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Discrimination of floor cover of dry deciduous forest using Hyperion (EO-1) data

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Abstract

A study was conducted to analyze high spectral reflectance data of the floor cover of dry deciduous forests (Shoolpaneshwar wildlife sanctuary, Gujarat, India) during the summer season. Hyperion data and field data were acquired in the month of April, 2006 (dry/summer season) when the vegetation was in different stages of senescence. Variations in spectral characteristics of different types of leaf litter were seen. Spectral reflectance curves were different for different thicknesses of leaf litter. Altitude also had an impact on the reflectance curves. Spectra of bare soil is easily separable from the ones covered by litter. Descriptive spectra were extracted for four cover types such as Tectona grandis L., Dendrocalamus strictus Nees., mixed deciduous species and bare soil. Continuum removal spectra were also extracted for these four types. Sharp absorption features were seen in VIS and SWIR-II wavelengths which were absent in the spectra of bare soil, indicating the ability of Hyperion data to discriminate dry forest floor from bare soil. The three cover types are also distinctly separable. SWIR-II wavelengths are more sensitive to the type of floor cover indicating its distinctiveness. Results are discussed highlighting the potential of Hyperion data in deciphering floor cover characteristics in the dry season.

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References

  • Asner GP and Lobell DB (2000) A biogeophysical approach for automated SWIR unmixing of soils and vegetation. Rem. Sen. Env. 74:94–112

    Google Scholar 

  • Bahuguna VK (1999) Fire situation in India. International Forest Fire News. 26:23–27

    Google Scholar 

  • Brandis K and Jacobson C (2003) Estimation of vegetative fuel loads using Landsat TM imagery in New South Wales. Aust. Int. J. Wildland Fire, 12:185–194

    Article  Google Scholar 

  • Brown JK and Bevins CD (1986) Surface fuel loadings and predicted fire behavior for vegetation types in the northern Rocky Mountains. US Department of Agriculture, Forest Service, Intermountain Forest and Range Experiment Station, Ogden, UT. Res. Note: INT-358, p 9

    Google Scholar 

  • Clark RN (1999) Spectroscopy of rocks and minerals and principles of spectroscopy. In: Remote Sensing for the Earth Sciences: Manual of Remote Sensing 3rd Edition, Vol. 3 (A.N. Rencz, Ed.), John Wiley and Sons, Inc., New York, pp 3–58

    Google Scholar 

  • Clark RN and Roush TL (1984) Reflectance spectroscopy: Quantitative analysis techniques for remote sensing applications. J. Geo. Research 89:6329–6340

    Article  Google Scholar 

  • Datt B, McVicar TR, Jupp DLB and Pearlman JS (2003) Pre-processing EO-1 Hyperion hyperspectral data to support the application of agricultural indexes. IEEE Trans. Geosci. Remote Sensing 41(2):1246–1259

    Article  Google Scholar 

  • Daughtry CST, Hunt Jr ER and McMurtrey III JE (2004) Assessing crop residue cover using shortwave infrared reflectance, Rem. Sen. Env. 90:126–134

    Article  Google Scholar 

  • Garg RK and Vyas LN (1975) Litter production in deciduous forest near Udaipur (south Rajasthan), India. Tropical Ecological Systems. New York: Springer-Verlag, pp 131–135

    Google Scholar 

  • Holdridge LR (1967) Life Zone Ecology. Tropical Science Center, San Jose, Costa Rica, p 206

    Google Scholar 

  • Ingle JD (1988) Spectrochemical Analysis, Prentice-Hall, Inc., Engelwood Cliffs, New Jersey, pp. 424–425

    Google Scholar 

  • Kaene RE, Burgan R and van Wagtendok J (2001) Mapping wildland fuels for fire management across multiple scales: integrating remote sensing, GIS, and biophysical modeling. Int. J. Willand Fire, 10:301–319

    Article  Google Scholar 

  • Kaene RE, Rollins MG, McNicoll CH and Persons RA (2002) Integrating ecosystem sampling, gradient modeling, remote sensing, and ecosystem simulation to create spatially explicit landscape inventories. US Department of Agriculture, Forest Service, Rocky Mountain Research Station, Fort Collins, CO. RMRS-GTR-92, p. 61

    Google Scholar 

  • Kokaly RF (2001) Investigating a physical basis for spectroscopic estimates of leaf nitrogen concentration. Rem. Sen. Env., 67:153–161

    Article  Google Scholar 

  • Kokaly RF, Despain DG, Clark RN and Livo KE (2003) Mapping vegetation in Yellowstone National Park using spectral feature analysis of AVIRIS data. Rem. Sen. Env. 84:437–456

    Article  Google Scholar 

  • Lee KS, Kin SH, Ma JR, Kook MJ and Shin J (2005) Spectral variation of vegetative areas in leaf-off season observed by hyperspectral data. IEEE, pp. 4347–4350

  • Lewis MM and Dunk I (2000) Seagrass and shallow water feature discrimination using HyMap. Proceedings Tenth Australasian Remote Sensing and Photogrammetry Conference, 21–25, Adelaide, Australia, 1, 1092–1108 (CD-ROM)

    Google Scholar 

  • Lumme JH (2004) Classification of vegetation & soil using imaging spectrometer data. Proceedings XXth ISPRS Congress, Istanbul, Turkey from July 12–23, 2004

  • Pradeepkumar G (1993) Vegetational & Ecological Studies of Shoolpaneshwar Wildlife Sanctuary. Ph.D Thesis, Botany Department, The M.S. University of Baroda, India

    Google Scholar 

  • Pyne SJ, Andrews PL and Laven RD (1996) Introduction to Wildland Fire. John Wiley & Sons Inc., New York, pp. 1–769

    Google Scholar 

  • Roberts DA, Dennison PE, Gardner ME, Hetzel Y, Ustin, SL and Lee CT (2003) Evaluation of the potential of Hyperion for fire danger assessment by comparison to the Airborne Visible/Infrared Imaging Spectrometer. IEEE Trans Geosci Remote Sensing 41(6):1297–1309

    Article  Google Scholar 

  • Sabnis SD and Amin JC (1992). Eco-Environmental studies of Sardar Sarovar Environs. The M.S. University of Baroda

  • Saksena AK and Tyagi S (2002) Management plan for SWS, Rajpipla (East) Division, Forest Department, Wild life wing, Gujarat state, pp. 125–136

  • Streeck NA, Rundquist D and Connot J (2002) Estimating Residual Wheat Dry Matter from Remote Sensing Measurements, Photogram. Engi. and Rem. Sen., 68(11):1193–1201

    Google Scholar 

  • Vyas LN, Garg RK and Vyas NL (1977) Stand structure and above ground biomass in dry deciduous forests of Aravalli Hills at Udaipur (Rajasthan), India. Biologia (Brastislava), 32:265–270

    Google Scholar 

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Correspondence to N. S. R. Krishnayya.

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Christian, B., Krishnayya, N.S.R. Discrimination of floor cover of dry deciduous forest using Hyperion (EO-1) data. J Indian Soc Remote Sens 36, 137–148 (2008). https://doi.org/10.1007/s12524-008-0014-2

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  • DOI: https://doi.org/10.1007/s12524-008-0014-2

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