VOLUME 74, NUMBER 8
PHOTOGRAMMETRIC ENGINEERING & REMOTE
SENSING
JOURNAL OF THE AMERICAN SOCIETY FOR PHOTOGRAMMETRY
AND REMOTE SENSING
The cover image shows a shaded relief model of the Los Coconucos volcanic chain located in the Central Cordillera of Colombia.
The image is based on a 3-m-posted digital elevation
model produced from X- and P-band interferometric synthetic
aperture radar (IFSAR) data, collected using Fugro
EarthData’s airborne GeoSAR system (see p. 939) .
The northwestern-most volcanic crater is Puracé, one
of Colombia’s most active volcanoes, whose peaks are
seldom seen as the chain is shrouded in near-permanent
cloud cover. Puracé rises to an elevation of over 4,650 m
above sea level and has a 500-m-wide summit crater. An
estimated 200,000 people live within 35 km of the rim.
Several associated cinder cones are also clearly defined,
as well as lava and mudflows.
This detailed model illustrated the advances in airborne
IFSAR mapping over the past decade. The high level of
detail shown here is a result of the combined X- and P-band
data, which enables accurate updates to contours
and topographic maps, even over equatorial regions
characteristically obscured by persistent cloud cover and
dense vegetation. For more information, contact Dr. Tom
Carson at tcarson@earthdata.com or go to our website at
www.fugroearthdata.com.
Assessing the predictive quality of Airborne Laser Scanning
for the quantitative mapping of hydrodynamic vegetation
density of deciduous lowland floodplain forests.
A mixed linear model to examine the effect of six categories
of factors on classification uncertainty in an object-based vegetation
mapping, including general membership, topography,
sample object density, spatial composition, sample object
reliability and object features.
Integrating evidence from a range of data sources was to
produce land cover mapping based on neural networks
trained to identify specific land cover classes.
An evaluation of an object-oriented approach to deciduous
and coniferous forest classification, as well as volume and
biomass estimation, using small-footprint lidar height and
intensity distributions, and highlights of the potential of perobject
lidar data analysis for stand-level forest inventories.
Three common spectral analytical techniques (regression
modeling, regression tree, and normalized spectral mixture
analysis) for estimation of percent impervious surface area explored
and compared in terms of model accuracy, factors that
influence model performance, and cost of image processing.