Data Analysis & Forecasting
Understand data. Identify trends. Assess the future with confidence. Statistical analysis, geostatistics, and AI-supported methods to enable informed decision-making in environmental management, water resources, and infrastructure.
Why Data Analysis?
The analysis of complex environmental and geospatial data provides the basis for reliable decision-making. The GeoData Competence Center combines classical statistical methods with modern approaches in geostatistics, machine learning, and artificial intelligence to detect patterns, identify relationships, and reliably forecast future developments.
Our Services
Statistical Data Analysis
- Descriptive and Exploratory Data Analysis
- Regression and Correlation Analyses
- Hypothesis Testing
- Time Series Analysis
Geostatistics
- Variogram Analysis
- Kriging
- Spatial Data Interpolation
- Uncertainty Analysis
- Fuzzy Logic Analysis
AI-Powered Analysis
- Artificial Neural Networks
- Random Forest
- Self-Organizing Maps (SOMs)
- Clustering and Classification
Multivariate Statistics
- Principal Component Analysis (PCA)
- Factor Analysis
- Cluster Analysis
- Discriminant Analysis
Forecasting Models
- Trend Analysis
- Scenario Analysis
- Risk Assessment
- Predictive Models
Data Visualization
- Interactive Dashboards
- Charts
- Map-Based Analysis
- Data-Storytelling
- Automated Reports
Areas of application
- Water Management – Analysis of groundwater levels, water quality data, and hydrochemical time series to identify long-term trends.
- Environmental Monitoring – Statistical analysis of extensive monitoring programs and identification of trends, anomalies, and spatial patterns.
- Industry and Contaminated Sites – Evaluation of complex measurement datasets for risk assessment, monitoring the effectiveness of remediation measures, and optimizing monitoring programs.
- Agriculture – Analysis of soil, vegetation, and remote sensing data to develop site-specific management strategies.
- Research and Public Authorities – Preparation and analysis of large datasets for environmental reports, scientific studies, and approval and planning procedures.
- Digitalization & Smart Monitoring – Automated analysis of large datasets and development of intelligent data evaluation and early warning systems.
Methods & Software
- Regression Analysis
- Time Series Analysis
- Principal Component Analysis
- Factor Analysis
- Cluster Analysis
- Random Forest
- Self-Organizing Maps (SOMs)
- Python
- R-Statistic
- ArcGIS Pro
- QGIS
- Jupyter Notebook
- PostgreSQL / PostGIS
Why a GeoData Competence Centre?
- Combination of Statistics, Geostatistics, and AI
- Scientifically sound data analysis
- Reproducible and transparent Analyses
- Practical forecasting models
- Customized solutions for complex datasets
- Modern Open-Source and commercial coftware