OEFS Projects Ideas

Students taking the course Observing Earth From Space are required to complete an individual project of their own choosing. Detailed information about project requirements can be found online. The following is a list of typical projects that could be accomplished to meet course requirements. Students are encouraged to pursue a project of personal interest, or one that enhances an area of your own research.

 

High lattitude mountain meterology

Explore aspects of mountain meterology, at high lattitudes, using a combination of Landsat imagery and elevation data. Physical properties such as temperature and albedo can be determined from these data. This will contribute to a new research project Ron Smith is considering in several mountainous regions. Pictured here is a Landsat ETM image of Denali on 27 September 2001.
Potential data sets to use: Landsat image of Denali at the CEO Archive and DEM data

 

Study the impact of Volcanic Eruptions

Use ASTER images to study the changes to the Island of Montserrat caused by volcanic eruptions.
Potential data sets to use: ASTER images of Montserrat that are in the CEO Archive.

 

Changes in land use practices in Central Asia

Several studies are possible focusing on, the Ferghana Valley, Syr-Darya or Amu-Darya rivers, Lake Balkash, or the Caucasus range). One could investigate changes in spatial extent of cultivation, cultivation intensity, changes from rainfed to irrigated agriculture, or changes in cropping practices (winter-, summer-cropping, single-, double-cropping, etc.).
Potential data sets to use: A combination of Landsat or ASTER (single date) to identify field patterns with NDVI time-series (Modis, SPOT-Vegetation, or AVHRR) from two different years to identify changes in annual cropping patterns.

 

Urban development in the Ferghana Valley, Uzbekistan

The Ferghana Valley is the main cropping area in the region, and at the same time it is also the most densely populated area in Uzbekistan. What is the impact of a growing population, and what does this mean for agriculture?
Potential data sets to use: Two Landsat or Aster scenes.

 

Desertification processes due to dropping sea levels in the Aral Sea

Dropping sea levels leave salt crusts and saline soils. Apart from the impact on human health, deflation of the evaporites affects fertility of the soils in neighboring areas. Other impacts of dropping sea levels include a drop of the water table. This produces several impacts including vegetation cover, albedo, and thermal characteristics in the region.
Potential data sets to use: NDVI time series from AVHRR, MODIS.

 

Examine the spread of the 2002 Biscuit Fire in Oregon and California

The Biscuit Fire in Oregon and Northern California began in July of 2002 and spread to approximately 500,000 acres. There were distinctive burn severity patterns that may be the result of topography, soils, vegetation cover, or a combination of these factors. Students could describe the spread over time and try to attribute casues to the observed burn patterns. Ann Camp would assist in the analysis of the burn information.
Potential data sets to use: MODIS.

 

Mountain Pine Beetle Infestation in British Columbia, Canada

Lodgepole Pine in British Columbia have been under severe threat from the Mountain Pine Beetle for the last several years. The Ministry of Forests now estimate that 9.2 million hectares are under red attack condition. A student could use MODIS images to map how this infestation has spread over time. This can be combined with DEM data to explore topographic impacts to the spread, i.e. changes in elevation, slope or aspect. Ann Camp could provide background information on forest infestation.
Potential data sets to use: MODIS and DEM data.

 

Sensitivity of phenological cycles to interannual climate variations

Compare dry or wet years to an average year. For example, 1999 was a particularly dry year in New England. How do different vegetation covers respond to water shortages and what is the impact on the plant's growing cycle as seen in NDVI time-series, or other vegetation relevant time-series (LAI, temperature, albedo,…).
Potential data sets to use: Modis, SPOT-Vegetation (two 1-year time series from years showing a different climate situation).

 

• Revegetation in Niger - See the N.Y. Times article dated 11 February 2007 in the CEO Lab
• Perform an analysis of the 2005 drought in Iowa/Illinois using a MODIS NDVI time series
• 5-year drought in the southwestern USA
• Ice shelf change in the Canadian archipelago
• Examine changes in Glacier National Park using an NDVI time series analysis or a Landsat TM change analysis
• Design a science project around the Near InfraRed sensitive camera
• Explore the changing albedo of grass as it turns brown using the spectrometer.
• Compare classification results from Max likelihood and decision tree methods
• Try to use MODIS or MISR anisotropy measurements to identify vegetation types.
• Perform anisotropy reflection measurements using the spectrometer
• Compare dark object subtraction with "regression" methods for radiometric normalization of images in change detection
• Compare day and night surface temperatures using the MODIS Thermal InfraRed bands or the MODIS Temperature products.
• Use MODIS products to investigate Arctic sea ice retreat connected with global warming, for one region (e.g. Baffin Bay, Hudsons Bay, Denmark Strait, Bering Sea, Barents Sea)
• Explore interannual variation in ocean productivity pattern in a region using MODIS or SeaWifs data.
• Perform a time series analysis of vegetation in Central Asia since 1990 and the collapse of the Soviet Union.
• Search for a lengthening of the green season in the Arctic connected with global warming (Myneni etc)
• Interannual variation in the Gulf of Mexico sea surface temperature may have implications to hurricane intensity issues.



• Explore and identify rubber, bamboo, and coconut plantations, favored habitat of Aedes albopictus (Asian Tiger Mosquito and vector of dengue) for classification of public risk associated with plantation tree crops.
• Determine vegetation cover of Rio, northeast to Natal, Brazil, associated with sand flies (vector for Leishmaniasis).
• Characterize landscape features associated with high and low densities of triatome (kissing bugs) and infection prevalence with Trypanosoma cruzi in villages of the Yucatan Peninsula of Mexico.



• Detect floristic change across topographic variations of an upland rain forest.
• Create a detailed landcover classification of the Quinnipiac River Watershed that can be draped over a digital elevation model (DEM) for educational uses.
• Relate land cover/succession to carbon sink strength by determining land cover types from satellite observations for several Ameriflux sites where monitoring of carbon uptake by forests is taking place.
• Determine the spatial extent, orientation, and longevity of dust plumes in the Middle East.
• Explore the potential of elevation data to improve Landcover/Landuse classification.
• Determine the amount, pattern and climatology of excessive rainfall upwind of mountain ranges such as the Western Ghats, Southern Andes, Southern Alps (i.e. New Zealand).
• Estimate the extent, patterns, and change in irrigation in a small part of the Syrian steppe.
• Examine changes in the forests of Northern Maine over time.
• Analysis of vegetation changes in the Yale Meyers Forest over time.
• Investigate terrain effects on temperature, snow and vegetation.

17 October 2007