Geoscience and Remote Sensing

The multi-effect fields in the grounded-wire source time-domain electromagnetic (TDEM) will be generated by complex physical characteristics and parameter information of polymetallic ore. The studies show that the induced polarization (IP) and magnetic viscosity (MV) effects are significant signs of polymetallic ore and have been proved t

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A direct three-dimensional (3-D) modeling of B-field in TDEM is proposed in the paper. We first introduce the forward modeling method of static magnetic field for the calculation of initial value of B-field. Then, we achieve the iterative calculation of B-field of magnetic media during the transient electromagnetic (TEM) stage by substituting the Cole–Cole susceptibility model into the B-field diffusion equation of double-curl induced magnetization intensity. The validity of this method is verified using several analytical solutions.

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The raw MTBS data were downloaded from the official website (https://www.mtbs.gov/direct-download), and we select the pre-fire images, post-fire images, and thematic burn severity layers from 2010 to 2019 (over 7000 fires) across the conterminous United States as the data source of Landsat-BSA dataset. The raw MTBS dataset is preprocessed, reformed, and relabeled to produce the Landsat-BSA dataset with a sample size of 256 × 256.

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Sea ice concentration is important because it helps in determining important climate variables. Together with sea ice thickness, important fluxes between air and sea as well as heat transfer between the atmosphere can be determined. We designed an adapted bootstrap algorithm called SARAL/AltiKa Sea Ice Algorithm (SSIA) with some tunings and segregated the algorithm into winter and summer algorithms to estimate daily sea ice concentration (SIC) in the Arctic.

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SAR-optical remote sensing couples are widely exploited for their complementarity for land-cover and crops classifications, image registration, change detections and early warning systems. Nevertheless, most of these applications are performed on flat areas and cannot be generalized to mountainous regions. Indeed, steep slopes are disturbing the range sampling which causes strong distortions in radar acquisitions - namely, foreshortening, shadows and layovers.

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Since meteorological satellites can observe the Earth’s atmosphere from a spatial perspective at a large scale, in this paper, a dust storm database is constructed using multi-channel and dust label data from the Fengyun-4A (FY-4A) geosynchronous orbiting satellite, namely, the Large-Scale Dust Storm database based on Satellite Images and Meteorological Reanalysis data (LSDSSIMR), with a temporal resolution of 15 minutes and a spatial resolution of 4 km from March to May of each year during 2020–2022.

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Adverse climatic events like heat stress, floods, unseasonal rainfall, and droughts frequently hinder crop productivity. Long-term crop yield data plays a crucial role in food security planning. This study presents historical wheat yield data at the satellite pixel level from 2001 to 2019 in Uttar Pradesh, India. We use various satellite indicators to develop wheat yield models, including the normalized difference vegetation index and gridded weather data, such as precipitation, temperature, and evapotranspiration.

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556 Views

Mapping millions of buried landmines rapidly and removing them cost-effectively is supremely important to avoid their potential risks and ease this labour-intensive task. Deploying uninhabited vehicles equipped with multiple remote sensing modalities seems to be an ideal option for performing this task in a non-invasive fashion. This report provides researchers with vision-based remote sensing imagery datasets obtained from a real landmine field in Croatia that incorporated an autonomous uninhabited aerial vehicle (UAV), the so-called LMUAV.

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