Evaluation of the potential for providing secondary labels in vegetation maps

Photogrammetric Engineering and Remote Sensing

Volumn 62, Issue 4, 1996, Pages 393-399

  Woodcock, Curtis E ^a   Gopal, Sucharita ^a   Albert, William ^a  

^a BOSTON UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFICATION; MAPPING; REMOTE SENSING; REMOTE SENSING DATA; SECONDARY LABEL; THEMATIC MAP; THRESHOLDING; VEGETATION MAP;

EID: 0030469734     PISSN: 00991112     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Review

References (14)

1. Adams, J.B., M.O. Smith, and P.E. Johnson, 1986. Spectral mixture modeling: A new analysis of rock and soil types at the Viking Lander 1 site, Journal of Geophysical Research, 91(B8):8098-8112.
2. Cohen, J., 1960. A coefficient of agreement for nominal scales, Educational Psychological Measurement, 20(1):37-46.
3. Congalton, R.G., 1991. A review of assessing the accuracy of classifications of remotely sensed data, Remote Sensing of Environment, 37:35-46.
4. Congalton, R.G., K. Green, and J. Teply, 1993. Mapping old growth forests on National Forest and Park lands in the Pacific North-west from remotely sensed data, Photogrammetric Engineering & Remote Sensing, 59(4):529-535.
5. Franklin, J., T.L. Logan, C.E. Woodcock, and A.H. Strahler, 1986. Coniferous forest classification and inventory using Landsat and digital terrain data, IEEE Transactions on Geoscience and Remote Sensing, GE-24(1):139-149.
6. Gopal, S., and C.E. Woodcock, 1994. Theory and methods for accuracy assessment of thematic maps using fuzzy sets, Photogrammetric Engineering & Remote Sensing, 60(2):181-188.
7. Li, X., and A.H. Strahler, 1985. Geometric-optical modeling of a conifer forest canopy, IEEE Transactions in Geoscience and Remote Sensing, GE-23(5):705-721.
8. Moody, A, S. Gopal, and A. Strahler, 1995. Sensitivity of neural network outputs to subpixel land-cover mixtures in coarse resolution satellite data, submitted to Remote Sensing of Environment, July 1994, revised, September, 1995.
9. Nalepka, R.F., and P.D. Hyde, 1972. Classifying unresolved objects from simulated space data, Proc. of the 8th Int. Symp. on Remote Sensing of Environment, Ann Arbor, Michigan, pp. 935-949.
10. Roberts, D.A., M.O. Smith, and J.B. Adams, 1993. Green vegetation, non-photosynthetic vegetation, and soils in AVIRIS data, Remote Sensing of Environment, 44:222-269.
11. Stenback, J.M., and R.G. Congalton, 1990. Using thematic mapper imagery to examine forest understory, Photogrammetric Engineering & Remote Sensing, 56(9):1285-1290.
12. Woodcock, C.E., J.B. Collins, S. Gopal, V.D. Jakabhazy, X. Li, S. Macomber, S. Ryherd, Y. Wu, V.J. Harward, J. Levitan, and R. Warbington, 1994a. Mapping forest vegetation using Landsat TM imagery and a canopy reflectance model, Remote Sensing of Environment, 50:240-254.
13. Woodcock, C.E., S. Gopal, S.A. Macomber, and V.D. Jakabhazy, 1994b. Accuracy Assessment of the Vegetation Map of the Plumas National Forest, Technical Report, Center for Remote Sensing, Boston University, 19 p.
14. Woodcock, C.E., and V.J. Harward, 1992. Nested-hierarchical scene models and image segmentation, International Journal of Remote Sensing, 13(16):3167-3187.