Development of Japanese inland water surface temperature database using ASTER thermal infrared imagery

2011 ◽  
Author(s):  
Hideyuki Tonooka ◽  
Masayuki Hirayama
Keyword(s):  
Surface Temperature ◽  
Water Surface ◽  
Thermal Infrared ◽  
Infrared Imagery ◽  
Inland Water ◽  
Water Surface Temperature ◽  
Thermal Infrared Imagery

scholarly journals Relationship between the distribution of aquatic plants and the water surface temperature using UAV with thermal infrared sensor.

2020 ◽  
Vol 22 (2) ◽  
pp. 155-163
Author(s):  
Hideyuki NIWA ◽  
Kosuke IMAI ◽  
Syunsuke SUZUKI ◽  
Ryou SHIMIZU ◽  
Shigeharu KOGUSHI
Keyword(s):  
Surface Temperature ◽  
Aquatic Plants ◽  
Water Surface ◽  
Thermal Infrared ◽  
Infrared Sensor ◽  
Water Surface Temperature

Surface Temperature Monitoring by Satellite Thermal Infrared Imagery at Mayon Volcano of Philippines, 1988-2019

2020 ◽  
Author(s):  
Hai-Po Chan ◽  
Kostas Konstantinou
Keyword(s):  
Remote Sensing ◽  
Time Series ◽  
Surface Temperature ◽  
Spatial Resolution ◽  
Satellite Remote Sensing ◽  
Thermal Infrared ◽  
Active Volcano ◽  
Infrared Imagery ◽  
Mayon Volcano ◽  
Thermal Infrared Imagery

<p>Mayon Volcano on eastern Luzon Island is the most active volcano in the Philippines. It is named and renowned as the "perfect cone" for the symmetric conical shape and has recorded eruptions over 50 times in the past 500 years. Geographically the volcano is surrounded by the eight cities and municipalities with 1 million inhabitants. Currently, its activity is daily monitored by on-site observations such as seismometers installed on Mayon's slopes, plus, electronic distance meters (EDMs), precise leveling benchmarks, and portable fly spectrometers. Compared to existing direct on-site measurements, satellite remote sensing is currently assuming an essential role in understanding the whole picture of volcanic processes. The vulnerability to volcanic hazards is high for Mayon given that it is located in an area of high population density on Luzon Island. However, the satellite remote sensing method and dataset have not been integrated into Mayon’s hazard mapping and monitoring system, despite abundant open-access satellite dataset archives. Here, we perform multiscale and multitemporal monitoring based on the analysis of a nineteen-year Land Surface Temperature (LST) time series derived from satellite-retrieved thermal infrared imagery. Both Landsat thermal imagery (with 30-meter spatial resolution) and MODIS (Moderate Resolution Imaging Spectroradiometer) LST products (with 1-kilometer spatial resolution) are used for the analysis. The Ensemble Empirical Mode Decomposition (EEMD) is applied as the decomposition tool to decompose oscillatory components of various timescales within the LST time series. The physical interpretation of decomposed LST components at various periods are explored and compared with Mayon’s eruption records. Results show that annual-period components of LST tend to lose their regularity following an eruption, and amplitudes of short-period LST components are very responsive to the eruption events. The satellite remote sensing approach provides more insights at larger spatial and temporal scales on this renowned active volcano. This study not only presents the advantages and effectiveness of satellite remote sensing on volcanic monitoring but also provides valuable surface information for exploring the subsurface volcanic structures in Mayon.</p>

Long-term changes in inland water surface temperature across China based on remote sensing data

2020 ◽  
Author(s):  
Rui Wang ◽  
Xin Yan ◽  
Zhenguo Niu ◽  
Wei Chen
Keyword(s):  
Climate Change ◽  
Surface Water ◽  
Surface Temperature ◽  
Water Surface ◽  
Annual Variation ◽  
Average Rate ◽  
Transform Method ◽  
Inland Water ◽  
The Past ◽  
Water Surface Temperature

AbstractWater surface temperature is a direct indication of climate change. However, it is not clear how have China’s inland waters responded to climate change in the past using a consistent method on a national scale. In this study, we used Moderate Resolution Imaging Spectroradiometer (MODIS) data from 2000 to 2015 to study the temporal and spatial variation characteristics of water surface temperature in China using the wavelet transform method. The results showed the following: (1) the freezing date of China inland water has shown a significant delaying trend during the past 16 years with an average rate of -1.5 d/a; (2) the shift of 0°C isotherm position of surface water across China has clear seasonal changes, which first moved eastward about 25° and northward about 15°, and then gradually moved back after the year 2009; (3) during the past 16 years, 0°C isotherm of China’s surface water has gradually moved north by about 0.09° in the latitude direction and east by about 1° in the longitude direction; (4) the inter-annual variation of water surface temperature in 17 lakes of China showed a similar fluctuation trend that increased before 2010, and then decreased. The El Niño and La Niña around 2010 could have impacts on the turning point of the annual variation of water surface temperature. This study validated the response of China’s inland surface water to global climate change and improved the understanding of the wetland environment’s response to climate change.

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