Soil moisture (SM) plays a key role in many environmental processes and has a high spatial and temporal variability. Collecting sample SM data through field surveys (e.g., for validation of remote sensing-derived products) can be very expensive and time consuming if a study area is large, and producing accurate SM maps from the sample point data is a difficult task as well. In this study, geosp...

from a single spot on the sample surface. Depending on the homogeneity of the sample, the small spot size sampled with the tightly focused laser beam may miss the target material completely. A larger laser beam and sampling aperture can be used to acquire data from a larger spot on the sample surface, but as the aperture size is increased, resolution decreases and the high spectral resolution n...

A novel method for fabricating an adhesive resistance surface is presented. Sandblasting and electrochemical machining were introduced to prepare micro-nano structures on the sample surface. Then, the prepared sample was immersed in a tridecafluoroctyltriethoxysilane ethanol solvent. The surface of the aluminum alloy sample roughened and covered with low-surface-energy chemical groups was exami...

Introduction: Argon Ion milling is the basic conventional means used since decades when speaking of sample preparation for TEM analysis. Applied to earth and planetary samples (usually on hand as thin sections) the shortcomings are (a) nearly impossible site specific thinning and (b) only small electron transparent areas obtained. A new technique named FIB (Focused Ion Beam) developed over the ...

Deep learning algorithms show good prospects for remote sensing flood monitoring. They mostly rely on huge amounts of labeled data. However, there is a lack available data in actual needs. In this paper, we propose high-resolution multi-source dataset area extraction: GF-FloodNet. GF-FloodNet contains 13388 samples from Gaofen-3 (GF-3) and Gaofen-2 (GF-2) images. We use multi-level sample selec...