Spatial pattern analysis for quantification of landscape structure of Tadoba-Andhari Tiger Reserve, Central India

Abstract

Landscape structure is often regarded as an important factor that governs the distribution and abundance of species. Therefore it is critical to understand the landscapes and their dynamics. Patterns of landscape elements strongly influence the ecological characteristics. This study was designed to document and map the current status of the tropical dry deciduous forest of the Tadoba-Andhari Tiger Reserve (TATR), Central India, (using IRS P6 LISS IV data) and to describe its landscape structure at three levels of organization viz. landscape, class, and patch. The study area was classified into 10 land cover classes that include 6 vegetation classes. The landscape structure was analyzed using FRAGSTATS using 12 set of indices. The TATR landscapes have a total of 2,307 patches with a mean patch size of 25.67 ha and patch density of 1.7 patches per km². Amongst all land cover classes, mixed bamboo forest is dominant—it occupied maximum area (77.99%)—while riparian forest is least represented (0.32%). Mixed forest has maximum number of patches among all vegetation classes. Results have shown that despite being dominant in the area, mixed bamboo forest has low patch density (0.25/100 ha). Dominance of mixed bamboo forest is attributed to large patch sizes and not to the number of patches. This study has focussed on the approach of integrating satellite forest classification and forest inventory data for studying forest landscape patterns.

Keywords

Spatial pattern analysis / landscape structure / FRAGSTATS / IRS P6 LISS IV

References

[1] Bahuguna A. Evaluation of high resolution Resourcesat-1 LISSIV data for coastal zone studies. National Natural Remote Management System, NNRMS Bulletin. 2004, Hyderabad: National Remote Sensing Agency

[2] Champion HG, Seth SK. A Revised Survey of the Forest Types of India. 2005, Dehradun: Natraj Publishers

[3] Cherill AJ, McClean C. A comparison of land cover types in an Ecological field survey in northern England and a remotely sensed land cover map of Great Britain. Biological Conservation, 1995, 71: 313-323.

[4] Chust G, Ducrot D, Pretus JL. Land cover mapping with patch-derived landscape indices. Landscape and Urban Planning, 2004, 69: 437-449.

[5] Correy RC, Nassauer JI. Limitations of using landscape pattern indices to evaluate the ecological consequences of alternative plans and designs. Landscape and Urban Planning, 2005, 72: 265-280.

[6] Cousins SAO, Eriksson O. The influence of management history and habitat on plant species richness in a rural hemi boreal landscape, Sweden. Landscape Ecology, 2002, 17: 517-529.

[7] Cushman SA, McGarigal K, Neel MC. Parsimony in landscape metrics: Strength, universality, and consistency. Ecological Indicators, 2008, 8: 691-703.

[8] Dubey Y, Mathur VB. Establishing computerized wildlife database for conservation, monitoring and evaluation in Tadoba-Andhari Tiger Reserve, Maharashtra. Final project report, 1999

[9] Dubey Y. Application of Geographic Information System in assessing habitat, resource availability and its management in Tadoba-Andhari Tiger Reserve, 1999 250.

[10] Formon RTT, Godron M. Landscape Ecology. 1986, New York, USA: John Wiley & Sons

[11] Franklin SE, Titus BD, Gillespie RT. Remote sensing of vegetation cover at forest regeneration site. Global Ecology and Biogeography Letters, 1994, 4: 40-46.

[12] Gachet S, Leduc A, Bergeron Y, Nguyen-Xuan T, Tremblay F. Understorey vegetation of boreal tree plantations: difference in relation to previous land use and natural forests. Forest Ecology and Management, 2007, 242: 49-57.

[13] Gould W. Remote sensing of vegetation, plant species richness and regional biodiversity hotspots. Ecological Applications, 2000, 10: 1861-1870.

[14] Griffith JA, Martinko EA, Price KP. Landscape structure analysis of Kansas at three scales. Landscape and Urban Planning, 2000, 52: 45-61.

[15] Groom GB, Fuller RM, Jones AR. Contextual correction: techniques for improving land cover mapping from remotely sensed images. International Journal of Remote Sensing, 1996, 17: 69-89.

[16] Gupta K, Jain S. Enhanced capabilities of IRS P6 LISS IV sensor for urban mapping. Current Science, 2005, 89: 1805-1812.

[17] Innes JI, Koch B. Forest biodiversity and its assessment by remote sensing. Global Ecology and Biogeography Letters, 1998, 7: 397-419.

[18] Jadhav RN, Murthy AK, Chauhan KK, Tandon MN, Arravatia AML, Kandya K, Saratbabu G, Oza MP, Kimothi MM, Sharma K, Thesia JK. Manual of procedures for forest mapping and damage detection using satellite data, 1990

[19] Kulkarni AV, Bahuguna IM, Rathore BP, Singh SK, Randhwa SS, Sood RK, Dhar S. Glacial retreat in Himalaya using Indian remote sensing satellite data. Current Science, 2007, 92: 69-74.

[20] Kumar V, Martha TR. Evaluation of Resourcesat-1 data for geological studies. National Natural Remote Management System, NNRMS Bulletin (B) 29. 2004, Hyderabad: National Remote Sensing Agency

[21] Lele N, Joshi PK, Agrawal SP. Assessing forest fragmentation in northeastern region (NER) of India using landscape matrices. Ecological Indicators, 2008, 8: 657-663.

[22] Lilesand TM, Kiefer RW. Remote Sensing and image interpretation, 1994

[23] Lu L, Li X, Cheng GD. Landscape evolution in the middle Heihe River Basin of north-west China during the last decade. Journal of Arid Environments, 2003, 53(3): 395-408.

[24] McGarigal K, Marks BJ. FRAGSTATS: spatial pattern analysis program for quantifying landscape structure. Gen. Tech. Rep. PNW-GTR-351. 1995, Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station, 122.

[25] Milanova EV, Lioubimtseva E Y, Tcherkashin PA, Yanvareva LF. Land use/Land cover change in Russia: mapping and GIS. Land use Policy, 1999, 16(3): 153-159.

[26] Miyamoto A, Sano M. The influence of forest management on landscape structure in the cool temperate forest region of central Japan. Landscape and Urban Planning, 2008, 86: 248-256.

[27] Nagendra H, Gadgil M. Satellite imagery as a tool for monitoring species diversity: an assessment. Journal of Applied Ecology, 1999, 36: 388-397.

[28] O’Neill RV, Krummel JR, Gardner RH, Jackson B, DeAngelis DL, Milne BT, Turner MG, Zygmunt B, Christensen SW, Dale VH, Graham RL. Indices of landscape pattern. Landscape Ecology, 1988, 1: 153-162.

[29] Rajankar PB, Balamwar SV, Shrivastava NT, Sinha AK. Utilization of Resourcesat-1 data in agriculture applications. National Natural Remote Management System, NNRMS Bulletin. 2004, Hyderabad: National Remote Sensing Agency

[30] Rao KN, Narendra K. Mapping and evaluation of urban sprawling in the Mehasdrigedda watershed in Visakhapatnam metropolitan region using remote sensing and GIS. Current Science, 2006, 91: 1552-1557.

[31] Sarangi RK, Chauhan P, Nayak S. Assessment of Resourcesat-1 AWiFS data for marine applications. National Natural Remote Management System, NNRMS Bulletin. 2004, Hyderabad: National Remote Sensing Agency

[32] Sharma A. Comparing the radiometric behavior of LISS III data of IRS 1D and IRS P6 for landscape ccological application. Environmental Informatics, 2009, 13: 66-74.

[33] Sinha R, Sharma A. Disturbance gradient analysis at landscape level in Daltonganj South Forest Division. Journal of Indian Society of Remote Sensing, 2006, 34: 233-243.

[34] Skole D, Tucker C. Tropical deforestation and habitat fragmentation in the Amazon: satellite data from 1978 to 1988. Science, 1993, 26: 1905-1910.

[35] Turner MG, Gardner RH, O’Neill RV. Landscape Ecology In Theory And Practice Pattern and Process. 2001, New York, USA: Springer-Verlag, 1 23

[36] Turner MG. Landscape heterogeneity and disturbance. 1987, New York: Springer-Verlag

[37] Turner MG. Spatial and temporal analysis of landscape pattern. Landscape Ecology, 1990, 3: 153-162.

[38] Wiens JA. Hansson L, Fahrig L, Merriam G. Landscapes mosaic and ecological theory. Mosaics Landscapes and Ecological Processes. 1995, London, UK: Chapman & Hall, 1 26