This article reports on the use of digital image processing techniques to analyze an ultravioletfluorescence photograph of the area of the Shroud of Turin where the radiocarbon dating samples were taken. Results of this analysis demonstrate the anomalous nature of the radiocarbon data sample area. The techniques employed in this investigation are those used by the land remote sensing community ...

Recent increases in forest diseases have produced significant mortality in boreal forests. These disturbances influence merchantable volume predictions as they affect the distribution of live and dead trees. In this study, we assessed the use of lidar, alone or combined with multispectral imagery, to classify trees and predict the merchantable volumes of 61 balsam fir plots in a boreal forest i...

During the last several years, lidar has become a widely used technique for data collection from the earth surface and vegetation canopy being the large volume of high density lidar data the main drawback for its interpretation and analysis. In addition, parcelbased segmentation of high-resolution remotely sensed data can provide convenient and useful spatial and structural information. In this...

Multispectral imaging (MSI) data collected at multiple angles over shallow water provide analysts with a unique perspective of bathymetry in coastal areas. Observations taken by DigitalGlobe’s WorldView-2 (WV-2) sensor acquired at 39 different view angles on 30 July 2011 were used to determine the effect of acquisition angle on bathymetry derivation. The site used for this study was Kailua Bay ...

This study investigates the effectiveness of combining multispectral very high resolution (VHR) and hyperspectral satellite imagery through a decision fusion approach, for accurate forest species mapping. Initially, two fuzzy classifications are conducted, one for each satellite image, using a fuzzy output support vector machine (SVM). The classification result from the hyperspectral image is t...

Detailed knowledge of forest structure is an important component in research focusing on forest biodiversity monitoring, carbon budgeting studies, fire modelling and forest inventory estimation. In forest inventory mapping, high spatial resolution multispectral imagery are becoming a valuable and often a critical tool to effective forest resource management planning. In this research, we descri...

A de-shadowing technique is presented for multispectral and hyperspectral imagery over land acquired by satellite / airborne sensors. The method requires a channel in the visible and at least one spectral band in the near-infrared (0.8-1 μm) region, but performs much better if bands in the short-wave infrared region (around 1.6 and 2.2 μm) are available as well. Five major processing steps are ...

This paper focuses on fusion of optical and Synthetic Aperture Radar (SAR) images to combine these two types of remotely sensed imagery for features enhancement. We have proposed a new fusion technique, namely Block-based Synthetic Variable Ratio (Block-SVR), which is based on block multiple linear regression to fuse optical and SAR imagery. In order to investigate the effectiveness, the fusion...

This paper describes the use of probabilistic graphical models, in particular Bayesian networks (BN), for the detection of two problem invasive alien plants, C. odorata and L. camara, from the recently-launched 8-band Worldview-2 satellite imagery acquired on 26 September 2010 over central Swaziland. The main objective of this work was to apply and evaluate the efficacy of the very high resolut...

GaoFen-2 (GF-2) is a civilian optical satellite self-developed by China equipped with both multispectral and panchromatic sensors, and is the first satellite in China with a resolution below 1 m. Because the pan-sharpening methods on GF-2 imagery have not been a focus of previous works, we propose a novel pan-sharpening method based on guided image filtering and compare the performance to state...