scholarly journals Evaluation of the morpho - sedimentologic character of the Nanaimo River Delta tidal flats using selected remote sensing and photogrammetric techniques: preliminary report

1979 ◽  
Author(s):  
J Leroux ◽  
J L Luternauer
Keyword(s):  
Remote Sensing ◽  
Preliminary Report ◽  
Tidal Flats ◽  
River Delta

In- Situ Optical measurements of sediment type and phytobenthos of tidal flats: A basis for imaging remote sensing spectroscopy

1997 ◽  
Vol 49 (2-3) ◽  
pp. 367-373 ◽  
Author(s):  
Hans Hakvoort ◽  
Kerstin Heymann ◽  
Christian Stein ◽  
Desmond Murphy
Keyword(s):  
Remote Sensing ◽  
Tidal Flats ◽  
Optical Measurements ◽  
Sediment Type

Spatio–Temporal Dynamics of Wetland Landscape Patterns Based on Remote Sensing in Yellow River Delta, China

Wetlands ◽  
2014 ◽  
Vol 34 (4) ◽  
pp. 787-801 ◽  
Author(s):  
Guilin Liu ◽  
Luocheng Zhang ◽  
Qian Zhang ◽  
Zipporah Musyimi ◽  
Qinghu Jiang
Keyword(s):  
Remote Sensing ◽  
Temporal Dynamics ◽  
Yellow River ◽  
Yellow River Delta ◽  
River Delta ◽  
Landscape Patterns ◽  
Wetland Landscape ◽  
Spatio Temporal

scholarly journals Variable Urbanization Warming Effects across Metropolitans of China and Relevant Driving Factors

2020 ◽  
Vol 12 (9) ◽  
pp. 1500 ◽  
Author(s):  
Qiang Zhang ◽  
Zixuan Wu ◽  
Huiqian Yu ◽  
Xiudi Zhu ◽  
Zexi Shen
Keyword(s):  
Remote Sensing ◽  
Spatial Scales ◽  
River Delta ◽  
Driving Factors ◽  
Landsat 8 ◽  
Temporal Scales ◽  
Linear Relations ◽  
Urban Agglomerations ◽  
Spatial And Temporal Scales ◽  
Urbanized Region

Urbanization is mainly characterized by the expansion of impervious surface (IS) and hence modifies hydrothermal properties of the urbanized areas. This process results in rising land surface temperature (LST) of the urbanized regions, i.e., urban heat island (UHI). Previous studies mainly focused on relations between LST and IS over individual city. However, because of the spatial heterogeneity of UHI from individual cities to urban agglomerations and the influence of relevant differences in climate background across urban agglomerations, the spatial-temporal scale independence of the IS-LST relationship still needs further investigation. In this case, based on Landsat-8 Operational Land Imager and Thermal Infrared Sensor (Landsat 8 OLI/TIRS) remote sensing image and multi-source remote sensing data, we extracted IS using VrNIR-BI (Visible red and NIR-based built-up Index) and calculated IS density across three major urban agglomerations across eastern China, i.e., the Beijing-Tianjin-Hebei (BTH), the Yangtze River Delta (YRD), and the Pearl River Delta (PRD) to investigate the IS-LST relations on different spatial and temporal scales and clarify the driving factors of LST. We find varying warming effects of IS on LST in diurnal and seasonal sense at different time scales. Specifically, the IS has stronger impacts on increase of LST during daytime than during nighttime and stronger impacts on increase of LST during summer than during winter. On different spatial scales, more significant enhancing effects of IS on LST can be observed across individual city than urban agglomerations. The Pearson correlation coefficient (r) between IS and LST at the individual urbanized region can be as high as 0.94, indicating that IS can well reflect LST changes within individual urbanized region. However, relationships between IS and LST indicate nonlinear effects of IS on LST. Because of differences in spatial scales, latitudes, and local climates, we depicted piecewise linear relations between IS and LST across BTH when the IS density was above 10% to 17%. Meanwhile, linear relations still stand between IS density and LST across YRD and PRD. Besides, the differences in the IS-LST relations across urban agglomeration indicate more significant enhancing effects of IS on LST across PRD than YRD and BTH. These findings help to enhance human understanding of the warming effects of urbanization or UHI at different spatial and temporal scales and is of scientific and practical merits for scientific urban planning.

scholarly journals Estimation of Cargo Handling Capacity of Coastal Ports in China Based on Panel Model and DMSP-OLS Nighttime Light Data

2019 ◽  
Vol 11 (5) ◽  
pp. 582 ◽  
Author(s):  
Aoshuang Liu ◽  
Ye Wei ◽  
Bailang Yu ◽  
Wei Song
Keyword(s):  
Remote Sensing ◽  
Statistical Data ◽  
Estimation Method ◽  
River Delta ◽  
Important Indicator ◽  
Strong Basis ◽  
Cargo Handling ◽  
Panel Model ◽  
Nighttime Light Data ◽  
Nighttime Light

The cargo handling capacity of a port is the most basic and important indicator of port size. Based on the Defense Meteorological Satellite Program-Operational Linescan System (DMSP-OLS) nighttime light data and panel model, this study attempts to estimate the cargo handling capacity of 28 coastal ports in China using satellite remote sensing. The study confirmed that there is a very close correlation between DMSP-OLS nighttime light data and the cargo handling capacity of the ports. Based on this correlation, the panel data model was established for remote sensing-based estimation of cargo handling capacity at the port and port group scales. The test results confirm that the nighttime light data can be used to accurately estimate the cargo handling capacity of Chinese ports, especially for the Yangtze River Delta Port Group, Pearl River Delta Port Group, Southeast Coastal Port Group, and Southwest Coastal Port Group that possess huge cargo handling capacities. The high accuracy of the model reveals that the remote sensing analysis method can make up for the lack of statistical data to a certain extent, which helps to scientifically analyze the spatiotemporal dynamic changes of coastal ports, provides a strong basis for decision-making regarding port development, and more importantly provides a convenient estimation method for areas that have long lacked statistical data on cargo handling capacity.

Analysis of Jiangsu tidal flats reclamation from 1974 to 2012 using remote sensing

2015 ◽  
Vol 29 (1) ◽  
pp. 143-154 ◽  
Author(s):  
Sai-shuai Zhao ◽  
Yong-xue Liu ◽  
Man-chun Li ◽  
Chao Sun ◽  
Min-xi Zhou ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Tidal Flats
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