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Predictive Analysis for Vegetation Biomass Assessment in Western Ghat Region (WG) Using Geospatial Techniques

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Abstract

Forests play a critical role in ecological functioning, global warming and climate change through its unique potential to capture and hold carbon (C). Biomass is one of the indicator of the status of forests hence accurate assessment and biomass mapping is important for sustainable forest management. The objectives of this study is to estimate above ground biomass (AGB) from field inventory data and to map AGB combining field inventory data, remote sensing and geo-statistical model. In the present study stratified random sampling were used for estimation of biomass in which 59 plots were laid down in different homogenous strata depending on the NDVI values for the region of Maharashtra Western Ghats. The above ground biomass from field ranged from 0.05 to 271 t-dry wt ha−1 in which trees added maximum towards total biomass followed by shrubs and herbs. This paper evaluates the best vegetation indices to estimate biomass. This study was carried out by using Landsat TM satellite data and field inventory data in the Ratnagiri district of Maharashtra, India. A significant correlation was observed between biomass and vegetation indices. The best fit regression equation developed from field above ground biomass and NDVI with R2 value of 0.61 was used for spectral modeling to estimate the geospatial distribution of AGB in the entire region. The results of spatial predictions Geostatistical technique and remotely sensed data as auxiliary variables were compared using statistical error methods. This study employed Mean error, Root-Mean-Square error, Average Standard error and Root-Mean Square Standardized error. The ME, RMSE, Average Standard error and Root-Mean Square Standardized error was 0.078, 8.032, 7.982 and 0.967 respectively. The results showed that cokriging technique is one of the geostatistical method for spatial predictions of biomass in the studied region. The present study revealed that remote sensing technique combined with field sampling provides quick and reliable estimates of above ground biomass and carbon pool and can be used as baseline information for further temporal studies of biomass status of the region and in planning of forest and natural resources management.

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Acknowledgements

Authors thank Indian Space Research Organisation (ISRO), Department of Space, Government of India for funding this project under ISRO-GBP/NCP-VCP. Authors also thank Dr. V.K. Dadhawal, Project Director VCP and Director NRSC to provide necessary Technical and Financial Support to execute the Project. Our thanks are also due to the forest department Maharashtra to support during field work in forest areas.

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  1. Symbiosis Institute of Geo-informatics (SIG), Symbiosis International University, Pune, 411016, India

    T. P. Singh & Sandipan Das

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  1. T. P. Singh
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  2. Sandipan Das
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Correspondence to T. P. Singh.

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Singh, T.P., Das, S. Predictive Analysis for Vegetation Biomass Assessment in Western Ghat Region (WG) Using Geospatial Techniques. J Indian Soc Remote Sens 42, 549–557 (2014). https://doi.org/10.1007/s12524-013-0335-7

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  • DOI: https://doi.org/10.1007/s12524-013-0335-7

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