Skip to main content
SpringerLink
Log in

Remote Sensing and GIS for Biodiversity Conservation

  • Chapter
  • First Online:
Recent Advances in Lichenology

Abstract

This chapter focuses on the application of space-borne remote sensing and GIS for biodiversity conservation in the context of the state-of-the-art technology which has enhanced the classical approach. It reviews currently available instruments, i.e. space-borne or satellite sensors providing data which can be used without analysis or interpretation for studying individual organisms, species assemblages or ecological communities on ground. Subsequently, the image processing and GIS techniques developed to derive information from the captured satellite data are reviewed, and finally, this chapter concludes by reviewing the use of remote sensing and GIS techniques for mapping, monitoring and modelling lichens and their habitats.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  • Aarrestad PA, Aamlid D (1999) Vegetation monitoring in South-Varanger, Norway-species composition of ground vegetation and its relation to environmental variables and pollution impact. Environ Monit Assess 58(1):1–21

    CAS  Google Scholar 

  • Adhikari D, Barik SK, Upadhaya K (2012) Habitat distribution modelling for reintroduction of Ilex khasiana Purk., a critically endangered tree species of northeastern India. Ecol Eng 40:37–43

    Google Scholar 

  • Akcakaya HR, Butchart SHM, Mace GM, Stuart SN, Hilton-Taylor C (2006) Use and misuse of the IUCN red list criteria in projecting climate change impacts on biodiversity. Glob Change Biol 12:2037–2043

    Google Scholar 

  • Amarnath G, Murthy MSR, Britto SJ, Rajashekar G, Dutt CBS (2003) Diagnostic analysis of conservation zones using remote sensing and GIS techniques in wet evergreen forests of the Western Ghats—an ecological hotspot, Tamil Nadu, India. Biodivers Conserv 12:2331–2359

    Google Scholar 

  • Araujo MB, Whittaker RJ, Ladle RJ, Erhard M (2005) Reducing uncertainty in projections of extinction risk from climate change. Glob Ecol Biogeogr 14:529–538

    Google Scholar 

  • Augusto S, Pinho P, Branquinho C, Pereira MJ, Soares A, Catarino F (2004) Atmospheric dioxin and furan deposition in relation to land-use and other pollutants: a survey with lichens. J Atmos Chem 49:53–65

    CAS  Google Scholar 

  • Austin MP (2007) Species distribution models and ecological theory: a critical assessment of some possible new approaches. Ecol Model 200:1–19

    Google Scholar 

  • Badarinath KVS, Sharma AR, Kharol SK (2011) Forest fire monitoring and burnt area mapping using satellite data: a study over the forest region of Kerala State, India. Int J Remote Sens 32(1):85–102

    Google Scholar 

  • Bannari A, Khurshid KS, Staenz K, Schwarz J (2008) Potential of Hyperion EO-1 hyperspectral data for wheat crop chlorophyll content estimation. Can J Remote Sens 34:S139–S157

    Google Scholar 

  • Barik SK, Adhikari D (2011) Predicting geographic distribution of an invasive species Chromolaena odorata L. (King) and H.E. Robins. In: Bhatt JR, Singh JS, Tripathi RS, Singh SP, Kohli RK (eds) Invasive alien plants—an ecological appraisal for the Indian sub-continent. CABI, Oxfordshire, pp 77–88

    Google Scholar 

  • Behera MD, Roy PS (2010) Assessment and validation of biological richness at landscape level in part of the Himalayas and Indo-Burma hotspots using geospatial modeling approach. J Indian Soc Remote Sens 38:415–429

    Google Scholar 

  • Behera MD, Srivastava S, Kushwaha SPS, Roy PS (2000) Stratification and mapping of Taxus baccata L. bearing forests in Talle Valley using remote sensing and GIS. Curr Sci 78(8):1008–1013

    Google Scholar 

  • Belnap J, Lange OL (2005) Biological soil crusts and global changes: what does the future hold? In: Dighton J, White JF, Oudemans P (eds) The fungal community: its organization and role in the ecosystem, 3rd edn. CRC Press, Boca Raton, pp 697–712

    Google Scholar 

  • Berry PM, Dawson TP, Berry PA, Harrison PA (2002) SPECIES: a spatial evaluation of climate impacts on the envelope of species. Ecol Model 154:289–300

    Google Scholar 

  • Berryman S, McCune B (2006) Estimating epiphytic macrolichen biomass from topography, stand structure and lichen community data. J Veg Sci 17(2):157–170

    Google Scholar 

  • Bharti RR, Adhikari BS, Rawat GS (2012) Assessing vegetation changes in timberline ecotone of Nanda Devi National Park, Uttarakhand. Int J Appl Earth Obs Geoinf 18:472–479

    Google Scholar 

  • Bisby FA (2000) The quiet revolution: biodiversity informatics and the internet. Science 289(5488):2309–2312

    CAS  PubMed  Google Scholar 

  • Bock M, Xofis P, Mitchley J, Rossner G, Wissen M (2005) Object-oriented methods for habitat mapping at multiple scales—case studies from Northern Germany and Wye Downs, UK. J Nat Conserv 13:75–89

    Google Scholar 

  • Botkin DB, Saxe H, Araujo MB, Betts R, Bradshaw RHW, Cedhagen T, Chesson P, Dawson TP, Etterson JR, Faith DP, Ferrier S, Guisan A, Hansen AS, Hilbert DW, Loehle C, Margules C, New M, Sobel MJ, Stockwell DRB (2007) Forecasting the effects of global warming on biodiversity. Bioscience 57:227–236

    Google Scholar 

  • Boyd DS, Danson FM (2005) Satellite remote sensing of forest resources: three decades of research development. Prog Phys Geogr 29:1–26

    Google Scholar 

  • Boyd DS, Foody GM (2011) An overview of recent remote sensing and GIS based research in ecological informatics. Ecol Inform 6:25–36

    Google Scholar 

  • Boyd DS, Sanchez-Hernandez C, Foody GM (2006) Mapping a specific class for priority habitats monitoring from satellite sensor data. Int J Remote Sens 27:2631–2644

    Google Scholar 

  • Burrough PA (2001) GIS and geo-statistics: essential partners for spatial analysis. Environ Ecol Stat 8:361–377

    Google Scholar 

  • Canada Centre for Remote Sensing (2007) Fundamentals of remote sensing: a remote sensing tutorial. http://ccrs.nrcan.gc.ca/resource/tutor/fundam/pdf/fundamentals_e.pdf

  • Caride C, Pineiro G, Paruelo JM (2012) How does agricultural management modify ecosystem services in the argentine Pampas? The effects on soil C dynamics. Agric Ecosyst Environ 154:23–33

    Google Scholar 

  • Carleer A, Wolff E (2004) Exploitation of very high resolution satellite data for tree species identification. Photogram Eng Remote Sens 70:135–140

    Google Scholar 

  • Carlson KM, Asner GP, Hughes RF, Ostertag R, Martin RE (2007) Hyperspectral remote sensing of canopy biodiversity in Hawaiian lowland rainforests. Ecosystems 10:536–549

    Google Scholar 

  • Carvalho SB, Brito JC, Pressey RL, Crespo E, Possingham HP (2010) Simulating the effects of using different types of species distribution data in reserve selection. Biol Conserv 143(2):426–438

    Google Scholar 

  • Clark DB, Read JM, Clark ML, Cruz AM, Dotti MF, Clark DA (2004) Application of 1-M and 4-M resolution satellite data to ecological studies of tropical rain forests. Ecol Appl 14:61–74

    Google Scholar 

  • Cleland EE, Chuine I, Menzel A, Mooney HA, Schwartz MD (2007) Shifting plant phenology in response to global change. Trends Ecol Evol 22(7):357–365

    PubMed  Google Scholar 

  • Collingwood A, Franklin SE, Guo X, Stenhouse G (2009) A medium-resolution remote sensing classification of agricultural areas in Alberta grizzly bear habitat. Can J Remote Sens 35:23–36

    Google Scholar 

  • Colpaert A, Kumpula J, Nieminen M (2003) Reindeer pasture biomass assessment using satellite remote sensing. Arctic 56:147–158

    Google Scholar 

  • Crittenden PD (2000) Aspects of the ecology of mat-forming lichens. Rangifer 20(2):127–139

    Google Scholar 

  • Crow WT, Zhan X (2007) Continental-scale evaluation of remotely sensed soil moisture products. IEEE Geosci Remote Sens Lett 4:451–455

    Google Scholar 

  • Culvenor DS (2002) TIDA: an algorithm for delineation of tree crowns in high spatial resolution remotely sensed imagery. Comput Geosci 28:33–44

    Google Scholar 

  • Dahdouh-Guebas F, Collin S, Lo SD, Ronnback P, Depommier D, Ravishankar T, Koedam N (2006) Analysing ethnobotanical and fishery related importance of mangroves of the East-Godavari Delta (Andhra Pradesh, India) for conservation and management purposes. J Ethnobiol Ethnomed 2(1):1–22

    Google Scholar 

  • Dahlberg U (2001) Quantification and classification of Scandinavian mountain vegetation based on field data and optical satellite images. Licentiate thesis, Report 12. Umeå: Swedish University of Agricultural Sciences, Department of Forest Resource Management and Geomatics, 82 pp

    Google Scholar 

  • Dalponte M, Bruzzone L, Vescovo L, Gianelle D (2009) The role of spectral resolution and classifier complexity in the analysis of hyperspectral images of forest areas. Remote Sens Environ 113:2345–2355

    Google Scholar 

  • de Garzon MB, Dios RS, Ollero HS (2007) Predictive modelling of tree species distributions on the Iberian Peninsula during the last glacial maximum and mid-Holocene. Ecography 30:120–134

    Google Scholar 

  • Dees M, Straub C, Koch B (2012) Can biodiversity study benefit from information on the vertical structure of forests? Utility of LiDAR remote sensing. Curr Sci 102(8):25

    Google Scholar 

  • DeFries R, Hansen A, Newton AC, Hansen MC (2005) Increasing isolation of protected areas in tropical forests over the past twenty years. Ecol Appl 15:19–26

    Google Scholar 

  • Dhar U (2000) Prioritization of conservation sites in the timberline zone of West Himalaya. In: Singh S, Sastry ARK, Mehta R, Uppal V (eds) Setting biodiversity conservation priorities for India. BCPP Process Document WWF India, New Delhi, pp 193–211

    Google Scholar 

  • Diniz-Filho JAF, Nabout JC, Bini LM, Soares TN, Campos Telles MP, Marco P, Collevatti RG (2009) Niche modelling and landscape genetics of Caryocar brasiliense (Pequi tree, Caryocaraceae) in Brazilian Cerrado. Tree Genet Genomes 5(4):617–627. ISSN 1614-2942

    Google Scholar 

  • Dudley N, Stolton S, Belokurov A, Krueger L, Lopoukhine N, MacKinnon K, Sandwith T, Sekhran N (2010) Natural solutions: protected areas helping people cope with climate change. IUCNWCPA, TNC, UNDP, WCS, The World Bank and WWF, Gland, Washington DC, p 130

    Google Scholar 

  • Duncanson LI, Niemann KO, Wulder MA (2010) Estimating forest canopy height and terrain relief from GLAS waveform metrics. Remote Sens Environ 114:138–145

    Google Scholar 

  • Duro D, Coops NC, Wulder MA, Han T (2007) Development of a large area biodiversity monitoring system driven by remote sensing. Prog Phys Geogr 31:235–260

    Google Scholar 

  • Eckert S (2012) Improved forest biomass and carbon estimations using texture measures from WorldView-2 satellite data. Remote Sens 4:810–829

    Google Scholar 

  • Edwards JL, Lane MA, Nielsen ES (2000) Interoperability of biodiversity databases: biodiversity information on every desktop. Science 289(5488):2312–2314

    CAS  PubMed  Google Scholar 

  • Engler R, Guisan A, Rechsteiner L (2004) An improved approach for predicting the distribution of rare and endangered species from occurrence and pseudo-absence data. J Appl Ecol 41:263–274

    Google Scholar 

  • Everitt JH, Yang C, Deloach CJ Jr (2006) Remote sensing of giant reed with QuickBird satellite imagery. J Aquat Plant Manage 43:81–85

    Google Scholar 

  • Fagan M, DeFries RS (2009) Measurement and monitoring of the world’s forests: a review and summary of remote sensing technical capability, 2009–2015. Resources for the Future

    Google Scholar 

  • Fairbanks DHK, McGwire KC (2004) Patterns of floristic richness in vegetation communities of California: regional scale analysis with multi-temporal NDVI. Glob Ecol Biogeogr 13:221–235

    Google Scholar 

  • Falkowski MJ, Smith AMS, Hudak AT, Gessler PE, Vierling LA, Crookston NL (2006) Automated estimation of individual conifer tree height and crown diameter via two-dimensional spatial wavelet analysis of lidar data. Can J Remote Sens 32:153–161

    Google Scholar 

  • Falldorf T, Strand O, Panzacchi M, Tømmervik H (2014) Estimating lichen volume and reindeer winter pasture quality from Landsat imagery. Remote Sens Environ 140:573–579

    Google Scholar 

  • Ferrier S, Guisan A (2006) Spatial modelling of biodiversity at the community level. J Appl Ecol 43:393–404

    Google Scholar 

  • Foody GM (2003) Remote sensing of tropical forest environments: towards the monitoring of environmental resources for sustainable development. Int J Remote Sens 24:4035–4046

    Google Scholar 

  • Foody GM (2004) Supervised image classification by MLP and RBF neural networks with and without an exhaustively defined set of classes. Int J Remote Sens 25:3091–3104

    Google Scholar 

  • Foody GM (2005) Mapping the richness and composition of British breeding birds from coarse spatial resolution satellite sensor imagery. Int J Remote Sens 26:3943–3956

    Google Scholar 

  • Foody GM, Cutler ME (2006) Mapping the species richness and composition of tropical forests from remotely sensed data with neural networks. Ecol Model 195(1):37–42

    Google Scholar 

  • Foody GM, Mathur A (2004) A relative evaluation of multiclass image classification by support vector machines. IEEE Trans Geosci Remote Sens 42(6):1335–1343

    Google Scholar 

  • Forster M, Kleinschmit B (2008) Object-based classification of Quickbird data using ancillary information for the detection of forest types and NATURA 2000 habitats. In: Blaschke T, Lang S, Hay GJ (eds) Object-based image analysis: spatial concepts for knowledge-driven remote sensing applications. Lecture notes in geoinformation and cartography, Sect. 3. Springer, Berlin, pp 275–290

    Google Scholar 

  • Foster JR, Townsend PA, Zganjar CE (2008) Spatial and temporal patterns of gap dominance by low-canopy lianas detected using EO-1 Hyperion and Landsat thematic mapper. Remote Sens Environ 112(5):2104–2117

    Google Scholar 

  • Franklin SE (1994) Discrimination of subapline forest species and canopy density sing digital CASI, SPOT PLA, and Landsat TM data. Photogram Eng Remote Sens 60:1223–1241

    Google Scholar 

  • Frati L, Caprasecca E, Santoni S, Gaggi C, Guttova A, Gaudino S, Pati A, Rosamilia S, Pirintsos SA, Loppi S (2006) Effects of NO2 and NH2 from road traffic on epiphytic lichens. Environ Pollut 142:58–64

    Google Scholar 

  • Fuller RM, Devereux BJ, Gillings S, Hill RA, Amable GS (2007) Bird distributions relative to remotely sensed habitats in Great Britain: towards a framework for national modeling. J Environ Manage 84:586–605

    PubMed  Google Scholar 

  • Giannini TC, Lira-Saade R, Ayala R, Saraiva AM, Alves dos Santos I (2011) Ecological niche similarities of Peponapis bees and non-domesticated Cucurbita species. Ecol Model 222(12):2011–2018, 0304-3800

    Google Scholar 

  • Gilbert OL (1973) Lichens and air pollution. In: Ahmadjian V, Hale ME (eds) The Lichens. Academic Press, New York, pp 443–472

    Google Scholar 

  • Gilichinsky M, Sandstrom P, Reese H, Kivinen S, Nilsson M (2011) Mapping ground lichens using forest inventory and optical satellite data. Int J Remote Sens 32:455–472

    Google Scholar 

  • Gillespie TW, Foody GM, Rocchini D, Giorgi AP, Saatchi S (2008) Measuring and modeling biodiversity from space. Prog Phys Geogr 32:203–221

    Google Scholar 

  • Gillies RR, Temesgen B (2004) Coupling thermal infrared and visible satellite measurements to infer biophysical variables at the land surface. Thermal Remote Sens Land Surf Process 160–184

    Google Scholar 

  • Giriraj A, Irfan-Ullah M, Ramesh BR, Karunakaran PV, Jentsch A, Murthy MSR (2008) Mapping the potential distribution of Rhododendron arboreum Sm. ssp. nilagiricum (Zenker) Tagg (Ericaceae), an endemic plant using ecological niche modelling. Curr Sci 94:12

    Google Scholar 

  • Giriraj A, Murthy MSR, Ramesh BR, Dutt CBS (2009) A method for assessing evergreen habitats using phytodiversity and geospatial techniques in tropical rain forests of Southern Western Ghats (India). Ecol Res 24:749–760

    Google Scholar 

  • Gombert S, Asta J, Seaward MRD (2003) Correlation between the nitrogen concentration of two epiphytic lichens and the traffic density in an urban area. Environ Pollut 123:281–290

    CAS  PubMed  Google Scholar 

  • Gottschalk TK, Huettmann F, Ehler M (2005) Thirty years of analyzing and modeling avian habitat relationships, using satellite imagery: a review. Int J Remote Sens 26:2631–2656

    Google Scholar 

  • Gould W (2000) Remote sensing of vegetation, plant species richness, and regional biodiversity hotspots. Ecol Appl 10(186):187

    Google Scholar 

  • Graham CH, Hijmans RJ (2006) A comparison of methods for mapping species ranges and species richness. Glob Ecol Biogeogr 15:578–587

    Google Scholar 

  • Guerschman JP, Hill MJ, Renzullo LJ, Barrett DJ, Marks AS, Botha EJ (2009) Estimating fractional cover of photosynthetic vegetation, non-photosynthetic vegetation and bare soil in the Australian tropical savanna region upscaling the EO-1 Hyperion and MODIS sensors. Remote Sens Environ 113:928–945

    Google Scholar 

  • Guisan A, Thuiller W (2005) Predicting species distribution: offering more than simple habitat models. Ecol Lett 8:993–1009

    Google Scholar 

  • Gupta S, Porwal MC, Roy PS (2004) Human modification of the tropical rain forest of Nicobar Islands: indicators from land use land cover mapping. J Hum Ecol 16(3):163–171

    Google Scholar 

  • Hamann ML, Wang TL (2006) Potential effects of climate change on ecosystem and tree species distribution in British Columbia. Ecology 87:2773–2786

    PubMed  Google Scholar 

  • He KS, Zhang J (2009) Testing the correlation between beta diversity and differences in productivity among global ecoregions, biomes, and biogeographical realms. Ecol Inform 4:93–98

    Google Scholar 

  • He H, Yang M, Pan Y, Zhu W (2005) Measurement of terrestrial ecosystem service value in China based on remote sensing. In: International geoscience and remote sensing symposium (IGARSS), pp 2965–2968

    Google Scholar 

  • Helmer EH, Lefsky MA, Roberts DA (2009) Biomass accumulation rates of Amazonian secondary forest and biomass of old-growth forests from Landsat time series and the Geoscience Laser Altimeter System. J Appl Remote Sens 3:033505

    Google Scholar 

  • Hirschmugl M, Ofner M, Raggam J, Schardt M (2007) Single tree detection in very high resolution remote sensing data. Remote Sens Environ 110:533–544

    Google Scholar 

  • Holt EA, McCune B, Neitlich P (2008) Spatial scale of GIS derived categorical variables affects their ability to separate sites by community composition. Appl Veg Sci 11(3):421–430

    Google Scholar 

  • Hurtt G, Xiao XM, Keller M, Palace M, Asner GP, Braswell R, Brondizio ES, Cardoso M, Carvalho CJR, Fearon MG, Guild L, Hagen S, Hetrick S, Moore B, Nobre C, Read JM, Sa T, Schloss A, Vourlitis G, Wickel AJ (2003) IKONOS imagery for the large scale biosphere-atmosphere experiment in Amazonia (LBA). Remote Sens Environ 88:111–127

    Google Scholar 

  • Hyyppa J, Wagner W, Hollaus M, Hyyppa H (2009) Airborne laser scanning. In: Warner TA, Nellis MD, Foody GM (eds) The SAGE handbook of remote sensing. SAGE Publications Ltd., London, pp 199–211

    Google Scholar 

  • ICIMOD (International Centre for Integrated Mountain Development) (2010) Climate change impact and vulnerability in the Eastern Himalayas-synthesis report. Kathmandu, Nepal

    Google Scholar 

  • Irfan-Ullah M, Amarnath G, Murthy MSR, Peterson AT (2006) Mapping the geographic distribution of Aglaia bourdillonii Gamble (Meliaceae), an endemic and threatened plant using ecological niche modeling. Biodivers Conserv 16:1917–1925

    Google Scholar 

  • Jensen JR, Im J, Hardin P, Jensen RR (2009) Image classification. In: Warner TA, Nellis MD, Foody GM (eds) The SAGE handbook of remote sensing. SAGE Publications Ltd., London, pp 269–281

    Google Scholar 

  • Jha CS, Goparaju L, Tripathi A, Gharai B, Raghubanshi AS, Singh JS (2005) Forest fragmentation and its impact on species diversity: an analysis using remote sensing and GIS. Biodivers Conserv 14:1681–1698

    Google Scholar 

  • Joseph S, Murthy MSR, Thomas AP (2011) The progress on remote sensing technology in identifying tropical forest degradation: a synthesis of the present knowledge and future perspectives. Environ Earth Sci 64(3):731–741

    Google Scholar 

  • Joshi PK, Rawat GS, Padaliya H, Roy PS (2005) Land use/land cover identification in an alpine and arid region (Nubra Valley, Ladakh) using satellite remote sensing. J Indian Soc Remote Sens 22:371–380

    Google Scholar 

  • Kamat DS (1986) An integrated approach to remote sensing studies for wildlife habitat evaluation. In: Proceedings of seminar-cum-workshop on wildlife habitat evaluation using remote sensing techniques, Dehradun, pp 165–182

    Google Scholar 

  • Kandwal R, Jeganathan C, Tolpekin V, Kushwaha SPS (2009) Discriminating the invasive species, lantana using vegetation indices. J Indian Soc Remote Sens 37:275–290

    Google Scholar 

  • Kanniah KD (2011) Worldview-2 remote sensing data for tropical mangrove species classification. Research report submitted to DigitalGlobe incorporated, USA for the WorldView-2, 8-Bands Research Challenge. Longmont, CO, DigitalGlobe

    Google Scholar 

  • Kapusta P, Szarek-Lukaszewska G, Kiszka J (2004) Spatial analysis of lichen species richness in a disturbed ecosystem (Niepolomice Forest, S Poland). Lichenologist 36(3–4):249–260

    Google Scholar 

  • Karnieli A, Kokaly R, West NE, Clark RN (2001) Remote sensing of biological soil crusts. In: Belnap J, Lange OL (eds) Biological soil crusts: structure, function and management. Springer, Berlin, pp 431–455

    Google Scholar 

  • Kellndorfer J, Walker W, Nepstad D, Stickler C, Brando P, Lefebvre P, Rosenqvist A, Shimada M (2008) Implementing REDD: the potential of ALOS/PALSAR for forest mapping and monitoring. Paper presented at the second GEOSS Asia-Pacific symposium, Tokyo, Japan

    Google Scholar 

  • Keramitsoglou I, Kontoes C, Sykioti O, Sifakis N, Xofis P (2008) Reliable, accurate and timely forest mapping for wildfire management using ASTER and Hyperion satellite imagery. For Ecol Manage 255:3556–3562

    Google Scholar 

  • Kerr JT, Ostrovsky M (2003) From space to species: ecological applications for remote sensing. Trends Ecol Evol 18(6):299–305

    Google Scholar 

  • Kerr JT, Southwood TRE, Cihlar J (2001) Remotely sensed habitat diversity predicts butterfly species richness and community similarity in Canada. Proc Natl Acad Sci USA 98:11365–11370

    CAS  PubMed Central  PubMed  Google Scholar 

  • Kimothi MM, Anitha D, Vasistha HB, Soni P, Chandola SK (2010) Remote sensing to map the invasive weed, Lantana camara in forests. Trop Ecol 51:67–74

    Google Scholar 

  • Kiran Chand TR, Badarinath KVS, Krishna Prasad V, Murthy MSR, Elvidge CD, Tuttle BT (2006) Monitoring forest fires over the Indian region using defense meteorological satellite program-operational linescan system nighttime satellite data. Remote Sens Environ 103(2):165–178

    Google Scholar 

  • Koch B, Heyder U, Weinacker H (2006) Detection of individual tree crowns in airborne lidar data. Photogram Eng Remote Sens 72:357–363

    Google Scholar 

  • Krishna PH, Reddy CS (2012) Assessment of increasing threat of forest fires in Rajasthan, India using multi-temporal remote sensing data (2005–2010). Curr Sci 102(10) (00113891)

    Google Scholar 

  • Kuliyev AN (1977) The effect of the dust pollution to tundra vegetation in Vorkuta outskirts (the eastern part of the Bolshezemelskaya Tundra). In: Syroyechkovskiy YeYe (ed) Scientific fundamentals of nature protection, Moscow, pp 22–28

    Google Scholar 

  • Kuliyev AN (1979) A study of the dust pollution effects to tundra vegetation in Vorkuta outskirts. Syroyechkovskiy YeYe (ed) The influence of human activities on natural ecosystems, Moscow, pp 60–66

    Google Scholar 

  • Kuliyev AN, Lobanov VA (1978) Distribution of dust pollution in Vorkuta outskirts. In: Syroyechkovskiy YeYe (ed) The influence of human activities on natural ecosystems, Moscow, pp 81–89

    Google Scholar 

  • Kumar S, Stohlgren TJ (2009) Maxent modeling for predicting suitable habitat for threatened and endangered tree Canacomyrica monticola in New Caledonia. J Ecol Nat Environ 1:94–98

    Google Scholar 

  • Kumar A, Ghosh SK, Dadhwal VK (2007) Full fuzzy land cover mapping using remote sensing data based on fuzzy c-means and density estimation. Can J Remote Sens 33(2):81–87

    Google Scholar 

  • Landenberger RE, McGraw JB, Warner TA, Brandtberg T (2003) Potential of digital color imagery for censusing Haleakala silverswords in Hawaii. Photogram Eng Remote Sens 69:915–923

    Google Scholar 

  • Lattman H, Bergman KO, Rapp M, Talle M, Westerberg L, Milberg P (2014) Decline in lichen biodiversity on oak trunks due to urbanization. Nord J Bot 32(4):518–528

    Google Scholar 

  • Lee Z, Casey B, Arnone R, Weidemann A, Parsons R, Montes MJ, Gao BC, Goode W, Davis CO, Dye J (2007) Water and bottom properties of a coastal environment derived from Hyperion data measured from the EO-1 spacecraft platform. J Appl Remote Sens 1:011502

    Google Scholar 

  • Lefsky MA (2010) A global forest canopy height map from the Moderate Resolution Imaging Spectroradiometer and the Geoscience Laser Altimeter System. Geophys Res Lett 37:L15401

    Google Scholar 

  • Lefsky MA, Keller M, de Pang Y, Camargo PB, Hunter MO (2007) Revised method for forest canopy height estimation from geoscience laser altimeter system waveforms. J Appl Remote Sens 1:013537

    Google Scholar 

  • Leidner AK, Turner W, Pettorelli N, Leimgruber P, Wegmann M (2012) Satellite remote sensing for biodiversity research and conservation applications: A Committee on Earth Observation Satellites (CEOS) workshop. http://remote-sensing-biodiversity.org/images/workshops/ceos/CEOS_SBA_Biodiversity_WorkshopReport_Oct2012_DLR_Munich.pdf

  • Lele N, Joshi PK (2009) Analyzing deforestation rates, spatial forest cover changes and identifying critical areas of forest cover changes in north-east India during 1972–1999. Environ Monit Assess 156:159–170

    PubMed  Google Scholar 

  • Levin N, Shimida A, Levanoni O, Tamari H, Kark S (2007) Predicting mountain plant richness and rarity from space using satellite-derived vegetation indices. Divers Distrib 13:1–12

    Google Scholar 

  • Leyequien E, Verrelst J, Slot M, Schaepman-Strub G, Heitkonig IMA, Skidmore A (2007) Capturing the fugitive: applying remote sensing to terrestrial animal distribution and diversity. Int J Appl Earth Obs Geoinf 9:1–20

    Google Scholar 

  • Li J, Chen W (2005) A rule-based method for mapping Canada’s wetlands using optical, radar, and DEM data. Int J Remote Sens 26:5051–5069

    Google Scholar 

  • Liebhold AM, Gurevitch J (2002) Integrating the statistical analysis of spatial data in ecology. Ecography 25:553–557

    Google Scholar 

  • Lim K, Treitz P, Wulder M, St-Onge B, Flood M (2008) LIDAR remote sensing of forest structure. Prog Phys Geogr 27:88–106

    Google Scholar 

  • Lindenmayer DB, Gibbons P, Bourke MAX, Burgman M, Dickman CR, Ferrier S, Zerger A (2012) Improving biodiversity monitoring. Aust Ecol 37(3):285–294

    Google Scholar 

  • Loarie SR, Joppa LN, Pimm SL (2008) Satellites miss environmental priorities: response to Loveland et al. and Kark et al. Trends Ecol Evol 23(4):183–184

    Google Scholar 

  • Lopez-Lopez P, Garcia-Ripolles C, Aguilar J, Garcia-Lopez F, Verdejo J (2006) Modelling breeding habitat preferences of Bonelli’s eagle (Hieraaetus fasciatus) in relation to topography, disturbance, climate and land use at different spatial scales. J Ornithol 147:97–106

    Google Scholar 

  • Loppi S (1996) Lichens as bioindicators of geothermal air pollution in central Italy. Bryologist 99(1):41–48

    Google Scholar 

  • Lorenzen ED, Nogués-Bravo D, Orlando L, Weinstock J, Binladen J, Marske KA, Ugan A, Borregaard MK, Gilbert MTP, Nielsen R, Ho SYW, Goebel T, Graf KE, Byers D, Stenderup JT, Rasmussen M, Campos PF, Leonard JA, Koepfli K-P, Froese D, Zazula G, Stafford TW Jr, Aaris-Sørensen K, Batra P, Haywood AM, Singarayer JS, Valdes PJ, Boeskorov G, Burns JA, Davydov SP, Haile J, Jenkins DL, Kosintsev P, Kuznetsova T, Lai X, Martin LD, McDonald HG, Mol D, Meldgaard M, Munch K, Stephan E, Sablin M, Sommer RS, Sipko T, Scott E, Suchard MA, Tikhonov A, Willerslev R, Wayne RK, Cooper A, Hofreiter M, Sher A, Shapiro B, Rahbek C, Willerslev E (2011) Species-specific responses of late quaternary megafauna to climate and humans. Nature 479:359–364

    CAS  PubMed Central  PubMed  Google Scholar 

  • Lu D, Weng Q (2007) A survey of image classification methods and techniques for improving classification performance. Int J Remote Sens 28:823–870

    Google Scholar 

  • Lucas KL, Carter GA (2008) The use of hyperspectral remote sensing to assess vascular plant species richness on Horn Island, Mississippi. Remote Sens Environ 112:3908–3915

    Google Scholar 

  • Lucas R, Rowlands A, Brown A, Keyworth S, Bunting P (2007) Rule-based classification of multi-temporal satellite imagery for habitat and agricultural land cover mapping. ISPRS J Photogram Remote Sens 62:165–185

    Google Scholar 

  • Lucas R, Medcalf K, Brown A, Bunting P, Breyer J, Clewley D, Key-worth S, Blackmore P (2011) Updating the phase 1 habitat map of Wales UK, using satellite sensor data. ISPRS J Photogram Remote Sens 66:81–102

    Google Scholar 

  • Luoto M, Kuussaari M, Toivonen T (2002) Modelling butterfly distribution based on remote sensing data. J Biogeogr 29:1027–1037

    Google Scholar 

  • Luoto M, Virkkala R, Heikkinen RK (2007) The role of land cover in bioclimatic models depends on spatial resolution. Glob Ecol Biogeogr 16:34–42

    Google Scholar 

  • Mildrexler DJ, Zhao MS, Heinsch FA, Running SW (2007) A new satellite-based methodology for continental-scale disturbance detection. Ecol Appl 17:235–250

    PubMed  Google Scholar 

  • Moerman DE, Estabrook GF (2006) The botanist effect: counties with maximal species richness tend to be home to universities and botanists. J Biogeogr 33:1969–1974

    Google Scholar 

  • Mokany K, Ferrier S (2011) Predicting impacts of climate change on biodiversity: a role for semi-mechanistic community-level modelling. Divers Distrib 17:374–380

    Google Scholar 

  • Mukhopadhyay A, Maulik U (2009) Unsupervised pixel classification in satellite imagery using multiobjective fuzzy clustering combined with SVM classifier. IEEE Trans Geosci Remote Sens 47(4):1132–1138

    Google Scholar 

  • Muldavin EH, Neville P, Harper G (2001) Indices of grassland biodiversity in the Chihuahuan Desert ecoregion derived from remote sensing. Conserv Biol 15:844–855

    Google Scholar 

  • Nagendra H (2001) Using remote sensing to assess biodiversity. Int J Remote Sens 22:2377–2400 (NRSA, 2007)

    Google Scholar 

  • Nagendra H (2008) Do parks work? Impact of protected areas on land cover clearing. AMBIO J Human Environ 37(5):330–337

    Google Scholar 

  • Nagendra H, Gadgil M (1999) Biodiversity assessment at multiple scales: linking remotely sensed data with field information. Proc Natl Acad Sci USA 96:9154–9158

    CAS  PubMed Central  PubMed  Google Scholar 

  • Nagendra H, Rocchini D (2008) High resolution satellite imagery for tropical biodiversity studies: the devil is in the detail. Biodivers Conserv 17:3431–3442

    Google Scholar 

  • Nagendra H, Rocchini D, Ghate R (2010) Beyond parks as monoliths: spatially differentiating park-people relationships in the Tadoba Andhari Tiger Reserve in India. Biol Conserv 143:2900–2908

    Google Scholar 

  • Nagendra H, Lucas R, Honrado JP, Jongman RH, Tarantino C, Adamo M, Mairota P (2013) Remote sensing for conservation monitoring: assessing protected areas, habitat extent, habitat condition, species diversity, and threats. Ecol Ind 33:45–59

    Google Scholar 

  • Nandy S, Kushwaha SPS (2010) Study on the utility of IRS 1D LISS-III data and the classification techniques for mapping of Sunderban mangroves. J Coast Conserv 15(1):123–137

    Google Scholar 

  • Nash T (ed) (1996) Lichen biology. Cambridge University Press, Cambridge

    Google Scholar 

  • Nativi S, Mazzettia P, Saarenma H, Kerr J, Tuama ÉÓ (2009) Biodiversity and climate change use scenarios framework for the GEOSS interoperability pilot process. Ecol Inf 4:23–33

    Google Scholar 

  • Nelson PR, Roland C, Macander MJ, McCune B (2013) Detecting continuous lichen abundance for mapping winter caribou forage at landscape spatial scales. Remote Sens Environ 137:43–54

    Google Scholar 

  • Nielson RM, McDonald LL, Sullivan JP, Burgess C, Johnson DS, Johnson DH, Bucholtz S, Hyberg S, Howlin S (2008) Estimating the response of Ringnecked Pheasants (Phasianus colchicus) to the conservation reserve program. Auk 125:434–444

    Google Scholar 

  • Nimis PL (1990) Air quality indicators and indices: the use of plants as bioindicators for monitoring air pollution. EUR 13060:93–126

    Google Scholar 

  • Nimis PL, Scheidegger C, Wolseley PA (2002) Monitoring with lichens-monitoring lichens. Springer, Netherlands, pp 1–4

    Google Scholar 

  • Nordberg ML (1998) Vegetation and biomass changes in mountainous areas in Sweden using satellite and airborne imaging scanner data. ISRSE/NSC. In: Proceedings for the 27th international symposium on remote sensing of environment, Tromso, Norway, pp 431–435

    Google Scholar 

  • Nordberg ML, Allard A (2002) A remote sensing methodology for monitoring cover. Can J Remote Sens 28:262–274

    Google Scholar 

  • Nosetto MD, Jobbagy EG, Paruelo JM (2005) Land-use change and water losses: the case of grassland afforestation across a soil textural gradient in central Argentina. Glob Change Biol 11:1101–1117

    Google Scholar 

  • Nylander W (1866) Les lichens du Jardin de Luxembourg (Lichens from the Luxembourg Gardens)

    Google Scholar 

  • O’Neill AL (1994) Reflectance spectra of microphytic soil crusts in semi-arid Australia. Int J Remote Sens 15:675–681

    Google Scholar 

  • Oindo BO, Skidmore AK (2002) Interannual variability of NDVI and species richness in Kenya. Int J Remote Sens 23:285–298

    Google Scholar 

  • Oldeland J, Wesuls D, Rocchini D, Schmidt M, Jurgens N (2010) Does using species abundance data improve estimates of species diversity from remotely sensed spectral heterogeneity? Ecol Ind 10:390–396

    Google Scholar 

  • Oliver I, Pik A, Britton D, Dangerfield JM, Colwell RK, Beattie AJ (2000) Virtual biodiversity assessment systems. Bioscience 50:441–449

    Google Scholar 

  • Olthof I, Pouliot D, Latifovic R, Chen W (2008) Recent (1986–2006) vegetation-specific NDVI trends in northern Canada from satellite data. Arctic 61(4):381–394

    Google Scholar 

  • Omar H (2010) Commercial timber tree species identification using multispectral Worldview-2 data. Research report submitted to DigitalGlobe Incorporated, USA for the WorldView-2, 8-Bands Research Challenge. DigitalGlobe, Longmont

    Google Scholar 

  • Palmer MW, Earls P, Hoagland BW, White PS, Wohlgemuth T (2002) Quantitative tools for perfecting species lists. Environmetrics 13:121–137

    Google Scholar 

  • Panigrahy S, Anitha D, Kimothi MM, Singh SP (2010) Timberline change detection using topographic map and satellite imagery. Trop Ecol 51:87–91

    Google Scholar 

  • Panwar HS (1986) Forest cover mapping for planning tiger corridors between Kanha and Bandhavgarh—a proposed project. In: Proceedings of seminar-cum-workshop wildlife habitat evaluation using remote sensing techniques, IIRS Dehradun, pp 209–212

    Google Scholar 

  • Pautasso M, McKinney ML (2007) The botanist effect revisited: plant species richness, county area, and human population size in the United States. Conserv Biol 21:1333–1340

    PubMed  Google Scholar 

  • Pavoine S, Vela E, Gachet S, Belair G, Bonsall MB (2011) Linking patterns in phylogeny, traits, abiotic variables and space: a novel approach to linking environmental filtering and plant community assembly. J Ecol 99(1):165–175. ISSN 1365-2745

    Google Scholar 

  • Pearson RG, Dawson TP (2003) Predicting the impacts of climate change on the distribution of species: are bioclimate envelope models useful? Glob Ecol Biogeogr 12:361–371

    Google Scholar 

  • Pennington DD (2007) Exploratory modelling of forest disturbance scenarios in central Oregon using computational experiments in GIS. Ecol Inf 2:387–403

    Google Scholar 

  • Perotto-Baldivieso HL, Melendez-Ackerman E, Garcia MA, Leimgruber P, Cooper SM, Martinez A, Calle P, Ramos Gonzales OM, Quinones M, Christen CA, Pons G (2009) Spatial distribution, connectivity, and the influence of scale: habitat availability for the endangered Mona Island rock iguana. Biodivers Conserv 18:905–917

    Google Scholar 

  • Perry JN, Liebhold AM, Rosenberg MS, Dungan J, Miriti M, Jakomulska A, Citron-Pousty S (2002) Illustrations and guidelines for selecting statistical methods for quantifying spatial pattern in ecological data. Ecography 25:578–600

    Google Scholar 

  • Peterson AT, Sánchez-Cordero V, Martínez-Meyer E, Navarro-Sigüenza AG (2006) Tracking population extirpations via melding ecological niche modeling with land-cover information. Ecol Model 195:229–236

    Google Scholar 

  • Petropoulos G, Carlson TN, Wooster MJ, Islam S (2009) A review of Ts/VI remote sensing based methods for the retrieval of land surface energy fluxes and soil surface moisture. Prog Phys Geogr 33:224–250

    Google Scholar 

  • Petzold DE, Goward SN (1988) Reflectance spectra of subarctic lichens. Remote Sens Environ 24:481–492

    Google Scholar 

  • Pfeifer M, Disney M, Quaife T, Marchant R (2011) Terrestrial ecosystems from space: a review of earth observation products for macroecology applications. Glob Ecol Biogeogr. doi:10.1111/j.1466-8238.2011.00712

  • Pflugmacher D, Cohen W, Kennedy R, Lefsky M (2008) Regional applicability of forest height and aboveground biomass models for the Geoscience Laser Altimeter System. For Sci 54:647–657

    Google Scholar 

  • Phillips OL, Martínez RV, Vargas PN, Monteagudo AL, Zans MEC, Galiano WG, Pena Cruz A, Timana M, Yli-Halla M, Rose S (2003) Efficient plot-based floristic assessment of tropical forests. J Trop Ecol 19:629–45

    Google Scholar 

  • Pignatti S, Cavalli RM, Cuomo V, Fusilli L, Pascucci S, Poscolieri M, Santini F (2009) Evaluating Hyperion capability for land cover mapping in a fragmented ecosystem: Pollino National Park, Italy. Remote Sens Environ 113:622–634

    Google Scholar 

  • Pinho P, Augusto S, Martins-Loução M, Pereira MJ, Soares A, Máguas C, Branquinho C (2008) Causes of change in nitrophytic and oligotrophic lichen species in a Mediterranean climate: impact of land cover and atmospheric pollutants. Environ Pollut 154:380–389

    Google Scholar 

  • Pitkanen J (2001) Individual tree detection in digital aerial images by combining locally adaptive binarization and local maxima methods. Can J For Res 31:832–844

    Google Scholar 

  • Planning Commission, Government of India (2006) Report of task force on the mountain ecosystem: environmental and forest sector. Planning Commission India, New Delhi

    Google Scholar 

  • Plourde LC, Ollinger SV, Smith ML, Martin ME (2007) Estimating species abundance in a northern temperate forest using spectral mixture analysis. Photogram Eng Remote Sens 73:829–840

    Google Scholar 

  • Porwal MC, Sharma L, Roy PS (2003) Stratification and mapping of Ephedra Gerardiana Wall. in Poh (Lahul and Spiti) using remote sensing and GIS. Curr Sci 84:208212

    Google Scholar 

  • Quattrochi DA, Luvall JC (2009) Thermal remote sensing in Earth science research. In: Warner TA, Nellis MD, Foody GM (eds) The SAGE handbook of remote sensing. SAGE Publications Ltd., London, pp 64–78

    Google Scholar 

  • Rahman M, Ullah R, Lan M, Sri Sumantyo JT, Kuze H, Tateishi R (2013) Comparison of Landsat image classification methods for detecting mangrove forests in Sundarbans. Int J Remote Sens 34(4):1041–1056

    Google Scholar 

  • Ravan SA, Roy PS, Sharma CM (1995) Space remote sensing for spatial vegetation characterisation. J Biosci 20:427–438

    Google Scholar 

  • Raxworthy CJ, Martinez-Meyer E, Horning N, Nussbaum RA, Schneider GE, Ortega-Huerta MA, Peterson AT (2003) Predicting distributions of known and unknown reptile species in Madagascar. Science 426:837–841

    CAS  Google Scholar 

  • Read JM, Clark DB, Venticinque EM, Moreira MP (2003) Application of merged 1-m and 4-m resolution satellite data to research and management in tropical forests. J Appl Ecol 40:592–600

    Google Scholar 

  • Reddy CS, Pattanaik C, Murthy MSR (2007) Assessment and monitoring of mangroves of Bhitarkanika Wildlife Sanctuary, Orissa, India using remote sensing and GIS. Curr Sci 92(10):1409–1415

    Google Scholar 

  • Reddy CS, Hari Krishna P, Anitha K, Joseph S (2012) Mapping and inventory of forest fires in Andhra Pradesh, India: current status and conservation needs. ISRN Forest 2012, Article ID 380412

    Google Scholar 

  • Rees WG, Tutubalina OV, Golubeva EI (2004) Reflectance spectra of subarctic lichens between 400 and 2400 nm. Remote Sens Environ 90:281–292

    Google Scholar 

  • Ribeiro MC, Pinho P, Llop E, Branquinho C, Sousa AJ, Pereira MJ (2013) Multivariate geostatistical methods for analysis of relationships between ecological indicators and environmental factors at multiple spatial scales. Ecol Ind 29:339–347

    Google Scholar 

  • Richardson DHS (1991) Lichens as biological indicators - recent developments. In: Jeffrey DW, Madden B (eds) Bioindicators and environmental management. Academic Press, London, pp 263–272

    Google Scholar 

  • Richardson DM, Iponga DM, Roura-Pascual N, Krug RM, Milton SJ, Hughes GO, Thuiller W (2010) Accommodating scenarios of climate change and management in modelling the distribution of the invasive tree Schinus molle in South Africa. Ecography 33:1049–1061

    Google Scholar 

  • Rocchini D (2007) Distance decay in spectral space in analysing ecosystem beta-diversity. Int J Remote Sens 28:2635–2644

    Google Scholar 

  • Rocchini D, Ricotta C (2007) Are landscapes as crisp as we may think? Ecol Model 204:535–539

    Google Scholar 

  • Rocchini D, Ricotta C, Chiarucci A (2007) Using satellite imagery to assess plant species richness: the role of multispectral systems. Appl Veg Sci 10:325–331

    Google Scholar 

  • Rocchini D, He KS, Zhang JT (2009) Is spectral distance a proxy of beta diversity at different taxonomic ranks? A test using quantile regression. Ecol Inf 4:254–259

    Google Scholar 

  • Roy PS (2003) Forest fire and degradation assessment using satellite remote sensing and geographic information system. In: Proceedings of a training workshop satellite remote sensing and GIS applications in agricultural meteorology, pp 361–400

    Google Scholar 

  • Roy PS (2011) Geospatial characterization of biodiversity: need and challenges. ISPRS Archives XXXVIII-8/W20. In: Workshop proceedings on earth observation for terrestrial ecosystem, Bhopal, Nov 8, pp 10–16

    Google Scholar 

  • Roy PS, Tomar S (2000) Biodiversity characterization at landscape level using geospatial modelling technique. Biol Conserv 95(1):95–109

    Google Scholar 

  • Roy PS, Tomar S (2001) Landscape cover dynamics pattern in Meghalaya. Int J Remote Sens 22(18):3813–3825

    Google Scholar 

  • Roy PS, Porwal MC, Sharma L (2001) Mapping of Hyppophae rhamnoides Linn. in the adjoining areas of Kaza in Lahul and Spiti using remote sensing and GIS. Curr Sci 80:1107–1111

    Google Scholar 

  • Roy PS, Kushwaha SPS, Murthy MSR, Roy A, Kushwaha D, Reddy CS, Behera MD, Mathur VB, Padalia H, Saran S, Singh S, Jha CS, Porwal MC (2012) Biodiversity characterisation at landscape level: national assessment, Indian Institute of Remote Sensing, Dehradun, India, p 140. ISBN 81-901418-8-0

    Google Scholar 

  • Roy PS, Murthy MSR, Roy A, Kushwaha SPS, Singh S, Jha CS, Behera MD, Joshi PK, Jagannathan C, Karnatak HC, Saran S, Reddy CS, Kushwaha D, Dutt CBS, Porwal MC, Sudhakar S, Srivastava VK, Padalia H, Nandy S, Gupta S (2013) Forest fragmentation in India. Curr Sci 105(6):774–780

    Google Scholar 

  • Ruoss E (1999) How agriculture affects lichen vegetation in Central Switzerland. Lichenologist 31:63–73

    Google Scholar 

  • Saatchi S, Agosti D, Alger K, Delabie J, Musinsky J (2001) Examining fragmentation and loss of primary forest in Southern Bahian Atlantic forest of Brazil with radar imagery. Conserv Biol 15:867–875

    Google Scholar 

  • Saatchi S, Buermann W, ter Mori S, Steege H, Smith T (2008) Modeling distribution of Amazonian tree species and diversity using remote sensing measurements. Remote Sens Environ 112(5):2000–2017

    Google Scholar 

  • SAC (2001) Report on Grassland mapping in Gujarat using remote sensing and GIS techniques. Space Application Centre (SAC) ISRO, Ahmedabad

    Google Scholar 

  • Sanchez-Hernandez C, Boyd DS, Foody GM (2007a) Mapping specific habitats from remotely sensed imagery: support vector machine and support vector data description based classification of coastal saltmarsh habitats. Ecol Inf 2:83–88

    Google Scholar 

  • Sanchez-Hernandez C, Boyd DS, Foody GM (2007b) One-class classification for mapping a specific land-cover class: SVDD classification of fenland. IEEE Trans Geosci Remote Sens 45:1061–1073

    Google Scholar 

  • Santos X, Brito JC, Sillero N, Pleguezuelos JM, Llorente GA, Fahd S, Parellada X (2006) Inferring habitat-suitability areas with ecological modelling techniques and GIS: a contribution to assess the conservation status of Vipera latastei. Biol Conserv 130:416–425

    Google Scholar 

  • Saran S, Joshi R, Sharma S, Padalia H, Dadhwal VK (2010) Geospatial modeling of brown oak (Quercus semecarpifolia Sm.) habitats in the Kumaun Himalaya under climate change scenario. J Indian Soc Remote Sens 38:534–547

    Google Scholar 

  • Saranya KRL, Reddy CS, Rao PP, Jha CS (2014) Decadal time-scale monitoring of forest fires in Similipal biosphere reserve, India using remote sensing and GIS. Environ Monit Assess 1–14(186):3283–3296

    Google Scholar 

  • Scheidegger C, Goward T (2002) Monitoring lichens for conservation: red lists and conservation action plans. In: Nimis PL, Scheidegger C, Wolseley PA (eds) Monitoring with lichens—monitoring lichens. IV. Earth and environmental science. Kluwer Academic, Dordrecht, pp 163–181

    Google Scholar 

  • Schulman L, Toivonen T, Ruokolainen K (2007) Analysing botanical collecting efforts in Amazonia and correcting for it in species range estimation. J Biogeogr 34:1388–1399

    Google Scholar 

  • Scribner KT, Arntzen JW, Cruddace N, Oldham RS, Burke T (2001) Environmental correlates of toad abundance and population genetic diversity. Biol Conserv 98(2):201–210

    Google Scholar 

  • Seaward MRD (1993) Lichens and sulphur dioxide air pollution: field studies. Environ Rev 1:73–91

    CAS  Google Scholar 

  • Seaward MRD (2004) The use of lichens for environmental impact assessment. Symbiosis 37:293–305

    Google Scholar 

  • Sharma S, Palni LMS, Roy PS (2002) Vegetation fragmentation and anthropogenic disturbance in a Himalayan landscape. Asian J Geoinformatics 12(4):62–69

    Google Scholar 

  • Shippert P (2004) Why use hyperspectral imagery? Photogram Eng Remote Sens 70(4):377–396

    Google Scholar 

  • Simard M, Rivera-Monroy VH, Mancera-Pineda JE, Castaneda-Moya E, Twilley RR (2008) A systematic method for 3D mapping of mangrove forests based on shuttle radar topography mission elevation data, ICEsat/GLAS waveforms and field data: application to Cienaga Grande de Santa Marta, Colombia. Remote Sens Environ 112:2131–2144

    Google Scholar 

  • Singh IJ, Singh SK, Kushwaha SPS, Ashutosh S, Singh RK (2004) Assessment and monitoring of estuarine mangrove forests of Goa using satellite remote sensing. J Indian Soc Remote Sens 32(2):167–174

    Google Scholar 

  • Singh S, Singh TP, Srivastava G (2005) Vegetation cover type mapping in Mouling National Park in Arunachal Pradesh, Eastern Himalayas—an integrated geospatial approach. J Indian Soc Remote Sens 33:547–563

    Google Scholar 

  • Singh JS, Roy PS, Murthy MSR, Jha CS (2010) Application of landscape ecology and remote sensing for assessment, monitoring and conservation of biodiversity. J Indian Soc Remote Sens 38:365–385

    Google Scholar 

  • Skov F, Svenning JC (2004) Potential impact of climatic change on the distribution of forest herbs in Europe. Ecography 27:366–380

    Google Scholar 

  • Spens J, Englund G, Lundqvist H (2007) Network connectivity and dispersal barriers: using geographical information system (GIS) tools to predict landscape scale distribution of a key predator (Esox lucius) among lakes. J Appl Ecol 44(6):1127–1137

    Google Scholar 

  • Stickler CM, Southworth J (2008) Application of a multi-scale spatial and spectral analysis to predict primate occurrence and habitat associations in Kibale National Park, Uganda. Remote Sens Environ 112:2170–2186

    Google Scholar 

  • Store R, Jokimaki J (2003) A GIS-based multi-scale approach to habitat suitability modeling. Ecol Model 169:1–15

    Google Scholar 

  • Subedi MR (2009) Climate change and its potential effects on tree line position: an introduction and analysis. Greenery J Environ Biodivers 7:17–21

    Google Scholar 

  • Sudeesh S, Reddy CS (2013) Forest fire monitoring in Nagarjunasagar-Srisailam Tiger Reserve, Andhra Pradesh, India using geospatial techniques. Natl Acad Sci Lett 36(4):437–446

    Google Scholar 

  • Talukdar G (2004) Geospatial modelling of shifting cultivation induced landscapes of Meghalaya. Doctoral dissertation, PhD thesis

    Google Scholar 

  • Thakur AK, Singh G, Singh S, Rawat GS (2011) Impact of pastoral practices on forest cover and regeneration in the outer fringes of Kedarnath Wildlife Sanctuary, Western Himalaya. J Indian Soc Remote Sens 39:127–134

    Google Scholar 

  • Theau J, Peddle DR, Duguay CR (2005) Mapping lichen in a caribou habitat of Northern Quebec, Canada, using an enhancement-classification method and spectral mixture analysis. Remote Sens Environ 94:232–243

    Google Scholar 

  • Timberlake J, Bayliss J, Alves T, Baena S, Francisco J, Harris T, da Sousa C (2007) The biodiversity and conservation of Mount Chiperone, Mozambique. Report Produced under the Darwin Initiative Award, 15, 036

    Google Scholar 

  • Tommervik H, Johansen ME, Pedersen J, Guneriussen PT (1998) Integration of remote sensed and in-situ data in an analysis of the air pollution effects on terrestrial ecosystems in the border areas between Norway and Russia. Environ Monit Assess 49:51–85

    CAS  Google Scholar 

  • Tommervik H, Hogda KA, Solheim I (2003) Monitoring vegetation changes in Pasvik (Norway) and Pechenga in Kola Peninsula (Russia) using multi-temporal Landsat MSS/TM data. Remote Sens Environ 85:370–388

    Google Scholar 

  • Tuomisto H, Poulsen AD, Ruokolainen K, Moran RC, Quintana C, Celi J, Canas G (2003) Linking floristic patterns with soil heterogeneity and satellite imagery in Ecuadorian Amazonia. Ecol Appl 13:352–371

    Google Scholar 

  • Turner W, Spector S, Gardiner N, Fladeland M, Sterling E, Steininger M (2003) Remote sensing for biodiversity science and conservation. Trends Ecol Evol 18(6):306–314

    Google Scholar 

  • Twele A, Erasmi S, Kappas M (2008) Spatially explicit estimation of leaf area index using EO-1 Hyperion and Landsat ETM+ data: implications of spectral bandwidth and shortwave infrared data on prediction accuracy in a tropical montane environment. GIScience Remote Sens 45:229–248

    Google Scholar 

  • Ulaby FT, Moore RK, Fung AK (1982) Microwave remote sensing, active and passive, II, radar remote sensing and surface scattering and emission theory. Artech House, Norwood

    Google Scholar 

  • Van Der Meer F, Schmidt KS, Bakker W, Bijker W (2002) New environmental remote sensing systems. In: Skidmore A (ed) Environmental modelling with GIS and remote sensing. Taylor & Francis, London, pp 26–51

    Google Scholar 

  • van Herk CM (1999) Mapping of ammonia pollution with epiphytic lichens in the Netherlands. Lichenologist 31:9–20

    Google Scholar 

  • van Herk CM (2001) Bark pH and susceptibility to toxic air pollutants as independent causes of changes in epiphytic lichen composition in space and time. Lichenologist 33:419–441

    Google Scholar 

  • van Herk CM, Aptroot A, van Dobben HF (2002) Long-term monitoring in the Netherlands suggests that lichens respond to global warming. Lichenologist 34:141–154

    Google Scholar 

  • Varshney PK, Arora MK (2004) Advanced image processing techniques for remotely sensed hyperspectral data. Springer, Berlin

    Google Scholar 

  • Virtanen T, Mikkola K, Patova E, Nikula A (2002) Satellite image analysis of human caused changes in the tundra vegetation around the city of Vorkuta, north-European Russia. Environ Pollut 120(3):647–658

    CAS  PubMed  Google Scholar 

  • Vogiatzakis IN, Mannion AM, Griffiths GH (2006) Mediterranean ecosystems: problems and tools for conservation. Prog Phys Geogr 30:175–200

    Google Scholar 

  • Volante JN, Alcaraz-Segura D, Mosciaro MJ, Viglizzo EF, Paruelo JM (2012) Ecosystem functional changes associated with land clearing in NW Argentina. Agric Ecosyst Environ 154:12–22

    Google Scholar 

  • Wabnitz CC, Andrefouet S, Torres-Pulliza D, Muller-Karger FE, Kramer PA (2008) Regional-scale seagrass habitat mapping in the Wider Caribbean region using Landsat sensors: applications to conservation and ecology. Remote Sens Environ 112:3455–3467

    Google Scholar 

  • Walsh SJ, Shao Y, Mena CF, McCleary AL (2008) Integration of Hyperion satellite data and a household social survey to characterize the causes and consequences of reforestation patterns in the northern Ecuadorian Amazon. Photogram Eng Remote Sens 74:725–735

    Google Scholar 

  • Wang L, Sousab WP, Gong P, Biging GS (2004) Comparison of IKONOS and QuickBird images for mapping mangrove species on the Caribbean coast of Panama. Remote Sens Environ 91:432–440

    Google Scholar 

  • Warren DL, Seifert SN (2011) Ecological niche modeling in Maxent: the importance of model complexity and the performance of model selection criteria. Ecol Appl 21(2):335–342

    PubMed  Google Scholar 

  • Waser LT, Keuchler M, Schwarz M, Ivits E, Stofer S, Scheidegger C (2007) Prediction of lichen diversity in an UNESCO biosphere reserve—correlation of high resolution remote sensing data with field samples. Environ Model Assess 12:315–328

    Google Scholar 

  • Whittaker RJ, Araujo MB, Jepson P, Ladle RJ, Watson JEM, Willis KJ (2005) Conservation biogeography: assessment and prospect. Divers Distrib 11:3–23

    Google Scholar 

  • Williams JN, Seo C, Thorne J, Nelson JK, Erwin S, O’Brien JM, Schwartz MW (2009) Using species distribution models to predict new occurrences for rare plants. Divers Distrib 15(4):565–576

    Google Scholar 

  • Willis KJ, Whittaker RJ (2002) Species diversity-scale matters. Science 295:1245–1248

    CAS  PubMed  Google Scholar 

  • Wilson EH, Sader SA (2002) Detection of forest harvest type using multiple dates of Landsat TM imagery. Remote Sens Environ 80:385–396

    Google Scholar 

  • Wilson RJ, Thomas CD, Fox R, Roy DB, Kunin WES (2004) Spatial patterns in species distributions reveal biodiversity change. Nature 432:393–396

    CAS  PubMed  Google Scholar 

  • Wolseley PA, James PW, Theobald MR, Sutton MA (2006) Detecting changes in epiphytic lichen communities at sites affected by atmospheric ammonia from agricultural sources. Lichenologist 38:161–176

    Google Scholar 

  • Xie Y, Sha Z, Yu M (2008) Remote sensing imagery in vegetation mapping: a review. J Plant Ecol 1(1):9–23

    Google Scholar 

  • Yang XQ, Kushwaha SPS, Saran S, Xu J, Roy PS (2013) Maxent modeling for predicting the potential distribution of medicinal plant, Justicia adhatoda L. in Lesser Himalayan foothills. Ecol Eng 51:83–87

    CAS  Google Scholar 

  • Youngentob KN, Wallis IR, Lindenmayer DB, Wood JT, Pope ML, Foley WJ (2011) Foliage chemistry influences tree choice and landscape use of a gliding marsupial folivore. J Chem Ecol 37:71–84

    CAS  PubMed  Google Scholar 

  • Zhang JT, Pennington DD, Liu XH (2007) GBD-explorer: extending open source java GIS for exploring ecoregion-based biodiversity data. Ecol Inf 2:94–102

    Google Scholar 

  • Zhang XY, Feng XZ, Jiang H (2010) Object-oriented method for urban vegetation mapping using IKONOS imagery. Int J Remote Sens 31:177–196

    Google Scholar 

  • Zimmermann HE, Edwards TC Jr, Graham CH, Pearman PB, Svenning JC (2010) New trends in species distribution modelling. Ecography 33(6):985–989 (0906-7590)

    Google Scholar 

Download references

Acknowledgments

Author Mr. Manoj Semwal is thankful to Director, CSIR-CIMAP, Lucknow, for providing the facilities and encouragement.

Author information

Authors and Affiliations

  1. GIS Consultant, JPS Consultants Pvt. Ltd., R-16, Hauz Khas Enclave, New Delhi, 110016, India

    Nupoor Prasad

  2. ICT Department, CSIR—Central Institute of Medicinal and Aromatic Plants, Lucknow, India

    Manoj Semwal

  3. Center for Earth and Space Sciences, University of Hyderabad, Hyderabad, India

    P. S. Roy

Authors
  1. Nupoor Prasad
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Manoj Semwal
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. P. S. Roy
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Nupoor Prasad .

Editor information

Editors and Affiliations

  1. Lichenology Laboratory, CSIR-National Botanical Research Institute, Lucknow, Uttar Pradesh, India

    Dalip Kumar Upreti

  2. Departmento de Biologia Vegetal II Facultad de Farmacia, Universidad Complutense de Madrid, Madrid, Madrid, Spain

    Pradeep K. Divakar

  3. Lichenology Laboratory, CSIR-National Botanical Research Institute, Lucknow, Uttar Pradesh, India

    Vertika Shukla

  4. Lichenology Laboratory, CSIR-National Botanical Research Institute, Lucknow, Uttar Pradesh, India

    Rajesh Bajpai

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer India

About this chapter

Cite this chapter

Prasad, N., Semwal, M., Roy, P.S. (2015). Remote Sensing and GIS for Biodiversity Conservation. In: Upreti, D., Divakar, P., Shukla, V., Bajpai, R. (eds) Recent Advances in Lichenology. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2181-4_7

Download citation

Publish with us

Policies and ethics

Search

Navigation