Pixel-wise spectral classiication is a widely used technique to produce thematic maps from remotely sensed multispectral imagery. It is commonly based on purely spectral features. In our approach we additionally consider additional spatial features in the form of local context information. After all, spatial context is the deening property of an image. Markov random eld modeling provides the as...

High spatial resolution multispectral/hyperspectral sensors are being developed by private industry with science/research customers as end users. With an increasingly wide range of sensor choices, it is important for the remote sensing science community and commercial community alike to understand the trade-offs between ground sample distance (GSD), spectral resolution, and signal-to-noise rati...

* Corresponding author Abstract In this paper, a modern spectral analysis method, based on the maximum entropy, for edge detection in multispectral imagery is presented. This technique is shown to be simple and easy to implement. Due to its distinct features, the maximum entropy is proven advantageous when compared to other conventional multidimensional edge detection methods. This method does ...

An automatic process for relative registering and merging the panchromatic and multispectral images of SPOT5 is presented. The automated hierarchical local registration process makes use of feature information to select tie points from both images. The tie points are then used to refine the sensor model of the multispectral image by method of least squares solution. Both panchromatic and multis...

The paper compares different data fusion techniques in order to choose an appropriate technique for accurate urban mapping. Availability of high spatial resolution Ikonos and Quickbird imagery has made accurate mapping of urban areas more feasible. Though Ikonos multispectral images have a good spatial resolution of 4 m, it is often desirable to have an increased spatial resolution for a more a...

With the recent advancements in image processing techniques and the increasing availability of high resolution satellite imagery, one has an increased ability to characterize human attributes. This paper will study the effects that image fusion has on the classification of Quickbird satellite imagery over a rural area in Eastern India. Two panchromatic sharpening algorithms will be used and com...

Unmanned aircraft have decreased the cost required to collect remote sensing imagery, which has enabled researchers to collect high-spatial resolution data from multiple sensor modalities more frequently and easily. The increase in data will push the need for semantic segmentation frameworks that are able to classify non-RGB imagery, but this type of algorithmic development requires an increase...

Obtaining detailed and reliable data about local economic livelihoods in developing countries is expensive, and data are consequently scarce. Previous work has shown that it is possible to measure local-level economic livelihoods using high-resolution satellite imagery. However, such imagery is relatively expensive to acquire, often not updated frequently, and is mainly available for recent yea...

Concerns over worldwide declines in marine resources have prompted the search for innovative solutions for their conservation and management, particularly for coral reef ecosystems. Rapid advances in sensor resolution, coupled with image analysis techniques tailored to the unique optical problems of marine environments have enabled the derivation of detailed benthic habitat maps of coral reef h...

-This is the second paper of the series on atmospheric correction of ETM+ land surface imagery. In the first paper, a new algorithm that corrects heterogeneous aerosol scattering and surface adjacency effects was presented. In this study, our objectives are to 1) evaluate the accuracy of this new atmospheric correction algorithm using ground radiometric measurements; 2) apply this algorithm to ...