Mathematical analysis of Sentinel-2 spectral signal evolution for mapping agriculture area in Senegal: case of millet, maize and peanuts

Agricultural monitoring has become an absolute necessity in the Sahel countries, especially with climate change which constitutes a real threat for this sector. The aim of this work is to develop a methodology for identifying crops and mapping agricultural areas using Sentinel-2 data from the Copernicus program. The purpose of this work consisted in discriminating the crops of millet, maize and peanuts. This is to analyse the scientific and technical obstacles related to this problem. For this, we have made a mathematical analysis of optical satellite images. High temporal and spatial resolution images (10m to 60m) of Sentinel 2 sensors were used in this work. This unique set of data coupled with field data, has permitted to carry out a diagnosis of land cover and cultivated land surfaces, and evaluating the contribution of this type of data for crop forecast

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

Remote Sensing ◽

10.3390/rs13081505 ◽

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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An Improved Boosting Learning Saliency Method for Built-Up Areas Extraction in Sentinel-2 Images

Remote Sensing ◽

10.3390/rs10121863 ◽

2018 ◽

Vol 10 (12) ◽

pp. 1863 ◽

Cited By ~ 2

Author(s):

Zhenhui Sun ◽

Qingyan Meng ◽

Weifeng Zhai

Keyword(s):

Satellite Images ◽

Good Accuracy ◽

Particle Swarm Optimization Algorithm ◽

Saliency Map ◽

Band Combination ◽

Saliency Maps ◽

Training Samples ◽

Different Types ◽

Optical Satellite Images ◽

Sentinel 2

Built-up areas extraction from satellite images is an important aspect of urban planning and land use; however, this remains a challenging task when using optical satellite images. Existing methods may be limited because of the complex background. In this paper, an improved boosting learning saliency method for built-up area extraction from Sentinel-2 images is proposed. First, the optimal band combination for extracting such areas from Sentinel-2 data is determined; then, a coarse saliency map is generated, based on multiple cues and the geodesic weighted Bayesian (GWB) model, that provides training samples for a strong model; a refined saliency map is subsequently obtained using the strong model. Furthermore, cuboid cellular automata (CCA) is used to integrate multiscale saliency maps for improving the refined saliency map. Then, coarse and refined saliency maps are synthesized to create a final saliency map. Finally, the fractional-order Darwinian particle swarm optimization algorithm (FODPSO) is employed to extract the built-up areas from the final saliency result. Cities in five different types of ecosystems in China (desert, coastal, riverside, valley, and plain) are used to evaluate the proposed method. Analyses of results and comparative analyses with other methods suggest that the proposed method is robust, with good accuracy.

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Influence of Wind on Suspended Matter in the Water of the Albufera of Valencia (Spain)

10.20944/preprints202102.0594.v1 ◽

2021 ◽

Author(s):

Juan Soria ◽

Miguel Jover-Cerdá ◽

Jose Antonio Domínguez-Gómez

Keyword(s):

Experimental Data ◽

Wind Speed ◽

Suspended Matter ◽

Field Data ◽

Satellite Images ◽

Great Influence ◽

Fine Sediment ◽

Total Suspended Matter ◽

Know How ◽

Sentinel 2

Wind is one of the factors that has a great influence on suspended matter in lakes, especially in shallow lagoons. In order to know how wind affects the water in Albufera of Valencia, a shallow coastal lagoon, the measured variables of turbidity and transparency have been correlated with the estimates by processing Sentinel-2 satellite images with the Sen2Cor processor. Data from four years of study show that most of them are light to gentle easterly breezes and moderate to fresh westerly breezes. The results obtained show significant correlations between the measured variables and those obtained from the satellite images for total suspended matter and water transparency and with the average daily wind speed. There is no significant correlation between wind and chlorophyll a. Moderate to fresh breezes resuspend the fine sediment reaching concentration values from 100 to 300 mg L-1 according to satellite data. However, it is necessary to obtain field data for the values of moderate and fresh winds, as for now there are no experimental data to verify the validity of the satellite estimates.

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Influence of Wind on Suspended Matter in the Water of the Albufera of Valencia (Spain)

Journal of Marine Science and Engineering ◽

10.3390/jmse9030343 ◽

2021 ◽

Vol 9 (3) ◽

pp. 343

Author(s):

Juan Soria ◽

Miguel Jover ◽

José Antonio Domínguez-Gómez

Keyword(s):

Experimental Data ◽

Wind Speed ◽

Coastal Lagoon ◽

Suspended Matter ◽

Field Data ◽

Satellite Images ◽

Fine Sediment ◽

Total Suspended Matter ◽

Know How ◽

Sentinel 2

Wind significantly influences suspended matter in lakes, especially in shallow lagoons. To know how wind affects the water in Albufera of Valencia, a shallow coastal lagoon, the measured variables of turbidity and transparency have been correlated with the estimates by processing Sentinel-2 satellite images with the Sen2Cor processor. Data from four years of study of winds show that most of them are light to gentle easterly breezes and moderate to fresh westerly breezes. The obtained results show significant correlations between the measured variables and those obtained from the satellite images for total suspended matter and water transparency, as well as with the average daily wind speed. There is no significant correlation between wind and chlorophyll a. Moderate to fresh breezes resuspend the fine sediment reaching concentration values from 100 to 300 mg L−1 according to satellite data. However, it is necessary to obtain field data for the values of moderate and fresh winds, as for now, there are no experimental data to verify the validity of the satellite estimates.

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Detection of Liquefaction Phenomena from the 2017 Pohang (Korea) Earthquake Using Remote Sensing Data

Remote Sensing ◽

10.3390/rs11182184 ◽

2019 ◽

Vol 11 (18) ◽

pp. 2184 ◽

Cited By ~ 4

Author(s):

Baik ◽

Son ◽

Kim

Keyword(s):

Satellite Images ◽

Remote Sensing Data ◽

Short Wave ◽

Landsat 8 ◽

Content Increase ◽

Infrared Band ◽

Water Index ◽

Before And After ◽

Optical Satellite Images ◽

Sentinel 2

On 15 November 2017, liquefaction phenomena were observed around the epicenter after a 5.4 magnitude earthquake occurred in Pohang in southeast Korea. In this study, we attempted to detect areas of sudden water content increase by using SAR (synthetic aperture radar) and optical satellite images. We analyzed coherence changes using Sentinel-1 SAR coseismic image pairs and analyzed NDWI (normalized difference water index) changes using Landsat 8 and Sentinel-2 optical satellite images from before and after the earthquake. Coherence analysis showed no liquefaction-induced surface changes. The NDWI time series analysis models using Landsat 8 and Sentinel-2 optical images confirmed liquefaction phenomena close to the epicenter but could not detect liquefaction phenomena far from the epicenter. We proposed and evaluated the TDLI (temporal difference liquefaction index), which uses only one SWIR (short-wave infrared) band at 2200 nm, which is sensitive to soil moisture content. The Sentinel-2 TDLI was most consistent with field observations where sand blow from liquefaction was confirmed. We found that Sentinel-2, with its relatively shorter revisit period compared to that of Landsat 8 (5 days vs. 16 days), was more effective for detecting traces of short-lived liquefaction phenomena on the surface. The Sentinel-2 TDLI could help facilitate rapid investigations and responses to liquefaction damage.

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Seasonal dynamics of snow ablation on selected glaciers in central Spitsbergen derived from Sentinel-2 satellite images

Journal of Glaciology ◽

10.1017/jog.2021.36 ◽

2021 ◽

pp. 1-6

Author(s):

Jan Kavan ◽

Vincent Haagmans

Keyword(s):

Snow Cover ◽

Wind Direction ◽

Satellite Images ◽

Prevailing Wind ◽

Seasonal Snow ◽

Glacier Melt ◽

Prevailing Wind Direction ◽

Surface Snow ◽

Temporal And Spatial ◽

Sentinel 2

Abstract The dynamics of seasonal snow ablation on six glaciers in central Spitsbergen (Dicksonland) were assessed by examining a set of Sentinel-2 satellite images covering the summer ablation season for the period 2016–19. All glaciers lost 80% or more of their surface snow cover during the studied ablation seasons. This bolsters the recently observed trend of local glacier thinning, even at higher altitudes. Snow ablation dynamics are highly dependent on the glaciers altitudes, their position relative to the prevailing wind direction and the exposure to insolation. The accumulation areas of the studied glaciers were delimited based on the overlap of the minimum extent of snow-covered areas in the four consecutive studied summer seasons. The high temporal and spatial resolutions of available images enabled a detailed description of the seasonal snow ablation dynamics. Moreover, an estimate of the average number of days with below threshold glacier snow cover was made. This study contributes to our understanding of recent processes and might further support the modelling of glacier melt and subsequent runoff.

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