Project Architectures
Real-world spatial analysis case studies featuring detailed methodologies, robust dataset requirements, and scalable execution workflows.
Flood Risk Modeling
Model flood extent and risk assessment using DEM and land cover data
Required Datasets
Execution Workflow
- 1Extract river networks from DEM
- 2Calculate flood extent using slope and elevation
- 3Create flow direction and flow accumulation rasters
- 4Overlay with land cover and settlements
- 5Calculate risk index by area
- 6Generate flood risk maps
Deliverables
Flood hazard zones, risk assessment report, vulnerability maps
Land Use / Land Cover Change Detection
Analyze LULC changes over 20 years using satellite imagery classification
Required Datasets
Execution Workflow
- 1Download multi-temporal satellite imagery (2003, 2013, 2023)
- 2Pre-process: atmospheric correction, cloud masking
- 3Collect training samples for each LULC class
- 4Supervised classification using Random Forest
- 5Compare classifications between time periods
- 6Quantify changes by class (transfer matrix)
- 7Generate change detection maps
Deliverables
LULC maps for each period, change matrix, transition maps
NDVI Vegetation Health Analysis
Monitor vegetation health and seasonal changes over a year
Required Datasets
Execution Workflow
- 1Calculate NDVI from satellite bands (B8-B4)/(B8+B4)
- 2Create monthly NDVI composites
- 3Analyze temporal trends and seasonality
- 4Correlate with rainfall and temperature
- 5Identify degradation and greening areas
Deliverables
NDVI time series, seasonal profiles, vegetation health report
Urban Growth Analysis (1990-2023)
Track urban expansion and development patterns using multi-temporal imagery
Required Datasets
Execution Workflow
- 1Collect Landsat imagery for multiple epochs (1990, 2000, 2010, 2023)
- 2Classify urban vs non-urban pixels using NDBI
- 3Create time series of urban extent
- 4Calculate annual growth rates
- 5Analyze spatial patterns of expansion
- 6Correlate with population and economic data
Deliverables
Urban growth maps, expansion rate statistics, hotspot identification
Watershed Delineation & Hydrological Analysis
Delineate watersheds and analyze drainage networks from DEM
Required Datasets
Execution Workflow
- 1Fill sinks and condition DEM for hydrology
- 2Calculate flow direction (D8 algorithm)
- 3Calculate flow accumulation
- 4Define pour points and watershed boundaries
- 5Extract and order stream networks (Strahler order)
- 6Calculate morphometric parameters (shape, relief ratio)
Deliverables
Watershed boundaries, stream networks, morphometric analysis
Vegetation Index & Classification
Classify vegetation types using spectral indices and machine learning
Required Datasets
Execution Workflow
- 1Calculate spectral indices (NDVI, NDBI, NDWI, EVI, SAVI)
- 2Prepare training and validation datasets
- 3Create multi-band classification features
- 4Train Random Forest/SVM classifier
- 5Validate with confusion matrix and kappa coefficient
- 6Generate vegetation type map
Deliverables
Vegetation classification map, accuracy report, species distribution
Urban Heat Island Analysis
Map and quantify urban heat island effect using thermal satellite data
Required Datasets
Execution Workflow
- 1Download and process Landsat thermal bands
- 2Calculate Land Surface Temperature (LST)
- 3Create urban heat island intensity maps
- 4Compare LST across LULC types
- 5Correlate with green cover and built-up density
- 6Identify mitigation areas
Deliverables
LST maps, UHI intensity maps, hotspot analysis, greening recommendations
Soil Erosion Risk Assessment (RUSLE)
Estimate soil erosion risk using the RUSLE model in a GIS environment
Required Datasets
Execution Workflow
- 1Calculate rainfall erosivity factor (R) from station data
- 2Derive soil erodibility factor (K) from soil map
- 3Compute slope length and steepness (LS) from DEM
- 4Determine cover management factor (C) from NDVI
- 5Assign support practice factor (P)
- 6Calculate RUSLE: A = R × K × LS × C × P
- 7Classify erosion risk zones
Deliverables
Soil erosion risk map, factor maps, priority conservation areas
Transportation Network Analysis
Analyze road networks for accessibility, shortest path, and service areas
Required Datasets
Execution Workflow
- 1Download and clean OSM road network data
- 2Build network topology in QGIS
- 3Calculate shortest paths between locations
- 4Generate service area polygons (isochrones)
- 5Identify underserved populations
- 6Create accessibility maps and dashboards
Deliverables
Accessibility maps, service area analysis, equity assessment
Earthquake Damage Assessment
Rapid damage assessment using pre/post-disaster satellite imagery
Required Datasets
Execution Workflow
- 1Collect pre and post-event imagery
- 2Apply change detection algorithms
- 3Calculate damage proxy maps from SAR coherence
- 4Classify damage severity levels
- 5Overlay with population and infrastructure data
- 6Generate rapid assessment reports
Deliverables
Damage extent maps, affected population estimates, response priority zones