1,658
Views
70
CrossRef citations to date
0
Altmetric
Original Articles

Quantifying land use/land cover spatio-temporal landscape pattern dynamics from Hyperion using SVMs classifier and FRAGSTATS®

ORCID Icon, ORCID Icon, , , , & show all
Pages 862-878 | Received 26 Oct 2016, Accepted 08 Feb 2017, Published online: 10 Apr 2017

References

  • Anderson JRHE, Roach JT, Witmer RE. 1976. A land use and land cover classification system for use with remote sensor data. Washington, DC: USG Survey.
  • Basto M, Pereira JM. 2012. An SPSS R – menu for ordinal factor analysis. J Statist Software. 46. doi: http://dx.doi.org/10.18637/jss.v046.i04.
  • Bazi Y, Melgani F. 2006. Toward an optimal SVM classification system for hyperspectral remote sensing images. IEEE Trans Geosci Remote Sens. 44:3374–3385, November.10.1109/TGRS.2006.880628
  • Beck R. 2003. EO-1 User Guide v. 2.3. Sioux Falls: Department of Geography University of Cincinnati.
  • Bissonette JA. 2008. Habitat fragmentation and landscape change: an ecological and conservation synthesis David B. Lindenmayer and Joern Fischer. 2006. Washington, DC: Island Press. Cloth $80.00, ISBN: 1-59726-020-7. Paper, $39.95. ISBN:1-59726-021-5. 352 pages. Ecological Restoration. 2008/05/13;26:162–164.
  • Bonan GB, Levis S, Kergoat L, Oleson KW. 2002. Landscapes as patches of plant functional types: an integrating concept for climate and ecosystem models. Global Biogeochem Cycles. May 22;16:5-1-5-23.
  • Borak JS. 1999. Feature selection and land cover classification of a MODIS-like data set for a semiarid environment. Int J Remote Sens. Jan;20:919–938.10.1080/014311699212993
  • Burges C. 1998. A tutorial on support vector machines for pattern recognition. Data Min Knowl Discov. 2:121–167.
  • Çakir G, Sivrikaya F, Keleş S. 2007. Forest cover change and fragmentation using Landsat data in Maçka State Forest Enterprise in Turkey. Environ Monit Assess. May 23;137:51–66.
  • Congalton R, Green K. 1998. Assessing the accuracy of remotely sensed data. In: Mapping science. CRC Press; p. 2154–7181. doi: http://dx.doi.org/10.1201/9781420048568.
  • Deng JS, Wang K, Hong Y, Qi JG. 2009. Spatio-temporal dynamics and evolution of land use change and landscape pattern in response to rapid urbanization. Landscape Urban Plann. Sep;92:187–198.10.1016/j.landurbplan.2009.05.001
  • Elatawneh A, Kalaitzidis C, Petropoulos GP, Schneider T. 2014. Evaluation of diverse classification approaches for land use/cover mapping in a Mediterranean region utilizing Hyperion data. Int J Digital Earth. 7:194–216. doi: 10.1080/17538947.2012.671378.
  • Elkie PC, Rempel RS, Carr AP. 1999. Patch analyst user’s manual: a tool for quantifying landscape structure. Ontario, Canada.
  • ENVI. 2008. ENVI user’s manual. Boulder (CO): ITT Visual Information Solutions.
  • Fahrig L. 1997. Relative effects of habitat loss and fragmentation on population extinction. J Wildlife Manage. Jul;61:603–610. doi: http://dx.doi.org/10.2307/3802168.10.2307/3802168
  • Fauvel M, Chanussot J, Benediktsson JA. 2006. Evaluation of kernels for multiclass classification of hyperspectral remote sensing data. Proceedings of the 2006 IEEE International Conference on Acoustics Speech and Signal Processing Proceedings; 2006 14–19 May 2006.
  • Foody GM, Mathur A. 2004. A relative evaluation of multiclass image classification by support vector machines. IEEE Trans Geosci Remote Sens. Jun;42:1335–1343.10.1109/TGRS.2004.827257
  • Galvão LS, Formaggio AR, Tisot DA. 2005. Discrimination of sugarcane varieties in Southeastern Brazil with EO-1 Hyperion data. Remote Sens Environ. Feb;94:523–534.10.1016/j.rse.2004.11.012
  • Herold M, Liu X, Clarke KC. 2003. Spatial metrics and image texture for mapping urban land use. Photogrammet Eng Remote Sens. Sep 1;69:991–1001.10.14358/PERS.69.9.991
  • Huang C, Song K, Kim S, Townshend JRG, Davis P, Masek JG, Goward SN. 2008. Use of a dark object concept and support vector machines to automate forest cover change analysis. Remote Sens Environ. Mar;112:970–985.10.1016/j.rse.2007.07.023
  • Jaeger JAG. 2000. Landscape division, splitting index, and effective mesh size: new measures of landscape fragmentation. Landscape Ecol. 15:115–130.
  • Jolliffe IT. 1986. Principal component analysis and factor analysis. In: Principal component analysis. New York (NY): Springer Science + Business Media; p. 115–128.10.1007/978-1-4757-1904-8
  • JRC-EEA. 2005. CORINE land cover updating for the year 2000. Image 2000 and CLC 2000. In: Lima V, editor. Products and methods ( Report EUR 21757 EN). JRCIspra.
  • Kamusoko C, Aniya M. 2007. Land use/cover change and landscape fragmentation analysis in the Bindura District, Zimbabwe. Land Degrad Dev. 18:221–233.10.1002/(ISSN)1099-145X
  • Karamesouti M, Petropoulos GP, Papanikolaou ID, Kairis O, Kosmas K. 2016. Erosion rate predictions from PESERA and RUSLE at a Mediterranean site before and after a wildfire: comparison & implications. Geoderma. Jan;261:44–58.10.1016/j.geoderma.2015.06.025
  • Kuemmerle T, Chaskovskyy O, Knorn J, Radeloff VC, Kruhlov I, Keeton WS, Hostert P. 2009. Forest cover change and illegal logging in the Ukrainian Carpathians in the transition period from 1988 to 2007. Remote Sens Environ. Jun 15;113:1194–1207.10.1016/j.rse.2009.02.006
  • Lamine S, Petropoulos GP. 2013. Evaluation of the spectral angle mapper “SAM” classification technique using hyperion imagery. Proceedings of the European Space Agency Living Planet Symposium; 2013 September; UK: The University of Nottingham.
  • Latifovic R, Fytas K, Chen J, Paraszczak J. 2005. Assessing land cover change resulting from large surface mining development. Int J Appl Earth Observ Geoinf. May;7:29–48.10.1016/j.jag.2004.11.003
  • Li D-C, Liu C-W. 2010. A class possibility based kernel to increase classification accuracy for small data sets using support vector machines. Expert Syst Appl. Apr;37:3104–3110.10.1016/j.eswa.2009.09.019
  • Li S, Kwok JTY, Tsang IWH, Wang Y. 2004. Fusing images with different focuses using support vector machines. IEEE Trans Neural Netw. Nov;15:1555–1561.10.1109/TNN.2004.837780
  • Lu D, Weng Q. 2007. A survey of image classification methods and techniques for improving classification performance. Int J Remote Sens. Mar;28:823–870.10.1080/01431160600746456
  • Lu L, Li X, Cheng G. 2003. Landscape evolution in the middle Heihe River Basin of north-west China during the last decade. J Arid Environ. Mar;53:395–408.10.1006/jare.2002.1032
  • Luo Y, Liao M, Yan J, Zhang C. 2012. A multi-features fusion support vector machine method (MF-SVM) for classification of mangrove remote sensing image. J Computat Inf Syst. 8:323–334.
  • MacLean MG, Congalton RG. 2015. A comparison of landscape fragmentation analysis programs for identifying possible invasive plant species locations in forest edge. Landscape Ecol. Feb 20;30:1241–1256.10.1007/s10980-015-0175-7
  • McGarigal K, Cushman S, Ene E. 2012. FRAGSTATS v4: spatial pattern analysis program for categorical and continuous maps. Amherst: University of Massachusetts.
  • Mathur A, Foody GM. 2008. Crop classification by support vector machine with intelligently selected training data for an operational application. Int J Remote Sens. Apr;29:2227–2240.10.1080/01431160701395203
  • Otukei JR, Blaschke T. 2010. Land cover change assessment using decision trees, support vector machines and maximum likelihood classification algorithms. Int J Appl Earth Observ Geoinf. Feb;12:S27–S31.10.1016/j.jag.2009.11.002
  • Pal M, Mather PM. 2006. Some issues in the classification of DAIS hyperspectral data. Int J Remote Sens. Jul 20;27:2895–2916.10.1080/01431160500185227
  • Pengra BW, Johnston CA, Loveland TR. 2007. Mapping an invasive plant, Phragmites australis, in coastal wetlands using the EO-1 Hyperion hyperspectral sensor. Remote Sens Environ. May;108:74–81.10.1016/j.rse.2006.11.002
  • Petropoulos GP, Knorr W, Scholze M, Boschetti L, Karantounias G. 2010. Combining ASTER multispectral imagery analysis and support vector machines for rapid and cost-effective post-fire assessment: a case study from the Greek wildland fires of 2007. Natural Hazards Earth Syst Sci. 10:305–317.10.5194/nhess-10-305-2010
  • Petropoulos GP, Kontoes C, Keramitsoglou I. 2011. Burnt area delineation from a uni-temporal perspective based on Landsat TM imagery classification using support vector machines. Int J Appl Earth Observ Geoinf. Feb;13:70–80.10.1016/j.jag.2010.06.008
  • Petropoulos GP, Kalaitzidis C, Prasad Vadrevu K. 2012. Support vector machines and object-based classification for obtaining land-use/cover cartography from Hyperion hyperspectral imagery. Comput Geosci. Apr;41:99–107.10.1016/j.cageo.2011.08.019
  • Petropoulos GP, Arvanitis K, Sigrimis N. 2012. Hyperion hyperspectral imagery analysis combined with machine learning classifiers for land use/cover mapping. Expert Syst Appl. 39:3800–3809.10.1016/j.eswa.2011.09.083
  • Petropoulos GP, Partsinevelos P, Mitraka Z. 2013. Change detection of surface mining activity and reclamation based on a machine learning approach of multi-temporal Landsat TM imagery. Geocarto Int. 28:323–342. doi:10.1080/10106049.2012.706648.
  • Petropoulos GP, Vadrevu KP, Kalaitzidis C. 2013. Spectral angle mapper and object-based classification combined with hyperspectral remote sensing imagery for obtaining land use/cover mapping in a Mediterranean region. Geocarto Int. Apr;28:114–129.10.1080/10106049.2012.668950
  • Petropoulos GP, Manevski K, Carlson TN. 2014. Hyperspectral remote sensing with emphasis on land cover mapping: from ground to satellite observations. In: Weng Q, editor. Scale issues in remote sensing. Hoboken (NJ): Wiley-Blackwell; p. 285–320. doi:10.1002/9781118801628.ch15.10.1002/9781118801628
  • Petropoulos GP, Kalivas DP, Georgopoulou H, Srivastava PK. 2015. Urban vegetation cover extraction from hyperspectral remote sensing imagery & GIS spatial analysis techniques: the case of Athens, Greece. J Appl Remote Sens. 9:1–18. 0091-3286/2015.
  • 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 of Environ. Mar;113:622–634.10.1016/j.rse.2008.11.006
  • Raines GL. 2002. Description and comparison of geologic maps with FRAGSTATS – a spatial statistics program. Comput Geosci. Mar;28:169–177.10.1016/S0098-3004(01)00030-9
  • Ricketts TH. 2001. The matrix matters: effective isolation in fragmented landscapes. Am Nat. Jul;158:87–99.10.1086/320863
  • Saumitra M, Satyanarayan S, Gupta M, Manoj KP, Chandar S, Sudhir KS, Srivastava PK, Kamalesh KS. 2007. Integrated water resource management using remote sensing and geophysical techniques: aravali quartzite, Delhi, India. J Environ hydrol. 15: 1–10.
  • Sawaya KE, Olmanson LG, Heinert NJ, Brezonik PL, Bauer ME. 2003. Extending satellite remote sensing to local scales: land and water resource monitoring using high-resolution imagery. Remote Sens Environ. Nov;88:144–156.10.1016/j.rse.2003.04.006
  • Singh SK, Srivastava PK, Pandey AC, Gautam SK. 2013a. Integrated assessment of groundwater influenced by a confluence river system: concurrence with remote sensing and geochemical modelling. Water Resour Manage. Jul 7;27:4291–4313.10.1007/s11269-013-0408-y
  • Singh SK, Srivastava PK, Gupta M, Thakur JK, Mukherjee S. 2013b. Appraisal of land use/land cover of mangrove forest ecosystem using support vector machine. Environ Earth Sci. Nov 8;71:2245–2255.
  • Singh SK, Mustak S, Srivastava PK, Szabó S, Islam T. 2015. Predicting spatial and decadal LULC changes through cellular automata markov chain models using earth observation datasets and geo-information. Environ Process. doi: 10.1007/s40710-015-0062-x.
  • Singh SK, Srivastava PK, Szabó S, Petropoulos GP, Gupta M, Islam T. 2016. Landscape transform and spatial metrics for mapping spatiotemporal land cover dynamics using Earth Observation data-sets. Geocarto Int. Jan 25;58:1–15.10.1080/10106049.2015.1130084
  • Srivastava PK, Han D, Rico-Ramirez MA, Bray M, Islam T. 2012. Selection of classification techniques for land use/land cover change investigation. Adv Space Res. Nov;50:1250–1265.10.1016/j.asr.2012.06.032
  • Srivastava PK, Mukherjee S, Gupta M, Islam T. 2014. Remote sensing applications in environmental research. In: Springer, editor. Switzerland: Springer International Publishing. doi:10.1007/978-3-319-05906-8.
  • Szabó S, Bertalan L, Kerekes Á, Novák TJ. 2015. Possibilities of land use change analysis in a mountainous rural area: a methodological approach. Int J Geograph Inf Sci. 30:1–19.
  • Szilassi P, Jordan G, van Rompaey A, Csillag G. 2006. Impacts of historical land use changes on erosion and agricultural soil properties in the Kali Basin at Lake Balaton, Hungary. CATENA. 68:96–108.10.1016/j.catena.2006.03.010
  • Turner M. 1989. Landscape ecology: the effect of pattern on process. Ann Rev Ecol Syst. Jan 1;20:171–197.10.1146/annurev.es.20.110189.001131
  • USGS. 2003. EO-1 user guide v. 2.3. Sioux Falls, SD: USGS-EROS. Available from: https://eo1.usgs.gov/documents/.
  • USGS. 2006. Hyperion level 1gst (L1GST) product output files data format control book (DFCB). Sioux Falls, SD 57198-0001.
  • Vapnik VN. 1998. Statistical learning theory. New York (NY): Wiley.
  • Volpi M, Petropoulo GP, Kanevski M. 2013. Flooding extent cartography with Landsat TM imagery and regularized kernel Fisher’s discriminant analysis. Comput Geosci. 57:24–31. doi:10.1016/j.cageo.2013.03.009.
  • Waldhardt R, Simmering D, Otte A. 2004. Estimation and prediction of plant species richness in a mosaic landscape. Landscape Ecol. 19:211–226.10.1023/B:LAND.0000021722.08588.58
  • Yuan J, Niu Z. 2007. Classification using EO-1 hyperion hyperspectral and ETM data. Fourth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2007). Institute of Electrical & Electronics Engineers (IEEE). doi:10.1109/fskd.2007.218.
  • Zhang L, Huang X. 2010. Object-oriented subspace analysis for airborne hyperspectral remote sensing imagery. Neurocomputing. 73:927–936.10.1016/j.neucom.2009.09.011

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.