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Harmonizing Earth Observation Data for Enhanced Spatial Analysis

  • Book

  • November 2026
  • Elsevier Science and Technology
  • ID: 6251537
Harmonizing Earth Observation Data for Enhanced Spatial Analysis explores the critical aspects of Earth observation (EO) data and its pivotal role in spatial analysis. The book begins by addressing the quality aspects of EO data, emphasizing the importance of reliable and accurate information for meaningful analysis. It reviews the interaction and integration of various EO datasets, highlighting the necessity of combining diverse data sources to enhance analytical outcomes. The text covers essential techniques such as downsampling, generalization, and upsampling, providing insights into how these processes can optimize data usability while maintaining integrity. A significant focus is placed on harmonization, detailing strategies to reduce uncertainty and improve data consistency across multidimensional datasets. This harmonization is crucial for effective spatial analysis, which relies on coherent datasets to derive actionable insights. Additionally, the book discusses the interplay between EO and geospatial data, illustrating how their integration can enhance spatial analysis capabilities. It presents comprehensive workflows and tools that facilitate advanced spatial analysis, equipping researchers and practitioners with the necessary resources to harness EO data effectively. The book serves as a valuable resource to emphasize the importance of high-quality, integrated datasets in fostering informed decision-making and advancing research in environmental monitoring, urban planning, and resource management.

Table of Contents

1. Earth Observation Data Quality Aspects
2. Interaction and Integration of Earth Observation Data
3. EO Data Downsampling, Generalization, and Upsampling
4. Cut Down Uncertainty Through Harmonization of EO Data
5. Multidimensional EO Data Harmonization
6. EO and Geospatial Data for Spatial Analysis
7. Comprehensive Workflows and Tools for Advanced Spatial Analysis of EO Data

Authors

Tomaz Podobnikar Faculty of Information Studies in Novo Mesto, Slovenia.

Tomaz Podobnikar is a geospatial information expert, currently work as lecturer at Faculty of Information Studies, and as undersecretary at Ministry of Spatial Planning, both Slovenia. He has experience in the areas of geospatial, environmental, natural and social sciences, EO, hazard and risk management, etc. from academic, governmental, international and consulting organizations. Career highlights include fieldwork in ecological, archaeological, anthropological and geomorphological mapping, geodetic survey and humanitarian, in resource-limited settings. Documented methods: [1] spatial data integration/conflation with semantic enrichment to reduce the cost of DEM up to 25-times, realized for the National DEM and implemented into the EU and Google Earth models; [2] geomorphometry based index for feature detection and recognition, used in the Esri World Topographic Map; [3] methodology to process geospatial data with special tools to make them 'analytics ready', realized for the spatial data infrastructure. Awarded with over 25 competitive grants including Skolkovo Innovation Center and Fulbright.