Environmental Engineering Reference
In-Depth Information
13
Small area population estimation
with high-resolution remote sensing
and lidar
Le Wang and Jose-Silvan Cardenas
Timely small-area population estimates are critical for both public and private sector decision-making. State and
local governments must allocate resources, and private businesses need to identify and delineate customer profiles,
market areas and site locations. Currently, such population data is only available for one date per decade through
the national census. This study focuses on developing methods for intercensal small-area population estimation
from integrative use of airborne light detection and ranging (lidar) and high spatial resolution aerial photographs.
Particularly, it addresses the following question: What level of information extracted from lidar and high-spatial
resolution imagery can be effectively infused in deriving small-area population estimation? This question was
addressed through a comparative study of seven linear models parameterized in terms of building count, building
area and/or building volume, at two different land use levels: single-family dwelling, multifamily dwelling and
other types, versus residential and other types. Results showed that while building volume is more relevant to
population counts at census block level; it also represents the most challenging parameter to measure by automated
analyses of lidar and high resolution remote sensing imagery. Because of that, a simple model that primarily utilizes
residential building counts resulted in more reliable population estimation.
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