Skip to main content
SpringerLink
Log in

Integration of Remotely Sensed Data into Geographical Information Systems

  • Chapter
Remote Sensing in Hydrology and Water Management

  • 1048 Accesses

Abstract

Remotely sensed data and information derived from them have a wide range of applications in hydrology and water resources management (Schultz, 1988; Engman and Gurney, 1991). Remote sensing and its associated image processing technology provide access to spatial and temporal information on watershed, regional, continental and global scales. Further, new sensors and imaging technology are increasing the capability of remote sensing to acquire information at a variety of spatial and temporal scales. Management and efficient utilization of such information is going to be one of the major challenges of the coming decade. With the advent of space programs such as the Earth Observing System (EOS), this problem is going to become even more complex especially because a variety of new sensors are employed to cover the full range of the electromagnetic spectrum. Effective utilization of this large spatial data volume is dependent upon existence of an efficient, geographic handling and processing system that will transform these data into usable information. A major tool for handling spatial data is the Geographical Information System (GIS).

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 109.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 139.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  • Bailey, R. G. (1988). Problems with using overlay mapping for planning and their implications for geographic information systems. Environmental Management, 12(1), 11–17.

    Article  Google Scholar 

  • Buehler, K., and McKee, L. (eds.) (1998). The OpenGIS Guide - Introduction to Interoperable Geoprocessing and the OpenGIS Specification. The Open GIS Consortium.

    Google Scholar 

  • Burrough, P. A. (1990). Principles of geographical information systems for land resources assessment. (Oxford: Clarendon).

    Google Scholar 

  • Conese, C., Maraechi, G., Maselli, F., Romani, M., and Bottai, L. (1992). Integration of remotely sensed data into a GIS for the assessment of land suitability. EARSeL Advances in Remote Sensing, 1,173–179.

    Google Scholar 

  • Crapper, P. F. (1980). Errors incurred in estimating an area of uniform land cover using Landsat. Photogrammetric Engineering and Remote Sensing, 46(10), 1295–1301.

    Google Scholar 

  • Djokic, D., and Maidment, D. R. (1991). Terrain analysis for stormwater modeling. Hydrological Processes, 5(1), 115–124.

    Article  Google Scholar 

  • Dubayah, R. (1992). Estimating net solar radiation using Landsat Thematic Mapper and digital elevation data. Water Resources Research, 28(9), 2469–2484.

    Article  Google Scholar 

  • Ehlers, M., Edwards, G., and Bedard, Y. (1989). Integration of remote sensing with geographic information systems: A necessary evolution. Photogrammetric Engineering and Remote Sensing, 55(11), 1619–1627.

    Google Scholar 

  • Eckhardt, D. W., Verdin, J. P., and Lyford, G. R. (1990). Automated update of an irrigated lands GIS using SPOT HRV imagery. Photogrammetric Engineering and Remote Sensing, 56(11), 1515–1522.

    Google Scholar 

  • Engman, E. T., and Gurney, R. J. (1991). Remote sensing in hydrology. (London: Chapman and Hall).

    Google Scholar 

  • ESRI (1991). ARC/INFO Version 6.0 Data Conversion User’s Manual. Environmental Systems Research Institute, Redlands, California.

    Google Scholar 

  • Evans, B. M., and Myers, W. L. (1990). A GIS-based approach to evaluating regional groundwater pollution potential with DRASTIC. Journal of Soil and Water Conservation, 45(2), 242–245.

    Google Scholar 

  • Fett, W., Neumann, P., and Schultz, G. A. (1990). Hydrological model based on satellite imagery and GIS. Proce. Int. Symp. on Remote Sensing and Water Resources (Enschede, The Netherlands), 347–357.

    Google Scholar 

  • Frolov, Y. S., and Maling, D. H. (1969). The accuracy of area measurement by point counting techniques. Cartographic Journal, 6(1), 21–35.

    Google Scholar 

  • Fulford, M. C. (1981). The fastrak automatic digitizing for line drawings. International Journal of Pattern Recognition, 14,65–72.

    Article  Google Scholar 

  • Goodenough, D. G. (1988). Thematic Mapper and SPOT integration with a geographic information system. Photogrammetric Engineering and Remote Sensing, 54(2), 167–176.

    Google Scholar 

  • Goodenough, D. G., Goldberg, M., Plunkett, G., and Zelek, J. (1987). An expert system for remote sensing. IEEE Transactions on Geoscience and Remote Sensing, 25,349–359.

    Article  Google Scholar 

  • Greene, R. G., and Cruise, J. F. (1996) Development of a geographic information system for urban watershed analysis. Photogrammetric Engineering and Remote Sensing, 62(7), 863–870.

    Google Scholar 

  • Gugan, D. J., and Dowman, I. J. (1988). Accuracy and completeness of topographic mapping from SPOT imagery. Photogrammetric Record, 12(72), 787–796.

    Article  Google Scholar 

  • Jurgens, C., and Fander, M. (1993). Soil erosion assessment and simulation by means of SGEOSand ancillary digital data. International Journal of Remote Sensing, 14(15), 2847–2855.

    Article  Google Scholar 

  • Johnson, L. E. (1989). MAPHYD - A digital map based hydrologic modeling system. Photogrammetric Engineering and Remote Sensing, 55(6), 911–917.

    Google Scholar 

  • Kim, K., and Ventura, S. (1993). Large-scale modeling of urban nonpoint source pollution using a geographical information system. Photogrammetric Engineering and Remote Sensing, 59(10), 1539–1544.

    Google Scholar 

  • Langran, G. (1992). Time in GIS. Taylor and Francis, New York.

    Google Scholar 

  • Lunetta, R. S., Congalton, R. G., Fenstermaker, L. K., Jensen, J. R., McGwire, K. C., and Tinney, L. R. (1991). Remote sensing and geographic information system data integration: error sources and research issues. Photogrammetric Engineering and Remote Sensing, 57,677–687

    Google Scholar 

  • MacDougall, E. B. (1975). The accuracy of map overlays. Landscape Planning, 2,23–30.

    Article  Google Scholar 

  • Maidment, D. R. (1993). GIS and hydrologic modeling. In: Goodchild, M., Parks, B., and Steyaert. L. (eds.) Environmental Modeling with GIS, Oxford University Press, New York, 147–167.

    Google Scholar 

  • Mattikalli, N. M., Engman, E. T., Jackson, T. J., and Ahuja, L. R. (1998). Microwave remote sensing of temporal variations of brightness temperature and near-surface soil water content during a watershed-scale field experiment, and its application to the estimation of soil physical properties. Water Resources Research, 34(9), 2289–2299.

    Article  Google Scholar 

  • Mattikalli, N. M. (1995). Integration of remotely sensed raster data with vector based geographical information system for land-use change detection. International Journal of Remote Sensing, 16(15), 2813–2828.

    Article  Google Scholar 

  • Mattikalli, N. M., Devereux, B. J., and Richards, K. S. (1995). Integration of remotely sensed satellite images with a geographical information system. Computers and Geosciences, 21(8), 947–956.

    Article  Google Scholar 

  • Mattikalli, N. M., Devereux, B. J., and Richards, K. S. (1996). Prediction of river discharge and surface water quality using an integrated geographical information system approach. International Journal of Remote Sensing, 17(4), 683–701.

    Article  Google Scholar 

  • McKeown, D. (1987). The role of artificial intelligence in the integration of remotely sensed data with geographic information systems. IEEE Transactions on Geoscience and Remote Sensing, 25, 330–348.

    Article  Google Scholar 

  • Michalak, W. Z. (1993). GIS in land use change analysis: integration of remotely sensed data into GIS. Applied Geography, 13,28–44.

    Article  Google Scholar 

  • Mitasova, H., Hofierka J., Zlocha, M., and Iverson, L. (1996). Modeling topographic potential for erosion and deposition using GIS. International Journal of Geographical Information Systems, 10(5), 629–641.

    Google Scholar 

  • Moeller, R. A. (1991). Application of a geographic information system to hydrologic modeling using HEC-1. In: Stafford, D. B. (ed.) Civil Engineering applications of remote sensing and GIS, ASCE, 269–277.

    Google Scholar 

  • Molenaar, M., and Janssen, L. L. F. (1992). Integrated processing of remotely sensed and geographic data for land inventory purposes. EARSeL Advances in Remote Sensing, 1,113–121.

    Google Scholar 

  • Muzik, I., and Chang, C. (1993). Flood simulation assisted by a GIS. IAHS Publication no. 211, 531–539.

    Google Scholar 

  • Newcomer, J. A., and Szajgin, J. (1984). Accumulation of thematic map errors in digital overlay analysis. American Cartographer, 11, 58–62.

    Article  Google Scholar 

  • Osmond, D. L., Gannon, R. W., Gale, J. A., Line, D. E., Knott, C. B., Phillips, K. A., Turner, M. H., Foster, M. A., Lehning, D. E., Coffey, S. W., and Spooner, J. (1997). WATERSHEDSS: A decision support system for watershed-scale nonpoint source water quality problems. Journal of American Water Resources Association, 33(2), 327–341.

    Article  CAS  Google Scholar 

  • Ott, M., Su, Z., Schumann, A. H., and Schultz, G. A. (1991). Development of a distributed hydrological model for flood forecasting and impact assessment of landuse change in the international Mosel basin. IAHS Publication no. 201.

    Google Scholar 

  • Pelletier, R. E. (1985). Evaluating non-point pollution using remotely sensed data in soil erosion models. Journal of Soil Water Conservation, 40, 332–335.

    Google Scholar 

  • Peuquet, D. J. (1984). A conceptual framework and comparison of spatial data models. Cartographica, 21(4), 66–113.

    Google Scholar 

  • Piwowar, J. M., LeDrew, E. F., and Dudycha, D. J. (1990). Integration of spatial data in vector and raster formats in a geographic information system environment. International Journal of Geographical Information Systems, 4,429–444.

    Article  Google Scholar 

  • Renard, G. K., Foster, G. R., Weesies, G. A., Porter, J. P. (1991). RUSLE-Revised universal soil loss equation. Journal of Soil Water Conservation, 46,30–33.

    Google Scholar 

  • Romanowicz, R. Beven, K., and Freer, J. (1993). TOPMODEL as an application module within WIS. IAHS Publication no. 211,211–223.

    Google Scholar 

  • Schultz, G. A. (1988). Remote sensing in hydrology. Journal of Hydrology, 100,239–265.

    Article  Google Scholar 

  • Schultz, G. A. (1993). Application of GIS and remote sensing in hydrology. IAHS Publication No. 211,127–140.

    Google Scholar 

  • Schultz, G. A. (1994). Meso-scale modeling of runoff and water balances using remote sensing and other GIS data. Hydrological Sciences Journal, 39(2), 121–142.

    Article  Google Scholar 

  • Sircar, J. K., Ragan, R. M., Engman, E. T., and R. A. Fink (1991). A GIS based geomorphic approach for the computation of time-area curves. In: Stafford, D. B. (ed.) Civil Engineering applications of remote sensing and GIS, ASCE, 287–296.

    Google Scholar 

  • Srinivasan, R., and Engel, B. A. (1994). A spatial decision support system for assessing agricultural nonpoint source pollution. Water Resources Bulletin, 30(3), 441–462.

    Google Scholar 

  • Su, Z., Neumann, P., Fett, W., Schumann, A., and Schultz, G. A. (1992). Application of remote sensing and geographical information system in hydrological modeling. EARSeL Advances in Remote Sensing, 1(3), 180–185.

    Google Scholar 

  • Swann, R., Hawkins, D., Westwell-Roper, A., and Johnstone, W. (1988). The potential for automated mapping from geocoded digital image data. Photogrammetric Engineering and Remote Sensing, 54(2), 187–193.

    Google Scholar 

  • Switzer, P. (1975). Estimation of the accuracy of qualitative maps. In: Davis and MacCullagh (eds.). Display and analysis of spatial data by), Wiley, New York, 1–13.

    Google Scholar 

  • USDA (United States Department of Agriculture) (1972). National Engineering Handbook. Soil Conservation Service. (Washington, DC: Government Printing Press).

    Google Scholar 

  • van der Laan, F. B. (1992). Integration of remote sensing in a raster and vector GIS environment. EARSeL Advances in Remote Sensing, 1, 71–80.

    Google Scholar 

  • Vieux, B. E. (1991). Geographic information systems and non-point source water quality and quantity modelling. Hydrological Processes, 5,101–113.

    Article  Google Scholar 

  • Walsh, S. J., Lightfoot, D. R., Butler, D. R. (1987). Recognition and assessment of error in geographic information systems. Photogrammetric Engineering and Remote Sensing, 53, 1423–1430.

    Google Scholar 

  • Wang, F., and Newkirk, R. T. (1987). Design and implementation of a knowledge based system for remotely change detection. Journal of Imaging Technology, 13,116–122.

    Google Scholar 

  • Welch, R., and Ehlers, M. (1988). Cartographic feature extraction from integrated SIR-B and Landsat TM images. International Journal of Remote Sensing, 9(5), 873–889.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Cambridge Research Associates, 1430 Spring Hill Road, Suite 200 McLean, Virginia, 22102, USA

    Nandish M. Mattikalli

  2. NASA-Goddard Space Flight Center, 20771, Greenbelt, MD, USA

    Edwin T. Engman

Authors
  1. Nandish M. Mattikalli
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Edwin T. Engman
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Lehrstuhl für Hydrologie, Wasserwirtschaft und Umwelttechnik, Ruhr-Universität Bochum, 44780, Bochum, Germany

    Gert A. Schultz

  2. NASA/Goddard Space Flight Center, Greenbelt, MD, USA

    Edwin T. Engman

Rights and permissions

Reprints and permissions

Copyright information

© 2000 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Mattikalli, N.M., Engman, E.T. (2000). Integration of Remotely Sensed Data into Geographical Information Systems . In: Schultz, G.A., Engman, E.T. (eds) Remote Sensing in Hydrology and Water Management. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-59583-7_4

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-59583-7_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-64036-0

  • Online ISBN: 978-3-642-59583-7

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics

Search

Navigation