scholarly journals A simple, robust, and automatic approach to extract water body from Landsat images (case study: Lake Urmia, Iran)

2019 ◽  
Author(s):  
Hadiseh Babaei ◽  
Milad Janalipour ◽  
Nadia Abbaszadeh Tehrani
Keyword(s):  
Saline Lakes ◽  
Continuous Monitoring ◽  
Landsat 8 ◽  
Lake Area ◽  
Spectral Indices ◽  
Lake Urmia ◽  
Landsat Images ◽  
The World ◽  
Study Lake

Abstract Lake Urmia is one of the largest saline lakes in the world, and has a great effect on its surrounding ecosystems as well as the economic, social, and even cultural condition of its basin inhabitants. Hence, continuous monitoring of lake area changes is necessary and unavoidable for better land management and prevention of its degradation. In this study, by using Landsat 8 images and by preforming some essential pre-processing tasks, the area of the lake was estimated using the number of traditional spectral indices and a new one and the automatic Otsu's thresholding method for 5 years (2013–2017). The results showed that this index shows more accurate results than other indices when estimating the area of the lake and can separate water class from land one with an average overall accuracy of 96%.

How Climate Change and Human Interaction Alter Chemical Regime in Salt Lakes, Case Study: Lake Urmia, Aral Sea, the Dead Sea, and Lake Issyk-Kul

2021 ◽  
Author(s):  
Evgeniy V. Yakushev ◽  
Natalia Yu. Andrulionis ◽  
Mahnaz Jafari ◽  
Hamid A. K. Lahijani ◽  
Peygham Ghaffari
Keyword(s):  
Climate Change ◽  
Dead Sea ◽  
Human Interaction ◽  
Aral Sea ◽  
Salt Lakes ◽  
Lake Urmia ◽  
Study Lake ◽  
The Dead

scholarly journals Fractional Vegetation Cover Change Detection In Megacities Using Landsat Time-Series Images: A Case Study Of Hanoi City (Vietnam) During 1986-2019

2019 ◽  
Vol 12 (4) ◽  
pp. 175-187
Author(s):  
Thanh Tien Nguyen
Keyword(s):  
Rural Areas ◽  
Vegetation Cover ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Classification Method ◽  
Landsat 8 ◽  
Landsat Images ◽  
Fractional Vegetation Cover ◽  
Multi Temporal

The objective of the study is to assess changes of fractional vegetation cover (FVC) in Hanoi megacity in period of 33 years from 1986 to 2016 based on a two endmember spectral mixture analysis (SMA) model using multi-spectral and multi-temporal Landsat-5 TM and -8 OLI images. Landsat TM/OLI images were first radiometrically corrected. FVC was then estimated by means of a combination of Normalized Difference Vegetation Index (NDVI) and classification method. The estimated FVC results were validated using the field survey data. The assessment of FVC changes was finally carried out using spatial analysis in GIS. A case study from Hanoi city shows that: (i) the proposed approach performed well in estimating the FVC retrieved from the Landsat-8 OLI data and had good consistency with in situ measurements with the statistically achieved root mean square error (RMSE) of 0.02 (R 2 =0.935); (ii) total FVC area of 321.6 km 2 (accounting for 9.61% of the total area) was slightly reduced in the center of the city, whereas, FVC increased markedly with an area of 1163.6 km 2 (accounting for 34.78% of the total area) in suburban and rural areas. The results from this study demonstrate the combination of NDVI and classification method using Landsat images are promising for assessing FVC change in megacities.

scholarly journals FLOOD MONITORING USING NDWI AND MNDWI SPECTRAL INDICES: A CASE STUDY OF AGHQALA FLOOD-2019, GOLESTAN PROVINCE, IRAN

2019 ◽  
Vol XLII-4/W18 ◽  
pp. 605-607
Author(s):  
F. Khalifeh Soltanian ◽  
M. Abbasi ◽  
H. R. Riyahi Bakhtyari
Keyword(s):  
Natural Hazards ◽  
Satellite Imagery ◽  
Water Bodies ◽  
Detection Methods ◽  
Spectral Indices ◽  
Landsat Images ◽  
Flood Monitoring ◽  
Golestan Province ◽  
Digital Methods

Abstract. Assessment of changes of water bodies and vegetation by traditional methods is very difficult and costly. The use of satellite data makes it possible to study water bodies and vegetation more accurately and cost effectively. Accordingly, various digital methods have been developed to discover and detect changes of earth's surface features. Flood is one of the important factors contributing to the destruction of natural resources. The purpose of this research is to evaluate the flood areas in the Aghqala area in Golestan province of Iran. The level of water bodies in the spring of 2018 and 2019 was compared and evaluated based on the NDWI and MNDWI indices using Landsat images. The results showed that water bodies’ area in the spring of 2018 was 24.13 km2 which increased to 185.34 km2 at 2019 using NDWI; while the MNDWI due to the excessive sensitivity to the water considered agriculture wetlands as an area of water bodies. Therefore, the NDWI yielded more logical results. Also, change detection methods based on spectral and radiometric information using indices are more accurate than the classification maps and more changes can be shown. Using satellite imagery to monitor changes is essential to facilitate the planning of natural hazards management.

Analysis of the relationships between land surface temperature and spectral indices pre- and during pandemic using Landsat-8 images (case study: Gerbangkertosusila)

2021 ◽  
Author(s):  
Akmal Hafiudzan ◽  
Anggita Sulistyarini ◽  
Zahwa U. Hikmah ◽  
Rohanita S. Pratiwi ◽  
Levita Ardyagarini ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Landsat 8 ◽  
Spectral Indices

scholarly journals A NOVEL WATER INDEX (SWI) FOR SALTY WATER FROM LANDSAT 8 OLI/TIRS

2019 ◽  
Vol XLII-4/W18 ◽  
pp. 1097-1105
Author(s):  
F. Yousefian ◽  
M. Sahebi ◽  
M. Shokri ◽  
M. Moradi
Keyword(s):  
Standard Deviation ◽  
Water Resources ◽  
High Performance ◽  
Salt Lake ◽  
Landsat 8 ◽  
Lake Urmia ◽  
Water Index ◽  
Salty Water ◽  
Near Ir

Abstract. Monitoring natural resources is one of the most important tasks in earth observation and remote sensing satellites. Water resources play a crucial role in the life of human on the planet. Among the water resources, salty lakes are of particular importance in biological, physical and environmental issues. In this study, a new Salty Water Index (SWI) for Landsat 8 Operational Land Imager (OLI) images is proposed based on salty lakes by particle swarm optimization (PSO), where water doesn’t combine by cloud, shadow, and salty areas. SWI is implemented on four famous and important salty lakes with the proper distribution of the whole world and different Salinity, including Lake Assal, Great Salt Lake, Eyre Lake, and Lake Urmia. The performance of SWI is compared with other water indices by overall accuracy, f-score, kappa coefficient, and standard deviation to mean ratio. Results show the efficiency of SWI on all cases due to 0.0055 Standard deviation to mean for SWI compared to 0.0395, 0.0255, 0.0873, 0.0214, 0.0524, 0.0408 and 0.0375 for NDWI, MNDWI, AWEIsh, AWEI, WRI, MOWI, and MBWI, respectively. Also, Effectiveness criteria (E) determines the efficiency of each band of Landsat 8. In this regard, results show the high performance of Green and Near IR band in all conditions and relatively proper performance of some other bands based on a special condition of each case study. The proposed method is also suggested to readers to obtain novel spectral indices of other classes and other sensors.

Culture and the plasticity of perception

2020 ◽  
Vol 43 ◽  
Author(s):  
Michael Lifshitz ◽  
T. M. Luhrmann
Keyword(s):  
Cultural Context ◽  
Sensory Experience ◽  
Cultural Learning ◽  
The World

Abstract Culture shapes our basic sensory experience of the world. This is particularly striking in the study of religion and psychosis, where we and others have shown that cultural context determines both the structure and content of hallucination-like events. The cultural shaping of hallucinations may provide a rich case-study for linking cultural learning with emerging prediction-based models of perception.

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