Sökning: "Supervised Object-Based Land Cover Classification"

Hittade 4 uppsatser innehållade orden Supervised Object-Based Land Cover Classification.

1. 1. Feature Extraction and FeatureSelection for Object-based LandCover Classification : Optimisation of Support Vector Machines in aCloud Computing Environment

   Master-uppsats, KTH/Geoinformatik

   Författare :Oliver Stromann; [2018]
   Nyckelord :Feature Extraction; Feature Selection; Dimensionality Reduction; Supervised Object-Based Land Cover Classification; Google Earth Engine;

   Sammanfattning : Mapping the Earth’s surface and its rapid changes with remotely sensed data is a crucial tool to un-derstand the impact of an increasingly urban world population on the environment. However, the impressive amount of freely available Copernicus data is only marginally exploited in common clas-sifications. LÄS MER

3. 2. Urban classification by pixel and object-based approaches for very high resolution imagery

   Magister-uppsats, Högskolan i Gävle/Samhällsbyggnad, GIS

   Författare :Fadi Ali; [2015]
   Nyckelord :Ancillary data; land use land cover classification; supervised algorithms; GIS; Remote sensing; OBIA;

   Sammanfattning : Recently, there is a tremendous amount of high resolution imagery that wasn’t available years ago, mainly because of the advancement of the technology in capturing such images. Most of the very high resolution (VHR) imagery comes in three bands only the red, green and blue (RGB), whereas, the importance of using such imagery in remote sensing studies has been only considered lately, despite that, there are no enough studies examining the usefulness of these imagery in urban applications. LÄS MER

4. 3. Object-Based Classification of Vegetation at Stordalen Mire near Abisko by using High-Resolution Aerial Imagery

   Master-uppsats, Lunds universitet/Institutionen för naturgeografi och ekosystemvetenskap

   Författare :Marco Giljum; [2014]
   Nyckelord :Physical Geography and Ecosystem Analysis; Object-Based Image Analysis; OBIA; Vegetation Classification; Permafrost; Arctic Peatland; Remote Sensing; Aerial Photography; Environmental Monitoring; Landscape Analysis; Earth and Environmental Sciences;

   Sammanfattning : The focus of this work is to investigate and apply the remote sensing method of object-based image analysis (OBIA) for vegetation classification of a permafrost underlain peatland in sub-arctic Sweden, by using aerial imagery of high resolution. Since the northern landscapes are an important source of naturally stored CH4 and CO2, their contribution to the global carbon cycle is a focus in research about climate change and the global methane exchange. LÄS MER

5. 4. Radar and Optical Data Fusion for Object Based Urban Land Cover Mapping

   Master-uppsats, KTH/Geodesi och geoinformatik

   Författare :Alexander Jacob; [2011]
   Nyckelord :Data Fusion; Image Segmentation; Object based Mapping; Urban Land Cover; SAR; Radar; Multispectral; Region growing and merging;

   Sammanfattning : The creation and classification of segments for object based urban land cover mapping is the key goal of this master thesis. An algorithm based on region growing and merging was developed, implemented and tested. The synergy effects of a fused data set of SAR and optical imagery were evaluated based on the classification results. LÄS MER