Environmental Earth Sciences

, Volume 71, Issue 5, pp 2245–2255 | Cite as

Appraisal of land use/land cover of mangrove forest ecosystem using support vector machine

  • Sudhir Kumar Singh
  • Prashant K. SrivastavaEmail author
  • Manika Gupta
  • Jay Krishna Thakur
  • Saumitra Mukherjee
Original Article


Human activities in many parts of the world have greatly changed the natural land cover. This study has been conducted on Pichavaram forest, south east coast of India, famous for its unique mangrove bio-diversity. The main objectives of this study were focused on monitoring land cover changes particularly for the mangrove forest in the Pichavaram area using multi-temporal Landsat images captured in the 1991, 2000, and 2009. The land use/land cover (LULC) estimation was done by a unique hybrid classification approach consisting of unsupervised and support vector machine (SVM)-based supervised classification. Once the vegetation and non-vegetation classes were separated, training site-based classification technology i.e., SVM-based supervised classification technique was used. The agricultural area, forest/plantation, degraded mangrove and mangrove forest layers were separated from the vegetation layer. Mud flat, sand/beach, swamp, sea water/sea, aquaculture pond, and fallow land were separated from non-vegetation layer. Water logged areas were delineated from the area initially considered under swamp and sea water-drowned areas. In this study, the object-based post-classification comparison method was employed for detecting changes. In order to evaluate the performance, an accuracy assessment was carried out using the randomly stratified sampling method, assuring distribution in a rational pattern so that a specific number of observations were assigned to each category on the classified image. The Kappa accuracy of SVM classified image was highest (94.53 %) for the 2000 image and about 94.14 and 89.45 % for the 2009 and 1991 images, respectively. The results indicated that the increased anthropogenic activities in Pichavaram have caused an irreversible loss of forest vegetation. These findings can be used both as a strategic planning tool to address the broad-scale mangrove ecosystem conservation projects and also as a tactical guide to help managers in designing effective restoration measures.


Land use/land cover Mangrove forest Pichavaram forest Support vector machine Urbanization indices 



Authors are highly thankful to Directorate of Census (Tamil Nadu division), Government of India, for providing the necessary reference data and HOD of K.Banerjee Centre of Atmospheric and Ocean Studies, Nehru Science Centre, IIDS, University of Allahabad, Allahabad-211002, India for their support throughout the project.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Sudhir Kumar Singh
    • 1
  • Prashant K. Srivastava
    • 2
    Email author
  • Manika Gupta
    • 3
  • Jay Krishna Thakur
    • 4
  • Saumitra Mukherjee
    • 5
  1. 1.K.Banerjee Centre of Atmospheric and Ocean Studies, Nehru Science Centre, IIDSUniversity of AllahabadAllahabadIndia
  2. 2.Department of Civil EngineeringUniversity of BristolBristolUK
  3. 3.Department of Civil EngineeringIITNew DelhiIndia
  4. 4.Department Hydrogeology and Environmental Geology, Institute of GeosciencesMartin Luther UniversityHalleGermany
  5. 5.School of Environmental SciencesJawaharlal Nehru UniversityNew DelhiIndia

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