Linking GIS and Remote Sensing Data to Study Vegetation Patterns

• Main Author: Lemenkova, Polina
• Other Authors: Ocean University of China (OUC), Kazan National Research Technical University n.a. A.N. Tupolev KNITU-KAI, O. Y. Gerasimova, E. L. Gunicheva, G. S. Mullagayanova
• Format: Conference Object
• Language: English
• Published: HAL CCSD 2015
• Subjects: Landsat TM and ETM data; Image classification; Satellite image interpretation; Spatial analysis; Spatial analysis statistics; GIS Analysis; SIG Systèmes d'information géographique; SIG et aménagement; SIG et modélisation spatiale; [SCCO]Cognitive science; [SCCO.COMP]Cognitive science/Computer science; [INFO.INFO-HC]Computer Science [cs]/Human-Computer Interaction [cs.HC]; [SHS.GEO]Humanities and Social Sciences/Geography; [SHS]Humanities and Social Sciences; [SHS.ENVIR]Humanities and Social Sciences/Environmental studies; [SDE]Environmental Sciences; [SDE.MCG]Environmental Sciences/Global Changes; [SDE.BE]Environmental Sciences/Biodiversity and Ecology; [STAT]Statistics [stat]; [STAT.CO]Statistics [stat]/Computation [stat.CO]; [STAT.ML]Statistics [stat]/Machine Learning [stat.ML]; [INFO]Computer Science [cs]; [INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV]; [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing; [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG]; [INFO.INFO-IU]Computer Science [cs]/Ubiquitous Computing; [INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR]; [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]; [INFO.INFO-CY]Computer Science [cs]/Computers and Society [cs.CY]; Arctic; Bovanenkovo; Yamal Peninsula; Tundra
• Online Access: https://hal.archives-ouvertes.fr/hal-01986732; https://hal.archives-ouvertes.fr/hal-01986732/document; https://hal.archives-ouvertes.fr/hal-01986732/file/Lemenkova_Naberezhniye_Chelny.pdf; https://doi.org/10.6084/m9.figshare.7210388

International audience The paper studies changes in land cover types in tundra landscapes during the past two decades. The study area is located in the Yamal Peninsula, north-central Russia. The main objective of this research is to analyse changes in vegetation distribution and land cover types over the area of Yamal Peninsula. Methodology of the work aims at technical application of the remote sensing and GIS tools for studies and includes georeferencing, creation of color composites, supervised classification. The research data includes Landsat scenes. The research method consists in Landsat image processing (Fig.1), georeferencing via the Google Earth and spatial analysis performed in ILIWIS GIS. The choice of Landsat scenes for land cover mapping is explained by their well-known advantages of application in geosciences and cartography. The final outcomes show changes in the vegetation coverage and land cover classes in Bovanenkovo region of the Yamal Peninsula, which happened during the past two decades. The results are received by comparing and analyzing of two classified maps covering the same geographic region with time span of 23 years: in 1988 and 2011. The changes mostly concern types of land covers and overall increase of shrubland and willows. It can be explained by the complex environmental changes in Arctic regions, which leads to ―greenness‖ processes, or unnatural increase of willows.