scholarly journals TEST SYSTEM OF ECOLOGICAL MONITORING OF FILM POLLUTIONS IN THE GORKOVSKY RESERVOIR

2020 ◽  
pp. 11-19
Author(s):  
Alexey V. Ermoshkin ◽  
Ivan A. Kapustin ◽  
Alexandr A. Molkov ◽  
Evgeny I. Poplavsky ◽  
Nikita S. Rusakov
Keyword(s):  
Remote Sensing ◽  
Environmental Monitoring ◽  
Physical Dependence ◽  
Data Modeling ◽  
Ecological Monitoring ◽  
Test System ◽  
Sea Surface ◽  
X Band ◽  
Coherent Radar ◽  
Model Approach

The article considers the issue of creating a system of environmental monitoring of film pollutions in the Gorky reservoir. A combination of the well-known model approach for calculating the drift trajectories of passive particles on the sea surface with the data of remote sensing, which provide primary detection of a spill of pollutants in the scanned area, is proposed. X-band digital coherent radar was the source of remote data. Modeling was based on the results of measurements of current velocities and the physical dependence of the slick drift. As a result of comprehensive studies, the developed system has demonstrated operability for detecting and predicting the spread of film pollution in the Gorky reservoir.

scholarly journals A New Shooting Bouncing Ray Method for Composite Scattering from a Target above the Electrically Large Scope Sea Surface

2017 ◽  
Vol 2017 ◽  
pp. 1-7
Author(s):  
Peng Peng ◽  
Guo Lixin
Keyword(s):  
Remote Sensing ◽  
Large Scale ◽  
Sea Surface ◽  
Radar Target ◽  
Hybrid Scheme ◽  
Ray Method ◽  
Electromagnetic Interactions ◽  
X Band ◽  
Large Scope ◽  
Low Altitude

A new shooting and bouncing ray (SBR) simulator based on the hybrid scheme of GO/PO/SDFM/EEC method is developed for the accurate prediction of composite scattering from a low altitude target above the electrically very-large-scale sea surface. It can adequately deal with the complex local electromagnetic interactions between the target and the large scope sea surface. The method is compared with the exact computational electromagnetic solver FEKO-MLFMM to validate its accuracy and efficiency. Then, it is applied to simulate the bistatic and monostatic scattering characteristics of an airplane above the electrically large sea surface at X-band, for different sea states. The results reveal the contributions from the target, sea surface, and interactions, which are of significance for radar target detection and remote sensing in real maritime environments.

Integrating remote sensing and machine learning into environmental monitoring and assessment of land use change

2021 ◽  
Vol 27 ◽  
pp. 1239-1254
Author(s):  
Hong Anh Thi Nguyen ◽  
Tip Sophea ◽  
Shabbir H. Gheewala ◽  
Rawee Rattanakom ◽  
Thanita Areerob ◽  
...  
Keyword(s):  
Machine Learning ◽  
Remote Sensing ◽  
Land Use ◽  
Land Use Change ◽  
Environmental Monitoring

scholarly journals Snapshot Wisconsin: networking community scientists and remote sensing to improve ecological monitoring and management

2021 ◽  
Author(s):  
Philip A. Townsend ◽  
John D.J. Clare ◽  
Nanfeng Liu ◽  
Jennifer L. Stenglein ◽  
Christine Anhalt‐Depies ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Ecological Monitoring

scholarly journals Remote Sensing Supported Sea Surface pCO2 Estimation and Variable Analysis in the Baltic Sea

2021 ◽  
Vol 13 (2) ◽  
pp. 259
Author(s):  
Shuping Zhang ◽  
Anna Rutgersson ◽  
Petra Philipson ◽  
Marcus B. Wallin
Keyword(s):  
Remote Sensing ◽  
Baltic Sea ◽  
Mean Squared Error ◽  
Numerical Models ◽  
Mixed Layer Depth ◽  
Sea Surface ◽  
The Baltic Sea ◽  
Chl A ◽  
Marginal Seas ◽  
The Baltic

Marginal seas are a dynamic and still to large extent uncertain component of the global carbon cycle. The large temporal and spatial variations of sea-surface partial pressure of carbon dioxide (pCO2) in these areas are driven by multiple complex mechanisms. In this study, we analyzed the variable importance for the sea surface pCO2 estimation in the Baltic Sea and derived monthly pCO2 maps for the marginal sea during the period of July 2002–October 2011. We used variables obtained from remote sensing images and numerical models. The random forest algorithm was employed to construct regression models for pCO2 estimation and produce the importance of different input variables. The study found that photosynthetically available radiation (PAR) was the most important variable for the pCO2 estimation across the entire Baltic Sea, followed by sea surface temperature (SST), absorption of colored dissolved organic matter (aCDOM), and mixed layer depth (MLD). Interestingly, Chlorophyll-a concentration (Chl-a) and the diffuse attenuation coefficient for downwelling irradiance at 490 nm (Kd_490nm) showed relatively low importance for the pCO2 estimation. This was mainly attributed to the high correlation of Chl-a and Kd_490nm to other pCO2-relevant variables (e.g., aCDOM), particularly in the summer months. In addition, the variables’ importance for pCO2 estimation varied between seasons and sub-basins. For example, the importance of aCDOM were large in the Gulf of Finland but marginal in other sub-basins. The model for pCO2 estimate in the entire Baltic Sea explained 63% of the variation and had a root of mean squared error (RMSE) of 47.8 µatm. The pCO2 maps derived with this model displayed realistic seasonal variations and spatial features of sea surface pCO2 in the Baltic Sea. The spatially and seasonally varying variables’ importance for the pCO2 estimation shed light on the heterogeneities in the biogeochemical and physical processes driving the carbon cycling in the Baltic Sea and can serve as an important basis for future pCO2 estimation in marginal seas using remote sensing techniques. The pCO2 maps derived in this study provided a robust benchmark for understanding the spatiotemporal patterns of CO2 air-sea exchange in the Baltic Sea.

scholarly journals SST Anomalies in the Mozambique Channel Using Remote Sensing and Numerical Modeling Data

2019 ◽  
Vol 11 (9) ◽  
pp. 1112
Author(s):  
Guoqing Han ◽  
Changming Dong ◽  
Junde Li ◽  
Jingsong Yang ◽  
Qingyue Wang ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Mixed Layer Depth ◽  
Surface Wind ◽  
Radiant Heat ◽  
Heat Fluxes ◽  
Sea Surface ◽  
Surface Mixed Layer ◽  
Mozambique Channel ◽  
Sea Surface Wind ◽  
Sst Anomalies

Based on both satellite remote sensing sea surface temperature (SST) data and numerical model results, SST warming differences in the Mozambique Channel (MC) west of the Madagascar Island (MI) were found with respect to the SST east of the MI along the same latitude. The mean SST west of the MI is up to about 3.0 °C warmer than that east of the MI. The SST differences exist all year round and the maximum value appears in October. The area of the highest SST is located in the northern part of the MC. Potential factors causing the SST anomalies could be sea surface wind, heat flux and oceanic flow advection. The presence of the MI results in weakening wind in the MC and in turn causes weakening of the mixing in the upper oceans, thus the surface mixed layer depth becomes shallower. There is more precipitation on the east of the MI than that inside the MC because of the orographic effects. Different precipitation patterns and types of clouds result in different solar radiant heat fluxes across both sides of the MI. Warm water advected from the equatorial area also contribute to the SST warm anomalies.

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