Registering video imagery in real-time is a demanding process. Multispectral imagery adds complexity due to the variances between different bands. This paper demonstrates a process that registers airborne multispectral imagery at a rate of thirty frames per second. It can create both mosaics and multispectral sets from a camera that captures a cycle of spectral bands with each spectral band in ...

Multispectral imagery (MSI) taken with high-spatial resolution systems provides a powerful tool for mapping kelp in water. MSI are not always available, however, and there are systems which provide only panchromatic imagery which would be useful to exploit for the purpose of mapping kelp. Kelp mapping with MSI is generally done by use of the standard Normalized Difference Vegetation Index (NDVI...

This study deals with the automatic interpretation of digital imagery and focuses on natural topographic objects, in particular vegetation. As a first step for developing a sound strategy combining pixel based and model based image analysis, we investigate the possibilities and limitations of pixel based methods in large scale applications. Throughout the paper we assume multispectral imagery a...

Mountain resort development is having increasing effects on ecological functions in the intermountain West. High-resolution remote sensing has the potential to assist in monitoring this development. We evaluated classification of mountain resort development in the Big Sky, Montana, watershed using Quickbird 2.4-m multispectral imagery with an object-oriented classification. Quickbird imagery, h...

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...

Two examples are shown of remote sensing data applications for integrated models of separate spheres of the Earth. Innovative techniques of vegetation biomass amount assessment using multispectral satellite imagery is given in the first example. Problems of temporal data series analysis for information products of satellite data processing using a gridded data representation to understand predi...

Most of Earth’s volcanic eruptions occur underwater, and these submarine can significantly impact large-scale Earth systems (e.g., enhancing local primary production by phytoplankton). However, detecting is challenging due to their remote locations, short eruption durations, lack sea surface signature (if do not breach the surface), transient nature manifestations an floating pumice clasts, hyd...

Unoccupied aerial vehicles (UAVs) have become increasingly commonplace in aiding planning and management decisions agricultural horticultural crop production. The ability of UAV-based sensing technologies to provide high spatial (<1 m) temporal (on-demand) resolution data facilitates monitoring individual plants over time can essential information about health, yield, growth a timely quantif...

Gross primary productivity (GPP) is an essential parameter to assess the efficiency of terrestrial ecosystems on carbon transfer. Although GPP regularly measured with eddy covariance (EC) systems, these are restricted tower footprint area, and remote sensing (RS) products have estimated using multispectral vegetation indexes (VIs) from farms whole ecosystems. Indeed, nowadays, unmanned aerial v...