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

Author(s):  
Hai-Po Chan ◽  
Kostas Konstantinou

<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>

1980 ◽  
Vol 60 (4) ◽  
pp. 1077-1085
Author(s):  
ROGER PAQUIN ◽  
GILLES LADOUCEUR

Crops from 888 fields in a 300-km2 area between Rougemont and St-Hyacinthe were surveyed to compare the efficiency of radar (3–80 cm) and thermal infrared (8–14 μm) imagery with color infrared photography for crop identification. The color infrared photography and the thermal infrared imagery were taken by the Canadian Centre for Remote Sensing on 11 Aug. 1978, and the radar imagery by Intera on 19 Aug. The analysis of the thermal infrared imagery showed some correlations with the ground truth data, but the image could not be used in crop identification. Accordingly, observations from radar imagery could not serve in crop identification. However, similarities were observed between the radar and the thermal infrared imageries. The results showed once more that the color infrared photography as a remote sensing technique is the most useful to survey field crops.


2020 ◽  
Vol 12 (9) ◽  
pp. 1399 ◽  
Author(s):  
Guangbin Lei ◽  
Ainong Li ◽  
Zhengjian Zhang ◽  
Jinhu Bian ◽  
Guyue Hu ◽  
...  

Grazing intensity (GI) is an important indicator for grazing situations in pastoral areas. However, it has been difficult to be observed directly in the field, due to the randomness and dynamics of the grazing behavior of livestock. Consequently, the lack of actual GI information has become a common issue in studies on quantitatively estimating GI. In this paper, a novel quantitative estimation method is proposed based on the Space-Air-Ground integrated monitoring technology. It systematically integrates GPS tracking technology, Unmanned Aerial Vehicle (UAV) observation technology, and satellite remote sensing technology. Taking Xiangdong Village on the Zoige Plateau as a study area, the trajectory data and UAV images were acquired by the GPS tracking experiments and UAV observation experiments, respectively. The GI at paddock scale (PGI) was then generated with the Kernel Density Estimation (KDE) algorithm and the above data. Taking the generated PGI as training data, an estimation model of GI at region scale (RGI) was constructed by using the time-series satellite remote sensing images and random forest regression algorithm. Finally, the time-series RGI data with a spatial resolution of 10 m in Xiangdong Village were produced by the above model. The accuracy assessment demonstrated that the generated time-series RGI data could reflect the spatial-temporal heterogeneity of actual GI, with a mean absolute error of 0.9301 and r2 of 0. 8573. The proposed method provides a new idea for generating the actual GI on the ground and the time-series RGI data. This study also highlights the feasibility and potential of using the Space-Air-Ground integrated monitoring technology to generate time-series RGI data with high spatial resolution. The generated time-series RGI data would provide data support for the formulation of policies and plans related to the sustainable development of animal husbandry.


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