COVID-19 lockdown effects on water turbidity of a highly polluted lake in Dhaka city, Bangladesh

2021 ◽  
Vol 67 (2) ◽  
pp. 122-133
Author(s):  
N M Refat Nasher ◽  
◽  
Md. Yachin Islam ◽  
Keyword(s):  
Lake Water ◽  
Qualitative Change ◽  
Landsat 8 ◽  
Dhaka City ◽  
Water Turbidity ◽  
Water Index ◽  
Normalized Difference Water Index ◽  
High Turbidity ◽  
Polluted Lake ◽  
Sentinel 2

Highly polluted lake water turbidity was analyzed to detect the changes during COVID-19 lockdown. Total eight Sentinel-2 Multispectral Instrument (MSI) and Landsat-8 Operational Land Imager (OLI) satellite imageries are used to observe the qualitative change of lake water turbidity for pre, during and post lockdown period. The imageries from January to June, and September and October were analyzed for change detections. Cloud free imageries have been chosen for analysis. The water pixels and turbidity are assessed by the Normalized Difference Water Index (NDWI) and Normalized Difference Turbidity Index (NDTI), respectively. The blue, red and NIR band reflectance indicates that most of the lake water becomes clearer than before the lockdown period except May. The turbidity index shows low pollution after the lockdown period. High turbidity was observed evenly distributed from January to June. In September and October, high turbidity only found the upper part of the lake. This probably indicates the floating pollutants in the lake. The qualitative study of lake water turbidity using a remote sensing approach indicates that the COVID-19 lockdown improves the water quality in city lake 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.

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 Improving flood monitoring in rural areas using remote sensing

2018 ◽  
Vol 14 (1) ◽  
pp. 160-171
Author(s):  
Zahra Ghofrani ◽  
Victor Sposito ◽  
Robert Faggian
Keyword(s):  
Rural Areas ◽  
Flood Control ◽  
Control Measures ◽  
Landsat 8 ◽  
Protective Measures ◽  
Rainfall Events ◽  
Water Index ◽  
Flood Monitoring ◽  
Normalized Difference Water Index ◽  
Heavy Rainfall Events

Abstract Precise information on the extent of inundated land is required for flood monitoring, relief, and protective measures. In this paper, two spectral indices, Normalized Difference Water Index (NDWI) and Modified Normalized Difference Water Index (MNDWI), were used to identify inundated areas during heavy rainfall events in the Tarwin catchment, Victoria, Australia, using Landsat-8 OLI imagery. By integrating the assessed condition of levees, this research also explains the inefficiency of the flood control measures of this region of Australia. NDWI and MNDWI indices performed well, but water features were enhanced better in the NDWI-derived image, with an accuracy of 96.04% and Kappa coefficient of 0.83.

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 Analysis of riverbank changes in Ho Chi Minh city in the period 1989 – 2015

2019 ◽  
Vol 2 (2) ◽  
pp. 80-88
Author(s):  
Thu Trang Hoang ◽  
Khoi Nguyen Dao ◽  
Loi Thi Pham ◽  
Hong Van Nguyen
Keyword(s):  
Remote Sensing ◽  
Remote Sensing Data ◽  
Ho Chi Minh City ◽  
Landsat 8 ◽  
River Bank ◽  
Water Index ◽  
Normalized Difference Water Index ◽  
Multi Temporal ◽  
Erosion And Accretion ◽  
Landsat Satellite

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.

scholarly journals Analisis Model Estimasi Tinggi Muka Air Tanah Menggunakan Indek Kekeringan

2018 ◽  
Vol 15 (1) ◽  
Author(s):  
Nur Febrianti ◽  
Kukuh Murtilaksono ◽  
Baba Barus
Keyword(s):  
Water Level ◽  
Drought Index ◽  
Greenhouse Gas Emission ◽  
Information Criteria ◽  
Water Levels ◽  
Drought Indices ◽  
Landsat 8 ◽  
Water Index ◽  
Normalized Difference Water Index ◽  
Shortwave Infrared

The Ground Water Level plays an important role in determining the greenhouse gas emission and, in turn, in regulating global climate system. Information on existing water levels is still using field measurements. The purpose of this study was to evaluate the best approximation model for estimating water level using drought index. This study utilizes Landsat 8 data to calculate Normalized Difference Water Index and Visible and Shortwave infrared Drought Index for 3 months (March, April and June 2016). The best estimation model is selected by the Akaike Information Criteria correction method and validated using K-Fold cross-validation. The results of this study indicate that the estimation of water level is affected by both drought indices with the TMA (mm) equation= -439,47 – 1639,7 * NDWI_Maret – 640,23 * NDWI_April + 477 * VSDI_Maret. Estimated water level began to detect hotspots ranging from 64,35 ± 36,9 6 cm (27 - 101 cm). The critical point for KHG Sei Jangkang - Sei Liong is 27 cm, thus the water level depth should be maintained less than that to avoid fire in peatlands.ABSTRAKTinggi muka air tanah lahan gambut atau secara teknis dikenal dengan kedalaman muka air tanah memegang peran penting dalam menentukan emisi gas rumah kaca dan mengatur sistem iklim global. Informasi tentang tinggi muka air yang ada saat ini masih menggunakan hasil pengukuran lapangan. Tujuan penelitian ini adalah mengevaluasi model aproksimasi terbaik untuk estimasi tinggi muka air dengan menggunakan indeks kekeringan. Penelitian ini memanfaatkan data Landsat 8 untuk menghitung Normalized Difference Water Index dan Visible and Shortwave infrared Drought Index selama 3 bulan (Maret, April dan Juni 2016). Model estimasi terbaik dipilih dengan metode koreksi Kriteria Informasi Akaike dan divalidasi menggunakan validasi silang K-Fold. Hasil penelitian ini menunjukkan bahwa estimasi tinggi muka air dipengaruhi oleh kedua indeks kekeringan tersebut dengan persamaan TMA (mm) = - 439,47 – 1639,7 * NDWI_Maret – 640,23 * NDWI_April + 477 * VSDI_Maret. Estimasi tinggi muka air mulai terdeteksi adanya hotspot berkisar antara 64,35±36,9 6 cm (27 – 101 cm). Titik kritis untuk KHG Sei Jangkang – Sei Liong adalah 27 cm, dengan demikian kedalaman tinggi muka air harus dipertahankan kurang dari itu untuk menghindari terjadinya kebakaran di lahan gambut.

scholarly journals ANALISIS PERUBAHAN GARIS PANTAI UJUNG PANGKAH DENGAN MENGGUNAKAN METODE EDGE DETECTION DAN NORMALIZED DIFFERENCE WATER INDEX (UJUNG PANGKAH SHORELINE CHANGE ANALYSIS USING EDGE DETECTION METHOD AND NORMALIZED DIFFERENCE WATER INDEX)

2018 ◽  
Vol 14 (2) ◽  
Author(s):  
Nanin Anggraini ◽  
Sartono Marpaung ◽  
Maryani Hartuti
Keyword(s):  
Edge Detection ◽  
Detection Method ◽  
Shoreline Change ◽  
Landsat 8 ◽  
Landsat Data ◽  
Change Analysis ◽  
Water Index ◽  
Normalized Difference Water Index ◽  
Landsat 7 ◽  
Edge Detection Method

Besides to the effects from tidal, coastline position changed due to abrasion and accretion. Therefore, it is necessary to detect the position of coastline, one of them by utilizing Landsat data by using edge detection and NDWI filter. Edge detection is a mathematical method that aims to identify a point on a digital image based on the brightness level. Edge detection is used because it is very good to present the appearance of a very varied object on the image so it can be distinguished easily. NDWI is able to separate land and water clearly, making it easier for coastline analysis. This study aimed to detect coastline changes in Ujung Pangkah of Gresik Regency caused by accretion and abrasion using edge detection and NDWI filters on temporal Landsat data (2000 and 2015). The data used in this research was Landsat 7 in 2000 and Landsat 8 in 2015. The results showed that the coastline of Ujung Pangkah Gresik underwent many changes due to accretion and abrasion. The accretion area reached 11,35 km2 and abrasion 5,19 km2 within 15 year period. Abstrak Selain akibat adanya pasang surut, posisi garis pantai berubah akibat adanya abrasi dan akresi. Oleh karena itu diperlukan adanya deteksi posisi garis pantai, salah satunya dengan memanfaatkan data Landsat dengan menggunakan filter edge detection dan NDWI. Edge detection adalah suatu metode matematika yang bertujuan untuk mengidentifikasi suatu titik pada gambar digital berdasarkan tingkat kecerahan. Filter edge detection digunakan karena sangat baik untuk menyajikan penampakan obyek yang sangat bervariasi pada citra sehingga dapat dibedakan dengan mudah. NDWI mampu memisahkan antara daratan dan perairan dengan jelas sehingga memudahkan untuk analisis garis pantai. Penelitian ini bertujuan untuk deteksi perubahan garis pantai di Ujung Pangkah Kabupaten Gresik yang disebabkan oleh adanya akresi dan abrasi dengan menggunakan filter edge detection dan NDWI pada data Landsat temporal (tahun 2000 dan 2015). Data yang digunakan pada penelitian ini adalah citra Landsat 7 tahun 2000 dan Landsat 8 tahun 2015. Hasil penelitian menunjukkan bahwa garis pantai di Ujung Pangkah Gresik banyak mengalami perubahan akibat adanya akresi dan abrasi. Luas akresi mencapai 11,35 km2 dan abrasi 5,19 km2 dalam periode waktu 15 tahun.

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