Final Projects - GERS Laboratory at UPRM

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Final Projects - GERS Laboratory at UPRM
University of Puerto Rico
Mayagüez Campus
Department of Geology
Two-dimensional temporal-spatial analysis of the “Rio Bayamón” river mouth’s
suspended sediment area and its relation to anthropological and atmospheric processes.
Professor Fernando Gilbes Santaella
Rosa M. Vargas Martes
Kelly M. Núñez Ocasio
GEOL4048
Image downloaded from: https://en.wikipedia.org/wiki/Geography_of_Puerto_Rico
Río Bayamón
•
The river initiates north of the Beatriz community in Cidra, PR
at an elevation of 1,476ft above sea level.
•
It has a longitude of 25km from its initial point to its river
mouth in the San Juan bay.
•
The river passes through the municipalities of Cidra,
Guayanabo, Toa Baja, Bayamón and Cataño.
•
The river is part of the Cidra and San Juan river dams.
Focus points
• Relationship between the increase/decrease of the
river plume area and the anthropological
development adjacent to the river stream and river
mouth.
• Increase/decrease in the reflectance of the river
plume as a function of time.
Why?
• Anthropological development near the coasts
and near the river streams can have an effect
of the aquatic ecosystems.
• Suspended sediments can have a negative
effect on the aquatic life and on human
health.
Objectives
•
The objective of this project is to study the area coverage of the
suspended sediments (SS) over time as they are released by the river
plums.
•
Identify human and natural influences on the SS area coverage over time
through an observational analysis and review of collateral information
such as specific atmospheric activity near the studied date.
•
Study the turbidity of the water over time to determine the impact of the
SS on the aquatic environment and human health.
Methodology
•
Images were obtained from the Earth Explorer database.
•
Seven images were selected between the years 1999-2015.
• The image quantity was limited due to the lack of data
availability on the database and an error in one of the satellite
sensors over a good portion of the time period that was
initially selected.
Methodology
•
1500x1500 image subsets were created and a dark
subtraction atmospheric correction was applied to them.
•
The NNDiffuse Pan Sharpening tool was used to obtain an
image with a better spatial resolution.
•
Area calculations were done using the ROI tools available in
ENVI for the river plume and the anthropological structures
adjacent to it.
Plume ROI
Anthropological Structures ROI
•
The same subset was
created for all
sharpened images and
the anthropological
development within it
was calculated.
Reflectance Methodology
• ENVI Classic Platform was utilized to produce reflectance
images for the years 1999, 2000, 2001, 2003.
Reflectance Methodology
• For the years 2013, 2014 and 2015, radiometric calibration
was performed to the images to produce the reflectance
values.
• Reflectance values at a specific location within the river
plume were then identified and recorded for all years.
Results
Atmospheric Events
●
November 27th 1999 at 8am
Results
Atmospheric Events
●
November 13th 2000 at 8am
Results
Atmospheric Events
●
March 5th 2001 at 5am
AREA FORECAST DISCUSSION
HOWEVER...STILL A SIGNIFICANT EVENT COMING
NATIONAL WEATHER SERVICE SAN JUAN PR
UP. WAVEWATCH SHOWS A NORTH SWELL
PEAKING BETWEEN 7AM SAT - NOON SUN WITH
1120 AM AST WED JAN 22 2003
HEIGHTS TO 3.7 METERS AT A PERIOD OF 11-12.5
SECONDS. THIS TRANSLATES TO SWELL
UPDATED FORECAST MAINLY TO REFRESH
WORDING...BUT DID INCREASE POPS AND
CLOUD COVER FOR ST. CROIX...AS AREA OF
CLOUDS AND SHOWERS WILL MOVE INTO THIS
AREA NEXT COUPLE OF HOURS. NO OTHER
CHANGES WERE MADE TO ZONES/SHORT TERM
GRIDS.
HEIGHTS OF 12 FEET...WITH BREAKING WAVES
AROUND 20 FEET ON THE NORTH COASTS. I
ONLY SLIGHTLY TWEAKED THE GRIDS JUST
DELAYING THE RAPID INCREASE IN SWELLS FOR
LATE FRIDAY/EARLY SATURDAY (SEAS SHOULD
REMAIN LOW DURING THE DAY ON FRIDAY)...AND
CHANGED THE WORDING OF THE TEXT TO
REFINE TIMING OF THIS EVENT. WILL BE
MARINE...VERY LARGE SWELL EVENT IN THE
INTERESTING TO SEE THE NEW WAVEWATCH
OFFING. LATEST WAVEWATCH MODEL DID BRING
GUIDANCE THIS AFTERNOON...TO SEE IF IT
THE NUMBERS DOWN SLIGHTLY.
MAINTAINS CONSISTENCY. TIMING WILL
CONTINUE TO BE REFINED AS WARRANTED.
STAY TUNED.
Results
Atmospheric Events
● January 21st, 2003 at 7pm
Results
Atmospheric Events
●
January 21st, 2003 at 7pm
AREA FORECAST DISCUSSION
NATIONAL WEATHER SERVICE SAN JUAN PR
258 PM AST SUN SEP 22 2013
.SYNOPSIS...
UPPER LEVEL TROUGH CONTINUE TO LIFT
NORTH NORTHEAST ACROSS THE
WEST AND SOUTHWEST ATLANTIC...AS THE
ATLANTIC RIDGE EXTENDED WEAKLY
ACROSS THE NORTHERN LEEWARDS INTO THE
EASTERN CARIBBEAN. FURTHER
EAST...A TUTT WILL CONTINUE TO BECOME
AMPLIFIED AND SPREAD WESTWARD
INTO THE EASTERN CARIBBEAN OVER THE NEXT
FEW DAYS. THE BROAD AREA
OF LOW PRESSURE NORTH NORTHEAST OF THE
REGION CONTINUED TO PULL
.
FURTHER NORTHWARDS...AS A BROAD
SURFACE HIGH RIDGE REESTABLISHES
NORTH OF THE AREA...THEN AND BUILDS WEST
AND SOUTH ACROSS CENTRAL
AND SOUTHWEST ATLANTIC OVER THE NEXT
FEW DAYS. AS A RESULT EXPECT
A RETURN OF THE PREVAILING EAST
SOUTHEAST TRADE WIND FLOW FOR THE
NEXT WEEK OR SO.
Results
Atmospheric Events
●
September 21nd 2013 at 8pm
AREA FORECAST DISCUSSION
NATIONAL WEATHER SERVICE SAN JUAN PR
222 PM AST FRI NOV 28 2014
.SYNOPSIS...RIDGE ALOFT WILL FLATTEN
TONIGHT AND SATURDAY AS POLAR
TROUGH MOVES ACROSS THE WESTERN
ATLANTIC. SURFACE HIGH WILL BUILD
ACROSS THE WESTERN ATLANTIC EARLY NEXT
WEEK...TIGHTENING THE LOCAL
PRESSURE GRADIENT.
.DISCUSSION...MOSTLY SUNNY SKIES
PREVAILED ACROSS THE LOCAL ISLANDS
THROUGH THE DAY...WITH FEW SPRINKLES
OBSERVED ACROSS THE CARIBBEAN
WATERS AND SAINT CROIX. TEMPERATURES
WERE IN THE MID TO UPPER 80S
AT LOWER ELEVATIONS AND NEAR 80 DEGREES
AT HIGHER ELEVATIONS.
EARLY NEXT WEEK AS SURFACE HIGH BUILDS
ACROSS THE WESTERN ATLANTIC...
TRADES WILL STRENGTHEN ACROSS THE LOCAL
AREA. THIS WILL ENHANCE LOW
LEVEL MOISTURE TRANSPORT FROM THE EAST
NORTHEAST...RESULTING IN THE
CONTINUED TREND OF PASSING SHOWERS
ACROSS THE NORTH AND EAST COASTAL
SECTIONS OF LOCAL ISLANDS MONDAY
THROUGH AT LEAST WEDNESDAY.
Results
Atmospheric Events
●
November 28th 2014 at 8am
NATIONAL WEATHER SERVICE SAN JUAN PR
..DISCUSSION...ONLY A FEW PASSING TRADE
601 AM AST SUN NOV 15 2015
WIND SHOWERS WERE NOTED MOVING
.SYNOPSIS...MID TO UPPER LEVEL TROUGH WILL
CONTINUE TO MOVE EASTWARD
WESTWARD ACROSS THE COASTAL WATERS
THIS MORNING...WITH LITTLE OR
ACROSS THE REGION TODAY AND REACH THE
NORTHERN LEEWARDS ON MONDAY. IN
NO PRECIPITATION REACHING THE COASTAL
AREAS SO FAR. EXCEPT FOR THESE
THE MEANTIME...A POLAR TROUGH WILL ENTER
THE NORTHWESTERN ATLANTIC LATER
PASSING SHOWERS...SOMEWHAT DRIER
CONDITIONS ARE EXPECTED DURING MOST
TODAY...THEN BECOME AMPLIFIED AND SINK
SOUTHWARDS TO JUST WEST OF THE
OF THE DAY AS THE REGION WILL BE ON THE
SUBSIDENT SIDE OF THE UPPER
REGION BY TUESDAY AND WEDNESDAY. BY
THEN...THE UPPER TROUGH PATTERN
TROUGH. STILL HOWEVER EXPECT DIURNALLY
INDUCED AFTERNOON SHOWERS
IS FORECAST TO PERSIST AT LEAST UNTIL
FRIDAY. SURFACE HIGH PRESSURE
MAINLY OVER PARTS OF THE INTERIOR AND
WEST SECTIONS OF PUERTO RICO.
WILL CONTINUE TO EXIT THE EASTERN
SEABOARD OF THE UNITED STATES...AND
RECENT SATELLITE IMAGERY SHOWED
ANOTHER SURGE OF TRADE WIND MOISTURE
SPREAD ACROSS THE WESTERN ATLANTIC
OVER THE NEXT SEVERAL DAYS. THIS
MOVING ACROSS THE NORTHERN LEEWARDS.
SOME OF THESE SHOWERS MAY REACH
WILL INCREASE THE EASTERLY TRADE WINDS
ACROSS THE REGION AS THE
PARTS OF THE VIRGIN ISLANDS LATER THIS
MORNING AND EARLY
PRESSURE GRADIENT TIGHTENS.
AFTERNOON BUT THEY WILL BE MOSTLY LIGHT
AND OF SHORT DURATION.
Results
Atmospheric Events
●
November 15 2015, at 8am
eeeee
eeeee
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Conclusions
● A quantitative analysis was performed to the river plume area of the Río
Bayamón. Calculations of both river plume suspended sediments and
anthropogenic areas close to the river were calculated as well as
reflectance values.
● Reflectance showed almost no relation and/or dependence with time
(R^2=.3637).
● Comparison of historical data with river plume area demonstrates a
direct relation between river plume active period and atmospheric
conditions.
● Although anthropogenic area did not show a positive relation with the
river plume area, statistics demonstrate a somewhat relation
(R^2=0.5687).
Recommendations
●
●
●
●
●
●
●
Use a larger data set.
Study a broader time period.
Use a specific and detailed algorithm tailored for the sensor
in use in order to calculate more accurate reflectance values.
Find the specific forecast discussions for the remaining years.
Improve the reflectance measurement techniques.
Use a single sensor for the study.
Use a sensor with a better spatial resolution.
Acknowledgements
This work was performed under the auspices of the University of
Puerto Rico at Mayagüez’ Geology Department. The work was
managed by Dr. Fernando Gilbes Santaella and was funded by the
University of Puerto Rico at Mayagüez.
This research was also possible thanks to the contribution of: Alexis
Rivera (UPRM), Alexis Orengo (WOLE), Isha Renta (NOAA) and
Rosalina Vásquez (NWS).
Cambio en la temperatura de
la superficie del Océano
Atlántico con el paso de los
huracanes
M Ó N I C A Y. AYA L A
D E PA R TA M E N TO D E G E O LO G I A , R U M
I VÁ N L . F O N TÁ N E Z
D E PA R TA M E N TO D E F I S I C A , R U M
P R O F. F E R N A N D O G I L B E S
G E O L 4 0 4 8 – G E O LO G I C A L A P P L I C AT I O N S O F R E M OT E S E N S I N G
Introducción
Los cambios en la temperatura del océano nos pueden ser indicativos sobre todo
cuando llega la temporada de huracanes en el Océano Atlántico. El aumento o
disminución en la temperatura del océano puede significar que los sistemas
ciclónicos se fortalezcan o se debiliten. Debido a que nuestro principal sistema para
investigar es el Huracán Joaquín es por eso que seleccionamos la zona de las
Bahamas como punto de interés en el estudio del cambio en temperatura superficial
del océano.
Esta zona de las Bahamas fue punto focal para seleccionar otros huracanes con una
trayectoria similar a la de Joaquín. Utilizando la herramienta “Sea Surface
Temperature (SST) AVHRR” del programa ENVI procesamos las imágenes obtenidas
de la base de datos de NOAA.
Objectivos
• Demostrar la influencia de los huracanes en la temperatura de los
océanos.
• La comparación entre el huracán Joaquín, Irene y Sandy.
• Investigar los beneficios y consecuencias del cambio en la
temperatura del océano.
Metodología
•Programa de ENVI
•Toolbox
Raster Management
Data-Specific Utilities
AVHRR
Sea Surface Temperature
• Toolbox
Geometric Correction
Georeference by Sensor
Georeference
AVHRR
•Toolbox
Raster Management
Masking
Build Mask
•Toolbox
Raster Management
Masking
Apply Mask
Metodología
•Programa de ENVI Classic
• Open Image File
Tools
Color Mapping
Overlay
Annotations
• Las imagenes de Joaquin fueron obtenidas NP=NOAA-19
• Fue lanzado el 6 de febrero de 2009
• Las imágenes de Sandy e Irene fueron obtenidas de M2 = Metop-A
• Satélite europeo y fue lanzado el 19 de octubre de 2006
• Las imagenes obtenidas fueron Level 1b y fueron procesadas en el
programa ENVI
NOA A - 1 9
ME TO P -A
Imagen 2: Modelo del Satélite Metop-A (M2).
Imagen 1: Satélite NOAA-19 (NP).
Metodología
• Sea Surface Temperature equations for • Sea Surface Temperature equations for
NOAA-19
NOAA MetOp-A
• Day
• Ts = a0 + a1*band4 + a2(band4 - band5) +
a3(band4 - band5)(sec(f) -1)
•
•
•
•
•
Infrared band
ao = -278.74596
a1 = 1.01922
a2 = 1.72270
a3 = 0.80263
• Night
• Ts = a0 + a1*band4 + a2(band4 - band5) +
a3(band4 - band5)(sec(f) -1)
•
•
•
•
•
Infrared band
ao = -277.71304
a1 = 1.01432
a2 = 1.91798
a3 = 0.72064
• Day
• Ts = a0 + a1*band4 + a2(band4 - band5) +
a3(band4 - band5)(sec(f) -1)
•
•
•
•
•
Infrared band
ao = -273.816
a1 = 1.00255
a2 = 2.39451
a3 = 0.903773
• Night
• Ts = a0 + a1*band4 + a2(band4 - band5) +
a3(band4 - band5)(sec(f) -1)
•
•
•
•
•
Infrared band
ao = -277.447
a1 = 1.01377
a2 = 2.52362
a3 = 1.03056
AVHRR/3 Channel Characteristics
Channel Number
Resolution at Nadir
Wavelength (um)
Typical Use
1
1.09 km
0.58 - 0.68
Daytime cloud and
surface mapping
2
1.09 km
0.725 - 1.00
Land-water boundaries
3A
1.09 km
1.58 - 1.64
Snow and ice detection
3.55 - 3.93
Night cloud mapping,
sea surface
temperature
3B
1.09 km
4
1.09 km
10.30 - 11.30
Night cloud mapping,
sea surface
temperature
5
1.09 km
11.50 - 12.50
Sea surface
temperature
Tabla 1: Tabla obtenida de NOAA en información sobres los satélites (De:
http://noaasis.noaa.gov/NOAASIS/ml/avhrr.html ).
Localización de Boya en las Bahamas
Imagen 3: Station 41047 – NE BAHAMAS (http://www.ndbc.noaa.gov )
Resultados Joaquin
Resultados Sandy
Resultados Irene
Imagen 4: Huracán Irene sobre las Bahamas.
24 de agosto de 2011. Foto del satélite GOES
Conclusión
• Luego de analizadas las imágenes se pudo detectar cambios en la temperatura
superficial del océano en la zona de las Bahamas. Estos datos fueron
corroborados tanto por las imágenes de satélites como con datos de las boyas
localizadas en las Bahamas.
• Al comparar las imágenes de los huracanes: Joaquín, Sandy e Irene observamos
un patrón similar en el comportamiento del SST, antes durante y después del
paso de los huracanes.
Conclusión
• Algunos de los beneficios del paso de los huracanes por esa zona es que
mantienen una distribución mas o menos igual en la temperatura del océano.
Previene el fortalecimiento de otros sistemas ciclónicos que vayan a pasar por la
zona en días posteriores.
• Algunas de las consecuencias es la perdida de bienes materiales y de vidas en las
zonas donde los huracanes afectan.
Recomendaciones
• Huracán Isabel 2003
• Dificultad con aplicar una máscara a las imágenes
• Resolución en la imagen de NOAA-19
Referencias
Cione, J. J. and Uhlhorn, E. W., 2003, Sea Surface Temperature Variability in Hurricanes:
Implications with Respect to Intensity Change, v. 131, p. 1783-1796.
DeMaria, M., Kaplan, J., 1993, Sea Surface Temperature and the Maximum Intensity of Atlantic
Tropical Cyclones: Journal of Climate, v. 7, p. 1324-1334.
NOAA, National Oceanic and Atmospheric Administration: URL:
http://www.nodc.noaa.gov/SatelliteData/pathfinder4km/ , Last modification: 29 January 2014
, (accessed 30 April 2016).
NOAA, 2014, NOAA KLM Users Guide (Revised), 8-343 p.
Harris Corporation, Exelis Visual Information Solutions: Geospatial Solutions: URL:
http://www.harrisgeospatial.com/docs/AVHRRSeaSurfaceTemperature.html , Last Modified:
2016, (accessed 29 April 2016).
Impacto del huracán Katrina en Louisiana,
utilizando imágenes del programa Landsat
(TM y ETM+) y MODIS
Por: Marielly Irizarry Ramírez
Manuel I. Ramos Rodriguez
Introducción:
Huracán Katrina
Introducción
El huracán Katrina tocó tierra en la costa este de Louisiana el
29 de agosto de 2005 (Barras, 2007).
Este huracán fue uno de los desastres naturales más hablados durante
la última década. Tanto el estado de Louisiana, como los estados
vecinos de Alabama y Mississippi, fueron grandemente afectados tras
el paso del huracán.
Algunas consecuencias del impacto del huracán fueron las pérdidas de
tierra que sufrieron las costas y las inundaciones debidos por la
presencia de humedales (Barras, 2007). Este fue uno de los huracanes
más costosos de Estados Unidos.
Introducción
Louisiana y los estados vecinos sufrieron, entre muchas cosas,
aumentos transitorios de agua causados por inundaciones
repentinas, eliminación de la vegetación acuática y una interrupción del
ecosistema nativo (Barras, 2007).
Islas cercanas y costas experimentaron una gran cantidad de erosión, un
ejemplo es “Dauphin Island” donde la primera fila de casas quedaron
expuestas al mar (Sallenger, Wright, y Lillycrop, 2007).
Introducción
Objetivos
Objetivos
• Utilizar imágenes del programa Landsat y sus sensores TM y ETM+,
así como los sensores GOES y MODIS.
• Hacer ajustes a las imágenes crudas o levemente procesadas
mediante el programa ENVI.
• Comparar la geografía del lugar antes y después del huracán.
• Analizar la erosión de costas.
• Analizar la eliminación de vegetación.
• Observar si estos daños tuvieron efectos permanentes.
Metodología
Metodología
• Se obtuvieron imágenes crudas y levemente procesadas de la base
de datos EarthExplorer.
• Se abrieron las imágenes obtenidas en el programa de
procesamiento y análisis de imágenes, ENVI.
• Se realizó un “stretch” linear de 2% a las imágenes para tener una
mejor visualización de la imagen en color verdadero.
• Se realizó un “subset” de las imágenes para analizar el área de New
Orleans y el Lago Pontchartrain, lugares donde se presentó el mayor
impacto del huracán.
Metodología
• A las imágenes recortadas, se les realizó un cambio del color de
bandas (Change RGB Bands) para obtener una imágenes de color
falso, donde la banda infrarroja cercana pasó a ser la banda roja, la
banda roja pasó a ser la banda verde, y la banda verde pasó a ser la
banda azul.
• Luego, se utilizó la herramienta “NDVI” con Green/White Linear y
“Band Mask” para las imágenes. A la imagen obtenida se le aplicó
una mascara para ocultar los cuerpos de agua.
Metodología
• Por último se realizó una Clasificación Supervisada sobre el area de
New Orleans para visualizer major las inundaciones.
• Las Regiones de Interés fueron:
-Amarillo-Ciudad
-Verde-Vegetación
-Blanco-Nubes
-Azul-Agua
Metodología
• Comparar:
• Imagen antes del Huracán vs. Días después del Huracán
• Imagen antes del Huracán vs. Meses después del Huracán
• Meses después del Huracán vs. Imagen Reciente
• Imagen antes del Huracán vs. Imagen Reciente
Resultados
Resultados- Color Verdadero
22Ago2005-30Ago2005
22Ago2005-7Sep2005
22Ago2005-2Nov2005
2Nov2005-10Oct2015
22Ago2005-10Oct2015
MODIS 28AGO-30AGO-31AG0
Resultados- Color Falso
22Ago2005-30Ago2005
22Ago2005-7Sep2005
22Ago2005-2Nov2005
2Nov2005-10Oct2015
22Ago2005-10Oct2015
Resultados- NVDI
22Ago2005-30Ago2005
22Ago2005-7Sep2005
22Ago2005-2Nov2005
2Nov2005-10Oct2015
22Ago2005-10Oct2015
ResultadosClasificación Supervisada
22Ago2005-30Ago2005
22Ago2005-7Sep2005
22Ago2005-2Nov2005
2Nov2005-10Oct2015
22Ago2005-10Oct2015
Concluciones
Concluciones
• Mediante el análisis de las imágenes obtenidas para este proyecto,
pudimos observar que la vegetación del área de Louisiana se vio afectada
de manera significativa. Esto se debe a que aún se puede observar áreas
oscuras en los lugares donde se observaron inundaciones tras el paso del
huracán Katrina.
• De igual forma, se pudo observar que las áreas cercanas a las costas no
poseen la misma forma previa al huracán Katrina, por lo que se puede
deducir que no solo se observaron inundaciones en las imágenes sino una
remoción del terreno.
• Concluimos que el huracán Katrina ocasionó daños irreversibles en el área
de Louisiana; daños que con el paso de 10 años aún pueden observarse.
Recomendaciones
Recomendaciones
• Para futuras investigaciones, pudiéramos obtener diferentes
imágenes, ya sea de diferentes sensores como aquellas de satélites
comerciales como IKONOS.
• Se recomienda utilizar imágenes de otras áreas donde se observen los
efectos del huracán Katrina.
Referencias
Referencias
Barras, J.A., 2007, Satellite images and aerial photographs of the effects of Hurricanes Katrina and Rita on coastal Louisiana: U.S.
Geological Survey Data Series 281, at http://pubs.usgs.gov/ds/2007/281.
Campbell, J.B., and Wynne, R.H., 2011, Introduction to Remote Sensing: New York, The Guilford Press, 718 pp.
Darling, D., 2003, The Complete Book of Spaceflight: From Apollo 1 to Zero Gravity: New Jersey, John Wiley & Sons, pp. 165-167.
Landsat missions, 2015, Landsat Project Description: http://landsat.usgs.gov//about_project_descriptions.php (accessed February
2016)
Nourbakhsh, Illah, et. al., 2006, Mapping disaster zones: Nature, v. 439, no. 7078, p. 787-788, doi:10.1038/439787a
Rykhus, R., and Lu, Z., 2007,Hurricane Katrina Flooding and Oil Slicks Mapped with Satellite Imagery: Virginia, USGS, pp. 49-52.
Sallenger, A., Wright, C., y Lillycrop, J., 2007, Coastal-Change Impacts during Hurricane Katrina: An Overview: Coastal Sediments
'07: pp. 888-896. doi: 10.1061/40926(239)68
Womble, J.A., Ghosh, S., Adams, B.J., and Friedland, C.J., 2006, Advanced Damage Detection for Hurricane Katrina: Integrating
Remote Sensing and VIEWS™ Field Reconnaissance: Louisiana, Louisiana State University, 154 pp.
¿Preguntas? ¿Comentarios?
Vegetation and crater analysis of Mt. St.
Helens Volcano related to eruptive
cycles and seasonal conditions
Evemarie Y. Bracetti Resto
Alexis D. Rivera Rosario
Prof. Fernando Gilbes
Geol 4048
(from: http://volcanoes.usgs.gov/vsc/images/ image _mngr/500-599/img569.jpg)
Introduction
• Mount Saint Helens is an active stratovolcano located in Skamania County,
Washington, USA.
• It is located in the Cascade Range and it is part of the Cascade Volcanic Arch and the
Pacific Ring of Fire, which includes over 160 active volcanoes.
• Youngest and most active volcano in the Cascade Range, it is one of the many
volcanoes in the U.S and the only one to have a continuous eruptive history.
• Mt. St. Helens is known for its catastrophic eruption on May 18, 1980 at 8:30 a.m.
• This eruption was the deadliest and most economically destructive volcanic event in
the history of the United States of America.
• Fifty-seven people were killed, 185 miles of road and 200 homes were damaged or
destroyed, and ashfall was seen nearly 22,000 square miles away from the eruption.
Cont. Introduction
Schematic Illustration of the
1980 Eruption
(from: Notable Natural Disasters)
Cont. Introduction
Modern Activity
• The last known volcanic activity occurred
in October, 2004
• Very few earthquakes were recorded and
those that were only reached 2.0. This
continued until the events subsided from
late January to early February, 2008.
• As of late, in February, 2011, an
earthquake north of the crater registered
a magnitude of 4.3, followed by
aftershocks with a magnitude of 2.8.
(from: https://volcanoes.usgs.gov/volcanoes/st_helens/st_helens_hazard_75.html)
Objectives
• Using satellite images provided by the Earth Explorer webpage to
determine the vegetation index and seasonal change.
• Determining the rate of change for the crater area of the volcano
related to its eruptive cycle.
Methodology
Image Acquisition
• The images were acquired from the Earth Explorer website.
• The following Landsat sensors were chosen:
• Multispectral Sensor (MSS) and Thematic Mapper (TM) Enhanced Thematic Mapper
Plus (ETM+), Operational Land Imager (OLI).
• The dates chosen were: August 28, 1986 (MSS), September 07, 1999 (MSS),
January 29, 2001 (ETM+), February 28, 2008 (TM), January 01, 2016 (OLI).
Cont. Methodology
Image Processing
• After opening the MLT files in EVNI a subset was created for each of the images,
with a size of 3000 x 3000.
• Using the same subset a Dark Subtraction was applied to enhance the image.
• A supervised classification was chosen, in this case Maximum Likelihood
Classification.
• For each subset a specific Region of Interest (ROI) was designed, using the
following criteria: Clouds, Ice, Vegetation and Water.
• A Normalized Difference Vegetation Index (NDVI) was made for the subsets to
determine the change of vegetation throughout the given area.
• In addition another ROI was created to estimate the change in area of the crater.
Results
Cont. Results
Cont. Results
Cont. Results
Cont. Results
Cont. Results
Cont. Results
Cont. Results
Cont. Results
Cont. Results
Date (m/d/y)
Area (km2)
August 26, 1986
2.721600
September 7, 1999
2.617200
January 29, 2001
2.617200
February 28, 2008
2.617200
January 1, 2016
2.617200
Table 1: Area of the crater throughout the years
Mt. St. Helens throughout the years (1979-2009)
Conclusion
• Given the images that were processed of the Mt. St. Helens
subsets the eruptive cycles of this volcano have no correlation
with the change of the craters diameter. Seasonal conditions add a
vast amount of snow during fall and winter seasons, which can
create lahars if future eruptions occurred at this time. There is
still regrowth of vegetation in the area even after such an
extensive period of volcanic activity.
Recommendations
• It would have been best to work on a 3-D scale of the volcano to
clearly understand its topography and details of the same. Images
related to prior eruptive history would be better suited to
determine the vegetation and crater changes of Mt. St. Helens.
QUESTIONS?
?
http://blogs.agu.org/magmacumlaude/files/2011/09/MSH82_st_helens_plume_from_harrys_ridge_05-19-82_med.jpg
NDVI Comparison for Pre and Post-tsunami Images
Using Quickbird High Resolution Images in Chilka
Lake, India
Pedro I. Matos-Llavona y Fabiola B. Torres-Toledo
GEOL 4048
Geological Applications of Remote Sensing
Professor: Fernando Gilbes, PhD.
Chilka
Lake
“The Dec. 26, 2004, earthquake ruptured 250 kilometers offshore of Sumatra, Indonesia; tsunami
waves traveled thousands of kilometers with enough power to kill hundreds of people and destroy
villages as far away as the east coast of Africa.” –Earth Magazine
NOAA 2004 Indian Ocean Tsunami Simulation
Chilka Lake, India
■ One of the most important wetlands in the
world, home to a phenomenal variety of birds.
■ 160 species in the peak season between
November and February.
■ Endangered species: Olive Ridley nesting
ground
■ Important for the economy; tourism.
http://www.orisatourism.org/chilka-lake.html
Objectives
■ Using QuickBird High Resolution Images:
– Calculate and compare NDVI values for pre-tsunami images and post-tsunami
images.
– Perform an accurate Supervised and Unsupervised classification in order to
assess tsunami damage.
Methodology
NDVI
Raw images
Seamless
Mosaic
Pansharpening
Subset of
overlapped
area
Supervised
Classification
Maximum
Likelihood
Unsupervised
classification
IsoData
K-Means
Pre-tsunami (December 11,
Post-tsunami (December 29, 2004)
NDVI
Pre-tsunami (December 11,
2004)
Post-tsunami (December 29, 2004)
NDVI Histograms
Mean: 0.196533
St. Dev.: 0.107187
Mean: 0.10729
St. Dev.: 0.10729
Supervised Classification: Maximum Likelihood
Pre-tsunami (December 11,
2004)
Post-tsunami (December 29, 2004)
IsoData
Pre-tsunami (December 11,
2004)
Post-tsunami (December 29, 2004)
K-mean
Pre-tsunami (December 11,
2004)
Post-tsunami (December 29, 2004)
Chilka Lake, Orissa (India)
■ Sand dunes of varying heights, which at places reach as high as 15 meters
■ Reports available after the Indian Ocean Tsunami 2004 indicated that the coast of
Orissa was the least affected by the tsunami.
■ Mix of estuarine, marine and freshwater ecosystem
■ Agriculture
– Shrimp farming (many have been abandoned)
– Paddy fields
Results
■ The 2004 tsunami that originated from the earthquake in Indonesia (December 26,
2004) did not affect Chilika lake. This might be due to the extensive line of high
altitude sand dunes and the coastal vegetation that served as barriers, and wave
energy dissipation due to continental platform.
■ Changes in the NDVI images are probably due to the land management.
■ Changes found on the unsupervised classification are also probably due to the land
management, and the water classification differences due to the change in salinity.
References
Adikanda, O., Jajnaseni, R., Samal, R.N, Rajesh, G, Pattnaik, A.K, Pritirekha, D., 2010, Evaluation of landuse / landcover
dynamics of chilika catchment. International Journal of Geomatics and Geosciences. Volume 4, No 2, 2013.
Kouchi, K., and Yamazaki, F., 2007, Characteristics of Tsunami-Affected Areas in Moderate-Resolution Satellite Images: IEEE
Trans. Geosci. Remote Sensing IEEE Transactions on Geoscience and Remote Sensing, v. 45, p. 1650–1657.
Kouchi, K., Yamazaki, F. and Matsuoka, M., 2006, Tsunami Damage Detection Using Moderate-Resolution Satellite Imagery:
Asia Conference on Earthquake Engineering Theme: Seismic Hazards and Damage Mitigation in the Asian Region.
Miura, H., A. C. Wijeyewickrema, and S. Inoue, 2006, Evaluation of tsunami damage in the eastern part of Sri Lanka due to
the
2004 Sumatra earthquake using remote sensing technique. Proc. 8th National Conference on Earthquake
Engineering, Paper No. 8.
Panigrahi, S., Wikner, J., Panigrahy, R.C., Satapathy, K.K., and Acharya, B.C., 2009, Variability of nutrients and phytoplankton
biomass in a shallow brackish water ecosystem (Chilika Lagoon, India): Limnology, v. 10, p. 73–85.
S.I.C., 2015, Satellite Imaging Corporation: QuickBird Satellite Imagery and Satellite Sensor Specifications,
http://www.satimagingcorp.com/satellite-sensors/quickbird/.
Venkatarathnam, K., 1970, Formation of the Barrier Spit and other sand ridges near Chilka Lake on the east coast of India:
Marine
Geology, v. 9, p. 101–116.
Using Aerial Photographs to Compare Coastal Erosion from El
Maní at Mayagüez, Puerto Rico, between 1930,1999 and 2010.
Irmarís Rivera -Llavona
Iris M. Díaz Olmo
Prof. Fernando Gilbes
Geological Applications for Remote Sensing
May 9, 2016
Introduction
The National Research Council of United States (1990) defines coastal erosion as the process by which coastlines and beaches
are worn out. This process is caused by wave action, wave currents and other natural and anthropogenic factors (McNab et.
al, 2011). Puerto Rico is located in the Caribbean and most of the infrastructure is located near the coast. Coastal erosion
changes will affect not only the geomorphology of the Island but also the infrastructure and human lifestyle, socially and
economically.
Storm surge can be one of the major hazards affecting the coast. Also, in 1998, Hurricane Georges caused extremely high
storm surge in the north coast of Puerto Rico (Turnipseed et. al, 1998). This is why the 1930 and 1999 period will let to
make a reasonable comparison of the north coast region by using aerial images. The images will be analyzed and processed
using ENVI software.
COASTAL EROSION
“... the process by which coastlines
and beaches are worn out.”
It can be caused by:
● wave action,
● wave currents;
● other natural &
anthropogenic factors
What factors contribute to coastal erosion?
● Storm surge conditions
● Human behavior
● Natural variations
[Objectives]
Motivated by the drastic changes seen in the coastal areas of
Puerto Rico, this research is focused on coastal erosion. The purpose of this
project is to make a comparison between aerial photographs from 1930, 1999 and 2010. By
analyzing coastal features we will be able to determine how coastal erosion has affected
El Maní coast from 1930 to 2010. Using aerial
photographs as a remote sensing technique was helpful for conclusions on what
phenomena causes or contribute to these changes.
Methodology
ENVI software
➔ Mark off coast line
➔ Compare the evolution
(1930)
(1999)
BEFORE
(2010)
Coastline from
El Maní (1930)
Coastline from
El Maní (1999)
Coastline from
El Maní (2010)
Supervised Classification
Maximum Likelihood
Maximum Likelihood Classification for El Maní (1999)
Maximum Likelihood Classification for El Maní (2010)
Conclusions
It was possible to make a comparison between 1930,
1999 and 2010 aerial photographs by creating a
shoreline from El Maní (using ROI tool in ENVI
Classic). It was notorious an erosion-deposition event
during this time lapse. Also, a Supervised
Classification (Maximum Likelihood) was made for
aerial photographs from 1999 and 2010, where the
main purpose was to compare city and vegetation in a
decadal time.
It was not possible to correlate specific phenomena
(such as Hurricane Georges) as the principal factor for
geomorphological changes around the coast, but it is
known that tropical cyclones, runoff during storm
events as well as anthropogenic activities are
constantly contributing to coastal erosion.
As Barreto, Morelock and Ramírez (2002) suggest in
past studies, a day of storm activity can contribute to
changes in geomorphology but it will take years under
normal conditions.
Recommendations
• Other supervised/unsupervised classification and indexes, such as NDVI.
• To keep improving coastal studies by analyzing coastal features using Remote
Sensing Techniques (ENVI);
References
Barreto, M., Morelock, J., Ramírez, W., 2002, The World’s Coasts - Puerto Rico, Mayagüez, Puerto Rico, University of Puerto Rico.
Morelock, J., 1978, Shoreline of Puerto Rico. Coastal Zone Management Program, Department of Natural Resources, Puerto Rico. 45 p.
McNab, R., Mullen, D., Yatim, M., Zeeb, K., 2011, Communicating Coastal Hazards and Oceanic Conditions in San Juan, Puerto Rico,
A Report for: Department of Natural and Environment Resources, 106p.
National Research Council (U.S.) Committee on Coastal Erosion Zone Management. (1990). Managing Coastal Erosion. Washington,
D.C.: National Academy Press.
Turnispseed, D. P., Giese, G. L., Pearman, J. L., Farris, G. S., Krohn, M. D., Sallenger, A., H., 1998, United States Geological Survey,
6p.
Questions?

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