scholarly journals Satellite Pre-Failure Detection and In Situ Monitoring of the Landslide of the Tunnel du Chambon, French Alps

Geosciences ◽  
2019 ◽  
Vol 9 (7) ◽  
pp. 313 ◽  
Author(s):  
Mathilde Desrues ◽  
Pascal Lacroix ◽  
Ombeline Brenguier
Keyword(s):  
Satellite Images ◽  
Failure Detection ◽  
Satellite Observation ◽  
In Situ Monitoring ◽  
Tertiary Creep ◽  
Strong Activity ◽  
French Alps ◽  
Optical Images ◽  
Optical Satellite Images

Recent studies using satellite data have shown a growing interest in detecting and anticipating landslide failures. However, their value for an actual landslide prediction has shown variable results. Therefore, the use of satellite images for that purpose still requires additional attention. Here, we study the landslide of the Tunnel du Chambon in the French Alps that ruptured in July 2015, generating major impacts on economic activity and infrastructures. To evaluate the contribution of very high-resolution optical satellite images to characterize and potentially anticipate the landslide failure, we conduct here a retro analysis of its evolution. Two time periods are analyzed: September 2012 to September 2014, and May to July 2015. We combine Pléiades optical images analysis and geodetic measurements from in situ topographic monitoring. Satellite images were correlated to detect pre-failure motions, showing 1.4-m of displacement between September 2012 and September 2014. In situ geodetic measures were used to analyze motions during the main activity of the landslide in June and July 2015. Topographic measurements highlight different areas of deformations and two periods of strong activity, related to the last stage of the tertiary creep and to anthropic massive purges of unstable masses. The law of acceleration toward the rupture observed in June and July 2015 over the topographic targets also fits well the satellite observation between 2012 and 2014, showing that the landslide probably already entered into tertiary creep 2.5 years before its failure.

Effect of Soil Depth on the Quantification of Soil Moisture Content Value Estimated from NOAA Satellite Images

2014 ◽  
Vol 567 ◽  
pp. 705-710
Author(s):  
Abdalhaleem A. Hassaballa ◽  
Abdul Nasir Matori ◽  
Helmi Z.M. Shafri
Keyword(s):  
Soil Moisture ◽  
Critical Parameter ◽  
Satellite Images ◽  
Soil Moisture Content ◽  
Soil Depth ◽  
Vegetation Indices ◽  
Field Measurements ◽  
Spatial Estimation ◽  
Optical Images

Soil moisture (MC) is considered as the most significant boundary conditions controlling most of the hydrological cycle’s processes especially over humid areas. However, MC is very critical parameter to measure because of its variability in both space and time. The fluctuation of MC along the soil depth in turn, makes it so difficult to assess from optical satellite techniques. The study aims to produce a rectified satellite’s surface temperature (Ts) in order to enhance the spatial estimation of MC. The study also aims to produce MC estimates from three variable depths of the soil using optical images from NOAA 17 in order to examine the potential of satellite techniques in assessing the MC along the soil depths. The universal triangle (UT) algorithm was used for MC assessment based on Ts, vegetation Indices (VI) and field measurements of MC; which were conducted at variable depths. The study area was divided into three classes according to the nature of surface cover. The resultant MC extracted from the UT method with rectified Ts, produced accuracies of MC ranging from 0.65 to 0.89 when validated with in-situ measured MC at depths 5cm and 10 cm respectively.

Remote sensing of cyanobacterial blooms in Lake Champlain, USA

2013 ◽  
Vol 13 (5) ◽  
pp. 1402-1409
Author(s):  
Adam Trescott ◽  
Elizabeth Isenstein ◽  
Mi-Hyun Park
Keyword(s):  
Remote Sensing ◽  
Satellite Images ◽  
Monitoring Program ◽  
In Situ Monitoring ◽  
Cyanobacterial Blooms ◽  
Lake Champlain ◽  
Initiation And Propagation ◽  
Landsat 7

The objective of this study was to develop cyanobacteria remote sensing models using Landsat 7 Enhanced Thematic Mapper Plus (ETM+) as an alternative to shipboard monitoring efforts in Lake Champlain. The approach allowed for estimation of cyanobacteria directly from satellite images, calibrated and validated with 4 years of in situ monitoring data from Lake Champlain's Long-Term Water Quality and Biological Monitoring Program (LTMP). The resulting stepwise regression model was applied to entire satellite images to provide distribution of cyanobacteria throughout the surface waters of Lake Champlain. The results demonstrate the utility of remote sensing for estimating the distribution of cyanobacteria in inland waters, which can be further used for presenting the initiation and propagation of cyanobacterial blooms in Lake Champlain.

Images Time Series Analysis for Land Deformation and Mapping Shallow Landslides based on SENTINEL - 1 and Optical Satellite Images Data: Case Study on Batam Island, Indonesia

2020 ◽  
Author(s):  
Tiggi Choanji ◽  
Michel Jaboyedoff ◽  
Marc-Henri Derron ◽  
Li Fei ◽  
Chunwei Sun
Keyword(s):  
Time Series ◽  
Satellite Images ◽  
Shallow Landslide ◽  
Shallow Landslides ◽  
Optical Images ◽  
Interferometry Method ◽  
Land Deformation ◽  
Optical Satellite Images ◽  
Immense Potential

<p>As a growing city, Batam Islands has an immense potential to become one of the strategic positions in Southeast Asia. However, as the city developed, it also followed with the deformation and potential areas which has prone to shallow landslides. Using 32 Sentinel-1A Satellite Images Data and 17 years of Optical images data, analysis of time series is conducted using Persistent Scattered Interferometry method and mapped for landslide events in the Islands. As a result, several regions impacted 4 – 10 mm/year of velocity deformation in the center part of the island and several locations simulated to be prone to shallow landslide. So, by coupling method of SAR data and optical images, has giving prominent possibility for detecting and predicting hazard potential in this island.</p>

scholarly journals Monitoring of the landslide area state on Bureya river in 2018-2019 according to radar and optical satellite images

2019 ◽  
pp. 26-35
Author(s):  
V. G. Bondur ◽  
L. N. Zakharova ◽  
A. I. Zakharov
Keyword(s):  
Optical Sensors ◽  
Large Scale ◽  
Satellite Images ◽  
Satellite System ◽  
Small Scale ◽  
Landslide Area ◽  
Interferometric Technique ◽  
Optical Images ◽  
Optical Satellite Images ◽  
Synthetic Aperture Radars

The monitoring results of the current state of landslide area on the Bureya River in 20182019 are given using images from synthetic aperture radars and optical sensors of Sentinel multi-satellite system. Differential radar interferometry technique allowed to reveal the stability of the landslide surface in the first four months after the landslide and since the end of July 2019. Small-scale dynamics of the surface within the landslide circus was detected. It is shown that the interferometric technique is inapplicable for the observation of the large-scale modifications of the shoreline unlike the optical images where the effects of the collapse of the shoreline fragments and shoreline flooding were clearly observed compared also with radar amplitude images. The ongoing landslide activity within the landslide circus and the coastline collapse area was detected using satellite images. It requires the establishment of continuous monitoring of this and other dangerous landslide zones on Bureya River.

AUTOMATIC REGISTRATION OF VECTOR DATA WITH OPTICAL IMAGES

2020 ◽  
Vol XLIII-B4-2020 ◽  
pp. 191-196
Author(s):  
Y. Tanguy ◽  
J. Michel ◽  
G. Salgues
Keyword(s):  
High Resolution ◽  
Image Registration ◽  
Prior Knowledge ◽  
Open Source Software ◽  
Satellite Images ◽  
Automatic Registration ◽  
Vector Data ◽  
Optical Images ◽  
Optical Satellite Images ◽  
Very High

Abstract. This paper presents a method to perform automatic vector-to-image registration. The proposed method performs well on different kinds of optical satellite images from Very High Resolution (VHR, sub-meter resolution) to images in the 10/20 m resolution range. It allows to automatically register vector dataset such as urban maps (by using building layers). In contrast with existing methods, our method needs few prior-knowledge on the features to match and can therefore adapt to different landscapes.This paper demonstrates the method robustness in several use-cases and presents the implementation which will soon be available as open-source software.

scholarly journals Spatio-temporal changes in glacier-wide mass balance quantified by optical remote sensing on 30 glaciers in the French Alps for the period 1983–2014

2016 ◽  
Vol 62 (236) ◽  
pp. 1153-1166 ◽  
Author(s):  
ANTOINE RABATEL ◽  
JEAN PIERRE DEDIEU ◽  
CHRISTIAN VINCENT
Keyword(s):  
Remote Sensing ◽  
Mass Balance ◽  
Satellite Images ◽  
Optical Remote Sensing ◽  
European Alps ◽  
Mass Balances ◽  
Glacier Surface ◽  
Uncertainty Range ◽  
French Alps ◽  
Optical Satellite Images

AbstractRemote sensing is a powerful method to reconstruct annual mass-balance series over past decades by exploiting archives of available images, as well as to study glaciers in inaccessible regions. We present the application of a methodological framework based only on optical satellite images to retrieve glacier-wide annual mass balances for 30 glaciers in the French Alps. The glacier-wide annual mass balance for the period 1983–2014 was reconstructed by combining changes in glacier volumes computed from remote-sensing derived DEMs with annual measurements of the snow line altitude on satellite images. Data from direct observations on two of the glaciers confirmed the accuracy of the annual mass balances quantified by remote sensing with an average difference of ~0.3 m w.e., within the uncertainty range of the methods. Our results confirm the significant increase in mass loss since the early 2000s, with a difference >1 m w.e. a−1 between the periods 1983–2002 and 2003–14. The region-wide mass balance for the French Alps over the period 1979–2011 was −0.66 ± 0.27 m w.e. a−1, close to that of the European Alps. We also show that changes in glacier surface area or length are not representative of changes in mass balance at the scale of a few decades.

scholarly journals Technologies for environmental monitoring of the city

2021 ◽  
Author(s):  
O. M. Bahatska ◽  
◽  
N. A. Pasichnyk ◽  
O. O. Opryshko ◽  
◽  
...  
Keyword(s):  
Satellite Imagery ◽  
Satellite Images ◽  
Agricultural Practices ◽  
Optical Range ◽  
Plant Identification ◽  
Direct Sunlight ◽  
Foreign Objects ◽  
Optical Images ◽  
Optical Satellite Images ◽  
Color Components

IoT technologies in the Big Data concept can radically change approaches in agricultural practices, but it is necessary to work out methods of processing and interpreting information that can be effective in crop practice. Since the dimensions of plants are too small for satellite imagery, the development of technologies can be done on trees whose dimensions are sufficient for their identification in satellite imagery. The purpose of the work is to identify and assess the condition of plantations, in particular trees, with the determination of their positioning on satellite images of megacities. Digital photographs created by optical and infrared lenses of the Obolonskyi district of Kyiv were used for the research. It was found that in the optical range for objects under direct sunlight, plant identification is possible, while shaded areas are identified with significant errors. When using the index for IR shooting IRtree = C1 - C2 + 100 it was possible to identify individual ranges that belong to the crown of trees and grass in direct sunlight and to some extent in the shade, which could not be achieved with the index for optical range GBtree = G - B + 100. Monochrome infrared and optical images were not suitable for plant identification, because when objects were in the shadow of buildings, the ranges of intensity of the color components of plants were superimposed on the ranges of foreign objects. For infrared and optical satellite images, spectral indices have been proposed that take into account several color components to assess the condition of plantations. For tree crowns under direct sunlight, approximately the same results were obtained for the proposed indices. However, the indices proposed for infrared photography are more selective, as they were able to identify separately the crowns of trees and plants on lawns, both in direct sunlight and in the shade of buildings.

scholarly journals ANALYSIS OF IN-SITU SPECTRAL REFLECTANCE OF SAGO AND OTHER PALMS: IMPLICATIONS FOR THEIR DETECTION IN OPTICAL SATELLITE IMAGES

2018 ◽  
Vol IV-3 ◽  
pp. 185-191
Author(s):  
Jojene Rendon Santillan ◽  
Meriam Makinano-Santillan
Keyword(s):  
Optical Sensors ◽  
Spectral Reflectance ◽  
Satellite Images ◽  
Spectral Response ◽  
Coconut Oil ◽  
Landsat 8 ◽  
Electromagnetic Spectrum ◽  
Palm Species ◽  
Optical Satellite Images

We present a characterization, comparison and analysis of in-situ spectral reflectance of Sago and other palms (coconut, oil palm and nipa) to ascertain on which part of the electromagnetic spectrum these palms are distinguishable from each other. The analysis also aims to reveal information that will assist in selecting which band to use when mapping Sago palms using the images acquired by these sensors. The datasets used in the analysis consisted of averaged spectral reflectance curves of each palm species measured within the 345–1045 nm wavelength range using an Ocean Optics USB4000-VIS-NIR Miniature Fiber Optic Spectrometer. This in-situ reflectance data was also resampled to match the spectral response of the 4 bands of ALOS AVNIR-2, 3 bands of ASTER VNIR, 4 bands of Landsat 7 ETM+, 5 bands of Landsat 8, and 8 bands of Worldview-2 (WV2). Examination of the spectral reflectance curves showed that the near infra-red region, specifically at 770, 800 and 875 nm, provides the best wavelengths where Sago palms can be distinguished from other palms. The resampling of the in-situ reflectance spectra to match the spectral response of optical sensors made possible the analysis of the differences in reflectance values of Sago and other palms in different bands of the sensors. Overall, the knowledge learned from the analysis can be useful in the actual analysis of optical satellite images, specifically in determining which band to include or to exclude, or whether to use all bands of a sensor in discriminating and mapping Sago palms.

scholarly journals ASSESSING SHORELINE CHANGE USING SATELLITE-DERIVED SHORELINES IN PROGRESO, YUCATÁN, MÉXICO

2012 ◽  
Vol 1 (33) ◽  
pp. 79
Author(s):  
Gabriela Garcia-Rubio ◽  
David Huntley ◽  
Paul Russsell
Keyword(s):  
Satellite Images ◽  
Shoreline Change ◽  
Valuable Resource ◽  
Confidence Bounds ◽  
Temporal Scales ◽  
Rates Of Change ◽  
Optical Satellite Images

Assessment of shoreline change during a six-year period using Satellite-Derived Shorelines (SDS) was carried out in Progreso, Yucatán, México. Confidence bounds for the SDS were defined based on the deviation between quasi-simultaneous in situ shoreline measurements and SDS. The main objective of this paper is to show that optical satellite images are a valuable resource to study shoreline change covering large geographical scales (>10km), as well as short (5 years) temporal scales. This approach can be particularly useful for those areas with a lack of shoreline records. The results presented here show that detection of differences between seasons and years is achievable using SDS. Furthermore, rates of change are also possible to assess.

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