메뉴 건너뛰기




Volumn 18, Issue 1, 2014, Pages 63-92

Using spatial data support for reducing uncertainty in geospatial applications

Author keywords

Data support; Mutual information; Sensor networks; Spatial data mining; Time series data

Indexed keywords

COMPUTATION THEORY; COST BENEFIT ANALYSIS; COST EFFECTIVENESS; DIGITAL DEVICES; INFORMATION THEORY; SENSOR NETWORKS; UNCERTAINTY ANALYSIS; VIRTUAL STORAGE; WIRELESS SENSOR NETWORKS;

EID: 84893776842     PISSN: 13846175     EISSN: None     Source Type: Journal    
DOI: 10.1007/s10707-013-0177-z     Document Type: Article
Times cited : (8)

References (34)
  • 1
    • 0002644607 scopus 로고
    • Fast similarity search in the presence of noise, scaling, and translation in time-series databases
    • Agrawal R, Lin K-I, Sawhney SH, Shim K (1995) Fast similarity search in the presence of noise, scaling, and translation in time-series databases, Proceedings of the 21st VLDB Conference, pp. 490-501.
    • (1995) Proceedings of the 21st VLDB Conference , pp. 490-501
    • Agrawal, R.1    Lin, K.-I.2    Sawhney, S.H.3    Shim, K.4
  • 2
    • 0036184573 scopus 로고    scopus 로고
    • Uncertainty propagation in wildland fire behavior modelling
    • Bachmann A, Allgöwer B (2002) Uncertainty propagation in wildland fire behavior modelling. Int J Geogr Inf Sci 16(2): 115-127.
    • (2002) Int J Geogr Inf Sci , vol.16 , Issue.2 , pp. 115-127
    • Bachmann, A.1    Allgöwer, B.2
  • 10
    • 0036557907 scopus 로고    scopus 로고
    • What is the best similarity measure for motion correction in fMRI time series?
    • Freire L, Roche A, Mangin J-F (2002) What is the best similarity measure for motion correction in fMRI time series? IEEE Trans Med Imaging 21(5): 470-484.
    • (2002) IEEE Trans Med Imaging , vol.21 , Issue.5 , pp. 470-484
    • Freire, L.1    Roche, A.2    Mangin, J.-F.3
  • 11
    • 39349101035 scopus 로고    scopus 로고
    • Techniques for computing fitness of use (FoU) for time series datasets with applications in the geospatial domain
    • Fu L, Samal A, Soh L-K (2008) Techniques for computing fitness of use (FoU) for time series datasets with applications in the geospatial domain. GeoInformatica 12(1): 91-115.
    • (2008) GeoInformatica , vol.12 , Issue.1 , pp. 91-115
    • Fu, L.1    Samal, A.2    Soh, L.-K.3
  • 12
    • 33646518088 scopus 로고    scopus 로고
    • Middleware challenges and approaches for wireless sensor networks
    • Hadim S, Mohamed N (2006) Middleware challenges and approaches for wireless sensor networks. IEEE Distrib Syst Online 7(3): 1.
    • (2006) IEEE Distrib Syst Online , vol.7 , Issue.3 , pp. 1
    • Hadim, S.1    Mohamed, N.2
  • 17
    • 84893770856 scopus 로고    scopus 로고
    • Online book, Chapter 8. Retrieved November 30, 2008, from
    • Jones F (2004) Volumes of parallelograms. Online book, Chapter 8. Retrieved November 30, 2008, from http://www. owlnet. rice. edu/~fjones/chap8. pdf.
    • (2004) Volumes of parallelograms
    • Jones, F.1
  • 18
    • 0036209752 scopus 로고    scopus 로고
    • Using process models to improve spatial analysis
    • Laffan SW (2002) Using process models to improve spatial analysis. Int J Geogr Inf Sci 16(3): 245-257.
    • (2002) Int J Geogr Inf Sci , vol.16 , Issue.3 , pp. 245-257
    • Laffan, S.W.1
  • 20
    • 24044470614 scopus 로고    scopus 로고
    • Clustering of time series data - a survey
    • Liao TW (2005) Clustering of time series data - a survey. Pattern Recognition 38: 1857-1874.
    • (2005) Pattern Recognition , vol.38 , pp. 1857-1874
    • Liao, T.W.1
  • 21
    • 0033556632 scopus 로고    scopus 로고
    • Streamflow trends in the United States
    • Lins HF, Slack JR (1999) Streamflow trends in the United States. Geophys Res Lett 26(2): 227-230.
    • (1999) Geophys Res Lett , vol.26 , Issue.2 , pp. 227-230
    • Lins, H.F.1    Slack, J.R.2
  • 29
    • 11144332044 scopus 로고    scopus 로고
    • The design space of wireless sensor networks
    • Römer K, Mattern F (2004) The design space of wireless sensor networks. IEEE Wireless Communications 11(6): 54-61.
    • (2004) IEEE Wireless Communications , vol.11 , Issue.6 , pp. 54-61
    • Römer, K.1    Mattern, F.2
  • 30
    • 84893714024 scopus 로고    scopus 로고
    • Lecture at University of Nebraska-Lincoln. June, 2007
    • Serre M (2007) Lecture at University of Nebraska-Lincoln. June, 2007.
    • (2007)
    • Serre, M.1
  • 31
    • 0031076340 scopus 로고    scopus 로고
    • On the definition and modelling of streamflow drought duration and deficit volume
    • Tallaksen LM, Madsen H, Clausen B (1997) On the definition and modelling of streamflow drought duration and deficit volume. Hydrol Sci 42: 15-33.
    • (1997) Hydrol Sci , vol.42 , pp. 15-33
    • Tallaksen, L.M.1    Madsen, H.2    Clausen, B.3
  • 32
    • 0002874545 scopus 로고    scopus 로고
    • Streamflow drought frequency analysis
    • J. V. Vogt and F. Somma (Eds.), Derdrecht: Kluwer Academic Publishers
    • Tallaksen LM (2000) Streamflow drought frequency analysis. In: Vogt JV, Somma F (eds) Drought and drought mitigation in Europe. Kluwer Academic Publishers, Derdrecht, pp 103-117.
    • (2000) Drought and Drought Mitigation in Europe , pp. 103-117
    • Tallaksen, L.M.1
  • 33
    • 84893731952 scopus 로고    scopus 로고
    • Fitness for use - to support military decision making
    • 7th International Symposium on Spatial Accuracy Assessment in Natural Resources and Environmental Sciences, Lisbon, Portugal, Instituto Geográfico Português
    • Wright EJ (2006) Fitness for use - to support military decision making, In Proceedings of Accuracy 2006; 7th International Symposium on Spatial Accuracy Assessment in Natural Resources and Environmental Sciences, Lisbon, Portugal, Instituto Geográfico Português, p. 760-769.
    • (2006) Proceedings of Accuracy 2006 , pp. 760-769
    • Wright, E.J.1
  • 34
    • 0023524214 scopus 로고
    • A method of streamflow drought analysis
    • Zelenhasic E, Salwai A (1987) A method of streamflow drought analysis. Water Resour Res 23(1): 156-168.
    • (1987) Water Resour Res , vol.23 , Issue.1 , pp. 156-168
    • Zelenhasic, E.1    Salwai, A.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.