LiDAR

We use two recent Japanese earthquakes to demonstrate the rich potential, as well as some of the challenges, of differencing repeat airborne Light Detection and Ranging (lidar) topographic data to measure coseismic fault zone deformation. We focus on densely-vegetated sections of the 14 June 2008 Iwate–Miyagi (Mw 6.9) and 11 April 2011 Fukushima–Hamadori (Mw 7.1) earthquake ruptures, each covered by 2 m-resolution pre-event and 1 m-resolution post-event bare Earth digital terrain models (DTMs) obtained from commercial lidar providers. Three-dimensional displacements and rotations were extracted from these datasets using an adaptation of the Iterative Closest Point (ICP) algorithm. These displacements remain coherent close to surface fault breaks, as well as within dense forest, despite intervals of ∼2 years (Iwate–Miyagi) and ∼4 years (Fukushima–Hamadori) encompassed by the lidar scenes. Differential lidar analysis is thus complementary to Interferometric Synthetic Aperture Radar (InSAR) and sub-pixel correlation techniques which often break down under conditions of long time intervals, dense vegetation or steep displacement gradients. Although the ICP displacements are much noisier than overlapping InSAR line-of-sight displacements, they still provide powerful constraints on near-surface fault slip. In the Fukushima–Hamadori case, near-fault displacements and rotations are consistent with decreased primary fault slip at very shallow depths of a few tens of meters, helping to account for the large, along-strike heterogeneity in surface offsets observed in the field. This displacement field also captures long-wavelength deformation resulting from the 11 March 2011 Tohoku great earthquake.

Management of highly dynamic coastal landscapes requires repeated mapping and analysis of observed changes. Modern mapping techniques such as lidar increased the frequency and level of detail in coastal surveys and new methods were developed to extract valuable information from these data using Geographic Information Systems. The brief presents techniques for analyzing and visualizing coastal topographic and shoreline change and sand dune dynamics using open source GRASS GIS.

What can remote sensing contribute to archaeological surveying in subarctic and arctic landscapes? The pros and cons of remote sensing data vary as do areas of utilization and method-ological approaches. We assessed the applicability of remote sensing for archaeological surveying of northern landscapes using airborne laser scanning (LiDAR) and satellite and aerial images to map archaeological features as a basis for a) assessing the pros and cons of the different approaches and b) assessing the potential detection rate of remote sensing. Interpretation of images and a Li-DAR-based bare-earth digital terrain model (DTM) was based on visual analyses aided by processing and visualizing techniques. 368 features were identified in the aerial images, 437 in the satellite images and 1186 in the DTM. LiDAR yielded the better result, especially for hunting pits. Image data proved suitable for dwellings and settlement sites. Feature characteristics proved a key factor for detectability, both ...

The urban heat island (UHI) phenomenon is a significant worldwide problem caused by rapid population growth and associated urbanization. The UHI effect exacerbates heat waves during the summer, increases energy and water consumption, and causes the high risk of heat-related morbidity and mortality. UHI mitigation efforts have increasingly relied on wisely designing the urban residential environment such as using high albedo rooftops, green rooftops, and planting trees and shrubs to provide canopy coverage and shading. Thus, strategically designed residential rooftops and their surrounding landscaping have the potential to translate into significant energy, long-term cost savings, and health benefits. Rooftop albedo, material, color, area, slope, height, aspect and nearby landscaping are factors that potentially contribute. To extract, derive, and analyze these rooftop parameters and outdoor landscaping information, high resolution optical satellite imagery, LIDAR (light detection and ranging) point clouds and thermal imagery are necessary. Using data from the City of Tempe AZ (a 2010 population of 160,000 people), we extracted residential rooftop footprints and rooftop configuration parameters from airborne LIDAR point clouds and QuickBird satellite imagery (2.4 m spatial resolution imagery). Those parameters were analyzed against surface temperature data from the MODIS/ASTER airborne simulator (MASTER). MASTER images provided fine resolution (7 m) surface temperature data for residential areas during daytime and night time. Utilizing these data, ordinary least squares (OLS) regression was used to evaluate the relationships between residential building rooftops and their surface temperature in urban environment. The results showed that daytime rooftop temperature was closely related to rooftop spectral attributes, aspect, slope, and surrounding trees. Night time temperature was only influenced by rooftop spectral attributes and slope.