Liquid water stored on the surface of ice sheets and glaciers impacts surface mass balance, ice dynamics, and heat transport. Multispectral remote sensing can be used to detect supraglacial lakes and estimate their depth and area. In this study, we use in situ spectral and bathymetric data to assess lake depth retrieval using the recently launched Landsat 8 Operational Land Imager (OLI). We als...

When light is reflected from object surface, its spectral characteristics will be affected by the surface’s elemental composition, and its polarimetric characteristics will be governed by the surface’s roughness and conductance. Polarimetric and multispectral imaging can provide complementary discriminative information in applications such as object separation. However, few methods have been pr...

Estimating aboveground carbon stocks of a forest affected by mountain pine beetle in Idaho using lidar and multispectral imagery" (2012). USDA Forest Service / UNL Faculty Publications. Paper 215. a b s t r a c t a r t i c l e i n f o Keywords: Carbon Mountain pine beetle Insect outbreak Tree mortality Aerial imagery Lidar Mountain pine beetle outbreaks have caused widespread tree mortality in ...

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Land surface temperature (LST) and emissivity are important components of land surface modeling and applications. The only practical means of obtaining LST at spatial and temporal resolutions appropriate for most modeling applications is through remote sensing. While the popular split-window method has been widely used to estimate LST, it requires known emissivity values. Multispectral thermal ...

The use of high resolution IKONOS imagery should make it possible to extract urban features like buildings and roads more easily than conventional satellite image data. This work examines the synergetic ability of using spectral information from multispectral data in combination with spatial information from panchromatic data in urban land cover mapping using IKONOS Imagery. In this work we tri...

In recent years the use of remote sensing imagery to classify and map vegetation over different spatial scales has gained wide acceptance in the research community. Many national and regional datasets have been derived using remote sensing data. However, much of this research was undertaken using multispectral remote sensing datasets. With advances in remote sensing technologies, the use of hyp...

High spatial resolution hyperspectral data often used in precision farming applications are not available from current satellite sensors, and difficult or expensive to acquire from standard aircraft. Alternatively, in precision farming, unmanned aerial vehicles (UAVs) are emerging as lower cost and more flexible means to acquire very high resolution imagery. Miniaturized hyperspectral sensors h...

The aim of this research is to determine an accuracy assessment of different multispectral gradient-based edge detectors. We will present and evaluate three different approaches: the mean-, the maximumand the multispectral gradient approach. The mean approach determines the overall gradient as the arithmetic mean of all (band-wise) gradient vectors, whereas the maximum approach selects the grad...

Data simulation is widely used in remote sensing to produce imagery for a new sensor in the design stage, for scale issues of some special applications, or for testing of novel algorithms. Hyperspectral data could provide more abundant information than traditional multispectral data and thus greatly extend the range of remote sensing applications. Unfortunately, hyperspectral data are much more...