1 |
Beck, R., 2003. EO-1 User Guide Version 2.3
|
2 |
Elmore, A. J. and G. P. Asner, 2005. Satellite monitoring of vegetation phenology and fire fuel conditions in Hawaiian drylands. Earth Interactions, 9(21): 1-21
|
3 |
Gong, P., R. Pu, G. S. Biging, and M. R. Larrieu, 2003. Estimation of Forest Leaf Area Index Using Vegetation Indices Derived FromHyperion Hyperspectral Data. IEEE Transaction Geoscience and Remote Sensing, 41(6): 1355-1362
DOI
ScienceOn
|
4 |
Kasischke, E. S., N. F. French, P. Harrell, N. L. Christensen, S. L. Ustin, and D. Barry, 1993. Monitoring of wildfires in boreal forest using large area AVHRR NDVI composite image. Remote Sensing of Environment, 44: 61-72
|
5 |
Tueller, P. T., 1987. Remote sensing science applications in arid environments. Remote Sensing of Environment, 23: 143-154
DOI
ScienceOn
|
6 |
Jensen, J. R., 1996. Introductory digital image processing: a remote sensing perspective. Prentice Hall, pp. 247-252
|
7 |
Adams, J. B., D. E. Sabol, V. Kapos, R. F. Almeida, D. A. Roberts, M. O. Smith, and A. R. Gillespie, 1995. Classification ofmultispectral images based on fractions ofendmembers: Applications to land-use change in the Brazilian Amazon. Remote Sensing of Environment, 52: 137-154
DOI
ScienceOn
|
8 |
Anderson, H. E., 1982. Aids to determining fuel models for estimating fire behavior. USDA Forest Service, Intermountain Forest and Range Experiment Station, INT-122
|
9 |
Tompkins, S., J. F. Mustard, C. M. Pieters, and D. W. Forsyth, 1997. Optimization of endmembers for spectral mixture analysis. Remote Sensing of Environment, 59: 472-489
DOI
ScienceOn
|
10 |
Rolf, A., N. Goodwin, and R. Merton, 2005. Assessing fuel loads using remote sensing. University of New South Wales, Australia, pp. 5-9
|
11 |
Wang, L., W. P. Sousa, P. Gong, and G. S. Biging, 2004. Comparison of IKONOS and QuickBird images for mapping mangrove species on the Caribbean coast of Panama. Remote Sensing of Environment, 91: 432-440
DOI
ScienceOn
|
12 |
Smith, M. O., S. L. Ustin, J. B. Adams, and A. R. Gillespie, 1990. Vegetation in deserts: I. A regional measure of abundance from multispectral images. Remote Sensing of Environment, 31: 1-26
DOI
ScienceOn
|
13 |
Dennision, P. E., D. A. Robers, and J. C. Regelbrugge, 2000. Characterizing chaparral fuels using combined hyperspectral and synthetic aperture radar data. Proc. 9th AVIRIS Earth Science Workshop, 6: 119-124
|
14 |
Penuelas, J., I. Filella, C. Biel, L. Serrano, and R. Save, 1993. The reflectance at the 950-970nm region as an indicator of plant water status. International Journal of Remote Sensing, 14: 1887-1905
DOI
ScienceOn
|
15 |
Han, T., D. G. Goodenough, A. Dyk, and L. Love, 2002. Detection and correction of abnormal pixels in hyperion images. International Geoscience and Remote Sensing Symposium 2002, pp. 1327-1330
|
16 |
Xiao, J. and A. Moody, 2005. A comparison of methods for estimating fractional green vegetation cover within a desert-to-upland transition zone in central New Mexico, USA. Remote Sensing of Environment, 98: 237-250
DOI
ScienceOn
|
17 |
Gao, B. C., 1996. NDWI - A normalized difference water index for remote sensing of vegetationliquid water from space. Remote Sensing of Environment, 58: 257-266
DOI
ScienceOn
|
18 |
Chuvieco, E. and J. Salas, 1996. Mapping the spatial distribution of forest fire danger using GIS. International Journal. of GIS, 10(3): 333-345
|
19 |
Roberts, D. A., P. E. Dennison, M. E. Gardner, Y. Hetzel, S. L. Ustin, and C. T. Lee, 2003.Evaluation of the potential of hyperion for fire danger assessment by comparison to the airborne visible / infrared imagine spectrometer. IEEE Transaction Geoscience and Remote Sensing, 41(6): 1297-1310
DOI
ScienceOn
|
20 |
Roberts, D. A. and P. E. Dennision, 2003. Hyperspectral technologies for wildfire fuel mapping. Proc. 4th International Workshop on RS and GIS Applications to Forest Fire Management, pp. 66-75
|
21 |
Chafer, C., M. Noonan, and E. Macnaught, 2004. The post-fire measurement of fire severity and intensity in the Christmas 2001 Sydney wildfires. International Journal of Wildland Fire, 13: 227-240
DOI
ScienceOn
|
22 |
Thenkabail, P. S., E. A. Enclona, M. S. Ashton, C. Legg, and M. J. De Dieu, 2004. Hyperion, IKONOS, ALI, and ETM+ sensors in the study of African rainforests. Remote Sensing of Environment, 90: 23-43
DOI
ScienceOn
|
23 |
Keane R. E., R. Burgan, and J. Watendon, 2001. Mapping wildland fuels for management across multiple scales: Integrating remote sensing, GIS, and biophysical modelling. International Journal of Wildland Fire, 10: 301-309
DOI
ScienceOn
|