Cropland productivity assessment for Ukraine based on time series of optical satellite images

2017 ◽  
Author(s):  
Nataliia Kussul ◽  
Mykola Lavreniuk ◽  
Sergii Skakun ◽  
Andrii Shelestov
Keyword(s):  
Time Series ◽  
Satellite Images ◽  
Cropland Productivity ◽  
Optical Satellite Images ◽  
Productivity Assessment

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 CHARACTERISTICS OF TEXTURE INDEX OF DAMAGED BUILDINGS USING TIME-SERIES HIGH-RESOLUTION OPTICAL SATELLITE IMAGES

2020 ◽  
Vol XLIII-B3-2020 ◽  
pp. 1709-1714
Author(s):  
M. Sonobe
Keyword(s):  
Time Series ◽  
High Resolution ◽  
Texture Analysis ◽  
Large Scale ◽  
Satellite Images ◽  
Image Interpretation ◽  
High Resolution Satellite Images ◽  
Survey Results ◽  
Occurrence Matrix ◽  
Optical Satellite Images

Abstract. A large-scale disaster has occurred due to the earthquake. In particular, 20% of the world's earthquakes with a magnitude of 6 or more occur near Japan. Damage analysis of buildings by image analysis have been effectively carried out using optical high-resolution satellite images and aerial photograph with spatial resolution of about 2 m or less. In this study, the damaged buildings caused by large-scale and continuous earthquakes in Kumamoto, Japan that occurred in April 2016 was selected as a typical example of damaged buildings. For these earthquake event, the applicability of damage distribution of buildings and recovery/restoration status by texture analysis was examined. The applicability of the representative in the dissimilarity texture analysis methods Gray- Level Co-occurrence Matrix (GLCM) method by image interpretation in the case of a large number of collapsed and wrecked buildings in a wide area was assessed. These results suggest that dissimilarity was applicable to the extraction of damaged and removed buildings in the event of such an earthquake. In addition, the analysis results were appropriately evaluated by comparing the field survey results with the image interpretation results of the pan-sharpened image. From these results, we confirmed the effectiveness of texture analysis using time-series high-resolution satellite images in grasping the damaged buildings before and immediately after the disaster and in the restoration situation 1 year after the disaster.

Reactivation of giant paleo-rockslides during the Sarpol-Zahab Mw7.3 earthquake, Iran

2020 ◽  
Author(s):  
Aya Cheaib ◽  
Pascal Lacroix ◽  
Swann Zerathe ◽  
Denis Jongmans ◽  
Najmeh Ajorlou ◽  
...  
Keyword(s):  
Time Series ◽  
Satellite Images ◽  
Ground Deformation ◽  
Large Earthquake ◽  
Controlling Factors ◽  
Zagros Mountains ◽  
Slope Failures ◽  
Runout Distance ◽  
Slow Moving ◽  
Optical Satellite Images

<p>                Zagros Mountains form a seismically active fold and thrust belt in western Iran. In addition to the high levels of seismicity, slope failures are common throughout the region, where historical records of very large landslides (> 30 km<sup>3</sup>) are documented. On the November 12<sup>th</sup> 2017, the largest earthquake (Mw 7.3) ever recorded in the Zagros occurred near the town of Sarpol-Zahab (NW Zagros/Iraq border). Following the earthquake, only one large co-seismic rockslide and some small rockfalls were documented near the epicenter. This rather small landslide activity for such a large earthquake raises the question of both the observation completeness and the controlling factors of the landslide triggering in this arid mountainous environment.</p><p>            We conducted an original inventory mapping of the landslides induced by this event along 200 km of the Iran-Iraq border. The landslides were detected by different methods: the scars of rapid co-seismic landslides were mapped using a comparison of pre- and post-seismic Planetlab images (3 m resolution), whereas slow-moving landslides (cm/yr-m/yr) were detected by deriving time-series of ground deformation from radar and optical satellite images. Interferometric measurements were constructed for 3 ascending and descending Sentinel-1 SAR tracks, over a time period of 15 months (spanning 6 months before and 9 months after the main shock), allowing the detection and monitoring of very-slow-moving landslides (cm/yr), while slow-moving landslides of higher velocities (m/yr) were detected from correlation of pre and post-earthquake optical satellite images (Planet and SPOT67 imagery; 3 m and 1.5 m resolution, respectively), orthorectified over precise DEMs.</p><p>            We detected 8 giant rotational rockslides (3.10<sup>6 </sup>to 3.10<sup>7</sup> m<sup>2</sup>) and 360 small rockfalls (2.10<sup>2</sup> to 2.10<sup>4</sup> m<sup>2</sup>) in our study area. The small slope-failures were concentrated in the steepest areas around the epicenter (within a radius of 45 km) while the giant ones were situated in far fields (150 km far from the epicenter). Geomorphological analysis of the giant landslides revealed the reactivation of huge masses with several hundreds meters scarps at their top and runout distance of several hundreds meters, advancing over a river at their toe. The geodetical analysis of these giant landslides, show their co-seismic acceleration by few cm.  Furthermore, the analysis of the displacement time-series of these giant rockslides shows that four of them are destabilized over the longer term. This observation raises question both of the risk posed by these rockslides and the controlling factors of their initiation. A geological and seismological analysis suggests that the triggering of these giant rockslides can be controlled by the geological structure (stratigraphy and folding) and the resulting topography, as well as by the fault mechanism of major earthquakes. Finally, the landslide reactivation mechanism during the Sarpol-Zahab earthquake is discussed.</p>

scholarly journals Monitoring of Damage in Sunflower and Maize Parcels Using Radar and Optical Time Series Data

2015 ◽  
Vol 2015 ◽  
pp. 1-25 ◽  
Author(s):  
György Surek ◽  
Gizella Nádor
Keyword(s):  
Time Series ◽  
Shannon Entropy ◽  
Satellite Images ◽  
Time Series Data ◽  
Series Data ◽  
Storm Damage ◽  
Temporal Behaviour ◽  
Radar Satellite ◽  
Optical Time ◽  
Optical Satellite Images

The objective of this paper is to monitor the temporal behaviour of geometrical structural change of cropland affected by four different types of damage: weed infection, Western Corn Rootworm (WCR), storm damage, and drought by time series of different type of optical and quad-pol RADARSAT2 data. Based on our results it is established that ragweed infection in sunflower can be well identified by evaluation of radar (mid-June) and optical (mid-August) satellite images. Effect of drought in sunflower is well recognizable by spectral indices derived from optical as well as “I”-component of Shannon entropy (SEI) from radar satellite images acquired during the first decade of July. Evaluation of radar and optical satellite images acquired between the last decade of July and mid-August proven to be the most efficient for detecting damages in maize fields caused by either by WCR or storm. Components of Shannon entropy are proven to have significant role in identification. Our project demonstrates the potential in integrated usage of polarimetric radar and optical satellite images for monitoring several types of agricultural damage.

A Novel Change Detection Method for Unregistered Optical Satellite Images

2012 ◽  
Vol E95.B (5) ◽  
pp. 1890-1893
Author(s):  
Wang LUO ◽  
Hongliang LI ◽  
Guanghui LIU ◽  
Guan GUI
Keyword(s):  
Change Detection ◽  
Satellite Images ◽  
Detection Method ◽  
Optical Satellite Images

scholarly journals Application of Satellite Sentinel-2 Images to Study Alternate Sandbars Movement at Lower Vistula River (Poland)

2021 ◽  
Vol 13 (8) ◽  
pp. 1505
Author(s):  
Klaudia Kryniecka ◽  
Artur Magnuszewski
Keyword(s):  
Satellite Images ◽  
Average Distance ◽  
Low Flow ◽  
Visual Interpretation ◽  
Time Intervals ◽  
Manual Delineation ◽  
Vistula River ◽  
Interclass Correlation ◽  
Optical Satellite Images ◽  
Sentinel 2

The lower Vistula River was regulated in the years 1856–1878, at a distance of 718–939 km. The regulation plan did not take into consideration the large transport of the bed load. The channel was shaped using simplified geometry—too wide for the low flow and overly straight for the stabilization of the sandbar movement. The hydraulic parameters of the lower Vistula River show high velocities of flow and high shear stress. The movement of the alternate sandbars can be traced on the optical satellite images of Sentinel-2. In this study, a method of sandbar detection through the remote sensing indices, Sentinel Water Mask (SWM) and Automated Water Extraction Index no shadow (AWEInsh), and the manual delineation with visual interpretation (MD) was used on satellite images of the lower Vistula River, recorded at the time of low flows (20 August 2015, 4 September 2016, 30 July 2017, 20 September 2018, and 29 August 2019). The comparison of 32 alternate sandbar areas obtained by SWM, AWEInsh, and MD manual delineation methods on the Sentinel-2 images, recorded on 20 August 2015, was performed by the statistical analysis of the interclass correlation coefficient (ICC). The distance of the shift in the analyzed time intervals between the image registration dates depends on the value of the mean discharge (MQ). The period from 30 July 2017 to 20 September 2018 was wet (MQ = 1140 m3 × s−1) and created conditions for the largest average distance of the alternate sandbar shift, from 509 to 548 m. The velocity of movement, calculated as an average shift for one day, was between 1.2 and 1.3 m × day−1. The smallest shift of alternate sandbars was characteristic of the low flow period from 20 August 2015 to 4 September 2016 (MQ = 306 m3 × s−1), from 279 to 310 m, with an average velocity from 0.7 to 0.8 m × day−1.

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