Sökning: "Spatial mapping"

Visar resultat 1 - 5 av 220 uppsatser innehållade orden Spatial mapping.

1. 1. The Sound of Skepticism Analyzing Climate Change Denial in Swedish Podcasts and YouTube Channels

   Kandidat-uppsats, Göteborgs universitet / / Institutionen för sociologi och arbetsvetenskap

   Författare :Victoria Vallström; [2024-02-14]
   Nyckelord :denialism; climate skepticism; social movements; countermovements; digital media; digital data; computational grounded theory; topic modeling; computational text analysis;

   Sammanfattning : This study explores Sweden's climate change denial by analyzing the spoken-word discourse of its countermovement, focusing on digital media content from Swedish parliament member Elsa Widding with an aim to provide empirical insights into the discourse of Sweden's Climate Change Countermovement (CCCM). Questions guiding this study are: What are the most prevalent topics and themes related to climate change denial and skepticism? How do they align with established categories of climate change denial, shaping the overall narrative? What mobilizing ideas and meanings are present, how are they shaped, and how do they contribute to the movement's goals? The material consists of Elsa Widding's complete audio-based "movement texts'' from 2019-2023, including YouTube content, podcasts, and appearances on Riks, totaling over 2000 minutes of audio transcribed into text via AI technology. LÄS MER

3. 2. Potential and Limitations of the Sketch Map Tool in the International Red Cross Red Crescent Movement

   Master-uppsats, Lunds universitet/Avdelningen för Riskhantering och Samhällssäkerhet

   Författare :Kimon Letzner; [2024]
   Nyckelord :Disaster risk reduction; Participatory action research; Community risk mapping; International Red Cross Red Crescent Movement; Colombia; Technology and Engineering;

   Sammanfattning : In disaster risk management, participatory mapping (PM) closes spatial data gaps in communities by integrating local risk knowledge. The thesis examined the potential and limitations of the Sketch Map Tool (SMT) as a PM tool for community-based disaster risk reduction (DRR) through an International Red Cross Red Crescent Movement case study. LÄS MER

4. 3. Automatic Semantic Segmentation of Indoor Datasets

   Master-uppsats, Blekinge Tekniska Högskola/Institutionen för datavetenskap

   Författare :Sai Swaroop Rachakonda; [2024]
   Nyckelord :Semantic Segmentation; Annotation; SLAM; Indoor datasets; YOLO V8; DETIC; Segment Anything Model.;

   Sammanfattning : Background: In recent years, computer vision has undergone significant advancements, revolutionizing fields such as robotics, augmented reality, and autonomoussystems. Key to this transformation is Simultaneous Localization and Mapping(SLAM), a fundamental technology that allows machines to navigate and interactintelligently with their surroundings. LÄS MER

5. 4. Exploring patterns in risk factors for bark beetle attack during outbreaks triggered by drought stress with harvester data on attacked trees: A case study in Southeastern Sweden

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

   Författare :Nikolaos Kouskoulis; [2023]
   Nyckelord :Geography; GIS; Geographic Information Science; Forest ecosystems; Bark beetle outbreak; Southeastern Sweden; Predisposing factors; Triggering factors; Drought stress; Earth and Environmental Sciences;

   Sammanfattning : ABSTRACT Raising temperatures and climate variability have intensified extreme weather events worldwide. These extremes can enhance and trigger possible pest outbreaks. Bark beetle attacks have become a major concern in regions with extensive spruce forest areas. Southeastern Sweden has faced repeated outbreaks resulting in widespread tree loss. LÄS MER

7. 5. Deep Learning-Based Depth Estimation Models with Monocular SLAM : Impacts of Pure Rotational Movements on Scale Drift and Robustness

   Master-uppsats, Linköpings universitet/Datorseende

   Författare :Daniel Bladh; [2023]
   Nyckelord :Deep Learning; Computer Vision; Monocular; SLAM; Depth Estimation;

   Sammanfattning : This thesis explores the integration of deep learning-based depth estimation models with the ORB-SLAM3 framework to address challenges in monocular Simultaneous Localization and Mapping (SLAM), particularly focusing on pure rotational movements. The study investigates the viability of using pre-trained generic depth estimation networks, and hybrid combinations of these networks, to replace traditional depth sensors and improve scale accuracy in SLAM systems. LÄS MER