Skip to main content
SpringerLink
Log in

Optical Remote Sensing

  • Chapter
  • First Online:
Environmental Geoinformatics

Part of the book series: Environmental Science and Engineering ((ENVSCIENCE))

Abstract

There are a large variety of systems for collecting remotely sensed data in operation today. Ramapriyan [1] asserts these can be categorized in several ways according.

It is not knowledge, but the act of learning, not possession but the act of getting there, which grants the greatest enjoyment.

—Carl Friedrich Gauss (1777–1855)

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 139.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 179.99
Price excludes VAT (USA)
  • Durable hardcover 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

Notes

  1. 1.

    All the tabulated sensors are passive, except RADARSAT and LiDAR that are active sensors.

References

  1. Ramapriyan HK (2002) Satellite imagery in earth science applications. In: Castelli V, Bergman LD (eds) Image databases: search and retrieval of digital imagery. Wiley, New York

    Google Scholar 

  2. Kiema JBK (2001) Multi-source data fusion and image compression in urban remote sensing. Doctor of Engineering. Dissertation. University of Karlsruhe. Shaker Verlag, 130pp, ISBN3-8265-9312-X

    Google Scholar 

  3. Jensen JR (2005) Introductory digital image processing: a remote sensing perspective, 3rd edn. Prentice-Hall, Upper Saddle River, NJ

    Google Scholar 

  4. Joseph G (2000) How well do we understand Earth observation electro-optical sensor parameters? ISPRS J Photogram Remote Sens 55:9–12

    Article  Google Scholar 

  5. Bähr H-P, Vögtle T (eds) (1998) Erderkundungssatelliten und ihre Produkte. Digitale Bildverarbeitung, vol 3. Wichmann Verlag, Heidelberg, pp 29–43

    Google Scholar 

  6. Forshaw MRB, Haskell A, Miller PF, Stanley DJ, Townshend JRG (1983) Spatial resolution of remotely sensed imagery: a review paper. Int J Remote Sens 4(3):497–520

    Article  Google Scholar 

  7. Kumi-Boateng B (2012) A spatio-temporal based estimation of vegetation changes in the Tarkwa mining area of Ghana. Doctor of Philosophy. Dissertation. University of Mines and Technology, Ghana, 165pp

    Google Scholar 

  8. Phinn SR (1998) A framework for selecting appropriate remote sensed data dimensions for environmental monitoring and management. Int J Remote Sens 19:3457–3463

    Article  Google Scholar 

  9. Weng Q (2010) Remote sensing and GIS integration: theories, methods, and applications. McGraw-Hill, 416p

    Google Scholar 

  10. Quattrochi DA, Goodchild MF (1997) Scale in remote sensing and GIS. Lewis Publishers, New York

    Google Scholar 

  11. Campbell JB (2007) Introduction to remote sensing, 4th edn. Guilford Press, New York

    Google Scholar 

  12. Fritz LW (1996) The era of commercial earth observation satellites. Photogram Eng Remote Sens 1:39–45

    Google Scholar 

  13. Aplin P, Atkinson PM, Curran PJ (1997) Fine spatial resolution satellite sensors for the next decade. Int J Remote Sens 18:3873–3881

    Article  Google Scholar 

  14. Murai S (2004) Remote sensing and GIS courses—distance education. Japan International Cooperation Agency (JICA)-Net

    Google Scholar 

  15. Guelman M, Ortenberg F (2009) Small satellite’s role in future hyperspectral earth observation missions. Acta Astronaut 64:1252–1263

    Article  Google Scholar 

  16. Kramer HJ, Cracknell A (2008) An overview of small satellites. Int J Remote sens 29:4285–4337

    Article  Google Scholar 

  17. Xue Y, Li Y, Guang J, Zhang X, Guo J (2008) Small satellite remote sensing applications—history, current and future. Int J Remote Sens 29:4339–4372

    Article  Google Scholar 

  18. McCoy R (2005) Field methods in remote sensing. The Guilford Press, New York, p 158p

    Google Scholar 

  19. Ho C, Robinson A, Millerm D, Davis M (2005) Overview of sensors and needs for environmental monitoring. Sensors 5:4–37

    Article  Google Scholar 

  20. Kussul N, Shelestov A, Skakun S (2009) Grid and sensor web technologies for environmental monitoring. Earth Sci Inf 2(1–2):37–51

    Article  Google Scholar 

  21. Porter J, Arzberger P, Braun H, Brynat P, Gage S, Hansen T, Lin C, Lin F, Kratz T, Michener W, Shapiro S, Williams T (2005) Wireless sensor networks for ecology. BioScience 55:561–572

    Article  Google Scholar 

  22. Congalton R, Green K (2009) Assessing the accuracy of remotely sensed data: principles and practices. Taylor & Francis Group

    Google Scholar 

  23. Devillers R, Jeansoulin R (eds) (2006) Fundamentals of spatial data quality. ISTE Ltd, London

    Google Scholar 

  24. Groot R, McLaughlin J (eds) (2000) Geospatial data infrastructure: concepts, cases and good practice. Oxford University Press, Oxford

    Google Scholar 

  25. Schiewe J (1998) Experiences from the MOMS-02-Project for Future Developments. Int Arch Photogram Remote Sens 32:533–539

    Google Scholar 

  26. Ackermann F (1999) Airborne laser scanning present status and future expectations. ISPRS J Photogram Remote Sens 54:64–67

    Article  Google Scholar 

  27. Alharthy A, Bethel J (2002) Heuristic filtering and 3D feature extraction from LIDAR data. In: International archives of photogrammetry and remote sensing (IAPRS), Graz, Austria, vol XXXIV, part 3A, pp 29–34

    Google Scholar 

  28. Baltsavias E (1999) A comparison between photogrammetry and laser scanning. ISPRS J Photogram Remote Sens 54:83–94

    Article  Google Scholar 

  29. Brunn A, Weidner U (1997) Extracting buildings from digital surface models. Int Arch Photogram Remote Sens 32:27–34

    Google Scholar 

  30. Clode S, Rottensteinerb F, Kootsookosc P, Zelniker E (2007) Detection and vectorization of roads from LiDAR data. Photogram Eng Remote Sens 73:517–535

    Article  Google Scholar 

  31. Forlani G, Nardinocchi C, Scaioni M, Zingaretti P (2006) Complete classification of raw LiDAR data and 3D reconstruction of buildings. Pattern Anal Appl 8:357–374

    Article  Google Scholar 

  32. Haala N, Brenner C (1999) Extraction of buildings and trees in urban environments. ISPRS J Photogram Remote Sens 54:130–137

    Article  Google Scholar 

  33. Kokkas N (2005) City modeling and building reconstruction with Socet Set v.5.2 BAE Systems. Customer presentation at the 2005 GXP Regional User Conference. Cambridge, England, pp 19–21

    Google Scholar 

  34. Konecny G (2003) Geoinformation: remote sensing, photogrammetry, geographic information systems. Taylor and Francis, London

    Book  Google Scholar 

  35. Lee DH, Lee KM, Lee SU (2008) Fusion of LiDAR and imagery for reliable building extraction. Photogram Eng Remote Sens 74:215–225

    Article  Google Scholar 

  36. Liu X (2008) Airborne LiDAR for DEM generation: some critical issues. Prog Phys Geogr 32(1):31–49. https://doi.org/10.1177/0309133308089496

    Article  Google Scholar 

  37. Ma R (2005) DEM generation and building detection from Lidar data. Photogram Eng Remote Sens 71(7):847–854

    Article  Google Scholar 

  38. Miliaresis G, Kokkas N (2007) Segmentation and object-based classification for the extraction of the building class from LiDAR DEMs. Comput Geosci 33:1076–1087

    Article  Google Scholar 

  39. Popescue SC, Wynne RH, Nelson RF (2003) Measuring individual tree crown diameter with LiDAR and assessing its influence on estimating forest volume and biomass. Can J Remote Sens 29:564–577

    Article  Google Scholar 

  40. Renslow M, Greenfield P, Guay T (2000) Evaluation of multi-return LiDAR for forestry applications. Project Report for the Inventory and Monitoring Steering Committee, RSAC-2060/4810-LSP-0001-RPT1

    Google Scholar 

  41. Schenk T, Csatho B (2002) Fusion of LIDAR data and aerial imagery for a more complete surface description. Arch Photogram

    Google Scholar 

  42. Secord J, Zakhor A (2007) Tree detection in urban regions using aerial lidar and image data. IEEE Geosci Remote Sens Lett 4:196–200

    Article  Google Scholar 

  43. Sohn G, Dowman I (2005) Data fusion of high-resolution satellite imagery and LiDAR data for automatic building extraction. ISPRS J Photogram Remote Sens 62(1):43–63

    Article  Google Scholar 

  44. Voss M, Sugumaran R (2008) Seasonal effect on tree species classification in an urban environment using hyperspectral data, LiDAR, and an object-oriented approach. Sensors 8:3020–3036

    Article  Google Scholar 

  45. Webster TL, Forbes DL, Dickie S, Shreenan R (2004) Using topographic LiDAR to map flood risk from storm-surge events for Charlottetown, Prince Edward Island, Canada. Can J Remote Sens 30:64–76

    Article  Google Scholar 

  46. Zhang Y, Xie P, Li H (2007) An online colour 2D and 3D image system for disaster management. In: Li J, Zlatanova S, Fabbri A (eds) Geomatics solutions for disaster management. Lecture notes in geoinformation and cartography. Springer, Berlin, pp 1–15

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Spatial Sciences, Curtin University, Perth, WA, Australia

    Joseph Awange

  2. Department of Geospatial and Space Technology, University of Nairobi , Nairobi, Kenya

    John Kiema

Authors
  1. Joseph Awange
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. John Kiema
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Joseph Awange .

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Awange, J., Kiema, J. (2019). Optical Remote Sensing. In: Environmental Geoinformatics. Environmental Science and Engineering(). Springer, Cham. https://doi.org/10.1007/978-3-030-03017-9_8

Download citation

Publish with us

Policies and ethics

Search

Navigation