The maximum noise fraction (MNF) transform, which produces the improved order of components by signal to noise ratio (SNR), has been commonly used for spectral feature extraction from hyperspectral remote sensing data before image classification. When hyperspectral data contains a spectral distortion, also known as a “smile” property, the first component of the MNF, which should have high image...

This paper discusses the role of scattering decomposition models in the classification of polarimetric SAR sea ice data. The iterative Wishart classifier was applied to 3-frequency airborne SAR data acquired in the Beaufort Sea, and the scattering models were found to be helpful in interpreting the assigned classes. In addition to using the full data set, reduced data sets based on an eigenvect...

the analytic signal method is usually used to interpret the magnetic and gravity anomalies. the main advantage of using analytic signal method in interpretation of magnetic source parameters from magnetic anomalies is that the amplitude dip of the analytic signal is independent of directional parameters like magnetization and the dip of the source. using the coefficient of the amplitude to esti...

The purpose of this research plan is to outline an approach to understanding public values and attitudes relating to policy initiatives in ecological risk management. Although key elements of the approach are intended to be broadly applicable, the specific case study of nitrogen deposition by air to the Tampa Bay, Florida estuary is used to illustrate and provide supplementary details of the pr...

Merging hyperspectral data from optical and thermal ranges allows a wider variety of minerals to be mapped and thus allows lithology to be mapped in a more complex way. In contrast, in most of the studies that have taken advantage of the data from the visible (VIS), near-infrared (NIR), shortwave infrared (SWIR) and longwave infrared (LWIR) spectral ranges, these different spectral ranges were ...

Estimating crop nitrogen (N) status with sensors can be useful to adjust fertilizer levels to crop requirements, reducing farmers’ costs and N losses to the environment. In this study, we evaluated the potential of hyperspectral indices obtained from field data and airborne imagery for developing N fertilizer recommendations in maize (Zea mays L.). Measurements were taken in a randomized field ...

Identification of crop species is an important issue in agricultural management. In recent years, many studies have explored this topic using multi-spectral and hyperspectral remote sensing data. In this study, we perform dedicated research to propose a framework for mapping crop species by combining hyperspectral and Light Detection and Ranging (LiDAR) data in an object-based image analysis (O...

Although many researchers have studied building reconstruction from remotely sensory data, most approaches are not yet satisfactory in terms of the degree of automation, the reconstructed details and the accuracy. With the innovation of sensory technology, more advanced sensors are now available and getting cheaper. This paper describes a framework for automatic generation of 3D building models...