Remote Estimation of Land Surface Temperature for Different LULC Features of a Moist Deciduous Tropical Forest Region

  • Suman Sinha
  • Prem Chandra Pandey
  • Laxmi Kant Sharma
  • Mahendra Singh Nathawat
  • Pavan Kumar
  • Shruti Kanga
Chapter
First Online:
Part of the Society of Earth Scientists Series book series (SESS)

Abstract

Potential of Landsat TM thermal sensor is investigated to retrieve land surface temperature (LST) using spectral index (NDVI), spectral radiance and surface emissivity for a moist deciduous tropical forest area of Munger forests (Bihar, India). Surface emissivity values derived from NDVI are directly used for LST estimation. LST varies spatially due to the complexity of land surface cover features and helps in land-use/land-cover profiling. Areas covered with vegetation show minimum temperatures; while barren and exposed land shows high values. Built-up land generally has higher LST, but when dispersed in small pockets in the forests, the LST value decreases as revealed in the results.

Keywords

Landsat Forest surface temperature (FST) Normalized difference vegetation index (NDVI) Land-use/land-cover (LULC) Emissivity 
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Notes

Acknowledgments

The authors express sincere gratitude to the DST, Government of India for providing funds to carry out the research, Officials of Project Tiger, Sariska and Sariska Forest Division are acknowledged for their support.

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Suman Sinha
    • 1
  • Prem Chandra Pandey
    • 2
  • Laxmi Kant Sharma
    • 3
  • Mahendra Singh Nathawat
    • 4
  • Pavan Kumar
    • 5
  • Shruti Kanga
    • 3
  1. 1.Department of Remote SensingBirla Institute of TechnologyRanchiIndia
  2. 2.Centre for Landscape and Climate Research, Department of GeographyUniversity of LeicesterLeicesterUK
  3. 3.Centre for Land Resource ManagementCentral University of JharkhandRanchiIndia
  4. 4.School of SciencesIndira Gandhi National Open University (IGNOU)New DelhiIndia
  5. 5.Department of Remote SensingBanasthali UniversityTonkIndia

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