Vegetation Classification and Mapping Project Report - the USGS

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Figure 4. Diagram showing photogrammetric, photointerpretation and GIS operations used to map the vegetation of GRSM. 14
Photogrammetric Operations The main objective of the photogrammetric procedure was to densify the sparse ground control in the Park by means of aerotriangulation, a photogrammetric operation whereby a relatively small number of ground control points (GCPs) are used to mathematically compute the ground coordinates of a much larger number of identified pass points (Jordan, 2002). In this way, the control network is adequately densified for the orthorectification process. At the outset, the 1:12,000-scale film transparencies were scanned at 600 dots per inch (dpi) using an Epson Expression 836xl desktop scanner to create black-and-white digital photos of 42-µm pixel resolution, providing a file of 35 Mbytes for each photo. These digital photos were then displayed on the computer monitor and with the aid of the R-WEL, Inc. Desktop Mapping System (DMS) software package, the image (x,y) coordinates of pass points and GCPs were measured in the softcopy environment. This was a painstaking and time-consuming task. In the absence of cultural features and the near continuous tree canopy cover, the passpoints, in the majority of instances, were individual tree-tops that had to be identified uniquely on overlapping photographs – not an easy job in terrain of high relief recorded on large-scale photographs (Figure 5). Ground control points were, for the most part, natural features (e.g., rock outcrops and forks in stream channels) identified on both the 1:12,000-scale color infrared transparencies and USGS Digital Orthophoto Quarter Quads (DOQQs) produced from 1:40,000-scale panchromatic aerial photographs recorded in 1993. The Universal Transverse Mercator (UTM) grid coordinates (X,Y tied to the North American Datum of 1927 or NAD 27) of these GCPs were measured directly from the DOQQs (accurate to within + 3 m). Elevations for the GCPs were derived using CRMS custom software to interpolate the Z-coordinates to within + 3 to + 5 m from USGS Level 2 Digital Elevation Models (DEMs) with 30-m post spacing (Figure 6). Thus, in this project, no ground survey work was required to obtain the GCPs needed as a framework for the aerotriangulation process. Analytical aerotriangulation was undertaken for blocks of up to 90 photos, where each block corresponded to the area covered by one of the 25 USGS 1:24,000-scale map sheets covering the Park. The PC Giant software package, in conjunction with the DMS software, was employed for the aerotriangulation process. Output from the aerotriangulation was a set of X, Y and Z coordinates in the UTM coordinate system for the nine or more pass points identified by CRMS personnel on each photo. Typical root-mean-square error (RMSE) values for these coordinates averaged + 7 m for the XY vectors and + 10 m for elevations (Z). The pass points with their X, Y and Z coordinates derived from the aerotriangulation process provided the ground control required to generate orthophotos and mosaics from the scanned air photos (Figure 7). These orthophotos and mosaics, in turn, were employed in the editing and attributing operations required to build the vector database. Most importantly, however, the control provided by the aerotriangulation process was essential for rectifying vector overlays generated as part of the photointerpretation procedure described below. 15
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: The understory vegetation was mappe
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 and 36: Figure 17. A sample of the fire fue
Page 37 and 38: The fuel class and percent canopy d
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
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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
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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
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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
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Attachment D Spruce with heath bald
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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
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Attachment F HxL 1403 4.9 0.0 141.1
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Attachment F R/T 26 2.4 0.4 6.8 62.
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Attachment G Attachment G Summary o
Page 111 and 112:
Attachment G PIsu/Rm 1 11.0 11.0 11
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Attachment G T/PIs/Ri 53 6.6 0.7 31
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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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