FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W3201218645> ?p ?o ?g. }

• W3201218645 endingPage "3745" @default.
• W3201218645 startingPage "3745" @default.
• W3201218645 abstract "The knowledge of water surface changes provides invaluable information for water resources management and flood monitoring. However, the accurate identification of water bodies is a long-term challenge due to human activities and climate change. Sentinel-1 synthetic aperture radar (SAR) data have been drawn, increasing attention to water extraction due to the availability of weather conditions, water sensitivity and high spatial and temporal resolutions. This study investigated the abilities of random forest (RF), Extreme Gradient Boosting (XGB) and support vector machine (SVM) methods to identify water bodies using Sentinel-1 imageries in the upper stream of the Yangtze River, China. Three sets of hyper-parameters including default values, optimized by grid searches and genetic algorithms, were examined for each model. Model performances were evaluated using a Sentinel-1 image of the developed site and the transfer site. The results showed that SVM outperformed RF and XGB under the three scenarios on both the validated and transfer sites. Among them, SVM optimized by genetic algorithm obtained the best accuracy with precisions of 0.9917 and 0.985, kappa statistics of 0.9833 and 0.97, F1-scores of 0.9919 and 0.9848 on validated and transfer sites, respectively. The best model was then used to identify the dynamic changes in water surfaces during the 2020 flood season in the study area. Overall, the study further demonstrated that SVM optimized using a genetic algorithm was a suitable method for monitoring water surface changes with a Sentinel-1 dataset." @default.
• W3201218645 created "2021-09-27" @default.
• W3201218645 creator A5000394846 @default.
• W3201218645 creator A5002596243 @default.
• W3201218645 creator A5019837427 @default.
• W3201218645 creator A5056183335 @default.
• W3201218645 creator A5090359316 @default.
• W3201218645 date "2021-09-18" @default.
• W3201218645 modified "2023-10-05" @default.
• W3201218645 title "Identifying Dynamic Changes in Water Surface Using Sentinel-1 Data Based on Genetic Algorithm and Machine Learning Techniques" @default.
• W3201218645 cites W1965895350 @default.
• W3201218645 cites W1975723678 @default.
• W3201218645 cites W1976087358 @default.
• W3201218645 cites W1979346804 @default.
• W3201218645 cites W1983822806 @default.
• W3201218645 cites W1997091620 @default.
• W3201218645 cites W1997998124 @default.
• W3201218645 cites W1998361807 @default.
• W3201218645 cites W2008055840 @default.
• W3201218645 cites W2029342456 @default.
• W3201218645 cites W2030336455 @default.
• W3201218645 cites W2038490935 @default.
• W3201218645 cites W2042315239 @default.
• W3201218645 cites W2047094503 @default.
• W3201218645 cites W2055668893 @default.
• W3201218645 cites W2085881988 @default.
• W3201218645 cites W2106129499 @default.
• W3201218645 cites W2125124513 @default.
• W3201218645 cites W2128158766 @default.
• W3201218645 cites W2134242644 @default.
• W3201218645 cites W2150961384 @default.
• W3201218645 cites W2159641772 @default.
• W3201218645 cites W2170940461 @default.
• W3201218645 cites W2174009612 @default.
• W3201218645 cites W2309165934 @default.
• W3201218645 cites W2312997001 @default.
• W3201218645 cites W2323760123 @default.
• W3201218645 cites W2330780237 @default.
• W3201218645 cites W2519338473 @default.
• W3201218645 cites W2529064413 @default.
• W3201218645 cites W2757713658 @default.
• W3201218645 cites W2792236667 @default.
• W3201218645 cites W2792652690 @default.
• W3201218645 cites W2800522401 @default.
• W3201218645 cites W2801420917 @default.
• W3201218645 cites W2808374792 @default.
• W3201218645 cites W2834916931 @default.
• W3201218645 cites W2887176733 @default.
• W3201218645 cites W2898533303 @default.
• W3201218645 cites W2900225740 @default.
• W3201218645 cites W2904122576 @default.
• W3201218645 cites W2910531141 @default.
• W3201218645 cites W2917249005 @default.
• W3201218645 cites W2941817696 @default.
• W3201218645 cites W2943197862 @default.
• W3201218645 cites W2945829261 @default.
• W3201218645 cites W2947750131 @default.
• W3201218645 cites W2951792693 @default.
• W3201218645 cites W2955754719 @default.
• W3201218645 cites W2955914832 @default.
• W3201218645 cites W2961681376 @default.
• W3201218645 cites W2973233981 @default.
• W3201218645 cites W2976601562 @default.
• W3201218645 cites W2996388350 @default.
• W3201218645 cites W3028081629 @default.
• W3201218645 cites W3080179817 @default.
• W3201218645 cites W3080628220 @default.
• W3201218645 cites W3094171127 @default.
• W3201218645 cites W3097170121 @default.
• W3201218645 cites W3097726034 @default.
• W3201218645 cites W3102283426 @default.
• W3201218645 cites W3134654044 @default.
• W3201218645 cites W3150837961 @default.
• W3201218645 cites W3155756093 @default.
• W3201218645 cites W3159623433 @default.
• W3201218645 cites W3164646400 @default.
• W3201218645 cites W4245214580 @default.
• W3201218645 cites W1994492082 @default.
• W3201218645 doi "https://doi.org/10.3390/rs13183745" @default.
• W3201218645 hasPublicationYear "2021" @default.
• W3201218645 type Work @default.
• W3201218645 sameAs 3201218645 @default.
• W3201218645 citedByCount "7" @default.
• W3201218645 countsByYear W32012186452022 @default.
• W3201218645 countsByYear W32012186452023 @default.
• W3201218645 crossrefType "journal-article" @default.
• W3201218645 hasAuthorship W3201218645A5000394846 @default.
• W3201218645 hasAuthorship W3201218645A5002596243 @default.
• W3201218645 hasAuthorship W3201218645A5019837427 @default.
• W3201218645 hasAuthorship W3201218645A5056183335 @default.
• W3201218645 hasAuthorship W3201218645A5090359316 @default.
• W3201218645 hasBestOaLocation W32012186451 @default.
• W3201218645 hasConcept C11413529 @default.
• W3201218645 hasConcept C119857082 @default.
• W3201218645 hasConcept C12267149 @default.
• W3201218645 hasConcept C124101348 @default.
• W3201218645 hasConcept C127313418 @default.
• W3201218645 hasConcept C154945302 @default.

• next