to be manifested.
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JACIE Civil Commercial Imagery Evaluation Workshop, Laurel, MD
“Traditional” Classification of Storm Damage 
from Pan-Sharpened IKONOS Data: 
Initial Findings
• Wood-dominated storm debris was classified for open areas but was not
classified in areas obscured by sufficiently dense forest. Some classification 
commission error was also noted for this storm damage type.
• The classification of woody storm debris was realized without having to resort to 
sub-pixel or contextual supervised classification software and techniques.
• Effective wall-to-wall land use/land cover classification was not achieved, in part 
because of time constraints in evaluating and refining classification results.
• Some confusion was noted between pavement, roofing, and mud-covered 
surfaces. Concrete and bright roof types were also confused. Forest cluster 
classes were difficult to categorize, in part because of storm damage effects.
• The classification process demonstrated here requires trial and error processing, 
which is not unusual for supervised classification of targeted surface cover 
types.
• The pan-sharpened output was similar to the input multispectral image in
appearance yet retained the texture of the 1-meter panchromatic image. This 
output enabled targeted ground features to be visualized and classified at the 1-
meter scale.
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JACIE Civil Commercial Imagery Evaluation Workshop, Laurel, MD
Final Remarks
• Additional classification refinement is needed to complete a 
wall to wall land cover classification
• More work is also required to quantify accuracy of storm 
damage types as well as land use/land cover types from the 
IKONOS pan-sharpened multispectral data
• Future work will involve use of multitemporal IKONOS and 
Landsat data for understanding MODIS change detection 
results in monitoring vegetation damage and recovery from 
Hurricane Katrina
Participation in this work by Science Systems and Applications, Inc., was supported by NASA at the John C. Stennis Space Center, Mississippi,
under Task Order NNS04AB54T.
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Additional Information
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Efforts to Assess Katrina’s Forest 
Damage
• The U.S. Forest Service is assessing Katrina forest damage 
and recovery in part via the Healthy Forests Initiative 
(http://www.healthyforests.gov/) 
– Assessments of forest damage as well as forest health due to 
post-storm insect outbreaks, diseases, and wildfire
• NASA is aiding the Federal effort to assess forest damage 
impacts from Hurricane Katrina, initially via analysis of multi-
temporal MODIS data for monitoring forest vegetation 
greenness and moisture indicators
– This effort uses multi-temporal Landsat and IKONOS data as 
reference data to aid analysis of MODIS-based change 
detection
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JACIE Civil Commercial Imagery Evaluation Workshop, Laurel, MD
Preliminary Map of Katrina Forest 
Damage
1 = Scattered, Light
2 = Light
3 = Moderate
4 = Severe
Hurricane Force Winds
Tropical Storm Winds
Map Source: USFS Forest Inventory and Analysis
http://www.srs.fs.usda.gov/katrina/


Assessing Hurricane Katrina Damage to the Mississippi Gulf Coast Using IKONOS Imagery

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