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The Devastation of Venezuela by Heavy Rains in December 1999:
Assessment of the Situation using ERS InSAR Tandem Data and SPOT Images.
1
Edmond Nezry, 3 Francesco Sarti, 2 Paul Romeijn, 1 Francis Yakam-Simen and 1 Iwan Supit
1
PRIVATEERS N.V., Private Experts in Remote Sensing
Great Bay Marina, P.O. Box 190, Philipsburg, Netherlands Antilles
Phone/Fax: (+33) 05-61-545827/991724; E-mail: [email protected]
Internet: http://www.treemail.nl/privateers/
2
TREEMAIL, International Forestry Advisors
Prins Bernhardlaan 37, BW 6866, Heelsum, The Netherlands. Internet: http://www.treemail.nl
3
CNES, Centre National dEtudes Spatiales, QTIS/SR
18 Avenue Edouard Belin, Bpi 811, 31401 Toulouse Cedex, France
Phone: (+33) 05-61-282133; E-mail: [email protected]
ABSTRACT
After the devastation caused by two weeks of torrential rain in Venezuela in the second half of December
1999, it is estimated that up to 50,000 people have died in floods and landslides; a further 200,000 people
have been left homeless as whole towns along the Caribbean coast have been washed away [1].
Concerned about the dramatic extent of this human tragedy, PRIVATEERS N.V. has immediately offered its
support to Venezuela. Supported by CNES and the European Space Agency (ESA) who provided the sets of
SPOT and ERS SAR (Synthetic Aperture Radar) images acquired before and after the disaster, this project
aims to the provision of cartographic maps designed to assess the situation and to help with the rehabilitation
of the country.
These maps are designed to be easily exploitable by local photo-interpreters.
1. INTRODUCTION
The satellite data made available for this project are summarized in the table below:
Satellite
SPOT-1
SPOT-4
ERS-1
ERS-2
ERS-1
ERS-2
Product
P
M
RAW
RAW
RAW
RAW
Date
18-01-1999
25-12-1999
29-11-1998
30-11-1998
23-01-2000
24-01-2000
Coverage
60 x 78 km
60 x 122 km
112 x 107 km
112 x 107 km
112 x 107 km
112 x 107 km
Table 1: Satellite imagery made available by for the present project.
All four ERS SAR images where acquired in repeat-pass conditions. Therefore, they cover the same area.
These ERS data form two interferometric couples, acquired before and after the disaster.
The SPOT data are single-channel images. The SPOT-P image acquired before the disaster is a panchromatic
image (0.50-0.90 µ), whereas the SPOT-M image after the disaster is acquired in the red part of the optical
spectrum (0.61-0.69 µ).
Regarding the data acquisitions during and after the heavy rains, the month elapsed between SPOT and ERS
acquisitions will provide a dynamic view of the event, despite of the different nature of the data.
The experience earned in past similar projects (e.g. Mitch hurricane in November 1998 [2], China floods in
the summer of 1999, Izmit earthquake in August 1999 [3], Lenny hurricane in November 1999 [4]) has been
extensively exploited in this project. Moreover, new techniques to detect changes due to a natural disaster
using homogeneous (same sensor) or heterogeneous (different sensors) data sets have been further developed.
2. SITUATION ON DECEMBER 25, 1999 (SPOT DATA ONLY)
To detect flood extension, violent sedimentation phenomena, and the main flood streams, change detection is
carried out using the SPOT-P archive and the SPOT-M present images. To this aim, the techniques used in
[2,4] are insufficient, and a split-window technique is applied to enable a comparison of the radiometries in
SPOT-P and SPOT-M data.
Some inconveniences with the data hampered the complete detection of important changes. First, the presence
of a stripe of clouds along the coastal cordillera in the SPOT-P archive image hindered the detection of
sedimentation phenomena between the coast and the city of Caracas. Second, the fact that the radiometry of
the SPOT-M image was saturated within urban areas hindered the detection of changes in such areas; it also
causes some serious confusion between built-up areas and violent sedimentation events at the vicinity of urban
areas.
Nevertheless, a good detection of the flooded areas, of the main flood streams and violent sedimentation
events is achieved in most part of the common coverage of the archive and recent data.
To obtain a more readable map, the detected changes are overlaid in color over the SPOT-M panchromatic
image acquired on December 25, 1999.
This final SPOT change detection map is produced at a spatial resolution and a pixel size of 10x10 meters. It
is georeferenced in UTM-WGS84 projection. A subset of this map is shown in Figure 1.
Figure 1: Change detection using SPOT panchromatic images: situation on December 25, 1999.
Flood streams and violent sedimentation are in violet. Eroded areas and coastal sedimentation are in blue.
Built-up areas are in white. Undamaged areas are in grey.
3. SITUATION ON JANUARY 24, 2000 (ERS SAR DATA ONLY)
Based on the calibrated radar reflectivity, the ERS SAR data are used to detect the damages. In the change
detection process, the ERS SAR archive data are compared to the ERS SAR data acquired just after the rains.
A combination of speckle filtering and super-resolution techniques [5] is applied to the ERS SAR data, to
detect and map existing targets at a spatial resolution and a pixel size of 15x15 meters, before and after the
rains, with particular emphasis to housing and infrastructures.
To achieve this objective, the radiometric resolution of the SAR images used must be of very high quality.
Since the radiometric resolution of SAR images is naturally corrupted by the presence of speckle, speckle
filtering is the most critical issue for the success of the whole operation.
The filter that has been used in this project is an adaptive speckle filter for multi-channel detected SAR
images, recently developed by PRIVATEERS N.V.: the Distribution-Entropy Maximum A Posteriori (DEMAP) filter [6].
The superiority of Bayesian speckle filters is mainly due to the introduction of A Priori scene knowledge in
the filtering process. Nevertheless, in the presence of very strong texture or of mixed textures, as it is often the
case in SAR images of dense tropical forest, and/or in the presence of relief (which is the case in coastal
Venezuela), it may be hazardous to make an assumption about the probability density function of the radar
reflectivity of the scene. In this context, the A Priori knowledge with regard to the observed scene can hardly
be an analytical first order statistical model. However, in the DE-MAP speckle filters, a Maximum Entropy
constraint on texture is introduced as A Priori knowledge regarding the imaged scene.
The new DE-MAP filter is particularly efficient to reduce speckle noise, while preserving textural properties
and spatial resolution, especially in strongly textured SAR images [5]. It adapts to a much larger range of
textures than the previous multi-channel MAP filters [6,7] developed under the assumption of K-distributed
SAR intensity [8].
From the theoretical point of view, it is noteworthy that:
- this filter presents the very attractive properties of a control system [7],
- it allows to super-resolve SAR images [6,7], which is of high particular interest for ERS and SPOTPanchromatic (pixel size: 10x10 meters) data fusion.
Figure 2: Change detection using ERS SAR images: situation on January 24, 2000.
Eroded areas, sedimentation areas, and damages to the vegetation cover are in red.
Areas that have been flooded are in dark blue. Damaged built-up areas are in light blue.
Undamaged areas are in grey (from black to white)
Detection of the changes due to the heavy rains is carried out in a similar way than in [2,4]. A set of
"DYNAMIC-RADAR" products [2] is produced to enable the detection and the photo-interpretation of the
changes and damages. Nevertheless, the DYNAMIC-RADAR products are presently improved: a combination
of more change indices is used, and a specific detection of changes occurred to point targets (built-up areas) is
performed on the original complex SAR data.
Finally, the spatial sampling rate adopted for these improved "DYNAMIC-RADAR" products is 15x15
meters. They are georeferenced in UTM-WGS84 projection. A subset of this map, featuring an area around
the city of Maracay (on the shores of the lago de Valencia), is shown in Figure 2.
Regarding the photo-interpretation keys, in these improved "DYNAMIC-RADAR" product, red tones denote
the areas where the vegetation has suffered heavy damages, or sedimentation areas. Dark blue tones denote in
most cases flooded areas, or water saturated areas. Light blue areas denote the location of heavily damages
built-up areas. Grey tones, from white to black, denote undamaged areas (cf. Figure 2).
4. GLOBAL ASSESSMENT: FUSION OF SPOT AND ERS SAR DATA
In the present project, fusion of SPOT and ERS change detection products makes sense if we intend to get a
synoptic view of the situation over the timeframe of one month, i.e. from the date of acquisition of the last
SPOT image to the date of acquisition of the last ERS SAR image.
To this end, the changes detected on December 25, 1999 using SPOT data and the changes detected on
January 24, 1999 using ERS SAR images are combined in a single map.
For a better representation, the SPOT-P archive image is used as mapping background. The final product is
the result of a common-sense data fusion process integrating ERS SAR change detection and SPOT-P archive
data, to facilitate photo-interpretation of the final product: above all, it allows a better understanding of the
total extend of the floods and of the damages suffered in December 1999 and January 2000.
The SPOT/ERS change detection map is produced at a spatial resolution and a pixel size of 10x10 meters. It
is georeferenced in UTM-WGS84 projection. A subset of this map, featuring the coastal area north of Caracas,
is shown in Figure 3.
Figure 3: Change detection using SPOT panchromatic and ERS SAR images: situation on January 24, 2000.
Still intact built-up areas are in white. Damaged built-up areas are in light blue.
Areas that have been flooded and coastal sedimentation plumes are in dark blue.
Flood streams and violent sedimentation areas are in violet.
Eroded areas and damages to the vegetation cover are in red.
5. ASSESSMENT OF THE USEFULNESS OF THE ERS InSAR COHERENCE
With the intent to detect additional changes caused by the rains, interferometric ERS tandem pairs acquired
before and after the disaster have been used to produce coherence maps.
These coherence maps have been filtered using a specific statistically adaptive filter developed by
PRIVATEERS N.V. [9], to improve their radiometric quality.
Although the coherence maps are unexploitable in most of the covered area, mainly due to the presence of
strong relief (from sea level to 2430 meters), a comparison of these coherence maps reveals dramatic changes
over flat terrain, as shown in the Figure 4, featuring the Marqueira international airport.
The strong increase of the ERS coherence observable on the runways can be attributed to the presence of
sediment deposits left by the erosion consequent to the rains.
Nevertheless, from a global point of view, coherence maps have proven here their limitations for the detection
of even important changes in the presence of strong relief, as it is the case in most of the area covered by our
ERS images.
Figure 4: Comparison of the ERS-1/ERS-2 tandem coherence before (29/30 November 1998 in red)
and after (23/24 January 2000 in blue) the heavy rains.
6. CONCLUSION
After the success of several previous similar projects, the present project proved that, in order to produce
useful results very shortly after a natural disaster, the use of appropriate and well mastered techniques leads to
rapid project implementation and execution, even if the concerned area is wide or very wide, and the
requirements in terms of spatial resolution are very strict.
In this project, 12.000 km2 were covered at the resolution of 15x15 meters, and an additional 3.000 km2 were
covered at the resolution of 10x10 meters, in the most toughly affected part of Venezuela - coastal area,
Caracas, etc.
Regarding the products themselves, they provide the local photo-interpreters and/or end-users with a clear
overview of the situation at the time of the satellite data acquisition, during or just after the crisis, at high
spatial resolution. In this overview the main changes of interest, such as damages to housing and
infrastructures, and damages to agriculture and forest cover are put into evidence.
Moreover, when data (even heterogeneous data) are available at different times during and/or just after the
crisis, it is possible to provide a clear synoptic overview of the whole event by fusion of the information
acquired over time, by the same or by different spaceborne sensors.
For instance, on the example shown in Figure 3, one can immediately evaluate the huge damages suffered by
the coastal area of Venezuela, and the devastation caused to the coastal cities by the violent flood streams and
sedimentation.
Previously, techniques similar to those presented in this paper have been successfully used to assess the effects
of the “Mitch” hurricane (Honduras, El Salvador and Nicaragua, November 1998) [2], the damages of the
giant floods of the Yang-Tse-Kiang river in China (July/August 1999), the damages caused by the Izmit
earthquake (Turkey, August 1999) [3], the damages due to the “Lenny” hurricane (Guadeloupe Island,
November 1999) [4].
In the course of these projects, the techniques used have been continuously improved by PRIVATEERS N.V.,
with the aim to obtain a better detection of changes and damages, as well as to get a better interpretation of
the detected changes in terms of nature of the damages. This technical progress will be pursued in the future.
These techniques are now fully operational. In a world increasingly affected by natural disasters, they must,
and will, be more intensively exploited to speed-up post-crisis reaction and establish rehabilitation projects.
However, in future projects of the same nature, improvements must be made with regard to the decisiontaking processes at the level of the political bodies on which the major data providers depend, in order to
shorten their delay of reaction, and with regard to the data delivery delays.
Improvements must also be made with regard to the dissemination of results and the procurement of
appropriate technical support to the concerned end-users. This applies in particular to most of the developing
countries (but not only) where remote sensing is still a little known, or poorly mastered technology.
7. ACKNOWLEDGEMENTS
We acknowledge herewith the Centre National d’Etudes Spatiales (CNES), the European Space Agency
(ESA), and Spotimage for the provision of the ERS SAR data and for the SPOT data which have been used in
this project.
8. REFERENCES
[1] J.C. Centeno, 1999: "Venezuela viste de luto", Open Letter circulated over the Internet, 7 p., 24 December
1999.
[2] E. Nezry, F. Yakam Simen, P. Romeijn, I. Supit and P.Bally, 2000: "Mapping and evaluation of "Mitch"
hurricane damages in Central America using ERS SAR and SPOT images", ERS-ENVISAT Symposium,
Gothenburg (Sweden), 16-20 October 2000, This issue.
[3] F. Sarti, E.Nezry and F. Adragna, 2000: "Complementarity of correlation and interferometry for the
analysis of the effects of the Izmit earthquake with radar data". Communication invited to Multi-Conference
On Systemics, Cybernetics and Informatics (SCI2000), 6 p., Orlando (Florida, USA), 23-26 July 2000.
[4] K. Fellah, E. Nezry, P. Bally, J. Bequignon, A. Herrmann, C. Bestault and P. de Fraipont, 2000: "Rapid
mapping system for hurricane damage assessment", ERS-ENVISAT Symposium, Gothenburg (Sweden), 1620 October 2000, This issue.
[5] E. Nezry, F. Zagolski, A. Lopes and F. Yakam-Simen, 1996: "Bayesian filtering of multi-channel SAR
images for detection of thin details and SAR data fusion", Proceedings of SPIE, Vol.2958, pp.130-139,
September 1996.
[6] E. Nezry and F. Yakam-Simen, 1999: "A family of distribution-entropy MAP speckle filters for
polarimetric SAR data, and for single or multi-channel detected and complex SAR images, Proceedings of the
CEOS SAR Workshop, ESA SP-450, pp.219-223, Toulouse (France), 26-29 October 1999.
[7] E. Nezry, F. Yakam-Simen, F. Zagolski and I. Supit, 1997: "Control systems principles applied to speckle
filtering and geophysical information extraction in multi-channel SAR images", Proceedings of SPIE,
Vol.3217, pp.48-57, September 1997.
[8] A. Lopes, E. Nezry, R. Touzi and H. Laur, 1993: "Structure detection and statistical adaptive speckle
filtering in SAR images", International Journal of Remote Sensing, Vol.14, nr.9, pp.1735-1758, June 1993.
[9] E. Nezry, 1996: "New polarimetric - interferometric filters using prior knowledge of phase difference and
degree of coherence first order statistics", 10 p., Unpublished.