Satellite Image Based Mapping of Wetland Tundra Landscapes Using ILWIS GIS

• Main Author: Lemenkova, Polina
• Other Authors: Ocean University of China (OUC), Volga State University of Technology
• Format: Conference Object
• Language: English
• Published: HAL CCSD 2015
• Subjects: Remote Sensing monitoring; Remote Sensing and Geomatics; Image Processing; Image Processing Computer-Assisted; Image Processing and Computer Vision; Image Processing and Forming; Remote Sensing; Remote Sensing Data; Remote Sensing Image; Remote Sensing Image Classification; ACM: H.: Information Systems; ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION; ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.8: Scene Analysis; ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.7: Feature Measurement; ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.6: Segmentation; ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.5: Reconstruction; ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION; ACM: I.: Computing Methodologies/I.6: SIMULATION AND MODELING; ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.3: Enhancement; ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.1: Digitization and Image Capture; 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.4.10: Image Representation; [INFO]Computer Science [cs]; [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]; [SDE.BE]Environmental Sciences/Biodiversity and Ecology; [SDE.MCG]Environmental Sciences/Global Changes; [INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV]; [INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS]; [INFO.INFO-GR]Computer Science [cs]/Graphics [cs.GR]; [INFO.INFO-IA]Computer Science [cs]/Computer Aided Engineering; [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation; [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG]; [INFO.INFO-AU]Computer Science [cs]/Automatic Control Engineering; [INFO.INFO-NA]Computer Science [cs]/Numerical Analysis [cs.NA]; [INFO.INFO-MS]Computer Science [cs]/Mathematical Software [cs.MS]; [INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR]; [INFO.INFO-LO]Computer Science [cs]/Logic in Computer Science [cs.LO]; [SDU]Sciences of the Universe [physics]; [SDU.STU]Sciences of the Universe [physics]/Earth Sciences; [SDE]Environmental Sciences; [SDE.IE]Environmental Sciences/Environmental Engineering; [SDE.ES]Environmental Sciences/Environmental and Society; Arctic; Yamal Peninsula; Tundra
• Online Access: https://hal.archives-ouvertes.fr/hal-02447111

International audience Presentation shows an application of ILWIS GIS for RS data processing with a case study of detecting land cover changes during 20-year period (1988-2011) in Yamal Peninsula, Arctic. Research goals: Distribution of different types of landscapes in the wetland tundra of the Yamal Peninsula; Monitoring changes in the landscapes of tundra; Analysis of the landscape dynamics for 2 decades (1988-2011). Data include 2 satellite images: Landsat TM for 1988 and 2011. Methods include clustering, segmentation and classification. Technical approach: Landsat TM data processing by ILWIS GIS. Methods: Supervised classification of Landsat TM images. Results demonstrated changes in selected land cover types. Study area: tundra landscapes in the wetlands of the Yamal Peninsula in the Far North of Russia. Statistical results of calculations of types of vegetation cover were obtained in a semi-automatic mode in ILWIS GIS. In 1988 ’willow shrubs’ type covered 412,292 pixels from the total part of the AOI, and ’high willow’ class is 823,430 pixels. 2011: willow increased to 651427 pixels, (’willow shrubs’), and 893092 pixels (’high willows’). Both combined classes of willows, typical for AOI with a high water content, cover total 1544519 pixels, which is 40.27 %. Area of grasses decreased compared to shrub and willow. Max area covered by class ’heather and dry grass’ is 933798 pixels