No abstract

No abstract

Abstract. The purpose of this research is to extract spectral reflectance characteristics of concretes through basic experiment on concrete specimens and site experiment on actual concrete structures using a field portable spectrometer and a VNIR hyperspectral sensor. A spectrometer (GER-3700) and a VNIR hyperspectral camera (AisaEagle VNIR Hyperspectral Camera) were utilized for extracting spectral characteristics of concrete specimens and actual concrete structures. General concretes show similar pattern with correlation more than 80%, while super high strength concrete shows very different aspect from general concretes. The GER-3700 spectrometer and the VNIR camera were applied to extracting spectral characteristics of the actual concrete structures such as a bridge slab and pier in road construction site. We also made certain in not only interior experiment on concrete specimens but also site experiment on actual concrete structures that both the spectrometer and the VNIR camera vary in spectral reflectance depending on concrete strength. Afterwards if the studies on hyperspectral characteristics of worn-out concretes, concrete aggregate condition diversity, super high-strength concretes are performed in depth, it is helpful in stability evaluation and maintenance management of concrete-based structures or facilities using airborne or satellite hyperspectral images for a wide area.

The Shuttle Radar Topography Mission (SRTM) data represent a major breakthrough in terms of providing accurate and consistent elevation data on a worldwide basis. These data are being used in many scientific applications, hydrology in particular. This letter examines the feasibility of using SRTM data for hydrologic characterizations, particularly in a region of low relief exemplified by the Otter Tail basin in Minnesota. The Version 2 SRTM data product provides a useful starting place for estimating the stage for larger lakes. Indications for Minnesota are that these estimates are accurate to several meters but are biased toward underestimation. Over land, the inherent noise in the data makes watershed boundary and stream network extraction problematic. We found large errors in estimated basin shape and area, and in the geometry of extracted stream networks, as compared to more traditional U.S. Geological Survey data products.

No abstract