Investigating Long-Term Subsidence at Medicine Lake Volcano, CA, Using Multi Temporal InSAR

2016 ◽  
pp. 25-58
Author(s):  
Amy Laura Parker
Keyword(s):  
Multi Temporal ◽  
Medicine Lake ◽  
Medicine Lake Volcano

scholarly journals Investigating long-term subsidence at Medicine Lake Volcano, CA, using multitemporal InSAR

2014 ◽  
Vol 199 (2) ◽  
pp. 844-859 ◽  
Author(s):  
Amy L. Parker ◽  
Juliet Biggs ◽  
Zhong Lu
Keyword(s):  
Medicine Lake ◽  
Medicine Lake Volcano

Constraints on the mechanism of long-term, steady subsidence at Medicine Lake volcano, northern California, from GPS, leveling, and InSAR

2006 ◽  
Vol 150 (1-3) ◽  
pp. 55-78 ◽  
Author(s):  
Michael Poland ◽  
Roland Bürgmann ◽  
Daniel Dzurisin ◽  
Michael Lisowski ◽  
Timothy Masterlark ◽  
...  
Keyword(s):  
Northern California ◽  
Gps Leveling ◽  
Medicine Lake ◽  
Medicine Lake Volcano

scholarly journals High Mountain Asian glacier response to climate revealed by multi-temporal satellite observations since the 1960s

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Atanu Bhattacharya ◽  
Tobias Bolch ◽  
Kriti Mukherjee ◽  
Owen King ◽  
Brian Menounos ◽  
...  
Keyword(s):  
Mass Loss ◽  
River Flow ◽  
Tien Shan ◽  
High Mountain ◽  
Glacier Mass Balance ◽  
Temperature And Precipitation ◽  
Multi Temporal ◽  
The 1960S ◽  
Northern Tien Shan

AbstractKnowledge about the long-term response of High Mountain Asian glaciers to climatic variations is paramount because of their important role in sustaining Asian river flow. Here, a satellite-based time series of glacier mass balance for seven climatically different regions across High Mountain Asia since the 1960s shows that glacier mass loss rates have persistently increased at most sites. Regional glacier mass budgets ranged from −0.40 ± 0.07 m w.e.a−1 in Central and Northern Tien Shan to −0.06 ± 0.07 m w.e.a−1 in Eastern Pamir, with considerable temporal and spatial variability. Highest rates of mass loss occurred in Central Himalaya and Northern Tien Shan after 2015 and even in regions where glaciers were previously in balance with climate, such as Eastern Pamir, mass losses prevailed in recent years. An increase in summer temperature explains the long-term trend in mass loss and now appears to drive mass loss even in regions formerly sensitive to both temperature and precipitation.

scholarly journals Cropland Abandonment in Slovakia: Analysis and Comparison of Different Data Sources

Land ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 334
Author(s):  
Juraj Lieskovský ◽  
Dana Lieskovská
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Spatial Data ◽  
Data Sources ◽  
Communist Regime ◽  
Corine Land Cover ◽  
Cropland Area ◽  
Cropland Abandonment ◽  
Multi Temporal

This study compares different nationwide multi-temporal spatial data sources and analyzes the cropland area, cropland abandonment rates and transformation of cropland to other land cover/land use categories in Slovakia. Four multi-temporal land cover/land use data sources were used: The Historic Land Dynamics Assessment (HILDA), the Carpathian Historical Land Use Dataset (CHLUD), CORINE Land Cover (CLC) data and Landsat images classification. We hypothesized that because of the different spatial, temporal and thematic resolution of the datasets, there would be differences in the resulting cropland abandonment rates. We validated the datasets, compared the differences, interpreted the results and combined the information from the different datasets to form an overall picture of long-term cropland abandonment in Slovakia. The cropland area increased until the Second World War, but then decreased after transition to the communist regime and sharply declined following the 1989 transition to an open market economy. A total of 49% of cropland area has been transformed to grassland, 34% to forest and 15% to urban areas. The Historical Carpathian dataset is the more reliable long-term dataset, and it records 19.65 km2/year average cropland abandonment for 1836–1937, 154.44 km2/year for 1938–1955 and 140.21 km2/year for 1956–2012. In comparison, the Landsat, as a recent data source, records 142.02 km2/year abandonment for 1985–2000 and 89.42 km2/year for 2000–2010. These rates, however, would be higher if the dataset contained urbanisation data and more precise information on afforestation. The CORINE Land Cover reflects changes larger than 5 ha, and therefore the reported cropland abandonment rates are lower.

Insight on the results of three different correlation analyses between satellite TIR anomalies and earthquake occurrence

2021 ◽  
Author(s):  
Carolina Filizzola ◽  
Roberto Colonna ◽  
Alexander Eleftheriou ◽  
Nicola Genzano ◽  
Katsumi Hattori ◽  
...  
Keyword(s):  
Seismic Hazard ◽  
International Workshop ◽  
Statistical Correlation ◽  
Physical Models ◽  
Short Term ◽  
Correlation Analyses ◽  
Multi Temporal ◽  
Casual Relation ◽  
Large Earthquakes

<p>In order to evaluate the potentiality of the parameter “RST-based satellite TIR anomalies” in relation with earthquake (M≥4) occurrence, in recent years we performed three long-term statistical correlation analyses on different seismically active areas, such as Greece (Eleftheriou et al., 2016), Italy (Genzano et al., 2020), and Japan (Genzano et al., 2021).</p><p>With this aim, by means of the RST (Robust Satellite Techniques; Tramutoli, 1998, 2007) approach we analysed ten-year time series of satellite images collected by the SEVIRI sensor (on board the MSG platforms) over Greece (2004-2013) and Italy (2004-2014), and by the JAMI and IMAGER sensors (on board the MTSAT satellites) over Japan (2005-2015).  By applying empirical spatial-temporal rules, which are established also taking account of the physical models up to now proposed to explain seismic TIR anomaly appearances, the performed long -term correlation analyses put in relief that a non-casual relation exists between satellite TIR anomalies and the occurrence of earthquakes.</p><p>At the same time, in the carried out studies we introduced and validated refinements and improvements to the RST approach, which are able to minimize the proliferation of the false positives (i.e. TIR anomalies independent from the seismic sources, but due to other causes such as meteorological factors).    </p><p>Here, we summarize the achieved results and discuss them from the perspective of a multi-parameter system, which could improve our present knowledge on the earthquake-related processes and increase our capacity to assess the seismic hazard in the medium-short term (months to days).</p><p> </p><p>References</p><p>Eleftheriou, A., C. Filizzola, N. Genzano, T. Lacava, M. Lisi, R. Paciello, N. Pergola, F. Vallianatos, and V. Tramutoli (2016), Long-Term RST Analysis of Anomalous TIR Sequences in Relation with Earthquakes Occurred in Greece in the Period 2004–2013, Pure Appl. Geophys., 173(1), 285–303, doi:10.1007/s00024-015-1116-8.</p><p>Genzano, N., C. Filizzola, M. Lisi, N. Pergola, and V. Tramutoli (2020), Toward the development of a multi parametric system for a short-term assessment of the seismic hazard in Italy, Ann. Geophys, 63, 5, PA550, doi:10.4401/ag-8227.</p><p>Genzano, N., C. Filizzola, K. Hattori, N. Pergola, and V. Tramutoli (2021), Statistical correlation analysis between thermal infrared anomalies observed from MTSATs and large earthquakes occurred in Japan (2005 - 2015), Journal of Geophysics Research – Solid Earth, doi: 10.1029/2020JB020108 (accepted).</p><p>Tramutoli, V. (1998), Robust AVHRR Techniques (RAT) for Environmental Monitoring: theory and applications, in Proceedings of SPIE, vol. 3496, edited by E. Zilioli, pp. 101–113, doi: 10.1117/12.332714</p><p>Tramutoli, V. (2007), Robust Satellite Techniques (RST) for Natural and Environmental Hazards Monitoring and Mitigation: Theory and Applications, in 2007 International Workshop on the Analysis of Multi-temporal Remote Sensing Images, pp. 1–6, IEEE. doi: 10.1109/MULTITEMP.2007.4293057</p>

scholarly journals CREATING MULTI-TEMPORAL MAPS OF URBAN ENVIRONMENTS FOR IMPROVED LOCALIZATION OF AUTONOMOUS VEHICLES

2020 ◽  
Vol XLIII-B2-2020 ◽  
pp. 317-323
Author(s):  
J. Schachtschneider ◽  
C. Brenner
Keyword(s):  
Urban Areas ◽  
Autonomous Vehicles ◽  
Weather Conditions ◽  
Point Clouds ◽  
Urban Environments ◽  
Seasonal Effects ◽  
Data Set ◽  
Multi Temporal ◽  
One Year

Abstract. The development of automated and autonomous vehicles requires highly accurate long-term maps of the environment. Urban areas contain a large number of dynamic objects which change over time. Since a permanent observation of the environment is impossible and there will always be a first time visit of an unknown or changed area, a map of an urban environment needs to model such dynamics.In this work, we use LiDAR point clouds from a large long term measurement campaign to investigate temporal changes. The data set was recorded along a 20 km route in Hannover, Germany with a Mobile Mapping System over a period of one year in bi-weekly measurements. The data set covers a variety of different urban objects and areas, weather conditions and seasons. Based on this data set, we show how scene and seasonal effects influence the measurement likelihood, and that multi-temporal maps lead to the best positioning results.

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