Peer-Reviewed Articles
249 Model-Based Conifer Canopy Surface Reconstruction
from Photographic Imagery: Overcoming the Occlusion, Foreshortening,
and Edge Effects
Yongwei Sheng, Peng Gong, and Gregory S. Biging
Abstract Download
Full Article (697Kb Adobe PDF)
Canopy surface data are desirable in forestry, but they are difficult to collect
in the field. Existing surface reconstruction techniques cannot adequately
extract canopy surfaces, esmetric pecially for conifer stands. This paper
develops an integrated model-based approach to reconstruct canopy surface
for conifer stands analytically from the crown level. To deal with dense
stands, critical problems are addressed in the process of model-based surface
reconstruction. These include the occlusion problem in disparity (parallax)
prediction from tree models, the edge effect of tree models on the disparity
map, and the foreshortening effect in image matching. The model-based approach
was applied to recover the canopy surface of a dense redwood stand using
images scanned from 1:2,400- scale aerial photographs. Compared with field
measurements, crown radius and tree height derived from the reconstructed
canopy surface model have an overall accuracy of 92 percent and 94 percent,
respectively. The results demonstrate the approach’s ability to reconstruct
complicated stands.
259 True Orthoimage Production for Forested Areas
from Large-Scale Aerial Photographs
Yongwei Sheng, Peng Gong, and Gregory S. Biging
Abstract Download
Full Article (503Kb Adobe PDF)
An orthophoto is a fundamental information source in forestry. Orthophoto production
is usually based on digital elevation models (DEM); however, the elevations
of 3D objects such as buildings and trees, which are visible in large-scale
photos, are not included in DEMs. Recently initiated “true orthophoto” generation
has been dedicated to urban scenes, removing the displacement caused by both
the terrain and buildings. This paper reports an effort on reducing occlusion
and distortion caused by trees in true orthoimage generation for forested
areas. Canopy surface models (CSM) depicting both the terrain and tree surfaces
were used in forest orthoimage production. Z-buffer techniques were incorporated
into indirect orthoimage production to remove occlusion. An angle-based strategy
was applied to composite multi-ocular images. The proposed techniques were
applied in the generation of high resolution orthoimages of a redwood stand
with 1:2,400-scale aerial photos.
267 A Portable Airborne Laser System for Forest
Inventory
Ross Nelson, Geoffrey Parker, and Milton Hom
Abstract Download
Full Article (340Kb Adobe PDF)
A simple, lightweight, inexpensive, portable airborne laser profiling system
has been assembled from off-the-shelf, commercially available components.
The system, which costs approximately $30,000, is designed to fly aboard
small helicopters and single- or twin-engine high-wing aircraft without airframe
modification. The system acquires firstcom, return range and amplitude measurements
at data rates up to 2000 hz (operator-controlled) and has an operational
envelope up to 300 m above terrain. The airborne laser profiling system includes
the laser transmitter/receiver, differential GPS receiver, a CCD video camera
and recorder, and a laptop computer which interleaves and records the GPS
and laser range/amplitude data. The portable airborne laser system (PALS)
was designed to acquire forest height measurements along linear flight transects
in order to conduct regional or subcontinental forest inventories worldwide.
This economical laser system now puts airborne laser mensuration within reach
of operational foresters and researchers interested in making rapid forest
structure and/or timber surveys in remote areas. PALS has been used to acquire
over 5000 km of flight transect data over the state of Delaware.
275 Spatial Analyses of Logging Impacts in Amazonia
Using Remotely Sensed Data
Jane M. Read
Abstract Download
Full Article (395Kb Adobe PDF)
Performances of selected spatial methods are investigated for characterizing
canopy disturbance in a reduced-impact logging operation in central Amazonia
using Landsat-7 ETM and Ikonos visible, near-infrared, and normalized difference
vegetation index data. Texture, fractal dimension (D), and Moran’s
I index of spatial autocorrelation were calculated for (1) 10-ha plots representing
logged (LF), logged excluding major roads and patios (L), and old-growth
(OG) forest; and (2) 335-ha plots representing LF and OG.
Ikonos data were sensitive to roads, patios, and some logging gaps, whereas ETM data were only sensitive to major logging features. The spatial methods were effective at characgradient, terizing the different logging feature treatments at both plot sizes; DTPSA and Moran’s I were most sensitive to fine-scale surface details. The spatial methods show potential for monitoring and management of logging activities over landscape scales. The importance of scale, given the ever-increasing choice of remotely sensed data, is emphasized.
283 Mountain Pine Beetle Red-Attack Forest Damage
Classification Using Stratified Landsat TM Data in British Columbia,
Canada
S.E. Franklin, M.A. Wulder, R.S. Skakun, and A.L. Carroll
Abstract Download
Full Article (595Kb Adobe PDF)
The identification and classification of mountain pine beetle, Dentroctonus
ponderosa (Hopkins), red-attack damage patterns in a mature lodgepole pine
(Pinus contorta) forest located in the Fort St. James Forest District, British
Columbia, was accomplished using 1999 Landsat TM satellite imagery, 1999
mountain pine beetle field and aerial survey point data, and GIS forest inventory
data. Unrelated variance in the observed spectral response at mountain pine
beetle field and aerial survey points was reduced following image stratification
with the GIS forest inventory data and removal of other factors uncharacteristic
of red-attack damage. Locations of known mountain pine beetle infestation
were used to train a maximum-likelihood algorithm; overall classification
accuracy was 73 percent, based on an assessment of 360 independent validation
points. If local stand variability is reduced prior to signature generation,
accuracies and map products can be useful for those involved in active forest
management decision- making regarding mountain pine beetle infestations.
289 Sampling Method and Placement: How Do They Affect
the Accuracy of Remotely Sensed Maps?
Lucie Plourde and Russell G. Congalton
Abstract Download
Full Article (460Kb Adobe PDF)
The accuracy of remotely sensed forest stand maps is traditionally assessed
by comparing a sample of the map data with actual ground conditions. Samples
most often comprise clusters of pixels within homogeneous areas, thereby
avoiding problems associated with accurately mapping “edges” (e.g.,
transition areas between two forest types). Consequently, they may well overestimate
accuracy, but the degree of overestimation is unknown. This paper examines
two important factors regarding accuracy assessment that are not well studied:
the effect on estimates of accuracy of (1) the sampling method and (2) the
exact placement of the samples. Overall accuracy, normalized accuracy, and
the KHAT statistic are computed from error matrices generated from simple
random sampling, stratified random sampling, and systematic sampling using
totally random sample placement and samples chosen from homogeneous areas
only. The results indicate that Kappa appears to be as appropriate to use
with systematic sampling and stratified random sampling as it is with simple
random sampling, but suggests that sample placement may have more of an effect
on estimates of accuracy than sampling method alone.
299 A Quantitative Assessment of a Combined Spectral
and GIS Rule-Based Land-Cover Classification in the Neuse River Basin
of North Carolina
Ross S. Lunetta, Jayantha Ediriwickrema, John Iiames, David Johnson,
John G. Lyon, Alexa McKerrow, and Andrew Pilant
Abstract Download
Full Article (492Kb Adobe PDF)
The 14,582 km2 Neuse River Basin in North Carolina was characterized based
on a user-defined land-cover (LC) classification system developed specifically
to support spatially explicit, non-point source nitrogen allocation modeling
studies. Data processing incorporated both spectral and GIS rule-based analytical
techniques using multiple date SPOT 4 (XS), Landsat 7 (ETM+), and ancillary
data sources. Unique LC classification elements included the identification
of urban classes based on impervious surfaces and specific row crop type
identifications. Individual pixels were aggregated to produce variable minimum
mapping units or landscape “patches” corresponding to both riparian
buffer zones (0.1 ha), and general watershed areas (0.4 ha). An accuracy
assessment was performed using reference data derived from in situ field
measurements and imagery (camera) data. Multiple data interpretations were
used to develop a reference database with known data variability to support
a quantitative accuracy assessment of LC classification results. Confusion
matrices were constructed to incorporate the variability of the reference
data directly in the accuracy assessment process. Accuracies were reported
for hierarchal classification levels with overall Level 1 classification
accuracy of 82 percent (n = 825) for general watershed areas, and 73 percent
(n = 391) for riparian buffer zone locations. A Kappa Test Z statistic of
3.3 indicated a significant difference between the two results. Classes that
performed poorly were largely associated with the confusion of herbaceous
classes with both urban and agricultural areas.
| Top | Home |