scholarly journals A NEW INDEX FOR IDENTIFYING WATER BODY FROM SENTINEL-2 SATELLITE REMOTE SENSING IMAGERY

2020 ◽  
Vol V-3-2020 ◽  
pp. 33-38
Author(s):  
W. Jiang ◽  
Y. Ni ◽  
Z. Pang ◽  
G. He ◽  
J. Fu ◽  
...  
Keyword(s):  
Water Body ◽  
Salt Lake ◽  
Spectral Characteristics ◽  
River Estuary ◽  
Yangtze River Estuary ◽  
Infrared Band ◽  
Water Index ◽  
Normalized Difference Water Index ◽  
Shortwave Infrared ◽  
Sentinel 2

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.

scholarly journals An Effective Water Body Extraction Method with New Water Index for Sentinel-2 Imagery

Water ◽  
2021 ◽  
Vol 13 (12) ◽  
pp. 1647
Author(s):  
Wei Jiang ◽  
Yuan Ni ◽  
Zhiguo Pang ◽  
Xiaotao Li ◽  
Hongrun Ju ◽  
...  
Keyword(s):  
Surface Water ◽  
Water Body ◽  
Extraction Method ◽  
Spectral Characteristics ◽  
Water Bodies ◽  
The Novel ◽  
Water Index ◽  
Novel Method ◽  
Effective Water ◽  
Sentinel 2

Surface water bodies, such as rivers, lakes, and reservoirs, play an irreplaceable role in global ecosystems and climate systems. Sentinel-2 imagery provides new high-resolution satellite remote sensing data. Based on the analysis of the spectral characteristics of the Sentinel-2 satellite, a novel water index called the Sentinel-2 water index (SWI) that is based on the vegetation-sensitive red-edge band (Band 5) and shortwave infrared (Band 11) bands was developed. Four representative water body types, namely, Taihu Lake, Yangtze River, Chaka Salt Lake, and Chain Lake, were selected as study areas to conduct a water body extraction performance comparison with the normalized difference water index (NDWI). We found that (1) the contrast value of the SWI was larger than that of the NDWI in terms of various water body types, including purer water, turbid water, salt water, and floating ice, which suggested that the SWI could achieve better enhancement performance for water bodies. An (2) effective water body extraction method was proposed by integrating the SWI and Otsu algorithm, which could accurately extract various water body types with high overall accuracy. The (3) method effectively extracted large water bodies and wide river channels by suppressing shadow noise in urban areas. Our results suggested that the novel method can achieve efficient water body extraction for rapidly and accurately extracting various water bodies from Sentinel-2 data and the novel method has application potential for larger-scale surface water mapping.

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
Keyword(s):  
Satellite Images ◽  
Spectral Characteristics ◽  
Remote Sensing Data ◽  
Space Systems ◽  
Water Index ◽  
Geotechnical Monitoring ◽  
Pipeline Systems ◽  
Normalized Difference Water Index ◽  
Automated Interpretation ◽  
Sentinel 2

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.

scholarly journals Modeling of Durum Wheat Yield Based on Sentinel-2 Imagery

Agronomy ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 1486
Author(s):  
Chris Cavalaris ◽  
Sofia Megoudi ◽  
Maria Maxouri ◽  
Konstantinos Anatolitis ◽  
Marios Sifakis ◽  
...  
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Vegetation Indices ◽  
Model Development ◽  
Wheat Yield ◽  
Growth Period ◽  
Yield Data ◽  
Water Index ◽  
Normalized Difference Water Index ◽  
Sentinel 2

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.

Thermal and multispectral images from Unmanned Aerial Vehicles (UAVs) for water presence detection in temporary streams: first results

2021 ◽  
Author(s):  
Massimo Micieli ◽  
Gianluca Botter ◽  
Giuseppe Mendicino ◽  
Alfonso Senatore
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Near Infrared ◽  
Infrared Band ◽  
Temporary Streams ◽  
Water Index ◽  
Long Wavelength ◽  
Research Activities ◽  
Aerial Vehicles ◽  
Normalized Difference Water Index ◽  
First Results

<p>UAVs (Unmanned Aerial Vehicles) are increasingly used for monitoring river networks with a broad range of purposes. In this contribution, we focus on the use of multispectral sensors, either in the thermal infrared band LWIR (Long-wavelength infrared, 8-15 µm) or in the infrared band NIR (Near-infrared, 0.75-1.4 µm) to map network dynamics in temporary streams. Specifically, we discuss the first results of a set of surveys carried out in 2020 within a small river catchment located in northern Calabria (southern Italy), as part of the research activities of the ERC-funded DyNET project. Preliminary, a rigorous methodology was identified to perform on-site surveys and to process and analyse the acquired images. Experimental results show that the combined use of LWIR and NIR sensors is a suitable solution for detecting water presence in channels characterized by different hydraulic and morphologic conditions. LWIR sensors alone allow one to discriminate water presence only when the thermal contrast with the surrounding environment is high. On the other hand, NIR sensors permit to detect the presence of water in most of the analyzed settings through the estimate of the Normalized Difference Water Index (NDWI). However, NIR sensors can be misled in case of shallow water depth, due to the NIR radiation emitted by the riverbed merging with that of the water. Overall, the study demonstrates that a combined LWIR/NIR approach allows addressing a broader range of conditions. Moreover, the information provided can be further enhanced by combining it with geomorphologic information and basic hydraulic concepts.</p>

Inland Saline Wetlandscapes

2020 ◽  
pp. 242-268
Author(s):  
Laxmikant Sharma ◽  
Rajashree Naik ◽  
Alok Raj
Keyword(s):  
Salt Lake ◽  
Research Work ◽  
Vital Role ◽  
Ramsar Convention ◽  
Wetland Ecosystems ◽  
Water Index ◽  
Strategic Plans ◽  
The World ◽  
Normalized Difference Water Index

Wetland ecosystems are one of the highly productive ecosystems in the world. These ecosystems have been deteriorating at a faster rate. Ramsar Convention is putting enormous effort to protect, maintain, and restore these ecosystems. Currently, the fourth phase of Strategic Plans of Ramsar Convention is going on, in which saline wetlandscapes can play vital role to attain 19 targets of this plan. In India there are 27 Ramsar sites in all the biogeographic zones; however, research work has been carried out in the past five years in only eight Ramsar sites. Currently, four years are available for the strategic plans to encourage more wetland researches. The chapter presents a case study of Sambhar Salt Lake, a Ramsar site of India that is on the verge of extinction. Normalized Difference Water Index has been calculated for three decades in 1992, 2009, and 2019, revealing the declining phases of the lake.

scholarly journals Open Surface Water Mapping Algorithms: A Comparison of Water-Related Spectral Indices and Sensors

Water ◽  
2017 ◽  
Vol 9 (4) ◽  
pp. 256 ◽  
Author(s):  
Yan Zhou ◽  
Jinwei Dong ◽  
Xiangming Xiao ◽  
Tong Xiao ◽  
Zhiqi Yang ◽  
...  
Keyword(s):  
Surface Water ◽  
Water Body ◽  
Landsat 8 ◽  
Open Surface ◽  
Body Mapping ◽  
Water Index ◽  
Landsat 7 ◽  
Surface Water Bodies ◽  
Water Indices ◽  
Sentinel 2

Open surface water bodies play an important role in agricultural and industrial production, and are susceptible to climate change and human activities. Remote sensing data has been increasingly used to map open surface water bodies at local, regional, and global scales. In addition to image statistics-based supervised and unsupervised classifiers, spectral index- and threshold-based approaches have also been widely used. Many water indices have been proposed to identify surface water bodies; however, the differences in performances of these water indices as well as different sensors on water body mapping are not well documented. In this study, we reviewed and compared existing open surface water body mapping approaches based on six widely-used water indices, including the tasseled cap wetness index (TCW), normalized difference water index (NDWI), modified normalized difference water index (mNDWI), sum of near infrared and two shortwave infrared bands (Sum457), automated water extraction index (AWEI), land surface water index (LSWI), as well as three medium resolution sensors (Landsat 7 ETM+, Landsat 8 OLI, and Sentinel-2 MSI). A case region in the Poyang Lake Basin, China, was selected to examine the accuracies of the open surface water body maps from the 27 combinations of different algorithms and sensors. The results showed that generally all the algorithms had reasonably high accuracies with Kappa Coefficients ranging from 0.77 to 0.92. The NDWI-based algorithms performed slightly better than the algorithms based on other water indices in the study area, which could be related to the pure water body dominance in the region, while the sensitivities of water indices could differ for various water body conditions. The resultant maps from Landsat 8 and Sentinel-2 data had higher overall accuracies than those from Landsat 7. Specifically, all three sensors had similar producer accuracies while Landsat 7 based results had a lower user accuracy. This study demonstrates the improved performance in Landsat 8 and Sentinel-2 for open surface water body mapping efforts.

Mariculture Zones Extraction Using NDWI and NDVI

2013 ◽  
Vol 659 ◽  
pp. 153-155 ◽  
Author(s):  
Hong Jun Pan ◽  
Xue Xian Li ◽  
Guang Wei Wang ◽  
Chong Song Qi
Keyword(s):  
Remote Sensing ◽  
Spectral Characteristics ◽  
Remote Sensing Images ◽  
Distribution Planning ◽  
Surface Features ◽  
Water Index ◽  
Normalized Difference Water Index

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.

scholarly journals DETECTING THE SURFACE WATER AREA IN CIRATA DAM UPSTREAM CITARUM USING A WATER INDEX FROM SENTINEL-2

2020 ◽  
Vol 17 (1) ◽  
pp. 1
Author(s):  
Suwarsono Suwarsono ◽  
Fajar Yulianto ◽  
Hana Listi Fitriana ◽  
Udhi Catur Nugroho ◽  
Kusumaning Ayu Dyah Sukowati ◽  
...  
Keyword(s):  
Surface Water ◽  
Water Area ◽  
Water Index ◽  
Index Model ◽  
Normalized Difference Water Index ◽  
Sentinel 2 ◽  
Water Vegetation

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.

scholarly journals Detecção e delimitação de pequenos reservatórios na Bacia Hidrográfica do Rio Cachoeira, Bahia, utilizando imagens multiespectrais

2020 ◽  
Vol 20 (4) ◽  
pp. 458-475
Author(s):  
Sabrina Brandão Cardoso ◽  
Caroline Favoreto da Cunha ◽  
Bruno Zanon Engelbrecht ◽  
Hung Kiang Chang
Keyword(s):  
Water Index ◽  
Normalized Difference Water Index ◽  
Sentinel 2

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%.

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