United States Department of Transportation
i
Using Information at Different Spatial Scales to Estimate Demand to Support Asset Management Decision Making
-
2019-07-01
-
[PDF-5.41 MB]
Details:
-
Creators:
-
Corporate Creators:
-
Corporate Contributors:
-
Subject/TRT Terms:
-
Publication/ Report Number:
-
Resource Type:
-
Geographical Coverage:
-
Edition:Final Report, 9/1/2014 – 8/31/2015
-
Corporate Publisher:
-
Abstract:Quantifying disaster recovery is important to be able to match resources to needs. The research explores the use of survey data, FEMA assessment data, aerial photographs and LIDAR data in the context of recovery from 2012 Hurricane Sandy in Sea Bright, New Jersey. The data cover the period 2010 to 2015. Each of the data sources differ in terms of completeness, resolution, accuracy, coverage and the time period in which it was collected. Using spatial analysis, the analysis found that different data sources gave similar estimates for recovery for the entire borough. More careful analysis of specific plots using data from different sources found that the redevelopment was slow and, in some cases, stagnant when the damage was extensive or demolition required. This report documents the sources of the data, presents a framework for data analysis and presents Sea Bright as a case study. These methods show promise and document the value in periodic analysis of publicly available data from different sources to document recovery. There are further opportunities to develop time series analysis with more recent data to both understand how to leverage this data and document the recovery process.
-
Format:
-
Funding:
-
Collection(s):
-
Main Document Checksum:
-
Download URL:
-
File Type:
