XXII ISPRS Congress 2012: Technical Commission VIII

Shortis, M.; Shimoda, H.; Cho, K.

Bibliographic data

Multivolume work

Persistent identifier:: 1663813779

Title:: XXII ISPRS Congress 2012

Sub title:: Melbourne, Australia, 25 August-1 September 2012

Year of publication:: 2013

Place of publication:: Red Hook, NY

Publisher of the original:: Curran Associates, Inc.

Identifier (digital):: 1663813779

Language:: English

Additional Notes:: Kongress-Thema: Imaging a sustainable future

Corporations:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Adapter:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Founder of work:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Other corporate:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Document type:: Multivolume work

Volume

Persistent identifier:: 1663822514

Title:: Technical Commission VIII

Scope:: 590 Seiten

Year of publication:: 2014

Place of publication:: Red Hook, NY

Publisher of the original:: Curran Associates, Inc.

Identifier (digital):: 1663822514

Illustration:: Illustrationen, Diagramme

Signature of the source:: ZS 312(39,B8)

Language:: English

Additional Notes:: Erscheinungsdatum des Originals ist ermittelt.; Literaturangaben

Usage licence:: Attribution 4.0 International (CC BY 4.0)

Editor:: Shortis, M.; Shimoda, H.; Cho, K.

Corporations:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Adapter:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Founder of work:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Other corporate:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Publisher of the digital copy:: Technische Informationsbibliothek Hannover

Place of publication of the digital copy:: Hannover

Year of publication of the original:: 2019

Document type:: Volume

Collection:: Earth sciences

Chapter

Title:: [VIII/8: Land]

Document type:: Multivolume work

Structure type:: Chapter

Chapter

Title:: GLOBAL LAND COVER CLASSIFICATION USING MODIS SURFACE REFLECTANCE PRODUCTS Haruhisa Shimoda, Kiyonari Fukue

Document type:: Multivolume work

Structure type:: Chapter

IX-B8, 2012 (D Q) 1ain co-occurrence ata set for a pixel- -series data set for MENTS 1ich are same with ories were used in P legend). HH BP 17 categories, ssification classes. h class and about | as training data. training data for arsely vegetated", ined time-domain eaf forest" and " International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXIX-B8, 2012 XXII ISPRS Congress, 25 August — 01 September 2012, Melbourne, Australia (a) ground view (b) training area (c)time series reflectance of = (d)time-domain one pixel in the training co-occurrence matrix of area the training area Figure 4. Training data example for "evergreen needleleaf forest". (a) ground view (b) training area (c) time series reflectance of (d)time-domain one pixel in the training area co-occurrence matrix of the training area Figure 5. Training data example for "barren/sparsely vegetated". (a) "deciduous needleaf (b) " savannas" forest" Figure 6. Examples of obtained time-domain co-occurrence matrix. Classification accuracies were measured by using test samples of 300 pixels that were sampled randomly from training area of each individual class. 4.3 Classification Results Because the cosine distance classifier has always produced several percent higher mean producer's classification accuracy than that of the Euclidean distance classifier regardless of the time-separation delta-t, only the results when the cosine distance is used is shown in the following. When time-domain co-occurrence matrix is defined with reflectance, the highest accuracy of 9596-9696 has been obtained for SR and NBAR products when time-separation delta-t is about 3 months as shown in Figure 7. e SR —9— NBAR Classification Accuracy [96] 90 T T T T T 1 1 2 3 4 5 6 Time Separation Delta-t [month] Figure 7. Classification accuracies obtained by time-domain co-occurrence matrix which is defined with reflectance. When time domain co-occurrence matrix is defined with spectral cluster, classification accuracies are increased according to the number of clusters as shown in Figure 8. The highest accuracy of about 99% has been obtained for SR and NBAR products when time-separation delta-t is about 4 months as shown in Figure 9. ** SR (delta-t- 5 months) 77$ NBAR (delta-t- 4 months) S 100 S 95 B o < Xm 5 = 85 3 o 80 T T T T T T T T TTA 30 60 120 250 500 1000 2000 4000 8000 The Number of Clusters Figure 8. The relationship between the number of clusters and classification accuracies obtained by time-domain co-occurrence matrix which is defined with spectral cluster.

Access restriction

Copyright

fullscreen: Technical Commission VIII (B8)

Multivolume work

Volume

Chapter

Chapter

Table of contents

Cite and reuse

Volume

Chapter

Image

Image fragment

Citation links

Citation recommendation