Target Classification and Remote Sensing of Ocean Current Shear Using a Dual-Use Multifrequency HF Radar

2006 ◽  
Vol 31 (4) ◽  
pp. 904-918 ◽  
Author(s):  
D. Trizna ◽  
L. Xu
Keyword(s):  
Remote Sensing ◽  
Hf Radar ◽  
Ocean Current ◽  
Target Classification ◽  
Dual Use

Spatio-Temporal Deep Learning for Ocean Current Prediction Based on HF Radar Data

2019 ◽  
Author(s):  
Nathachai Thongniran ◽  
Peerapon Vateekul ◽  
Kulsawasd Jitkajornwanich ◽  
Siam Lawawirojwong ◽  
Panu Srestasathiern
Keyword(s):  
Deep Learning ◽  
Radar Data ◽  
Hf Radar ◽  
Ocean Current ◽  
Spatio Temporal

scholarly journals Strongly Coupled Assimilation of a Hypothetical Ocean Current Observing Network within a Regional Ocean-Atmosphere Coupled Model: An OSSE Case Study of Typhoon Hato

2021 ◽  
Author(s):  
Luke Phillipson ◽  
Yi Li ◽  
Ralf Toumi
Keyword(s):  
Coupled Model ◽  
Ocean Currents ◽  
Hf Radar ◽  
Ocean Current ◽  
Coastal Current ◽  
Strongly Coupled ◽  
Ocean Atmosphere ◽  
Atmospheric Observations ◽  
Surface Drifters ◽  
The Impact

AbstractThe forecast of tropical cyclone (TC) intensity is a significant challenge. In this study, we showcase the impact of strongly coupled data assimilation with hypothetical ocean currents on analyses and forecasts of Typhoon Hato (2017). Several observation simulation system experiments were undertaken with a regional coupled ocean-atmosphere model. We assimilated combinations of (or individually) a hypothetical coastal current HF radar network, a dense array of drifter floats and minimum sea-level pressure. During the assimilation, instant updates of many important atmospheric variables (winds and pressure) are achieved from the assimilation of ocean current observations using the cross-domain error covariance, significantly improving the track and intensity analysis of Typhoon Hato. As compared to a control experiment (with no assimilation), the error of minimum pressure decreased by up to 13 hPa (4 hPa / 57 % on average). The maximum wind speed error decreased by up to 18 knots (5 knots / 41 % on average). By contrast, weakly coupled implementations cannot match these reductions (10% on average). Although traditional atmospheric observations were not assimilated, such improvements indicate there is considerable potential in assimilating ocean currents from coastal HF radar, and surface drifters within a strongly coupled framework for intense landfalling TCs.

scholarly journals Spectral Unmixing for Thermal Infrared Multi-Spectral Airborne Imagery over Urban Environments: Day and Night Synergy

2020 ◽  
Vol 12 (11) ◽  
pp. 1871
Author(s):  
Carlos Granero-Belinchon ◽  
Aurelie Michel ◽  
Veronique Achard ◽  
Xavier Briottet
Keyword(s):  
Remote Sensing ◽  
Urban Environments ◽  
Spectral Unmixing ◽  
Urban Heat Islands ◽  
European Security ◽  
Dual Use ◽  
Heat Islands ◽  
Spectral Bands ◽  
Urban Heat ◽  
Study Case

TRUST (Thermal Remote sensing Unmixing for Subpixel Temperature) is a spectral unmixing method developed to provide subpixel abundances and temperatures from radiance images in the thermal domain. By now, this method has been studied in simple study cases, with a low number of endmembers, high spatial resolutions (1 m) and more than 30 spectral bands in the thermal domain. Thus, this article aims to show the applicability of TRUST on a highly challenging study case: the analysis of a heterogeneous urban environment with airborne multispectral (eight thermal bands) images at 8-m resolution. Thus, this study is necessary to generalize the use of TRUST in the analysis of urban thermography. Since TRUST allows linking intrapixel temperatures to specific materials, it appears as a very useful tool to characterize Surface Urban Heat Islands and its dynamics at high spatial resolutions. Moreover, this article presents an improved version of TRUST, called TRUST-DNS (Day and Night Synergy), which takes advantage of daytime and nighttime acquisitions to improve the unmixing performances. In this study, both TRUST and TRUST-DNS were applied on daytime and nighttime airborne thermal images acquired over the center of Madrid during the DESIREX (Dual-use European Security IR Experiment) campaign in 2008. The processed images were obtained with the Aircraft Hyperspectral Scanner (AHS) sensor at 4-m spatial resolution on 4 July. TRUST-DNS appears to be more stable and slightly outperforms TRUST on both day and night images. In addition, TRUST applied on daytime outperforms TRUST on nighttime, illustrating the importance of the temperature contrasts during day for thermal unmixing.

Study of Marine Environment and Squid Fishing Fisheries in North Pacific Ocean Based on Remote Sensing and GIS Technology

2013 ◽  
Vol 726-731 ◽  
pp. 4604-4609 ◽  
Author(s):  
Feeng Hua Tang ◽  
Yu Mei Wu ◽  
Wei Feng Zhou ◽  
Xue Sen Cui ◽  
Wei Fan ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Pacific Ocean ◽  
Surface Temperature ◽  
Marine Environment ◽  
North Pacific ◽  
North Pacific Ocean ◽  
Ocean Current ◽  
Fish Catch ◽  
Neon Flying Squid ◽  
Feeding Migration

Through the surface temperature (SST), sea chlorophyll and ocean current data got by satellite remote sensing inversion technology, and the statistic of fishing boat in the North Pacific from 2006 to 2011, this paper analyzes the relationship of marine environment and squid fishing fisheries fluctuate in North Pacific Ocean. It is determined that the sea surface temperature scope of high squid fisheries is 10~22°C, and the appropriate temperature is 18~20°C. The chlorophyll density of squid fish is approximately 0.02~0.40mg/m3.The frequency is the highest when the chlorophyll density is between 0.08~0.24 mg/m3. GAM module analysis indicates that neon flying squid the relation of the entertainment factor and north feeding migration every June to August and South action every October to November has different features. There is a positive correlation between SST and neon flying squid catch while north feeding migration. It is a negative correlation while going south. And there is a good correspondence between the distribution of chlorophyll and the distribution of the fish catch of core fishery. Fish catch doesn`t has great change as with longitude, but it correspond well with the latitude.

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