Master ArcGIS, QGIS, Python for GIS and Google Earth Engine through real Kannur case studies — from local rivers and wetlands to coastal and forest landscapes.
From the Valapattanam River delta and Dharmadam Island’s tidal beaches to the Aralam forest belt in the Western Ghats foothills, Kannur’s handloom towns and military cantonment sit within one of north Kerala’s most diverse coast-to-forest landscapes. Space Borne’s Kannur-focused Remote Sensing & GIS course uses this landscape as a live case study, teaching you to map, classify, and analyze real natural resources instead of generic textbook data.
Download and process Landsat 8/9 and Sentinel-2 imagery covering Kannur’s coast and Western Ghats foothills; learn band combinations and spectral indices (NDVI, NDWI, NDBI).
Classify Land Use / Land Cover from Kannur’s beaches to the Aralam forest fringe — built-up, forest, river, and coastal classes — using supervised classification in QGIS & ArcGIS.
Build interactive web maps using Leaflet.js to publish Kannur’s natural resource layers online — exactly like the live map below.
Take a single focused course or combine several into our Full-Stack capstone track. Every program below is taught using Kannur’s own geography as the working dataset.
Master the leading open-source GIS platform — vector & raster analysis, geoprocessing, cartographic layout, and plugin-based workflows.
Industry-standard ArcMap workflows: geodatabases, spatial joins, interpolation, network analysis, and professional map production.
Modern ArcGIS Pro 3D scenes, model builder automation, image analysis, and enterprise geodatabase management.
Automate repetitive GIS tasks using ArcPy & PyQGIS, build custom geoprocessing scripts, and batch-process spatial data.
Cloud-based time-series analysis of satellite archives — large-area LULC, change detection, and climate datasets without local storage limits.
Electromagnetic spectrum, sensor types, Landsat/Sentinel image correction, classification, and spectral index (NDVI/NDWI/NDBI) workflows.
Build and publish interactive Leaflet.js / web maps so your spatial layers can be shared and explored online — like the live map on this page.
Apply machine learning and deep learning models to satellite imagery for automated feature extraction and predictive spatial analytics.
Our combined flagship track — QGIS + ArcGIS + Python + GEE + Web GIS — culminating in an end-to-end mapping project for your own study area.
From the Valapattanam River delta and Dharmadam Island’s tidal beaches to the Aralam forest belt in the Western Ghats foothills, Kannur’s handloom towns and military cantonment sit within one of north Kerala’s most diverse coast-to-forest landscapes. Course modules use the following resource zones for hands-on mapping exercises:
North Kerala’s longest river system mapped for sediment transport and seasonal flow-change analysis.
Tidal-island and shoreline-erosion zone studied through multi-date satellite imagery and change detection.
Western Ghats foothill forest reserve analyzed for forest-cover and biodiversity monitoring.
Handloom-town and cantonment growth corridor mapped for built-up expansion studies.
Irrigation reservoir and its agricultural command area used for water-spread and crop-cycle mapping.
Coastal fishing-harbour ecosystem classified using NDVI & NDWI composites for ecosystem-health study.
This interactive Leaflet.js map marks key natural resource zones around Kannur that students explore during the course. Click each marker for context.
Base map © OpenStreetMap contributors. Markers indicate illustrative locations of natural resource zones used in coursework.
Kerala has several GIS training providers — here’s what genuinely sets Space Borne apart for learners in Kannur.
A formally certified institute, not an unregistered tuition center — your certificate carries genuine institutional backing.
Every LULC and NDVI map you see on this page is a genuine classified output produced by Space Borne — not a stock mock-up.
Learn from trainers who have worked on live mapping, environmental monitoring, and GIS consultancy projects, not just textbook theory.
You build a complete capstone project on a study area of your choice — a portfolio piece you can show employers, not just a certificate.
Weekend and evening batch options so students, researchers, and full-time employees can all complete the course without conflict.
Trainers remain reachable on WhatsApp through the course and beyond, instead of disappearing once the batch ends.
Course content is mapped to real GIS/RS job requirements in government agencies, consultancies, and the NewSpace/GeoAI industry.
No hidden software-license upsells or surprise add-on fees — what you’re quoted is what you pay.
Geospatial skills are in growing demand across government, research, and private-sector roles connected to Kannur’s economy, including Kannur Cantonment infrastructure projects, handloom & fisheries cooperatives, Western Ghats forest divisions, and district planning offices. Entry-level GIS/RS roles typically start as junior analyst or GIS executive positions, with strong growth in pay and responsibility as you add ArcGIS Pro, Python automation, and Google Earth Engine skills to your profile — exactly the stack covered in this course.
State remote sensing centres, forest and irrigation departments, disaster management authorities, and urban planning bodies regularly hire GIS-trained staff.
Civil, environmental, and urban-planning firms use GIS for site selection, infrastructure mapping, and environmental impact assessment.
Kerala’s growing IT and space-tech ecosystem is creating new roles in satellite analytics, Web GIS development, and geospatial machine learning.
Below are genuine LULC and NDVI maps produced by Space Borne — real classified satellite outputs, not mock-ups — showing exactly the kind of deliverable you will learn to build during this course for your own Kannur study area.
| Module | Topics Covered |
|---|---|
| 1. GIS Fundamentals | Coordinate systems, projections, vector & raster data, QGIS/ArcGIS interface |
| 2. Remote Sensing Basics | Electromagnetic spectrum, sensors, Landsat 8/9 & Sentinel-2 data download workflows |
| 3. Image Processing | Band combinations, atmospheric correction, spectral indices (NDVI, NDWI, NDBI) |
| 4. LULC Classification | Supervised & unsupervised classification of Kannur’s landscape |
| 5. Natural Resource Mapping | Wetland delineation, forest-cover mapping, shoreline change detection |
| 6. Python for GIS | ArcPy & PyQGIS scripting for automated, repeatable geoprocessing workflows |
| 7. Google Earth Engine | Cloud-based time-series analysis of Kannur’s natural resource zones |
| 8. Web GIS Development | Building interactive Leaflet.js maps to publish natural resource layers online |
| 9. GeoAI Foundations | Introduction to machine learning for automated feature extraction from satellite imagery |
| 10. Capstone Project | End-to-end LULC & resource-mapping project on a Kannur study area of choice |
This course is conducted as live online training. It’s delivered live online, so learners across Kannur and anywhere else in Kerala can attend from home or office.
You’ll learn QGIS, ArcGIS, ArcGIS Pro, Python for GIS, Google Earth Engine, Web GIS development, and GeoAI — applied directly to Kannur’s own landscape through real local case studies.
Students, researchers, and working professionals from environmental science, civil engineering, urban planning, forestry, agriculture, and geography backgrounds can join — no prior GIS experience is required.
Yes. Space Borne issues a course-completion certificate from an ISO 9001:2015 & MSME certified institute, recognized for academic and professional use.
QGIS (free/open-source), ArcGIS Desktop & ArcGIS Pro, Python (ArcPy/PyQGIS), Google Earth Engine, and Leaflet.js for Web GIS — the same stack used in professional geospatial roles.
Most modules run 6–8 weeks with weekend and evening batch options, so students and working professionals can complete the course without schedule conflicts.
No. The course is built primarily around QGIS and Google Earth Engine, which are free. Where ArcGIS is used, guidance is provided on trial/educational licensing options.
You’ll complete an end-to-end LULC and resource-mapping project on a study area of your choice — many students choose a Kannur landmark featured on this page.