Lectures related to Acquisition of Primary Data

Data Acquisition Methods

Reviews methods for acquiring primary data and suggests further exploration.

Acquisition de données primaires: Positioning and Thematic Data

Covers primary data acquisition methods in GIS, including positioning and thematic data techniques.

Google Earth Engine: Analyzing Geospatial Data

Introduces Google Earth Engine, focusing on its capabilities for geospatial analysis and environmental monitoring.

Data Wrangling with Hive: Managing Big Data Efficiently

Covers data wrangling techniques using Apache Hive for efficient big data management.

Bush fires in the Sahelian area

Explores the causes and consequences of bush fires in the Sahelian area, emphasizing the role of Geographic Information Systems.

Wildfires in Sahel: Case Study

Covers the role of GIS in managing wildfires in the Sahel region.

Imaging Techniques: Geometric and Radiometric Distortions

Discusses imaging techniques, focusing on geometric and radiometric distortions in aerial photography and their implications for data interpretation.

Big Data Best Practices and Guidelines

Covers best practices and guidelines for big data, including data lakes, architecture, challenges, and technologies like Hadoop and Hive.

Geospatial Data Sources

Covers geospatial data sources, including geoservers, satellite imagery, and virtual globes.

Stockage et transmission des données 1: introduction; besoin de structure

Discusses the importance of structuring data for efficient storage and retrieval.

Data Analysis to AI and ML, Social Media

Explores the evolution from data analysis to AI and ML, emphasizing big data, machine learning, and social media interaction.

Big Data Ecosystems: Technologies and Challenges

Covers the fundamentals of big data ecosystems, focusing on technologies, challenges, and practical exercises with Hadoop's HDFS.

Storage of geographic information

Covers the storage of geographic information using vector and grid formats, coordinate reference systems, and image formats.

Satellite Location: Reflection Surface Analysis

Explores satellite reflection surface analysis for precise positioning and its implications for tsunami prediction.

General Introduction to Big Data

Covers data science tools, Hadoop, Spark, data lake ecosystems, CAP theorem, batch vs. stream processing, HDFS, Hive, Parquet, ORC, and MapReduce architecture.

In Silico Neuroscience: Data Reproducibility and Reusability

Emphasizes data reproducibility and reusability in in silico neuroscience, focusing on neuroinformatics tools and methods.

Introduction to Data: Data Types and Quality

Covers data types, quantity, quality, and representativeness in the world of data.

Cache Memory

Explores cache memory design, hits, misses, and eviction policies in computer systems, emphasizing spatial and temporal locality.

Derived Variables 2: Applications and Analysis

Covers thematic variables derived from DEMs and their applications in GIS.

Data, big data, clouds and IoT

Explores data representation, databases, cloud computing, and challenges in the cloud environment.