Estimating average tree crown size using spatial information from Ikonos and QuickBird images: Across-sensor and across-site comparisons

Remote Sensing of Environment

Volumn 114, Issue 5, 2010, Pages 1099-1107

  Song, Conghe ^a   Dickinson, Matthew B ^b   Su, Lihong ^a   Zhang, Su ^a   Yaussey, Daniel ^b  

^a University of North Carolina at Chapel Hill   (United States)

^b Northern Research Station   (United States)

Author keywords

Ikonos; Image spatial information; QuickBird; Tree crown size

Indexed keywords

BIOPHYSICAL PROCESS; CANOPY STRUCTURE; DEPENDENT VARIABLES; DIAMETER-AT-BREAST HEIGHTS; FOREST CANOPIES; FOREST ECOSYSTEM; FOREST INVENTORY; FOREST RESOURCES; HARDWOOD STANDS; IKONOS IMAGES; IMAGE VARIANCE; INDEPENDENT VARIABLES; INVENTORY AND MONITORING; MANAGEMENT AREAS; MOMENTUM EXCHANGE; NORTH CAROLINA; QUICKBIRD; QUICKBIRD IMAGES; SPATIAL INFORMATIONS; SPATIAL RESOLUTION; STATISTICAL MODELS; STRUCTURAL PARAMETER; STUDY SITES; TREE CROWNS; TREE HEIGHT;

DATA STORAGE EQUIPMENT; ECOSYSTEMS; INFORMATION USE; SENSORS;

FORESTRY;

CANOPY ARCHITECTURE; FOREST CANOPY; FOREST INVENTORY; FOREST RESOURCE; IKONOS; QUICKBIRD; SATELLITE IMAGERY; SENSOR; SPATIAL ANALYSIS;

DATA; ECOSYSTEMS; EQUIPMENT; FORESTRY; IMAGE ANALYSIS; INFORMATION RETRIEVAL; SENSORS; STORAGE; TREES;

DUKE FOREST; NORTH CAROLINA; OHIO; UNITED STATES;

EID: 76049089659     PISSN: 00344257     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.rse.2009.12.022     Document Type: Article

References (44)

1. Asner G.P., Palace M., Keller M., Pereira R., Silva J.N.M., and Zweede J.C. Estimating canopy structure in an Amazon Forest from laser range finder and IKONOS satellite observations. Biotropica 34 4 (2002) 483-492
2. Botkin D.B., Janak J.F., and Wallis J.R. Rationale, limitations, and assumptions of a northeastern forest growth simulator. IBM Journal of Research and Development 16 (1972) 101-116
3. Brandtberg T., and Walter F. Automated delineation of individual tree crowns in high spatial resolution aerial images by multiple-scale analysis. Machine Vision and Applications 11 (1998) 64-73
4. Brown S., Pearson T., Slaymaker D., Ambagis S., Moore N., Novelo D., et al. Creating a virtual tropical forest from three dimensional aerial imagery to estimate carbon stocks. Ecological Applications 15 3 (2005) 1083-1095
5. Chen D.X., and Coughenour M.B. GEMTM - A general-model for energy and mass-transfer of land surfaces and its application at the FIFE sites. Agricultural and Forest Meteorology 68 3-4 (1994) 145-171
6. Clark D.B., Read J.M., Clark M.L., Cruz A.M., Dotti M.F., and Clark D.A. Application of 1-M and 4-M resolution satellite data to ecological studies of tropical rain forests. Ecological Applications 14 1 (2004) 61-74
7. Cohen W.B., and Spies T.A. Estimating structural attributes of Douglas-fir/western hemlock forest stands from Landsat and SPOT imagery. Remote Sensing of Environment 41 (1992) 1-17
8. Culvenor D.S. TIDA: An algorithm for the delineation of tree crowns in high spatial resolution remotely sensed imagery. Computers and Geosciences 28 (2002) 33-44
9. Falkowski M.J., Smith A.M.S., Hudak A.T., Gessler P.E., Vierling L.A., and Crookston N.L. Automated estimation of individual conifer tree height and crown diameter via two-dimensional spatial wavelet analysis of Lidar data. Canadian Journal of Remote Sensing 32 (2006) 153-161
10. Falkowski M.J., Smith A.M.S., Gessler P.E., Hudak A.T., Vierling L.A., and Evans J.S. The influence of conifer forest canopy cover on the accuracy of two individual tree measurement algorithms using Lidar data. Canadian Journal of Remote Sensing 34 (2008) S338-S350
11. Franklin J., and Strahler A.H. Invertible canopy reflectance modeling of vegetation structure in semi-arid woodland. IEEE Transactions on Geoscience and Remote Sensing 26 (1988) 809-825
12. Gholz H.L., Grier C.C., Campbell A.G., and Brown A.T. Equations for estimating biomass and leaf area of plants in the Pacific Northwest (1979), Forest Research Laboratory, School of Forestry, Oregon State University
13. Grier C.C., and Logan R.S. Old-growth Pseudotsuga menziesii of a western Oregon watershed: Biomass distribution and production budgets. Ecological Monographs 47 (1977) 373-400
14. Heurich M. Automatic recognition and measurement of single trees based on data from airborne laser scanning over the richly structured natural forests of the Bavarian Forest National Park. Forest Ecology and Management 255 (2008) 2,416-2,433
15. Jenkins J.C., Chojnacky D.C., Heath L.S., and Birdsey R.A. Comprehensive database of diameter-based biomass regressions for North America tree species. USDA Forest Service, General Technical Report NE-319 (2004)
16. Jupp, D. L B. 1999. INVDISK - Inversion of disk model "images" using mean, variance & variogram data. unpublished work through personal communication.
17. Jupp D.L.B., Strahler A.H., and Woodcock C.E. Auto-correlation and regularization in digital images: 1. Basic theory. IEEE Transactions on Geoscience and Remote Sensing 26 4 (1988) 463-473
18. Leckie D.G., Gougeon F.A., Walsworth N., and Pardine D. Stand delineation and composition estimation using semi-automated individual tree crown analysis. Remote Sensing of Environment 85 (2003) 355-369
19. Lee A.C., and Lucas R.M. A LiDAR-derived canopy density model for tree item and crown mapping in Australian forests. Remote Sensing of Environment 111 (2007) 493-518
20. Ni W., Li X., Woodcock C.E., Boujean J., and Davis R.E. Transmission of solar radiation in boreal conifer forests: Measurements and models. Journal of Geophysical Research 102 D24 (1997) 29,555-29,566
21. Palace M., Keller M., Asner G.P., Hagen S., and Braswell B. Amazon forest structure from IKONOS satellite data and the automated characterization of forest canopy properties. Biotropica 40 2 (2008) 141-150
22. Persson A., Holmgren J., and Soderman U. Detecting and measuring individual trees using an airborne laser scanner. Photogrammetric Engineering and Remote Sensing 68 (2002) 925-932
23. Pollock, R. J. (1996). A model-based approach to automatically locating individual tree crowns in high-resolution images of forest canopies. PhD Dissertation, Department of Computer Science, University of British Columbia, Vancouver, Canada.
24. Popescu S.C., and Wynne R.H. Seeing the trees in the forest: Using Lidar and multispectral data fusion with local filtering and variable window size for estimating tree height. Photogrammetric Engineering and Remote Sensing 70 (2004) 589-604
25. Popescu S.C., Wynne R.H., and Nelson R.E. Measuring individual tree crown diameter with Lidar and assessing its influence on estimating forest volume and biomass. Canadian Journal of Remote Sensing 29 (2003) 564-577
26. Pouliot D.A., King D.J., Bell F.W., and Pitt D.G. Automated tree crown detection and delineation in high-resolution digital camera imagery of coniferous forest regeneration. Remote Sensing of Environment 82 (2002) 322-334
27. Schaaf C.B., Li X., and Strahler A.H. Topographic effects on bidirectional and hemispherical reflectances calculated with a geometric-optical canopy model. IEEE Transactions on Geoscience and Remote Sensing 32 6 (1994) 1186-1193
28. Shugart H.H., and West D.C. Development of an Appalachian deciduous forest succession model and its application to assessment of the impact of the chestnut blight. Journal of Environmental Management 5 (1977) 161-179
29. Song C. Estimating tree crown size with spatial information of high resolution optical remotely sensed imagery. International Journal of Remote Sensing 28 15 (2007) 3305-3322
30. Song C., and Band L.E. MVP: A model to simulate the spatial patterns of photosynthetically active radiation under discrete forest canopies. Canadian Journal of Forest Research 34 (2004) 1192-1203
31. Song C., and Dickinson M.B. Extracting forest canopy structure from spatial information of high resolution optical imagery: Tree crown size versus leaf area index. International Journal of Remote Sensing 29 19 (2008) 5605-5622
32. Song C., and Woodcock C.E. Estimating tree crown size from multiresolution remotely sensed imagery. Photogrammetric Engineering and Remote Sensing 69 11 (2003) 1263-1270
33. Song C., Katul G., Oren R., Band L.E., Tague C.L., Stoy P.C., et al. Energy, water and carbon fluxes in a loblolly pine stand: Results from uniform and gappy canopy models with comparisons to eddy flux data. Journal of Geophysical Research-Biogeosciences 114 (2009) G04021 10.1029/2009JG000951
34. Strahler A.H., Woodcock C.E., and Smith J.A. On the nature of models in remote sensing. Remote Sensing of Environment 20 (1986) 121-139
35. Urban D.L. A versatile model to simulate forest pattern: A user's guide to ZELIG, version 1.0 (1990), University of Virginia, Charlottesville, VA
36. Wang L., Sousa W.P., Gong P., and Biging G.S. Comparison of IKONOS and QuickBird images for mapping mangrove species on the Caribbean coast of Panama. Remote Sensing of Environment 91 3-4 (2004) 432-440
37. Wolter P.T., Townsend P.A., and Sturtevant B.R. Estimation of forest structural parameters using 5 and 10 meter SPOT-5 satellite data. Remote Sensing of Environment 113 9 (2009) 2019-2036
38. Woodcock C.E., Strahler A.H., and Jupp D.L.B. The use of variograms in remote sensing: I. Scene models and simulated images, Remote Sensing of Environment 25 (1988) 323-348
39. Woodcock C.E., Strahler A.H., and Jupp D.L.B. The use of variograms in remote sensing: II. Real digital images. Remote Sensing of Environment 25 (1988) 349-379
40. Woodcock C.E., Collins J.B., Gopal S., Jakabhazy V.D., Li X., Macomber S.A., et al. Mapping forest vegetation using Landsat TM imagery and a canopy reflectance model. Remote Sensing of Environment 50 (1994) 240-254
41. Woodcock C.E., Collins J.B., Jakabhazy V.D., Li X., Macomber S.A., and Wu Y. Inversion of the Li-Strahler canopy reflectance model for mapping forest structure. IEEE Transactions on Geoscience and Remote Sensing 35 (1997) 405-414
42. Wu Y., and Strahler A.H. Remote estimation of crown size, stand density and foliage biomass on the Oregon transect. Ecological Application 4 (1993) 299-312
43. Wulder M., Niemann K.O., and Goodenough D. Local maximum filtering for the extraction of tree locations and basal area from high spatial resolution imagery. Remote Sensing of Environment 73 1 (2000) 103-114
44. Wulder M.A., White J.C., Niemann K.O., and Nelson T. Comparison of airborne and satellite high spatial resolution data for the identification of individual trees with local maxima filtering. International Journal of Remote Sensing 25 11 (2004) 2225-2232