Vegetation Classification and Mapping Project Report - the USGS

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a . b. Figure 19. Percent canopy within the Gatlinburg quadrangle in leaf-on (a) and leaf-off (b) conditions color-coded according to canopy classes based on percent of canopy closure (c). c. 36
The fuel class and percent canopy data layers and associated maps provide fire managers with information that can be quickly assessed to determine general patterns of fire ignition and spread. In the event of a forest fire within the Park, these data also can be used as input, along with percent canopy cover derived from the overstory vegetation data layer and terrain characteristics, to a fire behavior prediction model called FARSITE Fire Area Simulator (Finney, 1998). Output from the FARSITE spatial model predicts the spread, intensity and behavior of forest fires. Managers can determine if fires should be observed or controlled, optimize their deployment of control measures and estimate the impact of fires on Park facilities and adjacent private lands. Understory Density The understory vegetation data set contains information on the density of Rhododendron and Kalmia. Since these two evergreen shrubs can often grow in dense thickets and are nearly impossible to traverse, information on the location of particularly dense stands is useful for field scientists, rescue workers and resource managers who must travel off-trail to access remote areas of the park. In response to the need of park managers to identify new sample plot locations for the ATBI research effort, GIS reclassification procedures were used to derive a simplified version of the understory vegetation data set in which approximately 190 unique classes were collapsed to 11 classes (Figure 20). Understory density classes included: herbaceous and deciduous understory (HD); 2) light, medium and heavy Rhododendron (Rh, Rm and Rl, respectively); 3) light, medium and heavy Kalmia (Kh, Km and Kl); 4) light, medium and heavy mixed Rhododendron and Kalmia (RKh, RKm and RKl); and 5) other understory (Ou). The geographic locations of future randomly located sample plots were overlaid on this understory density data set by GRSM resource managers to determine the accessibility of the samples. If a plot, for example, was found to be located in the middle of a high density Rhododendron thicket, then an assessment would be made concerning the level of effort needed to reach the plot and the suitability of the particular plot location for the study. A decision could then be made to keep the location or discard it and select an alternate site. 37
Page 1 and 2: Digital Vegetation Maps for the Gre
Page 3 and 4: Table of Contents Page List of Figu
Page 5 and 6: List of Figures (Continued) Figure
Page 7 and 8: List of Attachments Attachment Atta
Page 9 and 10: and animals in the world. It has be
Page 11 and 12: logged or burned (Walker, 1991). Th
Page 13 and 14: The understory vegetation was mappe
Page 15 and 16: Photogrammetric Operations The main
Page 17 and 18: Figure 7. A mosaic of orthorectifie
Page 19 and 20: The term “overstory vegetation”
Page 21 and 22: provided in Attachment D, and furth
Page 23 and 24: Figure 11. Hardcopy vegetation maps
Page 25 and 26: to the terrain. Applications of the
Page 27 and 28: Figure 13. Total area (hectares) of
Page 29 and 30: Modeling Applications In addition t
Page 31 and 32: Fuel Class 1 Short Grass Fuel Class
Page 33 and 34: understory type and density, was th
Page 35: Figure 17. A sample of the fire fue
Page 39 and 40: interfaced to auxiliary data system
Page 41 and 42: References Albini, F. A., 1976. Est
Page 43 and 44: Moore, H.L.A., 1988. A Roadside Gui
Page 45 and 46: Control Extension and Orthorectific
Page 47 and 48: Figure 2. The vegetation map produc
Page 49 and 50: Table 2. Results of different image
Page 51 and 52: Attachment B Attachment B Vegetatio
Page 53 and 54: Attachment B Sub-Alpine Woodland 6.
Page 55 and 56: Attachment B c. S. Appalachian Cove
Page 57 and 58: Attachment B 10. White Oak-Red Mapl
Page 59 and 60: Attachment B E. Southern Blue Ridge
Page 61 and 62: Attachment B :G Graminoid spp. :Ht
Page 63 and 64: Attachment C Photointerpreters from
Page 65 and 66: Attachment C Our ecologically based
Page 67 and 68: Attachment C Mesic Oak-Hardwoods (l
Page 69 and 70: Attachment C Mixed (Virginia-Pitch-
Page 71 and 72: Attachment C prints for greatest di
Page 73 and 74: Attachment C the inhospitable smila
Page 75 and 76: Attachment C An NVCS association (a
Page 77 and 78: Attachment C only in protected cove
Page 79 and 80: Attachment C MOr/R-K (CEGL 7299) an
Page 81 and 82: Attachment C everything”: Fraser
Page 83 and 84: Attachment C 30. NHx:Bol, Southern
Page 85 and 86: Attachment C elevation, the hemlock
Page 87 and 88:
Attachment C the surrounding tree c
Page 89 and 90:
Attachment C Tom Govus should be al
Page 91 and 92:
Attachment C Madden, M., 2003. Visu
Page 93 and 94:
Attachment D species and it is beli
Page 95 and 96:
Attachment D Hemlock understory wit
Page 97 and 98:
Attachment D Spruce with heath bald
Page 99 and 100:
Attachment E Attachment E Notes on
Page 101 and 102:
Attachment E Springs, Wear Cove and
Page 103 and 104:
Attachment E number of leaves are n
Page 105 and 106:
Attachment F HxL 1403 4.9 0.0 141.1
Page 107 and 108:
Attachment F R/T 26 2.4 0.4 6.8 62.
Page 109 and 110:
Attachment G Attachment G Summary o
Page 111 and 112:
Attachment G PIsu/Rm 1 11.0 11.0 11
Page 113 and 114:
Attachment G T/PIs/Ri 53 6.6 0.7 31
Page 115 and 116:
Attachment H Vegetation Modeling, A
Page 117 and 118:
Attachment H Department of Agricult
Page 119 and 120:
Attachment H isolated from the over
Page 121:
Attachment H 8
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Vegetation Classification and Mapping Project Report - the USGS

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