Change detection of landscape connectivity arisen by forest transformation in Hazaribagh wildlife sanctuary, Jharkhand (India)

  • Saurabh Kumar Gupta
  • Arvind Chandra PandeyEmail author


Forest land conversion is the primary driver of biodiversity decline worldwide. Hazaribagh wildlife sanctuary is a region of rich biodiversity in which forests and wildlife are deteriorating fast. The prime reasons for forest degradation and wildlife loss are the landscape connectivity weakening and forest transformation. In the present work, landscape connectivity and forest transformation relationships were analyzed in a spatio-temporal domain. The forest patches as a group of spectral abundance were extracted using the endmember retrieval technique. The connectivity analysis was performed by using a connectivity index in the extracted forest patches. Forest transformation is calculated using a post-classification change detection strategy for five types of forest cover during the four phases of the year (1992–2005, 2005–2010, 2010–2017 and 1992–2017). The forest cover was measured using a forest canopy density model using spectral indices. The landscape connectivity of 80–100% exhibit a rapid increase of 38% in 2005 from 1992 contrary to a 13% decrease in 2010 and 2017. The 23% loss of forest cover from 2005 to 2010 and a 17% loss in 2010–2017 phase of forest transformation weakened the forest connectivity. Forest cover, having a density higher than 40% was more vulnerable to degradation and landscape connectivity loss. The result shows that such declines of forest cover and landscape connectivity will reduce the genetic diversity in the forest, especially the mammalian population.


Landscape connectivity Biodiversity Forest transformation Wildlife Forest degradation 



The authors would like to thanks forest department of Jharkhand, for their support in field and providing useful data. The authors are thankful to USGS earth explorer for providing Landsat data. Authors like to thanks National fellowship for disabilities for providing funds for the research.


Funding was provided by RGNF (Grant No. F.549-Jharkhand 2015-2017).

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.


  1. 1.
    Andrén, H. (1994). Effects of habitat fragmentation on birds and mammals in landscapes with different proportions of suitable habitat: A review. Oikos,71, 355–366.CrossRefGoogle Scholar
  2. 2.
    Laurance, W. F., Camargo, J. L. C., Luizão, R. C. C., Laurance, S. G., Pimm, S. L., Bruna, E. M., et al. (2011). The fate of Amazonian forest fragments: A 32-year investigation. Biological Conservation,144, 56–67. Scholar
  3. 3.
    Vos, C. C., Berry, P., Opdam, P., Baveco, H., Nijhof, B., O’Hanley, J., et al. (2008). Adapting landscapes to climate change: Examples of climate-proof ecosystem networks and priority adaptation zones. Journal of Applied Ecology,45(6), 1722–1731.CrossRefGoogle Scholar
  4. 4.
    Lindenmayer, D. B., Franklin, J. F., Lõhmus, A., Baker, S. C., Bauhus, J., Beese, W., et al. (2012). A major shift to the retention approach for forestry can help resolve some global forest sustainability issues. Conservation Letters,5(6), 421–431.CrossRefGoogle Scholar
  5. 5.
    Gupt, K. S., & Chandra, P. A. (2018). Forest canopy density and fragmentation analysis for evaluating spatio-temporal status of Forest in the Hazaribagh Wild Life Sanctuary, Jharkhand (India). Research Journal of Environmental Sciences,12(4), 198–212. Scholar
  6. 6.
    Kshirsagar, M. (2004). Landscape characterisation of Jhabua and Ratlam District (Madhya Pradesh) using satellite remote sensing data and geographic information system. Pune: University of Pune, Forestry & Ecology Division, Indian Institute of Remote Sensing (NRSA).Google Scholar
  7. 7.
    Feng, S., Guo, L., Li, D., & Huang, Q. (2018). Spatial patterns of landscape change in the Three Rivers Headwaters Region of China, 1987–2015. Acta Ecologica Sinica,38(2), 76–80. Scholar
  8. 8.
    Franklin, J. F. (1994). (1994). Developing information essential to policy, planning and management decision-making: the promise of GIS. In A. V. Sample (Ed.), Remote sensing and GIS in ecosystem management (pp. 18–24). Washington, DC: Island Press.Google Scholar
  9. 9.
    Taylor, P. D., Fahrig, L., Henein, K., & Merriam, G. (1993). Connectivity is a vital element of landscape structure. Oikos, 68(3), 571–572.CrossRefGoogle Scholar
  10. 10.
    Crooks, K. R., Burdett, C. L., Theobald, D. M., Rondinini, C., & Boitani, L. (2011). Global patterns of fragmentation and connectivity of mammalian carnivore habitat. Philosophical Transactions of the Royal Society B. Biological Sciences,366(1578), 2642–2651.CrossRefGoogle Scholar
  11. 11.
    Baranyi, G., Saura, S., Podani, J., & Jordán, F. (2011). Contribution of habitat patches to network connectivity: Redundancy and uniqueness of topological indices. Ecological Indicators,11(5), 1301–1310. Scholar
  12. 12.
    MPLO (Montreal Process Liaison Office). (2000). Montréal process year 2000 progress report—Progress and innovation in implementing criteria and indicators for the conservation and sustainable management of temperate and boreal forests. The Montréal Process Liaison Office, Canadian Forest Service, Ottawa, CanadaGoogle Scholar
  13. 13.
    Message from Malahide. (2004). Halting the decline of biodiversity—priority objectives and targets for 2010. Stakeholders conference, Final Version 27.5.2004, Malahide.Google Scholar
  14. 14.
    ITTO (International Tropical Timber Organization). (2005). Revised ITTO criteria and indicators for the sustainable management of tropical forests including reporting format. ITTO Policy Devel- opment Series No. 15, ISBN 4 902045 20 6, International Organizations Center, 5th Floor, Pacifico-Yokohama, 1-1-1, Minato-Mirai, Nishi-ku, Yokohama 220-0012, JapanGoogle Scholar
  15. 15.
    FAO (Food and Agriculture Organization of the United Nations). (2001). Criteria and indicators for sustainable forest management: A compendium. In F. Castañeda, C. Palmberg-Lerche, & P. Vuorinen (Eds.), Forest Management Working Paper FM/5. FAO, Rome, Italy.Google Scholar
  16. 16.
    Henry, R. C., Palmer, S. C. F., Watts, K., Mitchell, R. J., Atkinson, N., & Travis, J. M. J. (2017). Tree loss impacts on ecological connectivity: Developing models for assessment. Ecological Informatics,42(July), 90–99. Scholar
  17. 17.
    Poiani, K. A., Richter, B. D., Anderson, M. G., & Richter, H. E. (2000). Biodiversity conservation at multiple scales: Functional sites, landscapes, and networks. BioScience,50(2), 133–146.CrossRefGoogle Scholar
  18. 18.
    Martinez, Pardo J., Paviolo, A., Saura, S., & De Angelo, C. (2017). Halting the isolation of jaguars: Where to act locally to sustain connectivity in their southernmost population. Animal Conservation,20(6), 543–554. Scholar
  19. 19.
    Pardini, R., Bueno, A. A., Gardner, T. A., Prado, P. I., & Metzger, J. P. (2010). Beyond the fragmentation threshold hypothesis: Regime shifts in biodiversity across fragmented landscapes. Public Library of Science ONE. Scholar
  20. 20.
    Fahrig, L. (2002). Effect of habitat fragmentation on the extinction threshold: A synthesis. Ecological Applications,12(2), 346–353.Google Scholar
  21. 21.
    Villard, M. A., & Metzger, J. P. (2014). Review: beyond the fragmentation debate: A conceptual model to predict when habitat configuration really matters. Journal of Applied Ecology,51, 309–318. Scholar
  22. 22.
    Lambin, E. F., Meyfroidt, P., Rueda, X., Blackman, A., Börner, J., Cerutti, P. O., et al. (2014). Effectiveness and synergies of policy instruments for land use governance in tropical regions. Global Environmental Change,28, 29–140. Scholar
  23. 23.
    Laurance, W., Sayer, J., & Cassman, K. (2014). Agricultural expansion and its impacts ontropical nature. Trends in Ecologyand Evolution,2, 107–116. Scholar
  24. 24.
    Champion, H. G., & Seth, S. K. (1968). A revised survey of forest types of India (pp. 1–404). New Delhi: Government of India Press.Google Scholar
  25. 25.
    Lu, D., Mausel, P., Brondizio, E., & Moran, E. (2002). Assessment of atmospheric correction methods for Landsat TM data applicable to amazon basin LBA research. International Journal of Remote Sensing,13, 2651–2671.CrossRefGoogle Scholar
  26. 26.
    McGarigal, K., Cushman, S. A., Neel, M. C., & Ene, E. (2002). FRAGSTATS: Spatial pattern analysis program for categorical maps. Computer software program produced by the authors at the University of Massachusetta.Google Scholar
  27. 27.
    Rikimaru, A. (1996). LANDSAT TM data processing guide for forest canopy density mapping and monitoring model. ITTO workshop on utilization of remote sensing in site assessment and planning for rehabilitation of logged-over forest, Bangkok, Thailand.Google Scholar
  28. 28.
    Gruninger, J. H., Ratkowski, A. J., & Hoke, M. L. (2004). The sequential maximum angle convex cone (SMACC) endmember model. In Proceedings SPIE, Algorithms for Multispectral and Hyper-spectral and Ultraspectral Imagery X, Orlando, April.Google Scholar
  29. 29.
    Martensen, A. C., Ribeiro, M. C., Banks-Leite, C., Prado, P. I., & Metzger, J. P. (2012). Associations of forest cover, fragment area, and connectivity with neotropical understory bird species richness and abundance. Conservation Biology,26, 1100–1111. Scholar
  30. 30.
    Harrison, L. R., Rudnick, D., Ryan, S. J., Beier, P., Cushman, S., Dieffenbach, F., et al. (1992). Published by the ecological society of America esa. America,7(3), 612–618. Scholar
  31. 31.
    Martín-Martín, C., Robert, G. H., Bunce, Saura S., & Elena-Rosselló, R. (2013). Changes and interactions between forest landscape connectivity and burnt area in Spain. Ecological Indicators,33, 129–138. Scholar
  32. 32.
    Frishkoff, L. O., Karp, D. S., M’Gonigle, L. K., Mendenhall, C. D., Zook, J., & Kremen, C. (2014). Loss of avian phylogenetic diversity in neotropical agricultural systems. Science,345(6202), 1343–1346. Scholar
  33. 33.
    Mendenhall, C. D., Karp, D. S., Meyer, C. F. J., Hadly, E. A., & Daily, G. C. (2014). Predicting biodiversity change and averting collapse in agricultural landscapes. Nature,509(7499), 213–217. Scholar
  34. 34.
    Reid, J. L., Mendenhall, C. D., Rosales, J. A., Zahawi, R. A., & Holl, K. D. (2014). Landscape context mediates avian habitat choice in tropical forest restoration. Plos One. Scholar
  35. 35.
    Ruiz-Gutierrez, V., Gavin, T. A., & Dhondt, A. A. (2008). Habitat fragmentation lowers survival of a tropical forest bird. Ecological Applications,18(4), 838–846.CrossRefGoogle Scholar
  36. 36.
    Hadley, A. S., Frey, S. J. K., Robinson, W. D., Kress, W. J., & Betts, M. G. (2014). Tropical forest fragmentation limits pollination of a keystone under story herb. Ecology.,95(8), 2202–2212.CrossRefGoogle Scholar
  37. 37.
    Shiva, V. (1991). The violence of the green revolution: Third world agriculture, Ecology, and politics. London: Zed Books.Google Scholar
  38. 38.
    Gupta, R. K., Naresh, R. K., & Hobbs, P. R. (2003). Sustainability of post-green revolution agriculture: The rice–wheat cropping systems of the Indo-Gangetic Plains and China (pp. 1–25). Madison: American Society of Agronomy, Inc., Crop Science Society of America, Inc., Soil Science Society of America, Inc.Google Scholar
  39. 39.
    Zhai, D., Xu, J., Dai, Z., & Schmidt-Vogt, D. (2017). Lost in transition: Forest transition and natural forest loss in tropical China. Plant Diversity,39(3), 149–153. Scholar
  40. 40.
    Kaim, D., Ziółkowska, E., Szwagrzyk, M., Price, B., & Kozak, J. (2019). Impact of future land use change on large carnivores connectivity in the polish Carpathians. Land,8(1), 8. Scholar
  41. 41.
    Nepstad, D. C., Tohver, I. M., Ray, D., Moutinho, P., & Cardinot, G. (2007). Mortality of large trees and lianas following experimental drought in an Amazon forest. Ecology,88(9), 2259–2269.CrossRefGoogle Scholar
  42. 42.
    Mueller, R. C., et al. (2005). Differential tree mortality in response to severe drought: Evidence for long-term vegetation shifts. Journal of Ecology,93(6), 1085–1093.CrossRefGoogle Scholar
  43. 43.
    Condit, R., Hubbell, S. P., & Foster, R. B. (1995). Mortality rates of 205 neotropical tree and shrub species and the impact of a severe drought. Ecological Monographs,65(4), 419–439.CrossRefGoogle Scholar
  44. 44.
    Pardini, R., de Arruda Bueno, A., Gardner, T. A., Prado, P. I., & Metzger, J. P. (2010). Beyond the fragmentation threshold hypothesis: Regime shifts in biodiversity across fragmented landscapes. PloS ONE,5(10), e13666. Scholar
  45. 45.
    Villard, M. A., & MetzgerJ, P. (2014). Review: beyond the fragmentation debate: A conceptual model to predict when habitat configuration really matters. Journal of Applied Ecology,51, 309–318. Scholar
  46. 46.
    Ostapowicz, K., Estreguil, C., Kozak, J., & Vogt, P. (2006). Assessing forest fragmentation and connectivity: A case study in the Carpathians. In Proceedings of SPIE, 6366, remote sensing for environmental monitoring, GIS Applications, and geology VI, 636608.
  47. 47.
    Zemanova, M. A., Perotto-baldivieso, H. L., Dickins, E. L., Gill, A. B., Leonard, J. P., & Wester, D. B. (2017). Impact of deforestation on habitat connectivity thresholds for large carnivores in tropical forests. Ecological Processes. Scholar

Copyright information

© Korean Spatial Information Society 2019

Authors and Affiliations

  1. 1.Department of Geoinformatics, School of Natural Resource ManagementCentral University of JharkhandRanchiIndia

Personalised recommendations