Final Projects - GERS Laboratory at UPRM
Transcription
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 eeeee 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?