A Survey on Global Thresholding Methods for Mapping Open Water Body Using Sentinel-2 Satellite Imagery and Normalized Difference Water Index

2020 ◽  
Author(s):  
Aliihsan Sekertekin
Keyword(s):  
Satellite Imagery ◽  
Water Body ◽  
Open Water ◽  
Water Index ◽  
Normalized Difference Water Index ◽  
Global Thresholding ◽  
Open Water Body ◽  
Sentinel 2

scholarly journals Automatic Extraction of Water Bodies from Landsat Imagery Using Perceptron Model

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Kshitij Mishra ◽  
P. Rama Chandra Prasad
Keyword(s):  
Satellite Imagery ◽  
Water Body ◽  
Landsat Imagery ◽  
Threshold Value ◽  
Water Bodies ◽  
Limit Function ◽  
Linear Predictor ◽  
Water Index ◽  
Feature Vectors ◽  
Normalized Difference Water Index

Extraction of water bodies from satellite imagery has been widely explored in the recent past. Several approaches have been developed to delineate water bodies from different satellite imagery varying in spatial, spectral, and temporal characteristics. The current study puts forward an automatic approach to extract the water body from a Landsat satellite imagery using a perceptron model. Perceptron involves classification based on a linear predictor function that merges few characteristic properties of the object commonly known as feature vectors. The feature vectors, combined with the weights, sum up to provide an input to the output function which is a binary hard limit function. The feature vector in this study is a set of characteristic properties shown by a pixel of the water body. Low reflectance of water in SWIR band, comparison of reflectance in different bands, and a modified normalized difference water index are used as descriptors. The normalized difference water index is modified to enhance its reach over shallow regions. For this study a threshold value of 2 has been proved as best among the three possible threshold values. The proposed method accurately and quickly discriminated water from other land cover features.

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 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.

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.

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%.

scholarly journals Synoptic Characteristics of Torrential Rains in Southwest and Southeast Iraq: A Case Study

2021 ◽  
Vol 32 (3) ◽  
pp. 1
Author(s):  
Aqeel Ghazi Mutar ◽  
Asraa Khtan ◽  
Loay E. George
Keyword(s):  
Satellite Images ◽  
Research Work ◽  
Heavy Rain ◽  
Moisture Flux ◽  
Relative Vorticity ◽  
Water Index ◽  
Normalized Difference Water Index ◽  
Modern Era ◽  
Sentinel 2

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.

scholarly journals The Dynamic Change of Bosten Lake Area in Response to Climate in the Past 30 Years

Water ◽  
2019 ◽  
Vol 12 (1) ◽  
pp. 4 ◽  
Author(s):  
Xiaoai Dai ◽  
Xingping Yang ◽  
Meilian Wang ◽  
Yu Gao ◽  
Senhao Liu ◽  
...  
Keyword(s):  
Climate Change ◽  
Surface Area ◽  
Water Body ◽  
Meteorological Factors ◽  
Lake Basin ◽  
Bosten Lake ◽  
Water Index ◽  
The Past ◽  
Normalized Difference Water Index

The widely distributed lakes, as one of the major components of the inland water system, are the primary available freshwater resources on the earth and are sensitive to accelerated climate change and extensive human activities. Lakes play an important role in the terrestrial water cycle and biogeochemical cycle and substantially influence the health of humans living in the surrounding areas. Given the importance of lakes in the ecosystem, long-term monitoring of dynamic changes has important theoretical and practical significance. Here, we extracted water body information and monitored the long-term dynamics of Bosten Lake, which is the largest inland lake in China. We quantified the meteorological factors of the study area from the observation data of meteorological stations between 1988 and 2018. The characteristics of climate change and its correlation with the change of area in the Bosten Lake Basin in the past 30 years were analyzed. The major contributions of this study are as follows: (1) The initial water body was segmented based on the water index model Normalized Difference Water Index (NDWI) and Modified Normalized Difference Water Index (MNDWI) with a pre-assigned threshold value. The results were evaluated with the area extracted through artificial visual interpretation. Then we conducted mathematical morphology operators, opening and closing operations, and median filter to eliminate noise to ensure the accuracy of water body information extraction from the Bosten Lake. A long-term water surface area database of the Bosten Lake was established from high-resolution remote sensing images during 1988–2018. (2) Due to the seasonal difference of snow, ice content, and other objects on images, the areadynamics of Bosten Lake in the recent 30 years were analyzed separately in dry season and rainy season. The water surface area of Bosten Lake showed large inter-annual variations between 1988–2018. (3) Based on the assumption that climatic change has more direct effects on lake than human activities, six meteorological factors were selected to analyze the impacts of climate change on the annual mean lake surface area. The result indicated that in the past 30 years, climate conditions in the Bosten Lake Basin fluctuated greatly. We conducted correlations analysis between the areal dynamics of the Bosten Lake and the meteorological factors. Here, the annual average evaporation had the highest correlation with the areal dynamics of Bosten Lake followed by air temperature, precipitation, sunshine hours, and relative humidity, while the annual average wind speed had the weakest correlation.

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