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Spatial sampling optimization is an important issue for both geo-chemists and geo-statisticians. Many spatial sampling optimization methods have been previously developed. In this paper, we present a ...
This study focus on the characterization of hydrocarbon microseepages in the northern Tucano Basin (Bahia State, Brazil), using geostatistical analysis of regional hydrocarbon geochemical data yielded...
Every year sugar beet diseases cause lower sugar beet yields and qualities compared to the average. For that reason, high resolution field and airborne hyperspectral data is used to recognize a fungal...
An image classification method based on Support Vector Machine (SVM) is proposed on hyperspectral and 3K DSM data. To obtain training data we applied an automatic method relating to four classes nam...
Rapid advancement in remote sensing open new avenues to explore the hyperspectral Hyperion imagery pre-processing techniques, analysis and application for land use mapping. The hyperspectral data cons...
Spectral mixing is inherent in any finite-resolution digital imagery of a heterogeneous surface, so that mixed pixels are inevitably created when multispectral images are scanned. Solving the spectra...
Grazing lands in the United States consist of approximately 312 million hectares of federal, state, and private land. A recent review by the National Research Council indicates a need to collect comp...
The first applications of a prototype 8-channel full waveform active hyperspectral lidar (HSL) show a possibility to determine various target 3D characteristics with remote observations. The results o...
Compact and lightweight hyperspectral imagers allow the application of close range hyperspectral imaging with a ground based scanning setup for geological fieldwork. Using such a scanning setup, steep...

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