scholarly journals STUDY ON THE WATER BODY EXTRACTION USING GF-1 DATA BASED ON ADABOOST INTEGRATED LEARNING ALGORITHM

2020 ◽  
Vol XLII-3/W10 ◽  
pp. 641-648
Author(s):  
J. Y. Sun ◽  
G. Z. Wang ◽  
G. J. He ◽  
D. C. Pu ◽  
W. Jiang ◽  
...  
Keyword(s):  
Surface Water ◽  
Water Body ◽  
Rapid Development ◽  
Kappa Coefficient ◽  
Water Bodies ◽  
Integrated Learning ◽  
Visual Interpretation ◽  
Adaboost Algorithm ◽  
Classification Time ◽  
Better Than

Abstract. Surface water system is an important part of global ecosystem, and the changes in surface water may lead to disasters, such as drought, waterlog, and water-borne diseases. The rapid development of remote sensing technology has supplied better strategies for water bodies extraction and further monitoring. In this study, AdaBoost and Random Forest (RF), two typical algorithms in integrated learning, were applied to extract water bodies in Chaozhou area (mainly located in Guangzhou Province, China) based on GF-1 data, and the Decision Tree (DT) was used for comparative tests to comprehensively evaluate the performance of classification algorithms listed above for surface water body extraction. The results showed that: (1) Compared with visual interpretation, AdaBoost performed better than RF in the extraction of several typical water bodies, such as rivers, lakes and ponds Moreover, the water extraction results of the strong classifiers using AdaBoost or RF were better than the weak basic classifiers. (2) For the quantitative accuracy statistics, the overall accuracy (96.5%) and kappa coefficient (93%) using AdaBoost exceeded those using RF (5.3% and 10.6%), respectively. The classification time of AdaBoost increased by 403 seconds and 918 seconds relative to RF and DT methods. However, in terms of visual interpretation, quantitative statistical accuracy and classification time, AdaBoost algorithm was more suitable for the water body extraction. (3) For the sample proportion comparison experiment of AdaBoost, four sampling proportions (0.1%, 0.2%, 1% and 2%) were chosen and 0.1% sampling proportion reached the optimum classification accuracy (93.9%) and kappa coefficient (87.8%).

scholarly journals Deep learning for intelligent diagnosis in thyroid scintigraphy

2021 ◽  
Vol 49 (1) ◽  
pp. 030006052098284
Author(s):  
Tingting Qiao ◽  
Simin Liu ◽  
Zhijun Cui ◽  
Xiaqing Yu ◽  
Haidong Cai ◽  
...  
Keyword(s):  
Deep Learning ◽  
Disease Diagnosis ◽  
Kappa Coefficient ◽  
Diagnostic Assessment ◽  
First Year ◽  
Thyroid Scintigraphy ◽  
Diagnostic Ability ◽  
The Third ◽  
Classification Time ◽  
Better Than

Objective To construct deep learning (DL) models to improve the accuracy and efficiency of thyroid disease diagnosis by thyroid scintigraphy. Methods We constructed DL models with AlexNet, VGGNet, and ResNet. The models were trained separately with transfer learning. We measured each model’s performance with six indicators: recall, precision, negative predictive value (NPV), specificity, accuracy, and F1-score. We also compared the diagnostic performances of first- and third-year nuclear medicine (NM) residents with assistance from the best-performing DL-based model. The Kappa coefficient and average classification time of each model were compared with those of two NM residents. Results The recall, precision, NPV, specificity, accuracy, and F1-score of the three models ranged from 73.33% to 97.00%. The Kappa coefficient of all three models was >0.710. All models performed better than the first-year NM resident but not as well as the third-year NM resident in terms of diagnostic ability. However, the ResNet model provided “diagnostic assistance” to the NM residents. The models provided results at speeds 400 to 600 times faster than the NM residents. Conclusion DL-based models perform well in diagnostic assessment by thyroid scintigraphy. These models may serve as tools for NM residents in the diagnosis of Graves’ disease and subacute thyroiditis.

scholarly journals Downscaling MODIS Surface Reflectance to Improve Water Body Extraction

2015 ◽  
Vol 2015 ◽  
pp. 1-13 ◽  
Author(s):  
Xianghong Che ◽  
Min Feng ◽  
Hao Jiang ◽  
Jia Song ◽  
Bei Jia
Keyword(s):  
Surface Water ◽  
Water Body ◽  
Terrestrial Ecosystems ◽  
Water Area ◽  
Water Bodies ◽  
Tibet Plateau ◽  
Surface Reflectance ◽  
Discrimination Ability ◽  
Automated Method ◽  
Landsat 7

Inland surface water is essential to terrestrial ecosystems and human civilization. Accurate mapping of surface water dynamic is vital for both scientific research and policy-driven applications. MODIS provides twice observation per day, making it perfect for monitoring temporal water dynamic. Although MODIS provides two bands at 250 m resolution, accurately deriving water area always depends on observations from the spectral bands with 500 m resolution, which limits its discrimination ability over small lakes and rivers. The paper presents an automated method for downscaling the 500 m MODIS surface reflectance (SR) to 250 m to improve the spatial discrimination of water body extraction. The method has been tested at Co Ngoin and Co Bangkog in Qinghai-Tibet plateau. The downscaled SR and the derived water bodies were compared to SR and water body mapped from Landsat-7 ETM+ images were acquired on the same date. Consistency metrics were calculated to measure their agreement and disagreement. The comparisons indicated that the downscaled MODIS SR showed significant improvement over the original 500 m observations when compared with Landsat-7 ETM+ SR, and both commission and omission errors were reduced in the derived 250 m water bodies.

scholarly journals A Water Body Extraction Methods Comparison Based on FengYun Satellite Data: A Case Study of Poyang Lake Region, China

2020 ◽  
Vol 12 (23) ◽  
pp. 3875
Author(s):  
Xufeng Wei ◽  
Wenbo Xu ◽  
Kuanle Bao ◽  
Weimin Hou ◽  
Jia Su ◽  
...  
Keyword(s):  
Surface Water ◽  
Water Body ◽  
Land Surface ◽  
Classification Accuracy ◽  
Poyang Lake ◽  
Kappa Coefficient ◽  
Classification Method ◽  
Discrete Particle Swarm Optimization ◽  
Swarm Optimization ◽  
Land Surface Water

Water body extraction can help eco-environmental policymakers to intuitively grasp surface water resources. Remote sensing technology can accurately and quickly extract surface water information, which is of great significance for monitoring surface water changes. Fengyun satellite images have the advantages of high time resolution and multispectral bands. This provides important image data suitable for high-frequency surface water monitoring. Based on Fengyun 3 medium resolution spectral imager (FY-3/MERSI) data, 7 methods were applied in this study, which include single-band threshold method, water body index method, knowledge decision tree classification method, supervised classification method, unsupervised classification method, spectral matching based on discrete particle swarm optimization (SMDPSO), and improved spectral matching based on discrete particle swarm optimization with linear feature enhancement (SMDPSO+LFE). These methods were used to extract the land surface water of Poyang Lake, check the samples from the Landsat image with similar times to the FY-3 images, and calculate the classification accuracy via the confusion matrix. The results showed that the overall classification accuracy (OA) of the SMDPSO+LFE is 97.64%, and the Kappa coefficient is 0.95. To analyze the stability of the surface water extracted by SMDPSO+LFE in different regions, this paper selected eight test sites with different surface water types, landscapes, and terrains to extract surface water. Based on an analysis of the land surface water results at the eight test sites, every OA in the eight sites was higher than 94.5%, the Kappa coefficient was greater than 0.88. In conclusion, the SMDPSO+LFE is found to be the most suitable method among the 7 methods and effectively distinguish between different surface water bodies and backgrounds with good stability.

scholarly journals WATER MONITORING IN UKRAINE: METHODS FOR ASSESSING WATER QUALITY FOR VARIOUS PURPOSES IN CONNECTION WITH CHANGES IN THE REGULATORY FRAMEWORK (2014-2021)

2021 ◽  
pp. 6-19
Author(s):  
V.K. Khilchevskyi
Keyword(s):  
Water Quality ◽  
Surface Water ◽  
Water Use ◽  
Water Body ◽  
Water Monitoring ◽  
Chemical State ◽  
Water Bodies ◽  
State Monitoring ◽  
Altered Surface ◽  
Surface Water Bodies

Over the past five years (2014-2021), there have been significant changes in regulatory methods for assessing water quality for various purposes, which is due to Ukraine’s course towards European integration. An important feature was the cancellation of the acts of sanitary legislation of the Ukrainian SSR and the USSR (from 01.01.2017), which were applied in Ukraine for a long time (order of the Cabinet of Ministers of Ukraine of 2016). The Law of Ukraine “On Amendments to Certain Legislative Acts of Ukraine Concerning the Implementation of Integrated Approaches in Water Resources Management Based on the Basin Principle” (2016) amended the Water Code of Ukraine regarding hydrographic zoning and water monitoring in accordance with the provisions of the EU Water Framework Directive. In 2018, by a resolution of the Cabinet of Ministers of Ukraine, the “Procedure for the implementation of state monitoring of waters” was approved. In 2019, the Ministry of Natural Resources of Ukraine approved the normative “Methodology for assigning a surface water array to one of the classes of the ecological and chemical states of a surface water array, as well as assigning an artificial or significantly altered surface water array to one of the classes of the ecological potential of an artificial or significantly altered surface water array” The objects of state monitoring of waters are land and ground water bodies and sea waters. Surface water body – a specially defined surface water body or part of it. The body of surface waters can be classified into one of five categories: 1) rivers; 2) lakes; 3) transitional waters; 4) coastal waters; 5) artificial or substantially altered surface water bodies. The program of state monitoring of waters provides for control over four groups of indicators: 1) biological; 2) physical and chemical; 3) chemical; 4) hydromorphological. Based on the data and information obtained as a result of the state monitoring of the waters of surface and groundwater bodies, the ecological and chemical state of the surface water bodies, the ecological potential of artificial or significantly altered surface water bodies, the quantitative and chemical state of the groundwater bodies are determined, taking into account which river basin management plans and assess the level of achievement of environmental objectives. The purpose of this study is to highlight the approaches that have developed at the present stage to the regulation of water quality for various purposes, the main of which are: environmental; hygienic (household and drinking and cultural and household or recreational water use), fishery. If, when assessing the quality of water for environmental purposes, a deviation from the maximum permissible concentrations (MPC) was made, then in other areas of water use, the MPC standards remain relevant. The importance of this study also lies in the need to convey generalized information to a wide range of authors who are interested in water quality issues.

scholarly journals Extraction of Water-body Area from High-resolution Landsat Imagery

2018 ◽  
Vol 8 (6) ◽  
pp. 4111
Author(s):  
B. Chandrababu Naik ◽  
B. Anuradha
Keyword(s):  
Surface Water ◽  
Satellite Data ◽  
Water Body ◽  
Water Area ◽  
Water Bodies ◽  
Landsat 8 ◽  
Indexing Methods ◽  
Water Index ◽  
Surface Water Body ◽  
Normalized Difference Water Index

Extraction of water bodies from satellite imagery has been broadly explored in the current decade. So many techniques were involved in detecting of the surface water bodies from satellite data. To detect and extracting of surface water body changes in Nagarjuna Sagar Reservoir, Andhra Pradesh from the period 1989 to 2017, were calculated using Landsat-5 TM, and Landsat-8 OLI data. Unsupervised classification and spectral water indexing methods, including the Normalized Difference Vegetation Index (NDVI), Normalized Difference Moisture Index (NDMI), Normalized Difference Water Index (NDWI), and Modified Normalized Difference Water Index (MNDWI), were used to detect and extraction of the surface water body from satellite data. Instead of all index methods, the MNDWI was performed better results. The Reservoir water area was extracted using spectral water indexing methods (NDVI, NDWI, MNDWI, and NDMI) in 1989, 1997, 2007, and 2017. The shoreline shrunk in the twenty-eight-year duration of images. The Reservoir Nagarjuna Sagar lost nearly around one-fourth of its surface water area compared to 1989. However, the Reservoir has a critical position in recent years due to changes in surface water and getting higher mud and sand. Maximum water surface area of the Reservoir will lose if such decreasing tendency follows continuously.

scholarly journals A high-resolution inland surface water body dataset for the tundra and boreal forests of North America

2021 ◽  
Author(s):  
Yijie Sui ◽  
Min Feng ◽  
Chunling Wang ◽  
Xin Li
Keyword(s):  
Surface Water ◽  
North America ◽  
Water Body ◽  
Boreal Forests ◽  
Water Bodies ◽  
Permafrost Region ◽  
Morphological Attributes ◽  
Complete Representation ◽  
Surface Water Body ◽  
Sentinel 2

Abstract. Inland surface waters are abundant in the tundra and boreal forests in North America, essential to environments and human societies but vulnerable to climate changes. These high-latitude water bodies differ greatly in their morphological and topological characteristics related to the formation, type, and vulnerability. In this paper we present an inland surface water body inventory (SWBI) dataset for the tundra and boreal forests of North America. Nearly 6.7 million water bodies were identified, with approximately 6 million (~90 %) of them smaller than 0.1 km2. The dataset provides geometry coverage and morphological attributes for every water body. During this study we developed an automated approach for detecting surface water extent and identifying water bodies in the 10 m resolution Sentinel-2 multispectral satellite data to enhance the capability for delineating small water bodies and their morphological attributes. The approach was applied to the Sentinel-2 data acquired in 2019 to produce the water body dataset for the entire tundra and boreal forests in North America, providing a more complete representation of the region than existing regional datasets, e.g., Permafrost Region Pond and Lake (PeRL). Total accuracy of the detected water extent by SWBI dataset was 96.36 % by comparing to interpreted data for locations randomly sampled across the region. Compared to the 30 m or coarser resolution water datasets, e.g., JRC GSW yearly water history, HydroLakes, and Global Lakes and Wetlands Database (GLWD), the SWBI provided an improved ability on delineating water bodies, and reported higher accuracies in the size, number, and perimeter attributes of water body by comparing to PeRL and interpreted regional dataset. This dataset is available on the National Tibetan Plateau/Third Pole Environment Data Center (TPDC, http://data.tpdc.ac.cn): DOI: 10.11888/Hydro.tpdc.271021 (Feng et al., 2020).

scholarly journals Technological Norms and Quality Objectives for Surface Waters

2015 ◽  
pp. 18
Author(s):  
Keyword(s):  
Water Quality ◽  
Surface Water ◽  
Surface Waters ◽  
Water Body ◽  
Water Bodies ◽  
Anthropogenic Factors ◽  
Resources Management ◽  
Best Available Techniques ◽  
Water Users ◽  
Surface Water Bodies

Analysis of the Russian legislation novels aimed at implementation of norms of impact upon environment at the best available techniques level applied to surface water bodies has been presented. It is noted that acting regulations do not completely secure realization of the combined approach to water resources management. In particular, there are no mechanisms to create incentives for further reduction of pollutants discharge to water bodies in case when the best available techniques do not secure attainment of water quality norms or the water body status objectives, when surface water bodies water quality norms accounting their natural and anthropogenic features stipulated by the acting Russian legislation are not yet developed. Proposals on accounting of objectives concerning the surface water body status in the process of regulating impacts upon it on the basis of technological norms and norms of permissible discharge have been made: to calculate surface water bodies water quality objective with taking into account natural and unavoidable anthropogenic factors according the proposed algorithm; when calculating norms of permissible impact to use objectives instead of water quality norms till up to development and approval of the latter (in accordance with the standing legislation); when delivering integrated environmental permissions it is necessary to take into account the norms of permissible impact but not only to observe the technological norms. The recommended procedure of obtaining an integrated environmental permission and setting of provisionally permitted discharge volume for water users discharging waste water to surface water bodies has been described. Proposals on elaboration of the legislative basis have been made.

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 Methodical Approaches to Determination of the Runoff Acceptable Irretrievable Withdrawal from Underexplored and Unexplored Rivers and Small Rivers

2015 ◽  
pp. 80
Author(s):  
Keyword(s):  
Surface Water ◽  
Human Impact ◽  
Water Body ◽  
Water Bodies ◽  
Water Withdrawal ◽  
Small Rivers ◽  
Water Runoff ◽  
Methodological Approaches ◽  
Surface Water Runoff

If the permissible impact of economic and other activities on a water body is exceeded, an irreversible degradation of the ecosystem may occur. Irretrievable water withdrawal is deemed significant human impact on water bodies. The establishment of a critical water limit for the ecosystem’s functioning and organisms’ reproduction is based on the water withdrawal limits’ assessment. The article suggests methodological approaches to defining acceptable irreversible withdrawal of surface water runoff for underexplored and unexplored rivers. It also includes a review of special features of water withdrawal from small rivers.

scholarly journals Long-Term Dynamics of Different Surface Water Body Types and Their Possible Driving Factors in China

2021 ◽  
Vol 13 (6) ◽  
pp. 1154
Author(s):  
Bowei Yu ◽  
Baoshan Cui ◽  
Yongge Zang ◽  
Chunsheng Wu ◽  
Zhonghe Zhao ◽  
...  
Keyword(s):  
Surface Water ◽  
Tibetan Plateau ◽  
Water Body ◽  
Driving Factors ◽  
Water Bodies ◽  
Human Society ◽  
Lakes And Reservoirs ◽  
Surface Water Bodies ◽  
Artificial Reservoirs

Various surface water bodies, such as rivers, lakes and reservoirs, provide water and essential services to human society. However, the long-term spatiotemporal dynamics of different types of surface water bodies and their possible driving factors over large areas remain very limited. Here, we used unprecedented surface water data layers derived from all available Landsat images and further developed two databases on China’s lakes and reservoirs larger than 1 km2 to document and understand the characteristics of changes in different water body types during 2000 to 2019 in China. Our results show that China is dominated by permanent water bodies. The areas of permanent and seasonal water bodies in China increased by 16,631.02 km2 (16.72%) and 16,994.95 km2 (25.14%), respectively, between 2000 and 2019, with permanent and seasonal water bodies exhibiting divergent spatial variations. Lakes and artificial reservoirs larger than 1 km2, which collectively represent a significant proportion of the permanent water bodies in China, displayed net increases of 6884.52 km2 (10.71%) and 4075.13 km2 (36.10%), respectively, from 2000 to 2019; these increases accounted for 41.40% and 24.50%, respectively, of the total permanent water body increment. The expanding lakes were mainly distributed on the Tibetan Plateau, whereas the rapidly growing reservoirs were mainly located on the Northeast Plain and Eastern Plain. Statistical analyses indicated that artificial reservoirs were an important factor controlling both permanent and seasonal water body changes in most of provinces. Climate factors, such as precipitation and temperature, were the main influencing factors affecting the changes in different water bodies in the sparsely populated Tibetan Plateau.

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