International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B3. Istanbul 2004
then to correct them. Points that it touch dams were eliminated
to avoid that generated mistakes in DTM construction. This was
stage that consumed largest amount of LIDAR data processing
time. At the end of this stage, it was had the points file that it
touch to bare earth and layer point files (vegetation, building
and " other ") edited and revised completely. All LIDAR point
files were recorded as ASCII X, Y, Z files for they be added
later as table in ArcView GIS for DTM and DSM generation.
3.2 Land use surveying using Photointerpretation
Current land use surveying was accomplished with intention of
aiding in study area recognition and analysis.
The expression current land use can be understood as form by
which space is being busy for the man and land use surveying
in certain area, became fundamental to quantify and to
understand the organization patterns of human activity on space
(DALE & MCLAUGHLIN, 1990).
A preliminary photointerpretation in orthophotos mosaic was
accomplished, being delineated land use areas with different
aspects. That material served as base for field study.
After field check, it was studied orthophotos mosaic
thoroughly, defining and digitizing the interest classes be
obtained in photointerpretation. The defined classes were: built
area; exposed soil; cultivation areas; pasture; reforestation;
dense vegetation; vegetatio; rivers; dams and roads.
3.3 Generation of Digital Terrain Model (DTM) and Digital
Surface Model (DSM)
For studies that involve a highway implantation project, a
Digital Terrain Model that describes implantation area closest
possible of real situation is very important. For KRAUS &
PFEIFER (1998), the derived contours of a DTM only with
LIDAR points are poor in geomorphologic details. This
happens even if filtering and classification are applied.
Three DTMs were generated for subsequent visual comparison
and choose of most appropriate: (1) starting from
aerophotogrammetric restitution contour lines, (2) starting from
LIDAR points and (3) starting from LIDAR points with
addition of breaklines digitizing in aerophotogrammetric
restitution.
To generate a DTM or DSM in ArcView GIS it was created a .
TIN (Triangulated Irregular Networking), that presents as
characteristic breaklines addition possibility to model.
3.4 Creation of slope maps
Slope Maps were created to make possible a terrain
visualization and analysis considering preservation permant
arcas due to your slope (BRASIL, 1965) and urbanization
suitable areas without restrictions (BRASIL, 1979). These last
ones were defined due to propensity of high-of-way and
highway close areas disordered occupation, what is today a
serious social and environmental problem in Brazil.
The slope maps were obtained from LIDAR points edited
manually with addition of natural and artificial breaklines.
3.5 Thematic analysis of study area
Thematic analysis in study area was accomplished through the
crossing of slope maps, land use maps and highway geometric
project. They were followed recommendations of the
Environmental Procedures Manual (DER/SC, 1998), being
verified, for instance, existence of preservation permanent area;
urbanization suitable areas without restrictions and areas be
deforested it for highway construction.
The maps crossing was made in digital ambient in a project in
ArcView GIS, what made possible an effective analysis of study
area.
4. RESULTS
4.1 treatment of LIDAR data
4.1.1 Filtering of LIDAR points
The amount of defined points through filtering, as bare earth,
was of 137.701 points, what represents 23,70% of laser points
total in area. And were defined as Objects 443.310 points, what
represents 76,30% of laser points total in the area.
Filtering problems found they referred mainly to laser pulse
reflection pattern in dams, to elements with small height in
relation to bare earth (barrages), areas with accentuated slope,
adjacent laser strip and linked objects to bare earth (bridges).
4.1.2 Classification of LIDAR points
Besides making possible the separation of point not beloging to
bare earth in different layers, classification aided in
identification of points defined erroneously in filtering process.
In classification, 8,423 points were defined as building, while
434.887 points were defined as vegetation and transmission
lines and towers.
Although the TerraScan classification routines have separated
points in different layers, difficulties were found mainly with
relationship to buildings classification. Many points that they
touch buildings were not classified as such, while other
belonging to bare earth and vegetation were defined for
software as being buildings. In some buildings (most with roofs
presenting little inclination), all the points were correctly
classified.
4.1.3 Manual edition of LIDAR points
Figure 3 show the result obtained after LIDAR point filtering,
classification and manual edition of part of study area. The
defined points as bare earth were represented in orange color,
the defined ones as buildings in red color, referring points to
transmission lines and towers are represented in purple color
and the defined ones as vegetation in green color.
Figure 3. LIDAR points after manual edition.
In table 2 it is had the amount of defined points as bare earth
and in different layers before and after manual edition.
Internati
Layer
Bare
earth
Buildin;
Vegeta
on
Other
Total
Table 2
and lay:
4.2 Lanc
Land use
2002, pe
Through
define tl
area foi
identific:
coming
surveyin
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3D point
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dense ve
laser poi
4.3 gene
The mo
contour
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Figure
restituti
Figure 5
derived
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