Above ground biomass estimation of arid rangelands using irs p6 imagery (case study: Deylam, Iran)

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Research Paper 01/01/2014
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Above ground biomass estimation of arid rangelands using irs p6 imagery (case study: Deylam, Iran)

Shahram Yousefi Khanghah, Hossein Arzani, Seyed Akbar Javadi, Mohammad Jafary
J. Bio. Env. Sci.4( 1), 157-163, January 2014.
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Ten vegetation indices (VIs) including Ratio, Normalized Difference Vegetation Index, Ratio Vegetation Index, Transformed Vegetation Index, Corrected Transformed Vegetation Index, Perpendicular Vegetation Index3, Difference Vegetation Index, Transformed Soil-Adjusted Vegetation Index2, Modified Soil-Adjusted Vegetation Index2, Weighted Difference Vegetation Index used for aboveground biomass estimation (AGB) were derived from Indian Remote Sensing Resource Sat (P6) imagery at an arid rangeland study site in Deylam south western of Iran. 100 sample locations (75 samples for model estimation, and 25 samples for model validation) were selected for the collection of AGB. Correlation coefficients between above ground biomass and VIs were calculated. The results demonstrate that biomass was linearly related to PVI3 (r= -0.491) and WDVI (r= 0.385). The higher bare soil is the main factor making the AGB estimation difficult. These results suggest that Distance Based VIs is useful and performed better than Slope Based VIs for estimating above ground biomass in arid rangelands of Iran.


Baret F, Guyot G. 1991. Potentials and Limits of Vegetation Indices for LAI and APAR Assessment. Journal of Remote Sensing of Environment 35, 161-173.

Booth T, Cox S, Fifield C, Philips M, Williamson N. 2005. Image Analysis Compared with other Methods for Measuring Ground Cover. Journal of Arid Land Resource Management 19, 91-100

Breckenridge RP,  Kepner  WG,  Mouat  DA. 1995. A process for selecting indicators of rangeland health. Journal of Environment Monitoring Assessment 36, 45-60.

Chavez PS. 1996. Image-Based Atmospheric Corrections: Revisited and Improved. Journal of Photogrammetric Engineering and Remote Sensing 62(9), 1025–1036.

Chen F, Keith Weber T, Gokhale B. 2011. Herbaceous Biomass Estimation from SPOT 5Imagery in Semiarid Rangelands of Idaho. Journal of GIScience & Remote Sensing 48(2), 195–209.

Cho MA, Skidmore A.K. 2009. Hyperspectral Predictors for Monitoring Biomass Production in Mediterranean Mountain Grasslands: Majella National Park, Italy. International Journal of Remote Sensing 30(2), 499–515.

Chuvieco E, Cocero D, Riano D, Martin P, Martinez-Vega J, Riva JDL, Perez F. 2004. Combining NDVI and Surface Temperature for the Estimation of Live Fuels Moisture Content in Forest Fire Danger Rating. Journal of Remote Sensing of Environment 92(3), 322–331.

Davidson A, Csillag F. 2001. The Influence of Vegetation Index and Spatial Resolution on a Two-Date Remote Sensing Derived Relation to C4 Species Coverage. Journal of Remote Sensing of Environment 75(1), 138–151.

Deering DW, Rouse JW, Haas RH, Schell JA. 1975. Measuring Forage Production of Grazing Units from Landsat MSS Data. Proceedings of the 10th International Symposium on Remote Sensing of Environment, II, p. 1169-1178.

Foody GM, Boyd DS, Cutler MEJ. 2003. Predictive Relations of Tropical Forest Biomass from Landsat TM Data and Their Transferability between Regions. Journal of Remote Sensing of Environment 85(4), 463–474.

Information. Journal of Photogrammetric Engineering and Remote Sensing, 43, 1541-1552

Richardson AJ, CL Wiegand. 1990. Comparison of two models for simulating the soil-vegetation

Huete AR. 1988. A Soil-Adjusted Vegetation Index (SAVI). Journal of Remote Sensing of Environment 25(3), 295–309.

Huntsinger L, Hopkinson P. 1996. Viewpoint: Sustaining Rangeland Landscapes: A Social and Ecological Process, Journal of Range Management 49(2), 167– 73.

Kogan F, Stark R, Gitelson A, Jargalsaikhan L, Tsooj S. 2004. Derivation of Pasture Biomass in Mongolia from AVHRR-Based Vegetation Health Indices, International Journal of Remote Sensing, 25(14), 2889–2896.

Numata I, Roberts DA, Chadwick OA, Schimel JP, Galvao LS, Soares JV. 2008. Evaluation of Hyper-spectral Data for Pasture Estimate in the Brazilian Amazon Using Field and Imaging Spectrometers. Journal of Remote Sensing of Environment 112(4), 1569–1583.

Milner C, Hughes RE. 1968. Methods for the measurement of the primary production of grassland. IBP Handbook No. 6, Oxford, p. 70.

Pickup G, Bastin GN Chewings VH. 1994. Remote Sensing based condition assessment for non-equilibrium rangelands under large scale commercial grazing. Journal of Ecological Application, 4, 497-517.

Qi J, Chehbouni A, Huete AR, Kerr YH, Sorooshian S. 1994. A Modified Soil Adjusted Vegetation Index. Journal of Remote Sensing of Environment, 48(2), 119– 126.

Richardson AJ Wiegand CL. 1977. Distinguishing Vegetation from Soil Background composite reflectance of a developing cotton canopy. International Journal of Remote Sensing, 11, 447-459.

Running SW, Nemani R R, Heinsch FA, Zhao M, Reeves MC, and Hashimoto H. 2004.  A Continuous Satellite-Derived Measure of Global Terrestrial Primary Production. International Journal of BioScience, 54(6), 547–560.

Sankey TT, Weber KT. 2009. Rangeland Assessments Using Remote Sensing: Is NDVI Useful, Final Report: Comparing Effects of Management Practices on Rangeland Health with Geospatial Technologies, 168 p.

Steininger MK. 2000. Satellite estimation of tropical secondary forest above ground biomass data from Brazil and Bolivia. International Journal of Remote Sensing, 21, 1139-1157.

Tucker CJ. 1979. Red and Photographic Infrared Linear Combinations for Monitoring Vegetation. Journal of Remote Sensing of Environment, 8(2), 127–150.

Weiser RL, Asrar G, Miller GP, Kanemasu ET 1986. Assessing grassland biophysical characteristics from spectral measurements. Journal of Remote Sensing of Environment, 20, 141-152.

Wylie BK, Meyer DJ, Tieszen LL, Mannel S. 2002. Satellite Mapping of Surface Biophysical Parameters at the Biome Scale over the North American Grasslands: A Case Study. Journal of Remote Sensing of Environment, 79, 266-278

Zheng D, Rademacher J, Chen J, Crow T, Bresee T, Moine JL, Ryu S. 2004. Estimation above ground biomass using Landsat 7 ETM+ data across a managed landscape in northern Wisconsin, USA. Journal of Remote sensing of Environment, 93, 402-411.