Review of High Resolution Thermal Infrared Applications and Requirements: The Fuegosat Synthesis Study

  • José A. Sobrino
  • Fabio Del Frate
  • Matthias Drusch
  • Juan C. Jiménez-Muñoz
  • Paolo Manunta
Chapter
Part of the Remote Sensing and Digital Image Processing book series (RDIP, volume 17)

Abstract

High resolution thermal infrared remote sensing can have a wide range of applications. In this chapter we describe the different applications and requirements identified after a revision study in the framework of the Fuegosat Synthesis Study (FSS). This project was funded by the European Space Agency (ESA), and the three main objectives were: (i) review of applications and analyses for user requirements, (ii) consolidation of user requirements over a broad range of applications, and (iii) matching of user requirements and industry concepts to identify and outline a set of potential mission scenarios and their corresponding requirements. This chapter focuses on issues (i) and (ii). These objectives were achieved by means of integrated studies within literature and ancillary documentation, and also by consultation of external experts. As a result, more than 30 applications were identified within three different fields: (i) Land and Solid Earth, (ii) Health and Hazards and (iii) Security and Surveillance. A complete set of requirements (spatial, temporal, and radiometric resolution, algorithms used, supporting data, among others) were also provided.

Keywords

Land Surface Temperature User Requirement European Space Agency Wildland Fire Urban Heat Island Effect 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. Barret B, Turquety S, Hurtmans D, Clerbaux C, Hadji-Lazaro J, Bey I, Auvray M, Coheur PF (2005) Global carbon monoxide vertical distributions from spaceborne high-resolution FTIR nadir measurements. Atmos Chem Phys 5:2901–2914CrossRefGoogle Scholar
  2. Bassani C, Cavalli RM, Cavalcante F, Cuomo V, Palombo A, Pascucci S, Pignatti S (2007) Deterioration status of asbestos-cement roofing sheets assessed by analyzing hyperspectral data. Remote Sens Environ 109:361–378CrossRefGoogle Scholar
  3. Beck LR, Bradley ML, Wood BL (2000) Remote sensing and human health: new sensor and new opportunities. Emerg Infect Dis 6(3):217–225CrossRefGoogle Scholar
  4. Billa L, Mansor S, Mahmud AR, Ghazali AH (2006) Modelling rainfall intensity from NOAA AVHRR data for operational flood forecasting in Malaysia. Int J Remote Sens 27(23):5225–5234CrossRefGoogle Scholar
  5. Blair R, Blair-Fitzharris B, Richards K (2002) Interpolation of growing degree-days in non-homogeneous terrain. The 14th annual colloquium of the Spatial Information Research Centre University of Otago, Dunedin, New ZealandGoogle Scholar
  6. Bowman KW, Rodgers CD, Kulawik SS, Worden J, Sarkissian E, Osterman G, Steck T, Lou M, Eldering A, Shephard M, Worden H, Lampel M, Clough S, Brown P, Rinsland C, Gunson M, Beer R (2006) Tropospheric emission spectrometer: retrieval method and error analysis. IEEE Trans Geosci Remote Sens 44:1297–1307CrossRefGoogle Scholar
  7. CEOS (2003) The use of earth observing satellites for hazard support: assessments and scenarios. Final report of the CEOS Disaster Management Support Group (DMSG), NovemberGoogle Scholar
  8. Chrysoulakis N (2002) Thermal detection of plumes produced by industrial accidents in urban areas based on the presence of the heat island. Int J Remote Sens 23(14):2909–2916CrossRefGoogle Scholar
  9. Chrysoulakis N, Cartalis C (2003) A new algorithm for detection of plumes caused by industrial accidents, based on NOAA/AVHRR imagery. Int J Remote Sens 24(17):3353–3367CrossRefGoogle Scholar
  10. Chrysoulakis N, Adaktylou N, Cartalis C (2005) Detecting and monitoring plumes caused by major industrial accidents with JPLUME, a new software tool for low-resolution image analysis. Environ Modell Softw 20:1486–1494CrossRefGoogle Scholar
  11. Corradini S, Pugnaghi S, Teggi S, Buongiorno MF, Bogliolo MP (2003) Will ASTER see the Etna SO2 plume? Int J Remote Sens 24(6):1207–1218CrossRefGoogle Scholar
  12. Duchemin B, Goubier J, Courrier G (1999) Monitoring phenological key stages and cycle duration of temperate deciduous forest ecosystems with NOAA/AVHRR data. Remote Sens Environ 67:68–82CrossRefGoogle Scholar
  13. Emch M, Feldacker C, Yunus M, Streatfield PK, Vu DT, Cahn DG, Alí M (2008) Local environmental predictors of cholera in Bangladesh and Vietnam. Am J Trop Med Hyg 78(5):823–832Google Scholar
  14. Feidas HN, Cartalis C, Cracknell AP (2000) Use of Meteosat imagery to define clouds linked with floods in Greece. Int J Remote Sens 21(5):1047–1072CrossRefGoogle Scholar
  15. Fisher JB, Tu K, Baldocchi DD (2008) Global estimates of the land–atmosphere water flux based on monthly AVHRR and ISLSCP-II data, validated at 16 FLUXNET sites. Remote Sens Environ 112:901–919CrossRefGoogle Scholar
  16. Gao Y, Mas JF, Maathuis BHP, Zhang X, Van Dijk PM (2006) Comparison of pixel-based and object-oriented image classification approaches – a case study in a coal fire area, Wuda, Inner Mongolia, China. Int J Remote Sens 27(18):4039–4055CrossRefGoogle Scholar
  17. Gao Y, Kerle N, Mas JF (2009) Object-based image analysis for coal fire-related land cover mapping in coal mining areas. Geocarto Int 24(1):25–36CrossRefGoogle Scholar
  18. Gemperli A, Vounatsou P, Anderegg D, Pluschke G (2004) EPIDEMIO: Earth observation in epidemiology. In: Proceedings of the 2004 Envisat & ERS Symposium, Salzburg, Austria, 6–10 Sept 2004 (ESA SP-572, April 2005), http://www.epidemio.info
  19. Giglio L, Loboda T, Roy DP, Quayle B, Justice CO (2009) An active-fire based burned area mapping algorithm for the MODIS sensor. Remote Sens Environ 113(2):408–420CrossRefGoogle Scholar
  20. Gil AI, Louis VR, Rivera ING, Lipp E, Huq A, Lanata CF (2004) Occurrence and distribution of Vibrio cholerae in the coastal environment of Peru. Environ Microbiol 6:699–706CrossRefGoogle Scholar
  21. Green RM, Hay SI (2002) The potential of Pathfinder AVHRR data for providing surrogate climatic variables across Africa and Europe for epidemiological applications. Remote Sens Environ 79:166–175CrossRefGoogle Scholar
  22. Harris AJL, Rose WI, Flynn LP (2003) Temporal trends in lava dome extrusion at Santiaguito 1922–2000. Bull Volcanol 65:77–89Google Scholar
  23. Hassan Q, Bourque CPA, Meng FR, Richards W (2007a) Spatial mapping of growing degree days: an application of MODIS-based surface temperatures and enhanced vegetation index. J Appl Remote Sens 1(1):013511CrossRefGoogle Scholar
  24. Hassan Q, Bourque CPA, Meng FR (2007b) Application of Landsat-7 ETM+and MODIS products in mapping seasonal accumulation of growing degree days at an enhanced resolution. J Appl Remote Sens 1(1):013539CrossRefGoogle Scholar
  25. Herbreteau V, Salem G, Souris M, Hugot JP, Gonzalez JP (2007) Thirty years of use and improvement of remote sensing, applied to epidemiology: from early promises to lasting frustration. Health Place 13:400–403CrossRefGoogle Scholar
  26. Jia L, Xi G, Liu S, Huang C, Yan Y, Liu G (2009) Regional estimation of daily to annual regional evapotranspiration with MODIS data in the Yellow River Delta wetland. Hydrol Earth Syst Sci 13:1775–1787CrossRefGoogle Scholar
  27. JRC (2008) Forest fires in Europe 2008, Report no 9, Joint Research Centre. Available at http://effis.jrc.ec.europa.eu/download/forest-fires-in-europe-2008.pdf
  28. Kato S, Yamaguchi Y (2007) Estimation of storage heat flux in an urban area using ASTER data. Remote Sens Environ 110:1–17CrossRefGoogle Scholar
  29. Kuenzer C, Zhang J, Li J, Voigt S, Mehl H, Wagner W (2007) Detecting unknown coal fires: synergy of automated coal fire risk area delineation and improved thermal anomaly extraction. Int J Remote Sens 28(20):4561–4585CrossRefGoogle Scholar
  30. Lakshmi V, Schaaf K (2001) Analysis of the 1993 midwestern flood using satellite and ground data. IEEE Trans Geosci Remote Sens 39(8):1736–1743CrossRefGoogle Scholar
  31. Lobitz B, Beck L, Huq A, Wood B, Fuchs G, Faruque ASG, Colwell R (2000) Climate and infectious disease: use of remote sensing of detection of Vibrio cholerae by indirect measurement. Proc Natl Acad Sci USA 97:1438–1443CrossRefGoogle Scholar
  32. Maathuis BHP, Van Genderen JL (2004) A review of satellite and airborne sensors for remote sensing based detection of minefields and landmines. Int J Remote Sens 25(23):5201–5245CrossRefGoogle Scholar
  33. Marj A, Mobasheri MR, Valadanzouje MJ, Rezaei Y, Abaei MR (2008) Using satellite images in determination of Malaria outbreaks potential region. Nature Precedings hdl:10101/npre.2008.2325.1Google Scholar
  34. Mikkelsen SA, Olesen JE (1984) Computer-aided mapping of growing degree days for Denmark, calculated from monthly temperature normals. Acta Agr Scand 34(3):330–338CrossRefGoogle Scholar
  35. Morales CA, Anagnostou EN (2003) Extending the capabilities of high-frequency rainfall estimation from geostationary-based satellite infrared via a network of long-range lightning observations. J Hydrometeorol 4:141–159CrossRefGoogle Scholar
  36. Oppenheimer C (1998) Volcanological applications of meteorological satellites. Int J Remote Sens 19:2829–2864CrossRefGoogle Scholar
  37. Pugnaghi S, Gangale G, Corradini S, Buongiorno MF (2006) Mt. Etna sulfur dioxide flux monitoring using ASTER-TIR data and atmospheric observations. J Volcanol Geotherm Res 152:74–90CrossRefGoogle Scholar
  38. Rahman A, Kogan F, Roytman L (2006) Short report: analysis of malaria cases in Bangladesh with remote sensing data. Am J Trop Med Hyg 74(1):17–19Google Scholar
  39. Roshier DA, Rumbachs RM (2004) Broad-scale mapping of temporary wetlands in arid Australia. J Arid Environ 56:249–263CrossRefGoogle Scholar
  40. Sanchez JM, Scavone G, Caselles V, Valor E, Copertino VA, Telesca V (2008) Monitoring daily evapotranspiration at a regional scale from Landsat-TM and ETM+ data: application to the Basilicata region. J Hydrol 351:58–70CrossRefGoogle Scholar
  41. Saraf AK, Choudhury S (2005) Cover: NOAA-AVHRR detects thermal anomaly associated with the 26 January 2001 Bhuj earthquake, Gujarat, India. Int J Remote Sens 26(6):1065–1073CrossRefGoogle Scholar
  42. Sepulcre-Cantó G, Zarco-Tejada PJ, Jiménez-Muñoz JC, Sobrino JA, de Miguel E, Villalobos FJ (2006) Detection of water stress in an olive orchard with thermal remote sensing imagery. Agr Forest Meteorol 136:31–44CrossRefGoogle Scholar
  43. Sepulcre-Cantó G, Zarco-Tejada PJ, Jiménez-Muñoz JC, Sobrino JA, Soriano MA, Fereres E (2007) Monitoring yield and fruit quality parameters in open-canopy tree crops under water stress. Implications for ASTER. Remote Sens Environ 107:455–470CrossRefGoogle Scholar
  44. Shcherbak SS, Lavrova OY, Mityagina MI, Bocharova TY, Krovotyntsev VA, Ostrovskii AG (2008) Multisensor satellite monitoring of seawater state and oil pollution in the northeastern coastal zone of the Black Sea. Int J Remote Sens 29(21):6331–6345CrossRefGoogle Scholar
  45. Sobrino JA, Gomez M, Jimenez-Muñoz JC, Olioso A, Chehbouni G (2005) A simple algorithm to estimate evapotranspiration from DAIS data: application to the DAISEX campaigns. J Hydrol 315:117–125CrossRefGoogle Scholar
  46. Sobrino JA, Jiménez-Muñoz JC, Sória G, Gómez M, Barella-Ortiz A, Romaguera M, Zaragoza M, Julien Y, Cuenca J, Atitar M, Hidalgo V, Franch B, Mattar C, Ruescas A, Morales L, Gillespie A, Balick L, Su Z, Nerry F, Peres L, Libonati R (2008) Thermal remote sensing in the framework of the SEN2FLEX project: field measurements, airborne data and applications. Int J Remote Sens 29(17–18):4961–4991CrossRefGoogle Scholar
  47. Stathopoulou M, Cartalis C, Chrysoulakis N (2006) Using midday surface temperature to estimate cooling degree-days from NOAA-AVHRR thermal infrared data: an application for Athens, Greece. Sol Energy 80:414–422CrossRefGoogle Scholar
  48. Tang D, Kester DR, Wang Z, Lian J, Kawamura H (2003) AVHRR satellite remote sensing and shipboard measurements of the thermal plume from the Daya Bay, nuclear power station, China. Remote Sens Environ 84:506–515CrossRefGoogle Scholar
  49. Tramutoli V, Cuomo V, Filizzola C, Pergola N, Pietrapertosa C (2005) Assessing the potential of thermal infrared satellite surveys for monitoring seismically active areas. The case of Kocaeli (İzmit) earthquake, August 17, 1999. Remote Sens Environ 96:409–426CrossRefGoogle Scholar
  50. Tronin AA (2000) Thermal IR satellite sensor data application for earthquake research in China. Int J Remote Sens 21(16):3169–3177CrossRefGoogle Scholar
  51. Tseng WY, Chiu LS (1994) AVHRR observations of Persian Gulf oil spills. In: Proceedings of IGARSS’94, 2:779–782Google Scholar
  52. UHI Project (2009) Requirements baseline Document, pkt258-25-2.0Google Scholar
  53. Vancutsem C, Ceccato P, Dinku T, Connor SJ (2010) Evaluation of MODIS land surface temperature data to estimate air temperature in different ecosystems over Africa. Rem Sens Environ 114:449–465CrossRefGoogle Scholar
  54. Vidal A, Devaux-Ros C (1995) Evaluating forest FIRE hazard with a Landsat TM derived water stress index. Agr Forest Meteorol 77:207–224CrossRefGoogle Scholar
  55. Voogt JA, Oke TR (2003) Thermal remote sensing of urban climates. Remote Sens Environ 86:370–384CrossRefGoogle Scholar
  56. WFSC World Fire Statistics (2009) Information Bulletin of the World Statistics Centre. Available at http://www.genevaassociation.org/PDF/WFSC/GA2009-FIRE25.pdf
  57. Wright R, Flynn L, Garbeil H, Harris A, Pilger E (2002) Automated volcanic eruption detection using MODIS. Remote Sens Environ 82:135–155CrossRefGoogle Scholar
  58. Wu C, Wang Q, Yang Z, Wang W (2007) Monitoring heated water pollution of the DaYaWan nuclear power plant using TM images. Int J Remote Sens 28(5):885–890CrossRefGoogle Scholar
  59. Zhang J, Wagner W, Prakash A, Mehl H, Voigt S (2004a) Detecting coal fires using remote sensing techniques. Int J Remote Sens 25(16):3193–3220CrossRefGoogle Scholar
  60. Zhang X, Zhang J, Kuenzer C, Voigt S, Wagner W (2004b) Capability evaluation of 3–5 μm and 8–12.5 μm airborne thermal data for underground coal fire detection. Int J Remote Sens 25(12):2245–2258CrossRefGoogle Scholar
  61. Zhukov B, Lorenz E, Oertel D, Wooster M, Roberts G (2006) Spaceborne detection and characterization of fires during the bi-spectral infrared detection (BIRD) experimental small satellite mission (2001–2004). Remote Sens Environ 100:29–51CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  • José A. Sobrino
    • 1
  • Fabio Del Frate
    • 2
  • Matthias Drusch
    • 3
  • Juan C. Jiménez-Muñoz
    • 1
  • Paolo Manunta
    • 4
  1. 1.Global Change Unit, Image Processing Laboratory (IPL)University of ValenciaValenciaSpain
  2. 2.GEO-KTor Vergata UniversityRomeItaly
  3. 3.European Space Research and Technology Centre (ESTEC)European Space Agency (ESA)NoordwijkThe Netherlands
  4. 4.PLANETEK ItaliaBariItaly

Personalised recommendations