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Evaluation of object-based image analysis techniques on very high-resolution satellite image for biomass estimation in a watershed of hilly forest of Nepal

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Abstract

Methods of forest carbon estimation using remote-sensing data and techniques are evolving within a short timeframe as compared to traditional forest inventory methods. Object-based image analysis (OBIA) provided new opportunities to improve biomass and carbon stock estimation and mapping by delineating and classifying crown projection area (CPA) of individual trees. In this paper, image segmentation techniques of OBIA (region growing and valley following) are being applied on GeoEye-1 satellite data and compared in terms of accuracy in Ludhikhola watershed in the Gorkha District of Nepal. Accuracy assessment of tree crown delineation of both segmentation approaches were analyzed using accuracy measures of D and one-to-one (1:1) correspondence. The combination of over-segmentation and under-segmentation, D is interpreted as the “closeness” measure to an ideal segmentation result in relation to a predefined reference set. Region growing and valley following segmentation 68 and 58 % accuracy, respectively, was achieved and linear regression model was developed for carbon stock for Shorea robusta which resulted into a coefficient of determination value of 0.67 at 95 % confidence level and the coefficient of determination resulted into a value of 0.70 for other species. The research concluded that region growing approach showed better delineation as compared to valley follow approach, since it used both features of local maxima and local minima.

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Acknowledgments

This study is an elaboration of the MSc thesis. The authors are grateful for the support received from the Netherlands Fellowship Program (NFP) for having sponsored the study costs. Special thanks to the International Centre for Integrated Mountain Development (ICIMOD) for their support during the data collection period in Nepal. Finally, we would like to express our special thanks to Dr. Bhaskar Karky, Eak Bhadur Rana, Govinda Joshi, and Seema Karki for providing support and feedback.

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Authors and Affiliations

  1. Faculty of Geo-Information Science and Earth Observation, University of Twente, P.O. Box 217, 7500 AE, Enschede, The Netherlands

    Yousif Ali Hussin & Louise van Leeuwen

  2. International Centre for Integrated Mountain Development, G.P.O. Box 3226, Khumaltar, Lalitpur, Kathmandu, Nepal

    Hammad Gilani, M. S. R. Murthy & Faisal Mueen Qamer

  3. School of Geomatics, Liaoning Technical University, 47 Zhonghua Road, Fuxin, Liaoning Province, China

    Hammad Gilani

  4. National Trust for Nature Conservation- Central Zoo, Kathmandu, Nepal

    Rachna Shah

  5. Rupantaran Nepal, P.O. Box 7345, Naxal Narayanchaur, Kathmandu, Nepal

    Srijana Baral

  6. Laboratory of Geo-Information Science and Remote Sensing, Wageningen University and Research Centre, P.O. Box 47, 6700 AA, Wageningen, The Netherlands

    Nandin-Erdene Tsendbazar

  7. Conservation and Sustainable Use of Wetlands in Nepal (CSUWN)/GoN/UNDP, Kathmandu, Nepal

    Saurav Shrestha

  8. Department of National Park and Wildlife Conservation, Babarmahal, Kathmandu, Nepal

    Shyam Kumar Shah

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  1. Yousif Ali Hussin
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  2. Hammad Gilani
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  3. Louise van Leeuwen
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  4. M. S. R. Murthy
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  10. Faisal Mueen Qamer
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Correspondence to Hammad Gilani.

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Hussin, Y.A., Gilani, H., van Leeuwen, L. et al. Evaluation of object-based image analysis techniques on very high-resolution satellite image for biomass estimation in a watershed of hilly forest of Nepal. Appl Geomat 6, 59–68 (2014). https://doi.org/10.1007/s12518-014-0126-z

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