Study of ground surface displacement estimation using ALOS/PALSAR D-InSAR interferometry

2007 ◽  
Author(s):  
Atsushi Iwashita ◽  
Marina Kudo ◽  
Hisatoshi Baba ◽  
Toshikazu Morohoshi ◽  
Masanao Hara ◽  
...  
Keyword(s):  
Ground Surface ◽  
Surface Displacement ◽  
Alos Palsar ◽  
Displacement Estimation

Surface displacement estimation using space-borne SAR interferometry in a small portion along Himalayan Frontal Fault

2014 ◽  
Vol 53 ◽  
pp. 164-178 ◽  
Author(s):  
Atanu Bhattacharya ◽  
Manoj K. Arora ◽  
Mukat L. Sharma ◽  
Malte Vöge ◽  
Raginder Bhasin
Keyword(s):  
Surface Displacement ◽  
Sar Interferometry ◽  
Displacement Estimation

scholarly journals Estimating Soil Moisture Distributions across Small Farm Fields with ALOS/PALSAR

2016 ◽  
Vol 2016 ◽  
pp. 1-8 ◽  
Author(s):  
Yuki Kojima ◽  
Kazuo Oki ◽  
Kosuke Noborio ◽  
Masaru Mizoguchi
Keyword(s):  
Soil Moisture ◽  
Soil Layer ◽  
Ground Surface ◽  
Time Domain Reflectometry ◽  
Moisture Distribution ◽  
Small Scale ◽  
Alos Palsar ◽  
Coverage Ratio ◽  
Fine Resolution ◽  
Soil Moisture Distribution

The ALOS (advanced land observing satellite) has an active microwave sensor, PALSAR (phased array L-band synthetic aperture radar), which has a fine resolution of 6.5 m. Because of the fine resolution, PALSAR provides the possibility of estimating soil moisture distributions in small farmlands. Making such small-scale estimates has not been available with traditional satellite remote sensing techniques. In this study, the relationship between microwave backscattering coefficient (σ) measured with PALSAR and ground-based soil moisture was determined to investigate the performance of PALSAR for estimating soil moisture distribution in a small-scale farmland. On the ground at a cabbage field in Japan in 2008, the soil moisture distribution of multiple soil layers was measured using time domain reflectometry when the ALOS flew over the field. Soil moisture in the 0–20 cm soil layer showed the largest correlation coefficient with σ (r=0.403). The σ values also showed a strong correlation with the ground surface coverage ratio by cabbage plants. Our results suggested that PALSAR could estimate soil moisture distribution of the 0–20 cm soil layer across a bare field and a crop coverage ratio when crops were planted.

AN ESTIMATING METHOD FOR LATERAL BEHAVIOR OF PILED-RAFT FOUNDATION

2017 ◽  
Vol 4 (1) ◽  
Author(s):  
Haruyuki Yamamoto ◽  
He Huang
Keyword(s):  
Ground Surface ◽  
Surface Displacement ◽  
Lateral Loading ◽  
Location Factors ◽  
Location Factor ◽  
Piled Raft ◽  
Piled Raft Foundation ◽  
Raft Foundation ◽  
Cone Model ◽  
Raft Foundations

Some simplified design methods were proposed to predict behavior of lateral loaded piled-raft foundations on homogenous soil. One of them is the cone model method. However, only one average solution of pile behavior can be given by this method. It can’t evaluate the location factors of piles. Therefore, this paper describes a new simplified method to predict behavior of lateral loaded piled raft foundations covering the location factor of piles. At first, ground surface displacement is derived theoretically by Cerutti’s solution, then assuming that the raft foundation has rigid stiffness, these displacements are the same to calculation lateral loading distribution. Second, the ground displacement where pile placed could be estimated under calculated lateral loading. Third, the piles behavior are evaluated based on these lateral ground displacements. In addition, 3-D FEM numerical analysis were performed to compared with these solutions.

scholarly journals Estimate of a spatially variable reservoir compressibility by assimilation of ground surface displacement data

2015 ◽  
Vol 372 ◽  
pp. 351-356 ◽  
Author(s):  
C. Zoccarato ◽  
D. Baù ◽  
F. Bottazzi ◽  
M. Ferronato ◽  
G. Gambolati ◽  
...  
Keyword(s):  
Land Surface ◽  
Ground Surface ◽  
Surface Displacement ◽  
Test Case ◽  
Geomechanical Model ◽  
Gas Field ◽  
Surface Displacements ◽  
Model Response ◽  
Synthetic Test ◽  
Gas Fields

Abstract. Fluid extraction from producing hydrocarbon reservoirs can cause anthropogenic land subsidence. In this work, a 3-D finite-element (FE) geomechanical model is used to predict the land surface displacements above a gas field where displacement observations are available. An ensemble-based data assimilation (DA) algorithm is implemented that incorporates these observations into the response of the FE geomechanical model, thus reducing the uncertainty on the geomechanical parameters of the sedimentary basin embedding the reservoir. The calibration focuses on the uniaxial vertical compressibility cM, which is often the geomechanical parameter to which the model response is most sensitive. The partition of the reservoir into blocks delimited by faults motivates the assumption of a heterogeneous spatial distribution of cM within the reservoir. A preliminary synthetic test case is here used to evaluate the effectiveness of the DA algorithm in reducing the parameter uncertainty associated with a heterogeneous cM distribution. A significant improvement in matching the observed data is obtained with respect to the case in which a homogeneous cM is hypothesized. These preliminary results are quite encouraging and call for the application of the procedure to real gas fields.

scholarly journals Deteksi Tinggi Vegetasi di Delta Mahakam dengan Penginderaan Jauh

2019 ◽  
Vol 4 (3) ◽  
pp. 175
Author(s):  
Nanin Anggraini ◽  
Atriyon Julzarika
Keyword(s):  
Remote Sensing ◽  
Ground Surface ◽  
Digital Terrain Model ◽  
Remote Sensing Data ◽  
Surface Model ◽  
Geoid Model ◽  
Alos Palsar ◽  
Vegetation Height ◽  
Vertical Accuracy ◽  
Mahakam Delta

<strong>Detection of Vegetation Height in Mahakam Delta Using Remote Sensing. </strong>The vegetation height is a vertical distance between top of the vegetation to ground surface. Vegetation height is one of the parameters for vegetation growth. There are various methods to measure vegetation height; one of them is the use of remote sensing technology. This study aims to map vegetation height in Mahakam Delta by using height models derived from remote sensing data. Such models are Digital Surface Model (DSM) and Digital Terrain Model (DTM). DSM was generated using a combination of interferometric processing of ALOS PALSAR interferometry, X-SAR, Shuttle Radar Topography Mission (SRTM), and geodetic height of Icesat/GLAS satellite imagery. This integration technique incorporated the Digital Elevation Model (DEM) method. The geoid model used in this study was EGM 2008. The following step was the correction of height errors of DSM. Terrain correction was undertaken to convert DSM into DTM, while vegetation heights were obtained from subtraction of DSM and DTM. Vertical accuracy verification refers to a tolerance of 1.96σ (95%) or ~80 cm. In DSM, a vertical accuracy value of 60.4 cm was obtained so that the DSM is feasible for mapping with scale of 1: 10,000, while the DTM was 37 cm so it is also applicable for mapping with such scale. Based on the subtraction of DSM and DTM, the vegetation heights in Mahakam Delta varied between 0 and 64 m.

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