scholarly journals The 2017 Nishinoshima eruption: combined analysis using Himawari-8 and multiple high-resolution satellite images

2019 ◽  
Vol 71 (1) ◽  
Author(s):  
Takayuki Kaneko ◽  
Fukashi Maeno ◽  
Atsushi Yasuda ◽  
Minoru Takeo ◽  
Kenji Takasaki
Keyword(s):  
Flow Direction ◽  
Temporal Variations ◽  
High Temporal Resolution ◽  
Landsat 8 ◽  
Effusion Rate ◽  
Lava Tubes ◽  
Thermal Anomalies ◽  
High Resolution Satellite Images ◽  
Lava Effusion ◽  
Lava Delta

AbstractNishinoshima volcano suddenly resumed eruptive activity in April 2017 after about 1.5 years of dormancy since its previous activity in 2013–2015. Nishinoshima is an uninhabited isolated island. We analyzed the eruption sequence and the eruptive process of the 2017 eruption (17 April–10 August: 116 days) by combining high-temporal-resolution images from Himawari-8 and high-spatial-resolution images from the ALOS-2, Landsat-8, and Pleiades satellites. We used these data to discuss how temporal variations in the lava effusion rate affected the flow formations and topographical features of the effused lava. The total effused volume was estimated to be 1.6 × 107 m3, and the average effusion rate was 1.5 × 105 m3/day (1.7 m3/s). Based on variations in the thermal anomalies in the 1.6-μm band of Himawari-8, which roughly coincided with that of the lava effusion rate estimated by ALOS-2, the activity was segmented into five stages. In Stage 1 (17–30 April: 14 days), the lava effusion rate was the highest, and lava flowed to the west and southwest. Stage 2 (1 May–5 June: 36 days) showed a uniform decrease in flow, and lava flowed to the southwest and formed the southwestern lava delta. During Stage 3 (6–15 June: 10 days), the lava effusion rate increased in a pulsed manner, the flow direction changed from southwestward to westward, and a narrow lava flow effused from the southern slope of the cone. In Stage 4 (16 June–31 July: 46 days), the lava effusion rate decreased and lava flowed westward through lava tubes, enlarging the western lava delta. Around the end of July, lava effusion mostly stopped. Finally, in Stage 5 (1–10 August: 10 days), explosive eruptions occurred sporadically. The variation in lava effusion rate seemed to play an important role in forming different flow patterns of lava on Nishinoshima. In Stages 1 and 3, lava flowed in multiple directions, while in Stages 2 and 4, it flowed in single direction, probably because the effusion rate was lower. A pulsed increase in the lava effusion rate during Stage 3 caused new breaks and disturbances of the lava passages near the vents, which resulted in changes in flow directions. Differences in the size of lava lobes between the southwestern and western deltas are also considered to result from differences in the lava effusion rate.

scholarly journals A Google Earth Engine Tool to Investigate, Map and Monitor Volcanic Thermal Anomalies at Global Scale by Means of Mid-High Spatial Resolution Satellite Data

2020 ◽  
Vol 12 (19) ◽  
pp. 3232
Author(s):  
Nicola Genzano ◽  
Nicola Pergola ◽  
Francesco Marchese
Keyword(s):  
Spatial Resolution ◽  
Satellite Data ◽  
Hot Spot ◽  
Global Scale ◽  
Google Earth ◽  
High Temporal Resolution ◽  
Landsat 8 ◽  
Thermal Anomalies ◽  
Google Earth Engine ◽  
Sentinel 2

Several satellite-based systems have been developed over the years to study and monitor thermal volcanic activity. Most of them use high temporal resolution satellite data, provided by sensors like the Moderate Resolution Imaging Spectroradiometer (MODIS) that if on the one hand guarantee a continuous monitoring of active volcanic areas on the other hand are less suited to map thermal anomalies, and to provide accurate information about their features. The Multispectral Instrument (MSI) and the Operational Land Imager (OLI), respectively, onboard the Sentinel-2 and Landsat-8 satellites, providing Short-Wave Infrared (SWIR) data at 20 m (MSI) and 30 m (OLI) spatial resolution, may make an important contribution in this area. In this work, we present the first Google Earth Engine (GEE) App to investigate, map and monitor volcanic thermal anomalies at global scale, integrating Landsat-8 OLI and Sentinel-2 MSI observations. This open tool, which implements the Normalized Hot spot Indices (NHI) algorithm, enables the analysis of more than 1400 active volcanoes, with very low processing times, thanks to the high GEE computational resources. Performance and limitations of the tool, such as its next upgrades, aiming at increasing the user-friendly experience and extending the temporal range of data analyses, are analyzed and discussed.

scholarly journals Spatiotemporal Fusion of Formosat-2 and Landsat-8 Satellite Images: A Comparison of “Super Resolution-Then-Blend” and “Blend-Then-Super Resolution” Approaches

2021 ◽  
Vol 13 (4) ◽  
pp. 606
Author(s):  
Tee-Ann Teo ◽  
Yu-Ju Fu
Keyword(s):  
Satellite Images ◽  
Traditional Approach ◽  
Spectral Band ◽  
Super Resolution ◽  
High Temporal Resolution ◽  
Landsat 8 ◽  
Fusion Model ◽  
Image Blending ◽  
Fine Resolution

The spatiotemporal fusion technique has the advantages of generating time-series images with high-spatial and high-temporal resolution from coarse-resolution to fine-resolution images. A hybrid fusion method that integrates image blending (i.e., spatial and temporal adaptive reflectance fusion model, STARFM) and super-resolution (i.e., very deep super resolution, VDSR) techniques for the spatiotemporal fusion of 8 m Formosat-2 and 30 m Landsat-8 satellite images is proposed. Two different fusion approaches, namely Blend-then-Super-Resolution and Super-Resolution (SR)-then-Blend, were developed to improve the results of spatiotemporal fusion. The SR-then-Blend approach performs SR before image blending. The SR refines the image resampling stage on generating the same pixel-size of coarse- and fine-resolution images. The Blend-then-SR approach is aimed at refining the spatial details after image blending. Several quality indices were used to analyze the quality of the different fusion approaches. Experimental results showed that the performance of the hybrid method is slightly better than the traditional approach. Images obtained using SR-then-Blend are more similar to the real observed images compared with images acquired using Blend-then-SR. The overall mean bias of SR-then-Blend was 4% lower than Blend-then-SR, and nearly 3% improvement for overall standard deviation in SR-B. The VDSR technique reduces the systematic deviation in spectral band between Formosat-2 and Landsat-8 satellite images. The integration of STARFM and the VDSR model is useful for improving the quality of spatiotemporal fusion.

Lava effusion rate evolution and erupted volume during the 2018 Kīlauea lower East Rift Zone eruption

2021 ◽  
Vol 83 (4) ◽  
Author(s):  
Hannah R. Dietterich ◽  
Angela K. Diefenbach ◽  
S. Adam Soule ◽  
Michael H. Zoeller ◽  
Matthew P. Patrick ◽  
...  
Keyword(s):  
Rift Zone ◽  
Effusion Rate ◽  
Lava Effusion

scholarly journals Simple empirical method for estimating lava-effusion rate using nighttime Himawari-8 1.6-µm infrared images

2021 ◽  
Vol 73 (1) ◽  
Author(s):  
Takayuki Kaneko ◽  
Atsushi Yasuda ◽  
Toshitsugu Fujii
Keyword(s):  
Lava Flow ◽  
Estimation Method ◽  
Simulation Software ◽  
Spectral Radiance ◽  
Effusion Rate ◽  
Actual Distribution ◽  
High Positive Correlation ◽  
Low Viscosity ◽  
Lava Effusion ◽  
The Relationship

AbstractThe effusion rate of lava is one of the most important eruption parameters, as it is closely related to the migration process of magma underground and on the surface, such as changes in lava flow direction or formation of new effusing vents. Establishment of a continuous and rapid estimation method has been an issue in volcano research as well as disaster prevention planning. For effusive eruptions of low-viscosity lava, we examined the relationship between the nighttime spectral radiance in the 1.6-µm band of the Himawari-8 satellite (R1.6Mx: the pixel value showing the maximum radiance in the heat source area) and the effusion rate using data from the 2017 Nishinoshima activity. Our analysis confirmed that there was a high positive correlation between these two parameters. Based on the linear-regression equation obtained here (Y = 0.47X, where Y is an effusion rate of 106 m3 day−1 and X is an R1.6Mx of 106 W m−2 sr−1 m−1), we can estimate the lava-effusion rate from the observation data of Himawari-8 via a simple calculation. Data from the 2015 Raung activity—an effusive eruption of low-viscosity lava—were arranged along the extension of this regression line, which suggests that the relationship is applicable up to a level of ~ 2 × 106 m3 day−1. We applied this method to the December 2019 Nishinoshima activity and obtained an effusion rate of 0.50 × 106 m3 day−1 for the initial stage. We also calculated the effusion rate for the same period based on a topographic method, and verified that the obtained value, 0.48 × 106 m3 day−1, agreed with the estimation using the Himawari-8 data. Further, for Nishinoshima, we simulated the extent of hazard areas from the initial lava flow and compared cases using the effusion rate obtained here and the value corresponding to the average effusion rate for the 2013–2015 eruptions. The former distribution was close to the actual distribution, while the latter was much smaller. By combining this effusion-rate estimation method with real-time observations by Himawari-8 and lava-flow simulation software, we can build a rapid and precise prediction system for volcano hazard areas.

scholarly journals Monitoring of the 2015 Villarrica Volcano Eruption by Means of DLR’s Experimental TET-1 Satellite

2018 ◽  
Vol 10 (9) ◽  
pp. 1379 ◽  
Author(s):  
Simon Plank ◽  
Michael Nolde ◽  
Rudolf Richter ◽  
Christian Fischer ◽  
Sandro Martinis ◽  
...  
Keyword(s):  
Infrared Imaging ◽  
Thermal Emission ◽  
Atmospheric Correction ◽  
Landsat 8 ◽  
Thermal Anomalies ◽  
Villarrica Volcano ◽  
Radiant Power ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
German Aerospace ◽  
Active Volcanoes

Villarrica Volcano is one of the most active volcanoes in the South Andes Volcanic Zone. This article presents the results of a monitoring of the time before and after the 3 March 2015 eruption by analyzing nine satellite images acquired by the Technology Experiment Carrier-1 (TET-1), a small experimental German Aerospace Center (DLR) satellite. An atmospheric correction of the TET-1 data is presented, based on the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Emissivity Database (GDEM) and Moderate Resolution Imaging Spectroradiometer (MODIS) water vapor data with the shortest temporal baseline to the TET-1 acquisitions. Next, the temperature, area coverage, and radiant power of the detected thermal hotspots were derived at subpixel level and compared with observations derived from MODIS and Visible Infrared Imaging Radiometer Suite (VIIRS) data. Thermal anomalies were detected nine days before the eruption. After the decrease of the radiant power following the 3 March 2015 eruption, a stronger increase of the radiant power was observed on 25 April 2015. In addition, we show that the eruption-related ash coverage of the glacier at Villarrica Volcano could clearly be detected in TET-1 imagery. Landsat-8 imagery was analyzed for comparison. The information extracted from the TET-1 thermal data is thought be used in future to support and complement ground-based observations of active volcanoes.

scholarly journals Spatial and Temporal Variations of Nitrogen and Phosphorus in Surface Water and Groundwater of Mudong River Watershed in Huixian Karst Wetland, Southwest China

2021 ◽  
Vol 13 (19) ◽  
pp. 10740
Author(s):  
Linyan Pan ◽  
Junfeng Dai ◽  
Zhiqiang Wu ◽  
Liangliang Huang ◽  
Zupeng Wan ◽  
...  
Keyword(s):  
Surface Water ◽  
Temporal Dynamics ◽  
Flow Direction ◽  
Influencing Factor ◽  
Shallow Groundwater ◽  
Temporal Variations ◽  
Field Investigation ◽  
Spatial And Temporal Variation ◽  
Nitrogen And Phosphorus ◽  
River Watershed

When considering the factors affecting the spatial and temporal variation of nitrogen and phosphorus in karst watersheds, the unique karst hydrogeology as an internal influencing factor cannot be ignored, as well as natural factors such as meteorological hydrology and external factors such as human activities. A watershed-scale field investigation was completed to statistically analyze spatial and temporal dynamics of nitrogen and phosphorus through the regular monitoring and collection of surface water and shallow groundwater in the agricultural-dominated Mudong River watershed in the Huixian Karst Wetland over one year (May 2020 to April 2021). Our research found that non-point source pollution of nitrogen (84.5% of 239 samples TN > 1.0 mg/L) was more serious than phosphorus (7.5% of 239 samples TP > 0.2 mg/L) in the study area, and shallow groundwater nitrogen pollution (98.3% of 118 samples TN > 1.0 mg/L) was more serious than surface water (68.6% of 121 samples TN > 1.0 mg/L). In the three regions with different hydrodynamic features, the TN concentration was higher and dominated by NO3−-N in the river in the northern recharge area, while the concentrations of TN and TP were the highest in shallow groundwater wells in the central wetland core area and increased along the surface water flow direction in the western discharge area. This research will help improve the knowledge about the influence of karst hydrodynamic features on the spatial patterns of nitrogen and phosphorus in water, paying attention to the quality protection and security of water in karst areas with a fragile water ecological environment.

scholarly journals Harmonizing Multi-Source Remote Sensing Images for Summer Corn Growth Monitoring

2019 ◽  
Vol 11 (11) ◽  
pp. 1266 ◽  
Author(s):  
Mingzheng Zhang ◽  
Dehai Zhu ◽  
Wei Su ◽  
Jianxi Huang ◽  
Xiaodong Zhang ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Time Series ◽  
Kalman Filter ◽  
Spatial Resolution ◽  
Temporal Resolution ◽  
Meteorological Data ◽  
High Temporal Resolution ◽  
Growth Monitoring ◽  
Landsat 8 ◽  
Data Set

Continuous monitoring of crop growth status using time-series remote sensing image is essential for crop management and yield prediction. The growing season of summer corn in the North China Plain with the period of rain and hot, which makes the acquisition of cloud-free satellite imagery very difficult. Therefore, we focused on developing image datasets with both a high temporal resolution and medium spatial resolution by harmonizing the time-series of MOD09GA Normalized Difference Vegetation Index (NDVI) images and 30-m-resolution GF-1 WFV images using the improved Kalman filter model. The harmonized images, GF-1 images, and Landsat 8 images were then combined and used to monitor the summer corn growth from 5th June to 6th October, 2014, in three counties of Hebei Province, China, in conjunction with meteorological data and MODIS Evapotranspiration Data Set. The prediction residuals ( Δ P R K ) in NDVI between the GF-1 observations and the harmonized images was in the range of −0.2 to 0.2 with Gauss distribution. Moreover, the obtained phenological curves manifested distinctive growth features for summer corn at field scales. Changes in NDVI over time were more effectively evaluated and represented corn growth trends, when considered in conjunction with meteorological data and MODIS Evapotranspiration Data Set. We observed that the NDVI of summer corn showed a process of first decreasing and then rising in the early growing stage and discuss how the temperature and moisture of the environment changed with the growth stage. The study demonstrated that the synthesized dataset constructed using this methodology was highly accurate, with high temporal resolution and medium spatial resolution and it was possible to harmonize multi-source remote sensing imagery by the improved Kalman filter for long-term field monitoring.

Downscaling sub-daily Land Surface Temperature time series for monitoring heat in urban environments

2020 ◽  
Author(s):  
Nikos Alexandris ◽  
Matteo Piccardo ◽  
Vasileios Syrris ◽  
Alessandro Cescatti ◽  
Gregory Duveiller
Keyword(s):  
Time Series ◽  
Heat Stress ◽  
Surface Temperature ◽  
Spatial Resolution ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Urban Environments ◽  
High Temporal Resolution ◽  
Landsat 8 ◽  
Fine Spatial Resolution

<p>The frequency of extreme heat related events is rising. This places the ever growing number of urban dwellers at higher risk. Quantifying these phenomena is important for the development and monitoring of climate change adaptation and mitigation policies. In this context, earth observations offer increasing opportunities to assess these phenomena with an unprecedented level of accuracy and spatial reach. Satellite thermal imaging systems acquire Land Surface Temperature (LST) which is fundamental to run models that study for example hotspots and heatwaves in urban environments.</p><p>Current instruments include TIRS on board Landsat 8 and MODIS on board of Terra satellites. These provide LST products on a monthly basis at 100m and twice per day at 1km respectively. Other sensors on board geostationary satellites, such as MSG and GOES-R, produce sub-hourly thermal images. For example the SEVIRI instrument onboard MSG, captures images every 15 minutes. However, this is done at an even coarser spatial resolution, which is 3 to 5 km in the case of SEVIRI. Nevertheless, none of the existing systems can capture LST synchronously with fine spatial resolution at a high temporal frequency, which is a prerequisite for monitoring heat stress in urban environments.</p><p>Combining LST time series of high temporal resolution (i.e. sub-daily MODIS- or SEVIRI-derived data) with products of fine spatial resolution (i.e. Landsat 8 products), and potentially other related variables (i.e. reflectance, spectral indices, land cover information, terrain parameters and local climatic variables), facilitates the downscaling of LST estimations. Nonetheless, considering the complexity of how distinct surfaces within a city heat-up differently during the course of a day, such a downscaling is meaningful for practically synchronous observations (e.g. Landsat-8 and MODIS Terra’s morning observations).</p><p>The recently launched ECOSTRESS mission provides multiple times in a day high spatial resolution thermal imagery at 70m. Albeit, recording the same locations on Earth every few days at varying times. We explore the associations between ECOSTRESS and Landsat-8 thermal data, based on the incoming radiation load and distinct surface properties characterised from other datasets. In our approach, first we upscale ECOSTRESS data to simulate Landsat-8 images at moments that coincide the acquisition times of other sensors products. In a second step, using the simulated Landsat-8 images, we downscale LST products acquired at later times, such as MODIS Aqua (ca. 13:30) or even the hourly MSG data. This composite downscaling procedure enables an enhanced LST estimation that opens the way for better diagnostics of the heat stress in urban landscapes.</p><p>In this study we discuss in detail the concepts of our approach and present preliminary results produced with the JEODPP, JRC's high throughput computing platform.</p>

scholarly journals Combining high-resolution satellite images and altimetry to estimate the volume of small lakes

2014 ◽  
Vol 18 (5) ◽  
pp. 2007-2020 ◽  
Author(s):  
F. Baup ◽  
F. Frappart ◽  
J. Maubant
Keyword(s):  
High Resolution ◽  
Satellite Data ◽  
Satellite Images ◽  
Temporal Variations ◽  
Water Levels ◽  
Water Volume ◽  
Small Scale ◽  
Altimetry Data ◽  
Small Lakes ◽  
High Resolution Satellite Images

Abstract. This study presents an approach to determining the volume of water in small lakes (<100 ha) by combining satellite altimetry data and high-resolution (HR) images. In spite of the strong interest in monitoring surface water resources on a small scale using radar altimetry and satellite imagery, no information is available about the limits of the remote-sensing technologies for small lakes mainly used for irrigation purposes. The lake being studied is located in the south-west of France and is only used for agricultural irrigation purposes. The altimetry satellite data are provided by an RA-2 sensor onboard Envisat, and the high-resolution images (<10 m) are obtained from optical (Formosat-2) and synthetic aperture radar (SAR) antenna (Terrasar-X and Radarsat-2) satellites. The altimetry data (data are obtained every 35 days) and the HR images (77) have been available since 2003 and 2010, respectively. In situ data (for the water levels and volumes) going back to 2003 have been provided by the manager of the lake. Three independent approaches are developed to estimate the lake volume and its temporal variability. The first two approaches (HRBV and ABV) are empirical and use synchronous ground measurements of the water volume and the satellite data. The results demonstrate that altimetry and imagery can be effectively and accurately used to monitor the temporal variations of the lake (R2ABV = 0.98, RMSEABV = 5%, R2HRBV = 0.90, and RMSEABV = 7.4%), assuming a time-varying triangular shape for the shore slope of the lake (this form is well adapted since it implies a difference inferior to 2% between the theoretical volume of the lake and the one estimated from bathymetry). The third method (AHRBVC) combines altimetry (to measure the lake level) and satellite images (of the lake surface) to estimate the volume changes of the lake and produces the best results (R2AHRBVC = 0.98) of the three methods, demonstrating the potential of future Sentinel and SWOT missions to monitor small lakes and reservoirs for agricultural and irrigation applications.

scholarly journals Spatial and temporal variations of the surface albedo and other factors influencing Urumqi Glacier No. 1 in Tien Shan, China

2017 ◽  
Vol 63 (241) ◽  
pp. 899-911 ◽  
Author(s):  
XIAOYING YUE ◽  
JUN ZHAO ◽  
ZHONGQIN LI ◽  
MINGJUN ZHANG ◽  
JIN FAN ◽  
...  
Keyword(s):  
Surface Albedo ◽  
Temporal Variations ◽  
Surface Energy Budget ◽  
Tien Shan ◽  
Spatial And Temporal Variations ◽  
Spatial And Temporal Variability ◽  
Landsat 8 ◽  
Topographic Effects ◽  
Landsat Images ◽  
Factors Influencing

ABSTRACTGlacier albedo controls the surface energy budget, the variability of which affects the glacier surface melt rate and, in turn, impacts the mass balance of the glacier. During 2013 and 2014, spatial and temporal variations of albedo were investigated using 18 Landsat images of Urumqi Glacier No. 1. Factors influencing these spatiotemporal profiles were analyzed. An established retrieval process, including geolocation, radiometric calibration, atmospheric, topographic, and anisotropic correction and narrow- to broadband conversion, was applied for the first time to Landsat-8 images. Differences between Landsat image derived albedo values and albedo values measured using a handheld spectroradiometer ranged from −0.024 to 0.049. Spatial and temporal variations of surface albedo were significant, especially in the ablation area. The variability of the values of ice albedo ranged from 0.06 to 0.44 due to topographic effects and light-absorbing impurities. The results suggest that this retrieval method can be used to investigate the spatial and temporal variability of surface albedo from Landsat-8 images on mountain glaciers. Moreover, as constant albedo values for ice and snow cannot be assumed, the distribution of albedo was not completely dependent on altitude under conditions of more intense ablation, and by reason of light-absorbing impurities during the melt season.

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