Cost-Effective Raster Image Processing for Geoecological Analysis using ISOCLUST Classifier: a Case Study of Estonian Landscapes

Autor: Lemenkova, Polina
Přispěvatelé: Ocean University of China (OUC), Belarus State University (BSU), A. N. Vitchenko
Rok vydání: 2014
Předmět:
Landsat Imagery
Landsat ETM+
Land Cover Types
Raster images
ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.8: Scene Analysis/I.4.8.3: Object recognition
Landscapes
ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.8: Scene Analysis
SIG et modélisation spatiale
geography
remote sensing
[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing
Image processing Pattern recognition
Earth Science
Image processing Digital image processing
mapping
Remote sensing and GIS
ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.3: Enhancement/I.4.3.3: Registration
ComputingMilieux_MISCELLANEOUS
GIS Data Modelling
Land cover change modeling
Geodata
SIG Systèmes d'information géographique
[SDE.IE]Environmental Sciences/Environmental Engineering
ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.3: Enhancement/I.4.3.1: Geometric correction
Clustering Algorithm
[INFO.INFO-LO]Computer Science [cs]/Logic in Computer Science [cs.LO]
Unsupervised Classification
[SHS.GEO]Humanities and Social Sciences/Geography
GIS
ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.6: Segmentation/I.4.6.0: Edge and feature detection
ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.1: Digitization and Image Capture
GIS Climat Environnement Société
[INFO.INFO-GR]Computer Science [cs]/Graphics [cs.GR]
Landsat 7 ETM+
[INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV]
ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.4: Restoration
[SDE]Environmental Sciences
ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.3: Enhancement
[INFO.EIAH]Computer Science [cs]/Technology for Human Learning
ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.8: Scene Analysis/I.4.8.8: Shape
ACM: I.: Computing Methodologies
ACM: K.: Computing Milieux/K.4: COMPUTERS AND SOCIETY
Estonia
Geospatial clustering
Geospatial analysis
Baltic Sea
[SDE.MCG]Environmental Sciences/Global Changes
ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.3: Enhancement/I.4.3.0: Filtering
ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.6: Segmentation/I.4.6.2: Region growing
partitioning

[SDU.STU]Sciences of the Universe [physics]/Earth Sciences
Image Analysis
Supervised Classification
Isoclust Classification
Geospatial Information System
Clustering
ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.0: General
ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.0: General/I.4.0.1: Image processing software
Clustering Algorithms
Satellite image analysis
ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.3: Enhancement/I.4.3.5: Smoothing
ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.1: Digitization and Image Capture/I.4.1.0: Camera calibration
Clustering Analysis
Idrisi GIS
[INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG]
ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.8: Scene Analysis/I.4.8.1: Depth cues
ACM: K.: Computing Milieux/K.3: COMPUTERS AND EDUCATION
[INFO]Computer Science [cs]
cartography
ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.8: Scene Analysis/I.4.8.0: Color
[SDU.STU.GM]Sciences of the Universe [physics]/Earth Sciences/Geomorphology
[INFO.INFO-HC]Computer Science [cs]/Human-Computer Interaction [cs.HC]
ACM: K.: Computing Milieux/K.3: COMPUTERS AND EDUCATION/K.3.2: Computer and Information Science Education
Spatial Analysis
raster segmentation
ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION
[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]
Geospatial
ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.6: Segmentation/I.4.6.1: Pixel classification
Land cover and land use changes
ACM: K.: Computing Milieux/K.4: COMPUTERS AND SOCIETY/K.4.2: Social Issues
[SDE.ES]Environmental Sciences/Environmental and Society
[INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation
Geospatial data
image processing
ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.6: Segmentation
ACM: K.: Computing Milieux/K.3: COMPUTERS AND EDUCATION/K.3.1: Computer Uses in Education
GIS & Spatial Analyses
[SHS.ENVIR]Humanities and Social Sciences/Environmental studies
ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.0: General/I.4.0.0: Image displays
[INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR]
[SDE.BE]Environmental Sciences/Biodiversity and Ecology
Satellite image interpretation
satellite images
image classification
Zdroj: Modern Problems of Geoecology & Landscapes Studies
Modern Problems of Geoecology & Landscapes Studies, Belarus State University (BSU), Oct 2014, Minsk, Belarus. pp.19, ⟨10.13140/RG.2.2.10024.62722⟩
Proceedings of 5th International Research Conference, Belarus State University (BSU)
Modern Problems of Geoecology and Landscapes Studies
Modern Problems of Geoecology and Landscapes Studies, Belarus State University (BSU), Oct 2014, Minsk, Belarus. pp.74-76, ⟨10.6084/m9.figshare.7211870⟩
DOI: 10.13140/RG.2.2.10024.62722⟩
Popis: International audience; The goal of the study is to perform comparative analysis of image processing methods, enabled by means of IDRISI GIS software. The purpose has two aims. First, a spatial analysis of land cover types in the coastal landscapes of western Estonia, Pärnu area, at two various temporal dates. Second, an overview of the technical methods of IDRISI GIS enabling to evaluate image processing. The main research method consists in classification of satellite images for resulting geoecological mapping of landscapes. The ISOCLUST classification enabled to create multi-spatiotemporal thematic maps of Pärnu area. The research method is based on the spatiotemporal analysis of the geospatial data, performed by means of GIS tools and remote sensing data. The images were downloaded from the Earth Science Data Interface, Global Land Cover Facility. The Landsat TM imagery include scenes of June 2006 and June 1992. Both images cover summer months, thus enabling vegetation coverage to be easily recognized.; 74 кулонометрия) и другие методы. Большое количество часов лабораторных ра-бот (70% от общего количества часов отведенных на изучение дисциплины), позволяют студентам на практике самостоятельно изучить основные современ-ные аналитические методы. Значительное внимание уделяется радиохимиче-скому анализу природных объектов, что связано с загрязнением окружающей среды естественными и искусственными радионуклидами. Поэтому в данном курсе предусмотрены работы по изучению методов дозиметрического контро-ля. Лабораторный практикум курса «Аналитические методы в геоэкологии» представлен следующими расчетно-аналитическими занятиями:-взвешивание на весах различных типов;-методы фильтрования растворов;-титриметрический метод определения общей щелочности и карбонатной жесткости воды;-спектрофотометрический метод определения концентрации вещества;-фотометрический метод определения нитритов с использованием реак-тива Грисса;-измерение рН раствора потенциометрическим методом;-оценка радиационной обстановки в помещениях и на открытом воздухе дозиметрическими методами. В рамках освоения каждого расчетно-аналитического занятия студенты свободно ориентируются в современных методах физико-химического анализа, могут выбирать аппаратуру в соответствии с типом образца, областью примене-ния, требуемой чувствительностью и точностью, использовать методы количе-ственного определения концентрации различных веществ и применять полу-ченные знания на практике для решения различных прикладных геоэкологиче-ских проблем. The goal of the study is to perform comparative analysis of image processing methods, enabled by means of IDRISI GIS software. The purpose has two aims. First, a spatial analysis of land cover types in the coastal landscapes of western Estonia, Pärnu area, at two various temporal dates. Second, an overview of the technical methods of IDRISI GIS enabling to evaluate image processing. The main research method consists in classification of satellite images for resulting geoecological mapping of landscapes. The ISOCLUST classification enabled to create multi-spatiotemporal thematic maps of Pärnu area (fig. 1). The research method is based on the spatiotem-poral analysis of the geospatial data, performed by means of GIS tools and remote
Databáze: OpenAIRE