scholarly journals Detection of terrain changes in southern Denmark using persistent scatterer interferometry

1969 ◽  
Vol 23 ◽  
pp. 41-44
Author(s):  
Stig A. Schack Pedersen ◽  
Geraint Cooksley ◽  
Marc Gaset ◽  
Peter Roll Jakobsen
Keyword(s):  
Environmental Monitoring ◽  
Persistent Scatterer Interferometry ◽  
The Past ◽  
The Earth ◽  
Satellite Repeats ◽  
Persistent Scatterer

Since 1991, a number of European satellites have acquired data of the Earth’s surface for environmental monitoring. In general, a satellite will orbit the Earth in about 1½ hours and it takes 35 days before an ERS or ENVISAT satellite repeats radar scanning of the same position. For younger generations of satellites, such as RADARSAT and TERRA, the scanning repeat interval has decreased to 24 and 11 days, respectively, so that hundreds of radar scenes of the same place, produced over the past c. 20 years, are now available.

scholarly journals EXTRACTING AND EVALUATING CLUSTERS IN DINSAR DEFORMATION DATA ON SINGLE BUILDINGS

2020 ◽  
Vol V-3-2020 ◽  
pp. 157-163
Author(s):  
P. J. Schneider ◽  
R. Khamis ◽  
U. Soergel
Keyword(s):  
Ground Truth ◽  
Deformation Space ◽  
Powerful Method ◽  
Persistent Scatterer Interferometry ◽  
Ground Truth Data ◽  
Precise Levelling ◽  
The Past ◽  
Persistent Scatterer ◽  
Displacement Patterns ◽  
Insight Into

Abstract. In the past two decades persistent scatterer interferometry (PSI) has become a well understood and powerful method to monitor the deformations of man-made structures. PSI can derive displacement histories of thousands of scattered points on a single building with accuracy of a few millimetre per year, by analysing space-borne SAR data. In this paper, we present a method to cluster PS points on a single building into segments which show the same deformation behavior. The spatial distribution of those clusters gives an insight into the structural behavior of a building. We use dimensionality reduction to visualize the clusters in the deformation space. The comparison of our extracted displacement patterns with ground truth data from precise levelling and 3D tachymetry confirms the plausibility of our remote sensing method.

Land Subsidence In Jharia Coalfields, Jharkhand, India – Detection, Estimation And Analysis Using Persistent Scatterer Interferometry

2020 ◽  
Author(s):  
Vamshi Krishna Rao Karanam ◽  
Mahdi Motagh ◽  
Kamal Jain
Keyword(s):  
Land Subsidence ◽  
Agricultural Land ◽  
Coal Mines ◽  
Abandoned Mines ◽  
Persistent Scatterer Interferometry ◽  
Mining Areas ◽  
The Past ◽  
Persistent Scatterers ◽  
Persistent Scatterer ◽  
Coal Fires

<p>Subsidence due to coal mining is an increasingly prominent concern in the management of the coalfields. Jharia coalfields, Jharkhand are the oldest and one of the largest coalfields in India. Due to poor management of the coal mines in the past, land subsidence due to coal fires has become a common phenomenon in Jharia. Throughout the year, several factors such as coal fires, seepage of rainwater into mines, and illegal settlements above the abandoned mines contribute to the mining-induced subsidence. Due to such varied causes, subsidence in mining areas is temporally and spatially irregular. Traditional techniques using GPS, leveling, and total station are tedious, time-consuming, and can measure subsidence only on a point basis.</p><p>From the past few years, Interferometric Synthetic Aperture Radar (InSAR) has become a powerful tool to calculate and monitor the land subsidence. Persistent Scatterer Interferometry (PSI) is an advanced time-series interferometry technique, which calculates temporal deformation rates at mm scale with the help of stable pixels in the dataset referred to as Persistent Scatterers. The study aims at the detection and estimation of land subsidence in Jharia coalfield, Jharkhand, India, using the Persistent Scatterer Interferometry (PSI) technique. We used 30 C Band Sentinel-1 SAR images acquired in TOPSAR mode for a period of two years from 2017 to 2019, captured in a descending direction. Data acquired during the dry season are preferred to ensure good coherence. Potential subsidence zones are identified and demarcated using the Differential Interferometry technique in SNAP. PSI analysis is carried out using the StaMPS method. High temporal decorrelation due to the surrounding agricultural land cover and atmospheric interference are significant challenges for the PSI analysis in mining areas. The temporal baseline is adapted accordingly to reduce de-correlation. Atmospheric interference is removed using the TRAIN toolbox using the GACOS correction model. The results show an average subsidence rate in Jharia coal mines of approximately 4 cm/yr. Among the 23 underground mines in Jharia, 6 mines are subsiding at the maximum rate of 12 cm/yr. We identified subsidence in several small coal mines in multiple locations surrounding settlements and agricultural areas that can lead to contamination of groundwater when collapsed. Kustore underground mine covering an area of 1.2 sq. km is the largest subsidence zone in the study area just 200 meters away from the settlements.</p>

The Origin of the Moon and its Relationship to the Origin of the Solar System

1962 ◽  
Vol 14 ◽  
pp. 133-148 ◽  
Author(s):  
Harold C. Urey
Keyword(s):  
Solar System ◽  
The Moon ◽  
The Past ◽  
The Earth ◽  
Short Period ◽  
Origin Of The Moon

During the last 10 years, the writer has presented evidence indicating that the Moon was captured by the Earth and that the large collisions with its surface occurred within a surprisingly short period of time. These observations have been a continuous preoccupation during the past years and some explanation that seemed physically possible and reasonably probable has been sought.

scholarly journals Calibration of Radiocarbon Dates for the Late Pleistocene Using U/Th Dates on Stalagmites

Radiocarbon ◽  
1997 ◽  
Vol 39 (1) ◽  
pp. 27-32 ◽  
Author(s):  
John C. Vogel ◽  
Joel Kronfeld
Keyword(s):  
South Africa ◽  
Magnetic Dipole ◽  
Satisfactory Agreement ◽  
Late Pleistocene ◽  
Calibration Curve ◽  
Dipole Field ◽  
Radiocarbon Dates ◽  
The Past ◽  
The Earth ◽  
Magnetic Dipole Field

Twenty paired 14C and U/Th dates covering most of the past 50,000 yr have been obtained on a stalagmite from the Cango Caves in South Africa as well as some additional age-pairs on two stalagmites from Tasmania that partially fill a gap between 7 ka and 17 ka ago. After allowance is made for the initial apparent 14C ages, the age-pairs between 7 ka and 20 ka show satisfactory agreement with the coral data of Bard et al. (1990, 1993). The results for the Cango stalagmite between 25 ka and 50 ka show the 14C dates to be substantially younger than the U/Th dates except at 49 ka and 29 ka, where near correspondence occurs. The discrepancies may be explained by variations in 14C production caused by changes in the magnetic dipole field of the Earth. A tentative calibration curve for this period is offered.

Plant leaf recognition with shallow and deep learning: A comprehensive study

2020 ◽  
Vol 24 (6) ◽  
pp. 1311-1328
Author(s):  
Jozsef Suto
Keyword(s):  
Machine Learning ◽  
Plant Species ◽  
Research Area ◽  
Research Papers ◽  
Plant Leaf ◽  
Leaf Characteristics ◽  
The Past ◽  
The Earth ◽  
Test Sets ◽  
Comprehensive Study

Nowadays there are hundreds of thousands known plant species on the Earth and many are still unknown yet. The process of plant classification can be performed using different ways but the most popular approach is based on plant leaf characteristics. Most types of plants have unique leaf characteristics such as shape, color, and texture. Since machine learning and vision considerably developed in the past decade, automatic plant species (or leaf) recognition has become possible. Recently, the automated leaf classification is a standalone research area inside machine learning and several shallow and deep methods were proposed to recognize leaf types. From 2007 to present days several research papers have been published in this topic. In older studies the classifier was a shallow method while in current works many researchers applied deep networks for classification. During the overview of plant leaf classification literature, we found an interesting deficiency (lack of hyper-parameter search) and a key difference between studies (different test sets). This work gives an overall review about the efficiency of shallow and deep methods under different test conditions. It can be a basis to further research.

scholarly journals Trajectories of the Earth System in the Anthropocene

2018 ◽  
Vol 115 (33) ◽  
pp. 8252-8259 ◽  
Author(s):  
Will Steffen ◽  
Johan Rockström ◽  
Katherine Richardson ◽  
Timothy M. Lenton ◽  
Carl Folke ◽  
...  
Keyword(s):  
Global Economy ◽  
Human Action ◽  
Behavioral Changes ◽  
Earth System ◽  
New Governance ◽  
Sea Levels ◽  
Average Temperature ◽  
The Past ◽  
The Earth ◽  
Potential Threshold

We explore the risk that self-reinforcing feedbacks could push the Earth System toward a planetary threshold that, if crossed, could prevent stabilization of the climate at intermediate temperature rises and cause continued warming on a “Hothouse Earth” pathway even as human emissions are reduced. Crossing the threshold would lead to a much higher global average temperature than any interglacial in the past 1.2 million years and to sea levels significantly higher than at any time in the Holocene. We examine the evidence that such a threshold might exist and where it might be. If the threshold is crossed, the resulting trajectory would likely cause serious disruptions to ecosystems, society, and economies. Collective human action is required to steer the Earth System away from a potential threshold and stabilize it in a habitable interglacial-like state. Such action entails stewardship of the entire Earth System—biosphere, climate, and societies—and could include decarbonization of the global economy, enhancement of biosphere carbon sinks, behavioral changes, technological innovations, new governance arrangements, and transformed social values.

scholarly journals Semi-Automatic Identification and Pre-Screening of Geological–Geotechnical Deformational Processes Using Persistent Scatterer Interferometry Datasets

2019 ◽  
Vol 11 (14) ◽  
pp. 1675 ◽  
Author(s):  
Tomás ◽  
Pagán ◽  
Navarro ◽  
Cano ◽  
Pastor ◽  
...  
Keyword(s):  
Regional Scale ◽  
Central Italy ◽  
Geographical Information ◽  
External Information ◽  
Automatic Identification ◽  
Persistent Scatterer Interferometry ◽  
Active Deformation ◽  
Persistent Scatterers ◽  
Persistent Scatterer ◽  
Map Scale

This work describes a new procedure aimed to semi-automatically identify clusters of active persistent scatterers and preliminarily associate them with different potential types of deformational processes over wide areas. This procedure consists of three main modules: (i) ADAfinder, aimed at the detection of Active Deformation Areas (ADA) using Persistent Scatterer Interferometry (PSI) data; (ii) LOS2HV, focused on the decomposition of Line Of Sight (LOS) displacements from ascending and descending PSI datasets into vertical and east-west components; iii) ADAclassifier, that semi-automatically categorizes each ADA into potential deformational processes using the outputs derived from (i) and (ii), as well as ancillary external information. The proposed procedure enables infrastructures management authorities to identify, classify, monitor and categorize the most critical deformations measured by PSI techniques in order to provide the capacity for implementing prevention and mitigation actions over wide areas against geological threats. Zeri, Campiglia Marittima–Suvereto and Abbadia San Salvatore (Tuscany, central Italy) are used as case studies for illustrating the developed methodology. Three PSI datasets derived from the Sentinel-1 constellation have been used, jointly with the geological map of Italy (scale 1:50,000), the updated Italian landslide and land subsidence maps (scale 1:25,000), a 25 m grid Digital Elevation Model, and a cadastral vector map (scale 1:5,000). The application to these cases of the proposed workflow demonstrates its capability to quickly process wide areas in very short times and a high compatibility with Geographical Information System (GIS) environments for data visualization and representation. The derived products are of key interest for infrastructures and land management as well as decision-making at a regional scale.

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