LiDAR (Light Detection And Ranging) is an active sensor now approved by FEMA for construction of digital terrain models (DTMs) and digital elevation models (DEMs). DTMs and DEMs, together with appropriate GIS layers, are key sources for the construction of digital flood insurance rate maps. LiDAR use has not yet supplanted the DEMs and DTMs that have been generated using other methods that have been available for decades. However, the momentum is in that direction; the goal of this research is to show that LiDAR - combined with multispectral data - can (1) detect watersheds in urban areas that are at the scale of a neighborhood and thus can be used for storm drainage management, and (2) collect sufficient detail of the urban structural landscape to be of real use in predicting property damage for given catastropic events such as floods or earthquakes. Both LiDAR and IKONUS multispectral imagery for New Orleans, Louisiana will be used. By a combination of new analytical techniques, field observation, and comparison to standard datasets, the value of LiDAR data now owned by many state and local jurisdictions will be increased. A key element of the research is the development of a set of information fusion algorithms-that answer each of the questions: (1) Can present USGS DEMs and DTMs be improved by automatic detection of break lines and neighborhood-scale watersheds gleaned from LiDAR elevation data fused with multi-spectral imagery? (2) Can the heights, geometries, and footprints of buildings be determined with an accuracy sufficient for disaster assessment? (3) Can the fusion product provide a modeling tool to predict, given factors such as water rising level, the potential damage and provide valuable information for pre- and post-disaster planning? To address these issues will require an interdisciplinary research team consisting of an environmental engineer and two computer scientists.
Intellectual Merit: Fusing sensory data from such very different modalities using signal-level methods would be a significant achievement. LiDAR data itself will become a much more valuable commodity in the communities that possess it.
Broader Impacts: The research contributes to scholarship and public policy in two ways. First, the results will demonstrate to State and Federal agencies responsible for environmental assessment and remediation new methods for quantifying the present and past states with data already collected for floodplain analysis. Second, it will provide urban planners an inexpensive way to acquire data for economic analysis, project evaluation, and disaster damage assessment. A specific, tangible outcome (when taken in conjuction with relevant commercial work) will be lower flood insurance rates for residential and business land owners as well as more accurate assessment of tax liabilities by all jurisdictions. Data and algorithmic products produced will be disseminated through the Army Corps of Engineers at no cost to FEMA or others.
