Task Your task is to identify application domains for remote sensing. Browse these web sites and read Campbell (2002) to list the Earth systems that have been observed by satellite and airborne systems.
Earth Observatory
[ URL ]
Source: NASA. Earth observatory. <http://earthobservatory.nasa.gov/Study/> URL last accessed 28-11-2006.
Applications Source: Campbell JB, 2002. Applications, Part IV in Introduction to remote sensing. Chichester: Wiley. 3rd edition.
Task Read a selection of these articles on remote sensing for observing the Earth. Your task is to assess the role of remote sensing in one or more application domain.
Disaster Prediction, Warning and Mitigation
[ URL ]
Source: United Nations, 1999. Disaster prediction, warning and mitigation, background paper prepared for the UNISPACE III conference. URL last accessed 28-9-2007.
Mapping Recent Lava Flows
[ pdf ]
Source: Lu Z, Rykhus R, Masterlark T and Dean KG, 2004. Mapping recent lava flows at Westdahl Volcano, Alaska, using radar and optical satellite imagery, Remote Sensing of Environment, 91, 345–353.
Mapping Volcano Topography
[ pdf ]
Source: Stevens NF, Garbeil H and Mouginis-Mark PJ, 2004. NASA EOS Terra ASTER: Volcanic topographic mapping and capability, Remote Sensing of Environment, 90, 405–414.
Lithologic Mapping
[ pdf ]
Source: Rowan LC and Mars JC, 2003. Lithologic mapping in the Mountain Pass, California area using Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data, Remote Sensing of Environment, 84, 350–366.
Playas
[ pdf ]
Source: Bryant R and Rainey MP, 2002. Investigation of flood inundation on playas within the Zone of Chotts, using a time-series of AVHRR, Remote Sensing of Environment, 82, 360–375.
Savannas
[ pdf ]
Source: Dube OP and Pickup G, 2001. Effects of rainfall variability and communal and semi-commercial grazing on land cover in southern African rangelands, Climate Research, 17, 195–208.
Fires Impacts on Savannas and Forests
[ pdf ]
Source: Bucini G and Lambin EF, 2002. Fire impacts on vegetation in Central Africa: a remote-sensing-based statistical analysis, Applied Geography, 22, 27–48.
Global Fire Activity
[ pdf ]
Source: Dwyer E, Pereira JMC, Gre´goire J-M and DaCamara CC, 1999. Characterization of the spatio-temporal patterns of global fire activity using satellite imagery for the period April 1992 to March 1993, Journal of Biogeography, 27, 57–69.
Forests
[ pdf ]
Source: Millington AC, Velez-Liendo XM and Bradley AV, 2003. Scale dependence in multitemporal mapping of forest fragmentation in Bolivia: implications for explaining temporal trends in landscape ecology and applications to biodiversity conservation, ISPRS Journal of Photogrammetry & Remote Sensing, 57, 289– 299.
Tundra
[ pdf ]
Source: Stow DA, Hope A, McGuire D, Verbyla D, Gamond J, Huemmrich F, Houston S, Racine C, Sturm M, Tapeh K, Hinzman L, Yoshikawa J, Tweedie C, Noyle B, Silapaswan C, Douglas D, Griffith B, Jiao G, Epstein H, Walker D, Daeschner S, Petersen A, Zhou L and Myneni R, 2004. Remote sensing of vegetation and land-cover change in Arctic tundra ecosystems, Remote Sensing of Environment, 89, 281–308.
Glaciers
[ pdf ]
Source: Gao J and Liu Y, 2001. Applications of remote sensing, GIS and GPS in glaciology: a review, Progress in Physical Geography, 25, 520–540.
Flooding
[ URL ]
Source: Dartmouth Flood Observatory. Current Flooding. <http://www.dartmouth.edu/~floods/> URL last accessed 13-1-2007.
Coastal Zone Source: Malthus TJ and Mumby PJ, 2003. Remote sensing of the coastal zone: an overview and priorities for future research, International Journal of Remote Sensing, 24, 2805-2815.
Environmental Change
[ pdf ]
Source: Donoghue DNM, 2002. Remote sensing: environmental change, Progress in Physical Geography, 26, 144–151.
Land Cover Change
[ pdf ]
Source: Zhan X, Sohlberg RA, Townshend JRG, DiMiceli C, Carroll ML, Eastman JC, Hansen MC, DeFries RS, 2002. Detection of land cover changes using MODIS 250 m data, Remote Sensing of Environment, 83, 336–350.
Global Net Primary Productivity
[ pdf ]
Source: Ramakrishna R. Nemani RR, Keeling CD, Hashimoto H, Jolly WM, Piper SC, Tucker CJ, Myneni RB and Running SW, 2003. Climate-driven increases in global terrestrial Net Primary Production from 1982 to 1999, Science, 1560-1563.
Urbanisation and Net Primary Productivity
[ pdf ]
Source: Imhoff ML, Bounouaa L, DeFries R, Lawrence WT, Stutzer D, Tucker CJ and Ricketts T, 2004. The consequences of urban land transformation on net primary productivity in the United States, Remote Sensing of Environment, 89, 434–443.
Urban Planning
[ pdf ]
Source: Fasona MJ and Omajola AS, 2004. GIS and remote sensing for urban planning, Proc. 12th Int. Conf. on Geoinformatics - Geospatial Information Research: Bridging the Pacific and Atlantic, University of Gävle, Sweden, 7-9 June 2004.
Land Registration
[ html ]
Source: Mikkonen K and Corker I, 2002. Using digital orthophotos to support land registration, GIS Cafe.
Estimating Population
[ pdf ]
Source: Pozzi F, Balk D, Yetman G, Nelson A and Deichmann U, 2003. Methodologies to improve global population estimates in urban and rural areas.
Thermal Remote Sensing of Urban Areas
[ pdf ]
Source: Voogta JA and Oke TR, 2003. Thermal remote sensing of urban climates, Remote Sensing of Environment, 86, 370–384.
Task Your task is to develop the image processing skills to extract useful information. Common activities performed by the image analyst are to analyse biophysical properties, such as biomass, and classify an image into land cover categories. You should complete the two exercises using either Erdas Imagine or ESRI ArcGIS.
Vegetation Indices - ArcGIS
[ pdf ]
Source: Trodd, N. 2012. Computing NDVI from a Landsat TM/ETM+ image in ArcGIS Image Analyst. GeoImaging and GeoInformatics.
Vegetation Indices - Imagine
[ pdf ]
Source: Modified from IS Ltd, 2005. Vegetation mapping, Module 5 in Image Processing Course for ERDAS Imagine. Tunbridge Wells: IS Ltd.
Land Cover Classification - Imagine
[ pdf ]
Source: IS Ltd, 2005. Classification, Module 6 in Image Processing Course for ERDAS Imagine. Tunbridge Wells: IS Ltd.
Land Cover Classification - ArcGIS
[ pdf ]
Source: Trodd, N., 2010. Image Classification in ArcGIS. GeoImaging and GeoInformatics.
Task Most studies combine data generated from remotely sensed imagery with other geographical information. To do so requires the analyst to georegister images to a known coordinate system. S/he is then able to exploit the rich data set by applying sophisticated tools for spatial analysis. Your task is to develop the knowledge and skills to integrate digital imagery with GIS.
Georeferencing - Imagine
[ html ]
Source: IS Ltd, 2005. Georeferencing images, Module 3 in Image Processing Course for ERDAS Imagine. Tunbridge Wells: IS Ltd.
Integration with GIS - Imagine
[ html ]
Source: IS Ltd, 2005. Integration with GIS - landslide susceptibility mapping, Module 9 in Image Processing Course for ERDAS Imagine. Tunbridge Wells: IS Ltd.