Coastal Zone
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2022 ◽  
Vol 131 (1) ◽  
Nikolay I Akulov ◽  
Maria N Rubtsova ◽  
Varvara V Akulova ◽  
Alexander A Shchetnikov

2022 ◽  
Vol 12 (2) ◽  
pp. 668
Piotr Szmytkiewicz ◽  
Rafał Ostrowski ◽  
Grzegorz R. Cerkowniak

The present paper addresses the litho-dynamic and morpho-dynamic processes in the coastal zone of Babie Doły (KM 93.6–93.9), Poland. As a background, the history of coastal engineering measures in this area is described. The impact of post-war structures on the seashore is analysed on the basis of historical maps, supported by results of the sediment transport modelling. Shore regression is caused by the so-called downstream erosion behind the headland with remains of rock palisade structures. The possible consequences for the seashore resulting from the removal of the analysed revetment are discussed. The paper also presents recommendations to the relevant authorities for the future.

Energies ◽  
2022 ◽  
Vol 15 (2) ◽  
pp. 445
Jeanie A. Aird ◽  
Rebecca J. Barthelmie ◽  
Tristan J. Shepherd ◽  
Sara C. Pryor

Two years of high-resolution simulations conducted with the Weather Research and Forecasting (WRF) model are used to characterize the frequency, intensity and height of low-level jets (LLJ) over the U.S. Atlantic coastal zone. Meteorological conditions and the occurrence and characteristics of LLJs are described for (i) the centroids of thirteen of the sixteen active offshore wind energy lease areas off the U.S. east coast and (ii) along two transects extending east from the U.S. coastline across the northern lease areas (LA). Flow close to the nominal hub-height of wind turbines is predominantly northwesterly and southwesterly and exhibits pronounced seasonality, with highest wind speeds in November, and lowest wind speeds in June. LLJs diagnosed using vertical profiles of modeled wind speeds from approximately 20 to 530 m above sea level exhibit highest frequency in LA south of Massachusetts, where LLJs are identified in up to 12% of hours in June. LLJs are considerably less frequent further south along the U.S. east coast and outside of the summer season. LLJs frequently occur at heights that intersect the wind turbine rotor plane, and at wind speeds within typical wind turbine operating ranges. LLJs are most frequent, intense and have lowest core heights under strong horizontal temperature gradients and lower planetary boundary layer heights.

Land ◽  
2022 ◽  
Vol 11 (1) ◽  
pp. 76
Imranul Islam ◽  
Shenghui Cui ◽  
Muhammad Ziaul Hoque ◽  
Hasan Muhammad Abdullah ◽  
Kaniz Fatima Tonny ◽  

Tree outside forest (TOF) has immense potential in economic and environmental development by increasing the amount of tree vegetation in and around rural settlements. It is an important source of carbon stocks and a critical option for climate change regulation, especially in land-scarce, densely populated developing countries such as Bangladesh. Spatio-temporal changes of TOF in the eastern coastal zone of Bangladesh were analyzed and mapped over 1988–2018, using Landsat land use land cover (LULC) maps and associated ecosystem carbon storage change by linking the InVEST carbon model. Landsat TM and OLI-TIRS data were classified through the Maximum Likelihood Classifier (MLC) algorithm using Semi-Automated Classification (SAC). In the InVEST model, aboveground, belowground, dead organic matter, and soil carbon densities of different LULC types were used. The findings revealed that the studied landscapes have differential features and changing trends in LULC where TOF, mangrove forest, built-up land, and salt-aquaculture land have increased due to the loss of agricultural land, mudflats, water bodies, and hill vegetation. Among different land biomes, TOF experienced the largest increase (1453.9 km2), and it also increased carbon storage by 9.01 Tg C. However, agricultural land and hill vegetation decreased rapidly by 1285.8 km2 and 365.7 km2 and reduced carbon storage by 3.09 Tg C and 4.89 Tg C, respectively. The total regional carbon storage increased by 1.27 Tg C during 1988–2018. In addition to anthropogenic drivers, land erosion and accretion were observed to significantly alter LULC and regional carbon storage, necessitating effective river channel and coastal embankment management to minimize food and environmental security tradeoff in the studied landscape.

2022 ◽  
Vol 42 (1) ◽  
石佳佳,李伟峰,刘亚丽,周伟奇,韩立建,田淑芳 SHI Jiajia

2021 ◽  
Vol 14 (1) ◽  
pp. 153
Marco Ottinger ◽  
Felix Bachofer ◽  
Juliane Huth ◽  
Claudia Kuenzer

Asia dominates the world’s aquaculture sector, generating almost 90 percent of its total annual global production. Fish, shrimp, and mollusks are mainly farmed in land-based pond aquaculture systems and serve as a primary protein source for millions of people. The total production and area occupied for pond aquaculture has expanded rapidly in coastal regions in Asia since the early 1990s. The growth of aquaculture was mainly boosted by an increasing demand for fish and seafood from a growing world population. The aquaculture sector generates income and employment, contributes to food security, and has become a billion-dollar industry with high socio-economic value, but has also led to severe environmental degradation. In this regard, geospatial information on aquaculture can support the management of this growing food sector for the sustainable development of coastal ecosystems, resources, and human health. With free and open access to the rapidly growing volume of data from the Copernicus Sentinel missions as well as machine learning algorithms and cloud computing services, we extracted coastal aquaculture at a continental scale. We present a multi-sensor approach that utilizes Earth observation time series data for the mapping of pond aquaculture within the entire Asian coastal zone, defined as the onshore area up to 200 km from the coastline. In this research, we developed an object-based framework to detect and extract aquaculture at a single-pond level based on temporal features derived from high-spatial-resolution SAR and optical satellite data acquired from the Sentinel-1 and Sentinel-2 satellites. In a second step, we performed spatial and statistical data analyses of the Earth-observation-derived aquaculture dataset to investigate spatial distribution and identify production hotspots at various administrative units at regional, national, and sub-national scale.

2022 ◽  
Vol 174 ◽  
pp. 113262
Manoranjan Mishra ◽  
Dipika Kar ◽  
Celso Augusto Guimarães Santos ◽  
Richarde Marques da Silva ◽  
Prabhu Prasad Das

2021 ◽  
Vol 14 (4) ◽  
pp. 41-54 ◽  
Оleg D. Tregubov ◽  
Vladimir E. Glotov ◽  
Pavel Ya. Konstantinov ◽  
Vladimir V. Shamov

The lakes of the Arctic lowlands are both the unique indicator and the result of climatic and permafrost changes. Remote sensing methods and field measurements were used to consider the patterns and features of the morphometric indicators dynamics of the Anadyr lowland lakes over 65 years. We analyzed the parameters of 36 lakes with an area of 0.02–0.3 km2 located in the bottoms of drained lake basins, in river floodplains, on sea-shore terraces. Field studies were conducted on 22 typical lakes. The considered dynamics of seasonal thawing are based on the monitoring of the active layer for 1994–2020. Due to an increase of mean annual air temperature by 1.8 °C, as well as an increase and then a decrease in the mean annual precipitation by 135 mm, the average share of a lake area in the study area decreased by 24%. It is shown for the first time that cryogenic processes of the lacustrine coastal zone affect the change in the area of lakes simultaneously with the influence of precipitation and air temperature. Based on field observations, we considered two causes of natural drainage: discharge of the lakes through newly formed thermokarst and thermoerosional surface flow channels and decrease in suprapermafrost groundwater recharge as a result of changing depth of seasonally thawed active layer in the coastal zone.

2021 ◽  
Vol 14 (1) ◽  
pp. 88
Xin Zhao ◽  
Rongjie Liu ◽  
Yi Ma ◽  
Yanfang Xiao ◽  
Jing Ding ◽  

Existing red tide detection methods have mainly been developed for ocean color satellite data with low spatial resolution and high spectral resolution. Higher spatial resolution satellite images are required for red tides with fine scale and scattered distribution. However, red tide detection methods for ocean color satellite data cannot be directly applied to medium–high spatial resolution satellite data owing to the shortage of red tide responsive bands. Therefore, a new red tide detection method for medium–high spatial resolution satellite data is required. This study proposes the red tide detection U−Net (RDU−Net) model by considering the HY−1D Coastal Zone Imager (HY−1D CZI) as an example. RDU−Net employs the channel attention model to derive the inter−channel relationship of red tide information in order to reduce the influence of the marine environment on red tide detection. Moreover, the boundary and binary cross entropy (BBCE) loss function, which incorporates the boundary loss, is used to obtain clear and accurate red tide boundaries. In addition, a multi−feature dataset including the HY−1D CZI radiance and Normalized Difference Vegetation Index (NDVI) is employed to enhance the spectral difference between red tides and seawater and thus improve the accuracy of red tide detection. Experimental results show that RDU−Net can detect red tides accurately without a precedent threshold. Precision and Recall of 87.47% and 86.62%, respectively, are achieved, while the F1−score and Kappa are 0.87. Compared with the existing method, the F1−score is improved by 0.07–0.21. Furthermore, the proposed method can detect red tides accurately even under interference from clouds and fog, and it shows good performance in the case of red tide edges and scattered distribution areas. Moreover, it shows good applicability and can be successfully applied to other satellite data with high spatial resolution and large bandwidth, such as GF−1 Wide Field of View 2 (WFV2) images.

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