Technological advances and increasing availability of high-resolution satellite imagery offer the potential for more accurate land cover classifications and pattern analyses, which could greatly improve the detection and quantification of land cover change for conservation. Such remotely-sensed products, however, are often expensive and difficult to acquire, which prohibits or reduces their use...

Leaf area index (LAI) is an important surface biophysical parameter as an input to many process-oriented ecosystem models. Remote sensing technology provides a practical way to estimate LAI at a large spatial scale, and hence, considerable effort has been expended in developing LAI estimation models from remotely sensed imagery. LAI estimation models were usually formulated using multi-spectral...

This paper describes our approach to the DSTL Satellite Imagery Feature Detection challenge [11] run by Kaggle. The primary goal of this challenge is accurate semantic segmentation of different classes in satellite imagery. Our approach is based on an adaptation of fully convolutional neural network for multispectral data processing. In addition, we defined several modifications to the training...

The existence of a relatively long (ca. 40 yr) satellite imagery archive for examination of potential worldwide forest change motivated an inspection of the relation between forest features observable from higher resolution airborne and satellite imagery and measures of forest biomass, height, and age. Using these data, we inspected the relation between stand age, mean diameter, height, and sta...

Vehicle targets extraction is a new research issue for high resolution satellite imagery application in transportation. In this paper, an artificial immune approach is presented to extract vehicle targets from high resolution panchromatic satellite imagery. This approach uses the antibody network concept inspired from the immune system to learn a set of templates called antibodies for vehicle d...

Numerous geoscience and engineering applications need denser and more accurate Digital Terrain Model (DTM) height data. Collecting additional height data in the field, if not impossible, is either expensive or time consuming or both. Stereo aerial or satellite imagery is often unavailable and very expensive to acquire. Interpolation techniques are fast and cheap, but have their own inherent dif...

The focus of this study was to thoroughly exploit the capability of very high-resolution VHR satellite imagery such as Ikonos and QuickBird for disaster mitigation. An efficient automated methodology that detects damage was implemented to derive the rich information available from VHR satellite imagery. Consequently, the detected results and the VHR satellite imagery are attractively presented ...

An accurate digital elevation model (DEM) is a critical data set for characterizing the natural landscape, monitoring natural hazards, and georeferencing satellite imagery. The ideal interferometric synthetic aperture radar (InSAR) configuration for DEM production is a single-pass two-antenna system. Repeat-pass single-antenna satellite InSAR imagery, however, also can be used to produce useful...