Identification of fugitive dust generation, transport and deposition areas using remote sensing

Environmental and Engineering Geoscience

Volumn 9, Issue 2, 2003, Pages 151-165

  Stefanov, William L ^a   Ramsey, Michael S ^b   Christensen, Philip R ^a  

^a ARIZONA STATE UNIVERSITY   (United States)

^b UNIVERSITY OF PITTSBURGH   (United States)

Author keywords

Air quality; Atmospheric (circulation) modeling; ETM+; Expert system; Fugitive dust; Land cover classification; Particulates; Remote sensing

Indexed keywords

AEROSOL COMPOSITION; AIR QUALITY; ATMOSPHERIC TRANSPORT; DUST; LAND COVER; REMOTE SENSING; SEASONAL VARIATION;

EID: 0041811790     PISSN: 10787275     EISSN: None     Source Type: Journal    
DOI: 10.2113/9.2.151     Document Type: Article

References (39)

1. ABRAMS, M., 2000, The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER): Data products for the high spatial resolution imager on NASA's Terra platform: International Journal Remote Sensing, Vol. 21, pp. 847-859.
2. BEN-DOR, E.; IRONS, J. R.; AND EPEMA, G. F., 1999, Soil reflectance. In Rencz, A. N. (Editor), Remote Sensing for the Earth Sciences: Manual of Remote Sensing, 3rd ed., Vol. 3: John Wiley & Sons, New York, pp. 111-188.
3. BOTKIN, D. B.; ESTES, J. E.; AND MACDONALD, R. B., 1984, Studying the earth's vegetation from space: BioScience, Vol. 34, pp. 508-514.
4. BROWN, E. R.; MCRAE, J. L.; AND CRAWLEY, A. B., 1989, Effect of aggregates on performance of bituminous concrete. In Implication of Aggregates in the Design, Construction, and Performance of Flexible Pavements: American Society of Testing and Materials STP 1016, pp. 34-62.
5. CHEN, F. AND DUDHIA, J., 2001a, Coupling an advanced land-surface/ hydrology model with the Penn State/NCAR MM5 modeling system. Part I: Model implementation and sensitivity: Monthly Weather Review. Vol. 129, pp. 569-585.
6. CHEN, F. AND DUDHIA, J., 2001b. Coupling an advanced land-surface/ hydrology model with the Penn State/NCAR MM5 modeling system. Part II: Preliminary model validation: Monthly Weather Review, Vol. 129, pp. 587-604.
7. CHOW, J. C.; WATSON, J. G.; LOWENTHAL, D. H.; SOLOMON, P. A.; MAGLIANO, K.; ZIMAN, S. D.; AND RICHARDS, L. W., 1992, PM10 source apportionment in California's San Joaquin Valley: Atmospheric Environment. Vol. 26A, pp. 3335-3353.
8. CONGALTON, R. G. AND GREEN, K., 1999, Assessing the Accuracy of Remotely Sensed Data: Principles and Practices: Lewis Publishers, New York, 137 p.
9. DANIN, A. AND GANOR, E., 1997, Trapping of airborne dust by Eig's meadowgrass (Poa eigii) in the Judean Desert, Israel: Journal Arid Environments, Vol. 35, pp. 77-86.
10. DONNAY, J. P.; BARNSLEY, M. J.; AND LONGLEY, P. A., 2001, Remote sensing and urban analysis. In Donnay, J. P.; Barnsley, M. J.; and Longley, P. A. (Editors), Remote Sensing and Urban Analysis: Taylor and Francis, London, pp. 3-18.
11. ERDAS, 1999, ERDAS Field Guide, 5th ed.: ERDAS, Inc., Atlanta, GA, 672 p.
12. EZEAMUZIE, C. I.; BEG, M. U.; AND AL-AJMI, D., 1998, Responses of alveolar macrophages to post- Gulf-War airborne dust from Kuwait: Environment International, Vol. 24, pp. 213-220.
13. FOODY, G. M., 2000, Estimation of sub-pixel land cover composition in the presence of untrained classes: Computers Geosciences, Vol. 26, pp. 469-478.
14. GANSTER, P.; SWEEDLER, A.; AND CLEMENT, N., 2000, Development, growth, and the future of the border environment. In Ganster, P. (Editor), The U.S.-Mexican Border Environment: A Road Map to a Sustainable 2020: San Diego State University Press, San Diego, CA, pp. 73-103.
15. GEOSYSTEMS GMBH, 1999, ATCOR2 for ERDAS Imagine User Manual: Germering, Germany, 81 p.
16. GÓMEZ, B.; GÓMEZ, M.; SANCHEZ, J. L.; FERNÁNDEZ, R.; AND PALACIOS, M. A., 2001, Platinum and rhodium distribution in airborne particulate matter and road dust: Science Total Environment, Vol. 269, pp. 131-144.
17. GONG, P. AND HOWARTH, P. J., 1990, The use of structural information for improving land-cover classification accuracies at the rural-urban fringe: Photogrammetric Engineering Remote Sensing, Vol. 56, pp. 67-73.
18. HARRIS, P. M. AND VENTURA, S. J., 1995, The integration of geographic data with remotely sensed imagery to improve classification in an urban area: Photogrammetric Engineering Remote Sensing, Vol. 61, pp. 993-998.
19. HEISLER, S.; BALENTINE, H.; BRADLEY, L.; AND GARCIA, M., 1999, Ambos Nogales Hazardous Air Pollution and Particulate Matter Air Quality Study Final Report: Arizona Department of Environmental Quality Document 0493-016-300, Phoenix, AZ, 421 p.
20. HUETE, A. R., 1988, A soil-adjusted vegetation index (SAVI): Remote Sensing Environment, Vol. 25, pp. 295-309.
21. IRISH, R., 1998, Landsat 7 Data Users Handbook: Goddard Space Flight Center, MD: http://ltpwww.gsfc.nasa.gov/IAS/handbook/ handbook_toc.html
22. IRONS, J. R. AND PETERSEN, G. W., 1981, Texture transforms of remote sensing data: Remote Sensing Environment. Vol. 11, pp. 359-370.
23. ISKANDER, F. Y.; VEGA-CARRILLO, H. R.; AND MANZANARES-ACUNA, E., 1997, Elemental analysis of air dust from Zacatecas City, Mexico: Environment International, Vol. 23, pp. 497-506.
24. JENSEN, J. R., 1996, Introductory Image Processing: A Remote Sensing Perspective, 2nd ed.: Prentice-Hall, Upper Saddle River, NJ, 318 p.
25. KAHLE, A. B.; PALLUCONI, F. D.; AND CHRISTENSEN, P. R., 1993, Thermal emission spectroscopy: Application to Earth and Mars. In Pieters, C. M. and Englert, P. A. J. (Editors), Remote Geochemical Analysis: Elemental and Mineralogical Composition: Cambridge University Press, New York, pp. 99-120.
26. LANCASTER, N. AND NICKLING, W. G., 1994, Aeolian sediment transport. In Abrahams, A. D. and Parsons, A. J. (Editors), Geomorphology of Desert Environments: Chapman & Hall, London, pp. 447-473.
27. MACMAHON, J. A., 1988, Warm deserts, In Barbour, M. G. and Billings, W. D. (Editors), North American Terrestrial Vegetation: Cambridge University Press, New York, pp. 231-264.
28. MIGUEL, A. G.; CASS, G. R.; GLOVSKY, M. M.; AND WEISS, J., 1999, Allergens in paved road dust and airborne particles: Environmental Science Technology, Vol. 33, pp. 4159-4168.
29. NIEUWENHUUSEN, M. J.; NODERER, K. S.; SCHENKER, M. B.; VALLYATHAN, V.; AND OLENCHOCK, S., 1999, Personal exposure to dust, endotoxin, and crystalline silica in California agriculture: Annals Occupational Hygiene, Vol. 43, pp. 35-42.
30. PÉWÉ, T. L.; PÉWÉ, E. A.; PÉWÉ, R. H.; JOURNAUX, A.; AND SLATT, R. M., 1981, Desert dust: Characteristics and rates of deposition in central Arizona. In Desert Dust: Origins, Characteristics, and Effects of Man: Geological Society of America Special Paper 186, pp. 169-190.
31. RIDD, M. K., 1995, Exploring a V-I-S (vegetation-impervious surface- soil) model for urban ecosystem analysis through remote sensing: Comparative anatomy for cities: International Journal Remote Sensing, Vol. 16, pp. 2165-2185.
32. SABINS, F. F., 1997, Remote Sensing: Principles and Interpretation, 3rd ed.: W.H. Freeman and Company, New York, 494 p.
33. SCHEFFE, R. D. AND MORRIS, R. E., 1993, A review of the development and application of the Urban Airshed Model: Atmospheric Environment, Vol. 27B, pp. 23-39.
34. SIMCOX, N. J.; FENSKE, R. A.; WOLZ, S. A.; LEE, I.-C.; AND KALMAN, D. A., 1995, Pesticides in household dust and soil: Exposure pathways for children of agricultural families: Environmental Health Perspectives, Vol. 103, pp. 1126-1134.
35. STEFANOV, W. L.; RAMSEY, M. S.; AND CHRISTENSEN, P. R., 2001, Monitoring urban land cover change: An expert system approach to land cover classification of semiarid to arid urban centers: Remote Sensing Environment, Vol. 77, pp. 173-185.
36. STUCKENS, J.; COPPIN, P. R.; AND BAUER, M. E., 2000, Integrating contextual information with per-pixel classification for improved land cover classification: Remote Sensing Environment, Vol. 71, pp. 282-296.
37. TRIETZ, P. M., 1992, Application of satellite and GIS technologies for land-cover and land-use mapping at the rural-urban fringe: A case study: Photogrammetric Engineering Remote Sensing, Vol. 58, pp. 439-448.
38. VOGELMANN, J. E.; SOHL, T.; AND HOWARD, S. M., 1998, Regional characterization of land cover using multiple sources of data: Photogrammetric Engineering Remote Sensing, Vol. 64, pp. 45-57.
39. ZHU, G. AND BLUMBERG, D. G., 2002, Classification using ASTER data and SVM algorithms: The case study of Beer Sheva, Israel: Remote.Sensing.Environment, Vol. 80, pp. 233-240.