Fuel Mapping - Wildland Fuel Fundamentals and Applications - page 167

Keane RE, Rollins M, Zhu ZL (2007) Using simulated historical time series to prioritize fuel treat-
ments on landscapes across the United States: the LANDFIRE prototype project. Ecol Model
204(3-4):485-502. doi:10.1016/j.ecolmodel.2007.2.005
Keane RE, Loehman RA, Holsinger LM (2011) The FireBGCv2 landscape fire and succes-
sion model: a research simulation platform for exploring fire and vegetation dynamics.
U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station, General
Technical Report RMRS-GTR-255 Fort Collins, CO USA, pp 137
Keane R, Gray K, Bacciu V, Leirfallom S (2012a) Spatial scaling of wildland fuels for six forest
and rangeland ecosystems of the northern Rocky Mountains, USA. Landsc Ecol 27(8):1213-
1234. doi:10.1007/s10980-012-9773-9
Keane RE, Gray K, Bacciu V (2012b) Spatial variability of wildland fuel characteristics in
northern Rocky Mountain ecosystems. USDA Forest Service Rocky Mountain Research
Station, Research Paper RMRS-RP-98 Fort Collins, Colorado USA, pp 58
Keane RE, Herynk JM, Toney C, Urbanski SP, Lutes DC, Ottmar RD (2013) Evaluating the per-
formance and mapping of three fuel classification systems using forest inventory and analy-
sis surface fuel measurements. For Ecol Manage 305:248-263. http://dx.doi.org/10.1016/j.
foreco.2013.06.001
Keramitsoglou I, Kontoes C, Sykioti O, Sifakis N, Xofis P (2008) Reliable, accurate, and timely
forest mapping for wildfire management using ASTER and Hyperion satellite imagery. For
Ecol Manage 255:3556-3562
Kessell SR (1976) Gradient modeling: a new approach to fire modeling and wilderness resource
management. Environ Manage 1(1):39-48
Kourtz PH (1977) An application of Landsat digital technology to forest fire fuel mapping. In:
Dube DE (ed) Fire ecology in resource mangement: a workshop. Northern Forest Research
Centre, Information Report NOR-X-210 Edmonton, Alberta, pp 79-81
Krasnow K (2007) Forest fuel mapping and strategic wildfire mitigation in the Montane zone of
Boulder County, Colorado. Graduate Thesis, University of Colorado, Boulder, CO USA, pp 55
Krivtsov V, Vigy O, Legg C, Curt T, Rigolot E, Lecomte I, Jappiot M, Lampin-Maillet C,
Fernandes P, Pezzatti GB (2009) Fuel modelling in terrestrial ecosystems: an overview in the
context of the development of an object-orientated database for wild fire analysis. Ecol Model
220(21):2915-2926
Lanorte A, Lasaponara R, Murgante B, Gervasi O, Iglesias A, Taniar D, Apduhan B (2011) On
the use of satellite remote sensing data to characterize and map fuel types. In: Computational
science and its applications—ICCSA 2011, vol 6783. Lecture Notes in Computer Science.
Springer Berlin/Heidelberg, pp 344-353. doi:10.1007/978-3-642-21887-3_27
Lasaponara R, Lanorte A (2007a) On the capability of satellite VHR Quickbird data for fuel type
characterization in fragmented landscapes. Ecol Model 204:79-84
Lasaponara R, Lanorte A (2007b) Remotely sensed characterization of forest fuel types by using
satellite ASTER data. Int J Appl Earth Obs Geoinf 9(3):225-234. http://dx.doi.org/10.1016/j.
jag.2006.08.001
Leenhouts B (1998) Assessment of biomass burning in the conterminous United States. Conserv
Ecol 2(1):1-23
Lenihan JM, Daly C, Bachelet D, Neilson RP (1998) Simulating broad scale fire severity in a
dynamic global vegetation model. Northwest Sci 72:91-103
Loveland TR, Merchant JM, Ohlen DO, Brown JF (1991) Development of a land-cover charac-
teristics database for the conterminous U.S. Photogramm Eng Remote Sens 57(11):1453-1463
Loveland TR, Ohlen DO, Brown JF, Reed BC, Merchant JW (1993) Prototype 1990 conterminous
United States land cover characteristics data set EROS Data Center, US Geological Survey,
CD-ROM 9307 Souix Falls, SD USA
McKenzie D, Raymond CL, Kellogg L-KB, Norheim RA, Andreu A, Bayard AC, Kopper KE,
Elman E (2007) Mapping fuels at multiple scales: landscape application of the fuel characteris-
tic classification system. Can J For Res 37:2421-2437. doi:10.1139/x07-056
Menakis JP, Keane RE., Long DG (2000) Mapping ecological attributes using an integrated veg-
etation classification system approach. J Sustain For 11(1-2):245-265