scholarly journals POSSIBILITIES OF USING SATELLITE IMAGES AND GIS TECHNOLOGIES FOR MONITORING INUNDATION OF PIPELINE SYSTEMS

2020 ◽  
Vol 4 (1) ◽  
pp. 21-28
Author(s):  
Vyacheslav A. Melkiy ◽  
Daniil V. Dolgopolov ◽  
Alexey A. Verkhoturov

The purpose of this research is the study of possibilities of practical use of multi-zone satellite images for implementation of geotechnical monitoring of pipeline transport facilities during floodings. Modern methods and approaches are required for monitoring extended objects and analyzing large amount of remote sensing data. Such methods can be applied for studying of spectral characteristics of the Earth's surface obtained using space systems, collected in databases using geoinformation technologies (GIS). Use of special indexes and technologies for automated interpretation of multi-zone satellite images allows obtaining and analyzing information about state of pipeline systems at time of flooding. Research showed that Sentinel-2 satellite data makes it possible for fairly correctly determine of flood situation by image indexed with using of Normalized Difference Water Index (NDWI) and highlight areas and objects flooded of water.

2021 ◽  
Vol 32 (3) ◽  
pp. 1
Author(s):  
Aqeel Ghazi Mutar ◽  
Asraa Khtan ◽  
Loay E. George

Torrential rains cause many losses in city infrastructure, crops, and deaths in several regions of the world including Iraq as in the case that we will discuss in this work, on January 28 and 29, 2019. Torrential rain caused the flow of torrents in several areas of Iraq and the neighboring areas. This research work aims to identify the synoptic characteristics of torrential rains and the causes of this case. This will be done by analyzing and interpreting the weather maps at different pressure levels with focusing on the troughs and fronts locations, relative vorticity, polar jet stream effect as well as the moisture flux. The Geographic Information System (GIS) was used to analyze the satellite images in order to calculate the Normalized Difference Water Index (NDWI) to confirm the heavy rain case. The weather maps were obtained from the Modern-Era Retrospective analysis for Research and Applications Version 2 (MERRA-2).  As for the satellite images we used the satellite imagery from Sentinel-2 and EMUTSAT.


2019 ◽  
Vol 11 (18) ◽  
pp. 2184 ◽  
Author(s):  
Baik ◽  
Son ◽  
Kim

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.


Geosciences ◽  
2020 ◽  
Vol 10 (7) ◽  
pp. 260
Author(s):  
Lorena Liuzzo ◽  
Valeria Puleo ◽  
Salvatore Nizza ◽  
Gabriele Freni

The normalized difference water index (NDWI) has been extensively used for different purposes, such as delineating and mapping surface water bodies and monitoring floods. However, the assessment of this index (based on multispectral remote sensing data) is highly affected by the effects of atmospheric aerosol scattering and built-up land, especially when green and near infrared bands are used. In this study, a modified version of the NDWI was developed to improve precision and reliability in the detection of water reservoirs from satellite images. The proposed equation includes eight different parameters. A Bayesian procedure was implemented for the identification of the optimal set of these parameters. The calculation of the index was based on Sentinel-2 satellite images of spectral bands collected over the 2015–2019 period. The modified NDWI was tested for the identification of small reservoirs in a subbasin of the Belice catchment in Sicily (southern Italy). To assess the effectiveness of the index, a reference image, representing the actual reservoirs in the study area, was used. The results suggested that the use of the proposed methodology for the parameterization of the modified NDWI improves the identification of water reservoirs with surfaces smaller than 0.1 ha.


Author(s):  
W. Jiang ◽  
Y. Ni ◽  
Z. Pang ◽  
G. He ◽  
J. Fu ◽  
...  

Abstract. Water body plays an irreplaceable role in the global ecosystem and climate system. Sentinel-2 is a new satellite data with higher spatial and spectral resolution. Through analysing spectral characteristics of Sentinel-2 satellite imagery, the brightness of water body in vegetation red edge band and shortwave infrared band showe sharply different than that of the not water body. Therefore, a new type of water index SWI (Sentinel-2 Water Index) was proposed by combing those two bands. Four representative water types, which included Taihu Lake, the Yangtze River Estuary, the ChaKa Salt Lake and the Chain Lake, were selected as experimental areas. Normalized difference water index (NDWI) and Sentinel-2 Water Index (SWI) with Otsu method were employed to extract water body. The results showed that overall accuracy and Kappa coefficient of SWI were higher than that of NDWI and SWI was efficient index to rapidly and accurately extract water for Sentinel-2 data. Therefore, SWI had application potential for larger scale water mapping in the future.


Agronomy ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 1486
Author(s):  
Chris Cavalaris ◽  
Sofia Megoudi ◽  
Maria Maxouri ◽  
Konstantinos Anatolitis ◽  
Marios Sifakis ◽  
...  

In this study, a modelling approach for the estimation/prediction of wheat yield based on Sentinel-2 data is presented. Model development was accomplished through a two-step process: firstly, the capacity of Sentinel-2 vegetation indices (VIs) to follow plant ecophysiological parameters was established through measurements in a pilot field and secondly, the results of the first step were extended/evaluated in 31 fields, during two growing periods, to increase the applicability range and robustness of the models. Modelling results were examined against yield data collected by a combine harvester equipped with a yield-monitoring system. Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) were examined as plant signals and combined with Normalized Difference Water Index (NDWI) and/or Normalized Multiband Drought Index (NMDI) during the growth period or before sowing, as water and soil signals, respectively. The best performing model involved the EVI integral for the 20 April–31 May period as a plant signal and NMDI on 29 April and before sowing as water and soil signals, respectively (R2 = 0.629, RMSE = 538). However, model versions with a single date and maximum seasonal VIs values as a plant signal, performed almost equally well. Since the maximum seasonal VIs values occurred during the last ten days of April, these model versions are suitable for yield prediction.


Author(s):  
Viacheslav V. Krylenko ◽  
◽  
Marina V. Krylenko ◽  
Alexander A. Aleynikov ◽  
◽  
...  

The study of the relief of large coastal accumulative forms, based on modern technologies, is rele-vant for solving many applied problems. Coastal and underwater bars, shoals, banks are characteristic elements of large coastal accumulative forms’ geosystems. Previously existing methods of relief re-searches, especially underwater, were labor-intensive and expensive. Accordingly, the development and implementation of new methods of geographical research are necessary. The Dolgaya Spit, includ-ing its underwater shoal and the Elenin Bank, is one of the largest accumulative forms of the Sea of Azov. The purpose of our work was to obtain new information on the relief structure and the shoreline dynamics of the Dolgaya Spit based on the use of new research methods. Digital models of surface and underwater relief were built on the basis of processing Sentinel-2 satellite images and data from unmanned aerial photography. The subsequent analysis allowed identify regularities that reflect the current and previous hydro-lithodynamic conditions that determined the transformation of the Dolgaya Spit during its evolution. The fulfilled studies confirmed the possibility of successful use of modern remote methods for studying the relief of coastal accumulative forms.


2013 ◽  
Vol 659 ◽  
pp. 153-155 ◽  
Author(s):  
Hong Jun Pan ◽  
Xue Xian Li ◽  
Guang Wei Wang ◽  
Chong Song Qi

On the analysis of spectral characteristics of Aoshan remote sensing images, we find the spectral differences between mariculture zones and other surface features. This paper combines normalized difference water index with mariculture zones distribution planning to complete the extraction and the statistics of the mariculture zones, in order to effectively achieve the regulation of mariculture zones.


Author(s):  
Suwarsono Suwarsono ◽  
Fajar Yulianto ◽  
Hana Listi Fitriana ◽  
Udhi Catur Nugroho ◽  
Kusumaning Ayu Dyah Sukowati ◽  
...  

This paper describes the detection of the surface water area in Cirata dam,  upstream Citarum, using a water index derived from Sentinel-2. MSI Level 1C (MSIL1C) data from 16 November 2018 were extracted into a water index such as the NDWI (Normalized Difference Water Index) model of Gao (1996), McFeeters (1996), Roger and Kearney (2004), and Xu (2006). Water index were analyzed based on the presence of several objects (water, vegetation, soil, and built-up). The research resulted in the ability of each water index to separate water and non-water objects. The results conclude that the NDWI of McFeeters (1996) derived from Sentinel-2 MSI showed the best results in detecting the surface water area of the reservoir.


2020 ◽  
Vol 20 (4) ◽  
pp. 458-475
Author(s):  
Sabrina Brandão Cardoso ◽  
Caroline Favoreto da Cunha ◽  
Bruno Zanon Engelbrecht ◽  
Hung Kiang Chang

No presente trabalho foram utilizadas imagens multiespectrais do satélite Sentinel-2 da Bacia Hidrográfica do Rio Cachoeira (BHRC), localizada no sul do estado da Bahia. O objetivo deste trabalho foi detectar, delimitar e quantificar a área ocupada por reservatórios de água na BHRC. Para tanto foram calculados os índices MNDWI (Modified Normalized Difference Water Index) e NDWI (Normalized Difference Water Index). A capacidade de detecção de pequenos corpos d’água pelos métodos empregados mostrou-se satisfatória, apresentando uma correspondência de até 78% entre os métodos, com superiores resultados para índice MNDWI frente ao NDWI. A partir desses índices foram observadas variações sazonais e espaciais quanto à distribuição de reservatórios na BHRC. A porção sudoeste da bacia apresentou maior concentração de pequenos reservatórios no período chuvoso. No contexto geral da bacia hidrográfica, os reservatórios de água ocupam até 0,13% da área da bacia, enquanto que em determinadas áreas do sudoeste da BHRC esse valor atinge até 0,86%.


Author(s):  
Thu Trang Hoang ◽  
Khoi Nguyen Dao ◽  
Loi Thi Pham ◽  
Hong Van Nguyen

The objective of this study was to analyze the changes of riverbanks in Ho Chi Minh City for the period 1989-2015 using remote sensing and GIS. Combination of Modified Normalized Difference Water Index (MNDWI) and thresholding method was used to extract the river bank based on the multi-temporal Landsat satellite images, including 12 Landsat 4-5 (TM) images and 2 Landsat 8 images in the period 1989-2015. Then, DSAS tool was used to calculate the change rates of river bank. The results showed that, the processes of erosion and accretion intertwined but most of the main riverbanks had erosion trend in the period 1989-2015. Specifically, the Long Tau River, Sai Gon River, Soai Rap River had erosion trends with a rate of about 10.44 m/year. The accretion process mainly occurred in Can Gio area, such as Dong Tranh river and Soai Rap river with a rate of 8.34 m/year. Evaluating the riverbank changes using multi-temporal remote sensing data may contribute an important reference to managing and protecting the riverbanks.


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