scholarly journals Using landsat satellite images for assessing riverbank changes in the Mekong and Bassac rivers in the An Giang province

2020 ◽  
Vol 2 (SI2) ◽  
pp. First
Author(s):  
Long Dinh Hoang Nguyen ◽  
Dao Nguyen Khoi
Keyword(s):  
Landsat Imagery ◽  
Mekong Delta ◽  
Water Extraction ◽  
Meandering River ◽  
Water Index ◽  
Protection Method ◽  
Riverbank Erosion ◽  
Normalized Difference Water Index ◽  
Suitable Index ◽  
Landsat Satellite

An Giang Province is one of the key economic regions of Mekong Delta and of Vietnam. With the development of urbanization and industrialization, An Giang has been suffering a burden from natural disasters, including salinity intrusion, drought, and riverbank erosion, due to natural and anthropological drivers. Amongst them, riverbank erosion is a key problem of the An Giang province, caused by changes in hydrological and sediment characteristics because of hydropower development and sand exploitation in the upstream part. In this study, we investigated the riverbank changes by using the water extraction index based on the Landsat imagery data. Amongst three extraction indices, such as Normalized Difference Water Index (NDWI), Modified Normalized Water Index (MNDWI), and Automated Water Extraction Index (AWEI), AWEI was identified the suitable index for the study area replied on the assessment of the index performance in extracting the riverbank in the four test sites in An Giang province (An Phu District, Vinh Hoa District, Cho Moi District, and Vam Nao River). Based on that, AWEI was then used for riverbank extraction for the study area in the period 1989-2015. After using the AWEI riverbank extracting method, Linear Regression Rate (LRR) had been applied to estimate the rate of the riverbank changes in the study area. The results stated that the rate of riverbank erosion was high in meandering river segments and upper part of islets, such as Tan Chau (-33m/year), Cho Moi (-36m/year) and Vam Nao (-3.07m/year). Besides analyzing the rate of erosion, this research also discusses some potential reasons as well as protection method to mitigate this problem. This study reveals that it is crucial to take sustainable measures to mitigate erosion in An Giang province.

scholarly journals MONITORING EROSION AND ACCRETION SITUATION IN THE COASTAL ZONE AT KIEN GIANG PROVINCE

2018 ◽  
Vol XLII-3/W4 ◽  
pp. 197-203
Author(s):  
N. T. H. Diep ◽  
N. T. Loi ◽  
N. T. Can
Keyword(s):  
Land Use ◽  
Coastal Area ◽  
Coastal Erosion ◽  
Landsat Imagery ◽  
Mekong Delta ◽  
The West ◽  
Shoreline Changes ◽  
Water Index ◽  
Normalized Difference Water Index ◽  
Erosion And Accretion

<p><strong>Abstract.</strong> Kien Giang is one of the coastal provinces in the Mekong Delta which is facing the problem of coastal erosion to affect people’s life in the coastal area. This project aims to monitor shoreline and to assess landslide and accretion situation in the period from 1975 to 2015 in the coastal area of Kien Giang province. The study applied Normalized Difference Water Index (MNWI) method and water level extraction using LANDSAT imagery from 1975 to 2015 for highlight the shoreline. Thus, analysis was identified erosion and accretion areas based on shoreline changes and land use influenced by landslides and deposition. The results show to create shoreline changes from 1997 to 2015 in the coastal area of Kien Giang province. A landslide occurred in the west from Nguyen Viet Khai commune to Thuan Hoa commune and Nam Yen commune to Vinh Hoa Hiep commune, Rach Gia city, Kien Giang province. An accretion situation was determined in the areas from Thuan Hoa commune, An Minh district to Nam Thai commune, An Bien district, Kien Giang province, Rach Gia sea encroachment at Rach Gia town and Ha Tien encroachment area at Ha Tien town, Kien Giang province. In general, the coastal area of Kien Giang province has a predominant tendency of accretion, however, the occurrence of erosion and accretion are happened interlacing in the coastal area at Kien Giang province.</p>

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 Spotting Green Tides over Brittany from Space: Three Decades of Monitoring with Landsat Imagery

2021 ◽  
Vol 13 (8) ◽  
pp. 1408
Author(s):  
Louise Schreyers ◽  
Tim van Emmerik ◽  
Lauren Biermann ◽  
Yves-François Le Lay
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Landsat Imagery ◽  
Google Earth ◽  
Green Tide ◽  
Green Tides ◽  
Green Macroalgae ◽  
Water Index ◽  
Nitrogen Inputs ◽  
Landsat Satellite

Green tides of macroalgae have been negatively affecting the coasts of Brittany, France, for at least five decades, caused by excessive nitrogen inputs from the farming sector. Regular areal estimates of green tide surfaces are publicly available but only from 2002 onwards. Using free and openly accessible Landsat satellite imagery archives over 35 years (1984–2019), this study explores the potential of remote sensing for detection and long-term monitoring of green macroalgae blooms. By using a Google Earth Engine (GEE) script, we were able to detect and quantify green tide surfaces using the Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI) at four highly affected beaches in Northern Brittany. Mean green tide coverage was derived and analyzed from 1984 to 2019, at both monthly and annual scales. Our results show important interannual and seasonal fluctuations in estimated macroalgae cover. In terms of trends over time, green tide events did not show a decrease in extent at three out of four studied sites. The observed decrease in nitrogen concentrations for the rivers draining the study sites has not resulted in a reduction of green tide extents.

scholarly journals FLOOD HAZARD MAPPING AT LONG XUYEN QUADRANGLE IN 2015 USING GEOGRAPHIC INFORMATION AND REMOTE SENSING

2019 ◽  
Vol XLII-3/W8 ◽  
pp. 275-281
Author(s):  
N. T. H. Diep ◽  
T. H. Duy ◽  
P. K. Diem ◽  
N. T. B. Nam ◽  
N. T. T. Huong
Keyword(s):  
Flood Hazard ◽  
Mekong Delta ◽  
Hazard Mapping ◽  
Hazard Map ◽  
Water Index ◽  
Flood Hazard Map ◽  
Severe Flood ◽  
Normalized Difference Water Index ◽  
Spss Software ◽  
Sentinel 2

<p><strong>Abstract.</strong> In recent year, the flooding has been occurred with higher frequency at Long Xuyen Quadrangle areas of Mekong Delta, Vietnam. It was considered as a major natural disaster which effects on the physical and spiritual in people’s life in this area. This research aims to generate a flood hazard map and assess the flood situation at Long Xuyen quadrangle in 2015. The MNDWI (Modification of Normalized Difference Water Index) extracting from Sentinel 2 image was used to map the flood extent at Long Xuyen quadrangle during rainy season in 2015. The statistics method was estimated correlation coefficient between flooding spatial distribution and hydrological stations on SPSS software. The results showed that the severe flood occurred from August to December in 2015. There were about 47.6% and 28.2% of the total area were inundated in October and August, respectively. The correlation between inundated areas and water level at Ha Tien and Chau Doc hydrological stations was 0.73 and 0.65 (p &amp;lt;0.01), respectively. The derived information was very essential and valuable for local managers in making decision on responding and mitigating to the flood disaster.</p>

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 Study on Monitoring Water Area in Irrigation Area by Local Space Self-correlation Index

2022 ◽  
Author(s):  
tao su ◽  
Jian Wang ◽  
Xingyuan Cui ◽  
Lei Wang
Keyword(s):  
Remote Sensing ◽  
Classification Accuracy ◽  
Hot Spot ◽  
Water Extraction ◽  
Vegetation Coverage ◽  
Hot Spot Analysis ◽  
Water Index ◽  
Water Classification ◽  
Normalized Difference Water Index ◽  
Spot Analysis

Abstract Landsat remote sensing image is a widely used data source in water remote sensing. Normalized difference water index (NDWI), modified normalized difference water index (MNDWI) and automated water extraction index (AWEI) are commonly used water extraction classifiers. In the process of their application, because the threshold varies with the location and time of the research object, how to select the threshold with the highest classification accuracy is a time-consuming and challenging task. The purpose of this study was to explore a method that can not only improve the accuracy of water extraction, but also provide a fixed threshold, and can meet the requirements of automatic water extraction. We introduced the local spatial auto correlation statistics and calculate the Getis-Ord Gi* index to have hot spot analysis. Comparative analysis showed that the accuracy of water classification had been greatly improved through hot spot analysis. AWEIsh classifier had the best classification accuracy under the condition of INVERSE_DISTANCE neighborhood rule and Z>1.96, and the accuracy changes least in different time, different location and different vegetation coverage images. Therefore, in the process of regional water extraction, hot spot analysis method was effective, which was helpful to improve the accuracy of water extraction.

scholarly journals Exploring Physical and Human Induced Coastal Morphodynamics: A Study with Reference to Nintavur to Addalaichenai Coastal Areas of Ampara District, Sri Lanka

2021 ◽  
Vol 10 (3) ◽  
pp. 347
Author(s):  
Kafoor Nijamir ◽  
T.M.S.P.K. Thennakoon ◽  
H.M. Jayani Rupi Herath ◽  
Mohamed Ibrahim Mohamed Kaleel
Keyword(s):  
Morphological Changes ◽  
Google Earth ◽  
Physical Factors ◽  
Water Separation ◽  
River Flooding ◽  
Water Index ◽  
Coastal Morphodynamics ◽  
Normalized Difference Water Index ◽  
Landsat Satellite

Observing and mapping the long-term coastal morphodynamics because of the human and physical induced factors using conventional methods could not give expected outcomes. State-of-the-art technology and tools are the best methods to do so. Thus, this study is to explore the long-term coastal morphodynamics of coastal strip from Nintavur to Addalaichenai area using the Landsat satellite images of the years 1991, 2001, 2011 and 2019, downloaded from the Earth Explorer website. Google Earth (GE) historical images were also used for the comparison of periodic coastal morphodynamics. Normalized Difference Water Index (NDWI) was processed for land and water separation. Direct observation, perspective of the respective officials and inhabitants, reports concerning the departments and authorities were also considered as the sources for this study. In conclusion, this study has found that the coastal morphological changes have been made because of the both human and physical induced factors of which waves and river flooding withing the study area are the physical factors and construction activities; port and breakwaters are the human activities which have modified the beach in the study area. In comparison, after the construction of the port, remarkable coastal morphodynamics have been recorded in the period from 2011 to 2019 in the study area.   Received: 11 February 2021 / Accepted: 22 March 2021 / Published: 10 May 2021

scholarly journals A Novel Method for River Bank Detection from Landsat Satellite Data: A Case Study in the Vietnamese Mekong Delta

2020 ◽  
Vol 12 (20) ◽  
pp. 3298
Author(s):  
Doan Van Binh ◽  
Basil Wietlisbach ◽  
Sameh Kantoush ◽  
Ho Huu Loc ◽  
Edward Park ◽  
...  
Keyword(s):  
Change Detection ◽  
Satellite Data ◽  
Vegetation Index ◽  
Mekong Delta ◽  
Detection Algorithm ◽  
River Bank ◽  
Water Index ◽  
Automated Method ◽  
Normalized Difference Water Index ◽  
Better Than

River bank (RB) erosion is a global issue affecting livelihoods and properties of millions of people. However, it has not received enough attention in the Vietnamese Mekong Delta (VMD), i.e., the world’s third largest delta, compared to salinity intrusion and flooding. There have been several studies examining RB and coastal erosion in the VMD using remotely sensed satellite data, but the applied methodology was not adequately validated. Therefore, we developed a novel SRBED (Spectral RB Erosion Detection) method, in which the M-AMERL (Modified Automated Method for Extracting Rivers and Lakes) is proposed, and a new RB change detection algorithm using Landsat data. The results show that NDWI (Normalized Difference Water Index) and MNDWI (Modified Normalized Difference Water Index) using the M-AMERL algorithm (i.e., NDWIM-AMERL, MNDWIM-AMERL) perform better than other indices. Furthermore, the NDWIM-AMERL; SMA (i.e., NDWIM-AMERL using the SMA (Spectral Mixture Analysis) algorithm) is the best RB extraction method in the VMD. The NDWIM-AMERL; SMA performs better than the MNDWI, NDVI (Normalized Difference Vegetation Index), and WNDWI (Weighted Normalized Difference Water Index) indices by 35–41%, 70% and 30%, respectively. Moreover, the NDVI index is not recommended for assessing RB changes in the delta. Applying the developed SRBED method and RB change detection algorithm, we estimated a net erosion area of the RB of –1.5 km2 from 2008 to 2014 in the Tien River from Tan Chau to My Thuan, with a mean erosion width of –2.64 m and maximum erosion widths exceeding 60 m in places. Our advanced method can be applied in other river deltas having similar characteristics, and the results from our study are helpful in future studies in the VMD.

scholarly journals A NEW MULTI-SPECTRAL THRESHOLD NORMALIZED DIFFERENCE WATER INDEX (MST-NDWI) WATER EXTRACTION METHOD – A CASE STUDY IN YANHE WATERSHED

2018 ◽  
Vol XLII-3 ◽  
pp. 2557-2564
Author(s):  
Y. Zhou ◽  
H. Zhao ◽  
H. Hao ◽  
C. Wang
Keyword(s):  
Extraction Method ◽  
Accuracy Assessment ◽  
Spectral Characteristics ◽  
Water System ◽  
Landsat Tm ◽  
Water Extraction ◽  
Water Volume ◽  
Threshold Segmentation ◽  
Water Index ◽  
Normalized Difference Water Index

Accurate remote sensing water extraction is one of the primary tasks of watershed ecological environment study. Since the Yanhe water system has typical characteristics of a small water volume and narrow river channel, which leads to the difficulty for conventional water extraction methods such as Normalized Difference Water Index (NDWI). A new Multi-Spectral Threshold segmentation of the NDWI (MST-NDWI) water extraction method is proposed to achieve the accurate water extraction in Yanhe watershed. In the MST-NDWI method, the spectral characteristics of water bodies and typical backgrounds on the Landsat/TM images have been evaluated in Yanhe watershed. The multi-spectral thresholds (TM1, TM4, TM5) based on maximum-likelihood have been utilized before NDWI water extraction to realize segmentation for a division of built-up lands and small linear rivers. With the proposed method, a water map is extracted from the Landsat/TM images in 2010 in China. An accuracy assessment is conducted to compare the proposed method with the conventional water indexes such as NDWI, Modified NDWI (MNDWI), Enhanced Water Index (EWI), and Automated Water Extraction Index (AWEI). The result shows that the MST-NDWI method generates better water extraction accuracy in Yanhe watershed and can effectively diminish the confusing background objects compared to the conventional water indexes. The MST-NDWI method integrates NDWI and Multi-Spectral Threshold segmentation algorithms, with richer valuable information and remarkable results in accurate water extraction in Yanhe watershed.

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