FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2000743281> ?p ?o ?g. }

• W2000743281 abstract "Urban green space plays an important and positive role in global carbon cycle, and it is very important for improving the ecological environment of the city, reducing the urban heat island effect, promoting the harmonious relationship between human and nature. In order to overcome the disadvantages of the existing method to extract green space information and solve the problem that consume much time and labor when changing detection of urban green space, and that is difficult to be monitored as well. This paper takes Xi'an urban green space as the researching object, using the LANDSAT TM satellite images, and making use of decision tree classifier based on simple rules and the classification method of support vector machine (SVM) respectively to extract the urban green space information and evaluate its accuracy. Then, the paper proposes to apply the fuzzy C-means method (FCM) into the extraction of green space to solve the problems of the mixed pixel, which exist in green space information extraction of the TM image, for example, the important green information of discrete green belt and street trees that are in the area less than 30 meters, cannot be extracted by the hard classification method. The introduced algorithm can calculate the fuzzy subjected value of the pixel in each classification category, and then automatically classify it as class subjected value, which is good to improve the classification accuracy. The research results show that: (1) compared to the decision tree classification method which is based on the simple rules, the classification accuracy of SVM increased by about 15%. However, the extraction of small area of green space information is still incomplete, such as the information of the green belt and street trees; (2) using the FCM algorithm could do a more refined and accurate classification result into different categories of subjected according to the pixel. Small area of green space information can be extracted first-rate and the classification accuracy is improved well. The proposed algorithm can solve the problem of mixed pixel in the green information extraction; (3) the dynamic monitoring results show that from 1995 to 2010, the green space of Xi'an city is significantly reduced, so the urban ecological construction is an urgent need." @default.
• W2000743281 created "2016-06-24" @default.
• W2000743281 creator A5044603028 @default.
• W2000743281 creator A5056366615 @default.
• W2000743281 creator A5057253985 @default.
• W2000743281 creator A5062980466 @default.
• W2000743281 creator A5088404682 @default.
• W2000743281 date "2012-08-01" @default.
• W2000743281 modified "2023-10-18" @default.
• W2000743281 title "Study on urban green space extracting and dynamic monitoring method" @default.
• W2000743281 cites W2114527611 @default.
• W2000743281 cites W2121524395 @default.
• W2000743281 cites W2123384846 @default.
• W2000743281 cites W2148603752 @default.
• W2000743281 cites W2390630311 @default.
• W2000743281 cites W2391508643 @default.
• W2000743281 doi "https://doi.org/10.1109/agro-geoinformatics.2012.6311601" @default.
• W2000743281 hasPublicationYear "2012" @default.
• W2000743281 type Work @default.
• W2000743281 sameAs 2000743281 @default.
• W2000743281 citedByCount "1" @default.
• W2000743281 countsByYear W20007432812021 @default.
• W2000743281 crossrefType "proceedings-article" @default.
• W2000743281 hasAuthorship W2000743281A5044603028 @default.
• W2000743281 hasAuthorship W2000743281A5056366615 @default.
• W2000743281 hasAuthorship W2000743281A5057253985 @default.
• W2000743281 hasAuthorship W2000743281A5062980466 @default.
• W2000743281 hasAuthorship W2000743281A5088404682 @default.
• W2000743281 hasConcept C111919701 @default.
• W2000743281 hasConcept C12267149 @default.
• W2000743281 hasConcept C124101348 @default.
• W2000743281 hasConcept C153180895 @default.
• W2000743281 hasConcept C154945302 @default.
• W2000743281 hasConcept C160633673 @default.
• W2000743281 hasConcept C2778572836 @default.
• W2000743281 hasConcept C2992075096 @default.
• W2000743281 hasConcept C41008148 @default.
• W2000743281 hasConcept C5481197 @default.
• W2000743281 hasConcept C58166 @default.
• W2000743281 hasConcept C84525736 @default.
• W2000743281 hasConcept C95623464 @default.
• W2000743281 hasConceptScore W2000743281C111919701 @default.
• W2000743281 hasConceptScore W2000743281C12267149 @default.
• W2000743281 hasConceptScore W2000743281C124101348 @default.
• W2000743281 hasConceptScore W2000743281C153180895 @default.
• W2000743281 hasConceptScore W2000743281C154945302 @default.
• W2000743281 hasConceptScore W2000743281C160633673 @default.
• W2000743281 hasConceptScore W2000743281C2778572836 @default.
• W2000743281 hasConceptScore W2000743281C2992075096 @default.
• W2000743281 hasConceptScore W2000743281C41008148 @default.
• W2000743281 hasConceptScore W2000743281C5481197 @default.
• W2000743281 hasConceptScore W2000743281C58166 @default.
• W2000743281 hasConceptScore W2000743281C84525736 @default.
• W2000743281 hasConceptScore W2000743281C95623464 @default.
• W2000743281 hasLocation W20007432811 @default.
• W2000743281 hasOpenAccess W2000743281 @default.
• W2000743281 hasPrimaryLocation W20007432811 @default.
• W2000743281 hasRelatedWork W1509061665 @default.
• W2000743281 hasRelatedWork W2041636156 @default.
• W2000743281 hasRelatedWork W2160451891 @default.
• W2000743281 hasRelatedWork W2188760412 @default.
• W2000743281 hasRelatedWork W2348097614 @default.
• W2000743281 hasRelatedWork W2387129993 @default.
• W2000743281 hasRelatedWork W2899635179 @default.
• W2000743281 hasRelatedWork W3043252291 @default.
• W2000743281 hasRelatedWork W3207273312 @default.
• W2000743281 hasRelatedWork W4242764575 @default.
• W2000743281 isParatext "false" @default.
• W2000743281 isRetracted "false" @default.
• W2000743281 magId "2000743281" @default.
• W2000743281 workType "article" @default.