Learn GIS from ₹2499/- Only
Lowest Fees I Best Training
Our Top Rated Trainings |
ArcGIS
Key Learnings:
- Cartography: Create professional-quality maps using advanced cartographic techniques.
- Geoprocessing: Perform spatial data analysis, processing, and automation of workflows.
- Satellite Imagery Analysis: Analyze and interpret satellite imagery for land use, vegetation, and urban studies.
- Map Layout: Design and customize high-quality map layouts for reports and presentations.
- 3D Visualization Techniques: Build and explore realistic 3D models for terrain and city planning.
ArcGIS Pro
Key Learnings:
- Cartography: Create professional-quality maps using advanced cartographic techniques.
- Geoprocessing: Perform spatial data analysis, processing, and automation of workflows.
- Satellite Imagery Analysis: Analyze and interpret satellite imagery for land use, vegetation, and urban studies.
- Map Layout: Design and customize high-quality map layouts for reports and presentations.
- 3D Visualization Techniques: Build and explore realistic 3D models for terrain and city planning.
QGIS
Key Learnings:
- Cartography: Create professional-quality maps using advanced cartographic techniques.
- Geoprocessing: Perform spatial data analysis, processing, and automation of workflows.
- Satellite Imagery Analysis: Analyze and interpret satellite imagery for land use, vegetation, and urban studies.
- Map Layout: Design and customize high-quality map layouts for reports and presentations.
- 3D Visualization Techniques: Build and explore realistic 3D models for terrain and city planning.
HEC-RAS
Key Learnings:
- River Hydraulics: Understand the fundamentals of river flow and hydraulic modeling using HEC-RAS.
- Floodplain Delineation: Simulate and map flood inundation areas for various flow scenarios.
- Cross-Section Analysis: Develop and refine cross-sections for accurate hydraulic modeling.
- Terrain Data Integration: Import and utilize terrain data (DEM) to enhance model accuracy.
- Boundary Conditions: Set up and calibrate boundary conditions for steady and unsteady flow simulations.
- Flood Risk Assessment: Analyze results to assess flood risk and identify vulnerable areas.
- Exporting Results: Generate flood maps and export results for GIS-based visualization and reporting.
Google Earth Pro
Key Learnings:
- Data Visualization: Display and analyze geographic data with high-resolution satellite imagery.
- Placemarks & Annotations: Create placemarks, paths, and polygons to mark and describe locations.
- Historical Imagery: Explore changes over time using historical satellite images.
- GIS Data Integration: Import and export shapefiles (SHP), KML, and KMZ files for seamless GIS integration.
- 3D Mapping: Visualize terrain and structures in 3D for better spatial understanding.
- Tour Creation: Develop engaging virtual tours with narration and animations.
- Data Measurement: Measure distances, areas, and elevations accurately for spatial analysis.
Erdas Imagine
Key Learnings:
- Image Processing: Perform advanced image preprocessing, including radiometric and geometric corrections.
- Image Classification: Classify satellite imagery using supervised and unsupervised techniques.
- Change Detection: Analyze temporal changes in land use, vegetation, and urban growth using multi-temporal imagery.
- Feature Extraction: Extract features such as water bodies, vegetation, and infrastructure from imagery.
- Mosaic and Subset: Combine multiple images into seamless mosaics and extract specific regions of interest.
- DEM Analysis: Generate and analyze digital elevation models (DEMs) for terrain analysis.
- GIS Integration: Seamlessly integrate processed data with other GIS platforms for further analysis.
Our Customized Training |
Estimation of Crop Yield, Crop Acreage, Crop Health using GIS & Machine Learning
- Crop Mapping: Use satellite imagery and GIS tools to identify and map crop types and coverage.
- Acreage Estimation: Accurately calculate crop acreage using spatial data and remote sensing techniques.
- Yield Prediction: Apply machine learning algorithms to predict crop yield based on historical and real-time data.
- Crop Health Monitoring: Assess crop health using vegetation indices like NDVI, EVI, and other spectral indicators.
- Data Integration: Combine weather data, soil properties, and remote sensing data for enhanced decision-making.
- Machine Learning Models: Implement regression, classification, and deep learning techniques for agricultural analytics.
- Geospatial Analysis: Leverage GIS for spatial variability analysis and pattern identification in agricultural fields.
Mapping of Ground Water Potential Zones using RS, GIS & AHP
- Remote Sensing Data Utilization: Use satellite data for identifying key groundwater influencing factors such as land use, soil type, and vegetation cover.
- Thematic Layer Preparation: Generate thematic maps of geology, slope, drainage density, rainfall, and lineament density.
- GIS Analysis: Integrate and overlay spatial data to analyze groundwater potential zones.
- Analytical Hierarchy Process (AHP): Apply the AHP technique for multi-criteria decision-making by assigning weights to influencing factors.
- Weighted Overlay Analysis: Perform weighted overlay in GIS to combine criteria and map groundwater potential zones.
- Validation Techniques: Validate potential zone maps using field data or well locations.
Watershed Simulation, Rainfall‐Runoff and Hydrological Modeling using RS & GIS
- Watershed Delineation: Use DEMs and GIS tools to define watershed boundaries and drainage networks.
- Rainfall-Runoff Modeling: Simulate runoff patterns and volumes using hydrological models like SCS-CN.
- Hydrological Parameters Extraction: Derive parameters such as slope, flow direction, flow accumulation, and stream order.
- Remote Sensing Integration: Incorporate satellite-derived data (e.g., land use/land cover, vegetation indices) into hydrological models.
- Soil and Land Use Analysis: Analyze soil types, permeability, and land use for accurate infiltration and runoff predictions.
- Hydrological Modeling Software: Work with tools like HEC-RAS, SWAT for comprehensive hydrological simulations.
Above Ground Biomass Estimation of Forests using RS, GIS
- Satellite Data Utilization: Use remote sensing data such as optical, radar (e.g., Sentinel-1), and LiDAR for biomass estimation.
- Vegetation Indices: Calculate indices like NDVI, EVI, and SAVI to assess forest health and density.
- Allometric Equations: Integrate field-measured data with remote sensing parameters to estimate biomass using allometric models.
- Land Cover Mapping: Identify and classify forest types and land cover using GIS tools.
- Canopy Structure Analysis: Analyze forest canopy height, density, and cover using remote sensing data.
- GIS Integration: Combine spatial layers such as topography, soil type, and climatic factors to refine biomass estimations.
- Carbon Stock Calculation: Estimate carbon sequestration potential from biomass data for climate change studies.
- Validation and Accuracy Assessment: Validate biomass estimations using field data and assess accuracy with statistical techniques.
Assessment of Flooding Risk with RS, GIS, HEC-RAS
- Remote Sensing for Flood Mapping: Utilize satellite imagery (e.g., Sentinel, Landsat) for flood extent and inundation analysis.
- DEM Analysis: Process digital elevation models (e.g., SRTM, LiDAR) to extract terrain parameters critical for flood modeling.
- Hydraulic Modeling with HEC-RAS: Simulate flood behavior, including water surface profiles and inundation extents, under different scenarios.
- GIS Integration: Use GIS to prepare input data (e.g., land use, soil type) and visualize HEC-RAS results as flood risk maps.
- Flood Hazard Zonation: Delineate areas at varying levels of flood risk based on hydraulic simulation outputs.
- Validation and Calibration: Validate model results using historical flood data or observed high-water marks.
- Flood Risk Assessment: Combine flood hazard maps with population density, infrastructure, and economic data for risk evaluation.
Integration of GIS and Remote Sensing with RUSLE Model for Estimation of Soil Erosion
- Understanding RUSLE Parameters: Learn the components of the Revised Universal Soil Loss Equation (RUSLE), including R (rainfall erosivity), K (soil erodibility), LS (slope length and steepness), C (crop management), and P (support practice).
- Remote Sensing for Input Data: Utilize satellite imagery to derive land use/land cover (LULC) maps for the C-factor and vegetation indices.
- DEM Analysis: Extract slope and aspect information from DEMs to calculate the LS-factor.
- Rainfall Erosivity (R-Factor): Use spatial rainfall data to compute the R-factor.
- Soil Erodibility (K-Factor): Integrate soil type maps to determine the soil erodibility factor.
- GIS Integration: Combine all RUSLE factors using GIS tools to generate soil erosion risk maps.
- Erosion Hotspot Identification: Identify and prioritize high-risk areas for soil conservation efforts.
- Soil Conservation Planning: Develop strategies for soil erosion mitigation based on analysis results.
Our Development Training |
ArcPy for ArcMap
Key Learnings:
- Geoprocessing Automation: Automate tasks like buffering, clipping, and spatial joins using ArcPy scripts.
- Data Management: Programmatically create, update, and manage shapefiles, feature classes, and geodatabases.
- Map Document Customization: Modify ArcMap documents (.mxd) by updating layers, layouts, and exporting maps.
- Cursor Operations: Efficiently manipulate attribute table data using search, insert, and update cursors.
- Spatial Analysis: Perform advanced analyses with ArcPy’s spatial analyst module for raster and vector data.
- Batch Processing: Simplify workflows by automating repetitive tasks for multiple datasets.
Python for Geospatial Analysis
Key Learnings:
- Geospatial Libraries: Learn key Python libraries like GeoPandas, Shapely, Rasterio, and Pyproj for spatial data manipulation.
- Spatial Data Handling: Read, write, and process vector and raster data formats such as shapefiles, GeoJSON, and TIFF.
- Geometric Operations: Perform tasks like buffering, intersecting, and spatial joins on geospatial datasets.
- Visualization: Create interactive and static maps using libraries like Folium, Matplotlib, and Plotly.
- Coordinate Transformations: Reproject spatial data between coordinate systems with GeoPandas.
- Integration with Machine Learning: Combine spatial data with ML frameworks .
Spatial Analysis with R
Key Learnings:
- Spatial Data Handling: Work with vector (sf, sp) and raster (raster, terra) data formats for geospatial analysis.
- Geospatial Visualization: Create static and interactive maps using ggplot2, tmap, and leaflet.
- Spatial Operations: Perform geoprocessing tasks such as buffering, intersection, and spatial joins.
- Geostatistics: Apply techniques like kriging, interpolation, and variogram modeling using R packages like gstat.
- Coordinate Transformations: Reproject spatial data into various coordinate reference systems (CRS).
- Integration with Big Data: Analyze large spatial datasets with efficient R packages like sf and data.table.
Training Mode Online Offline
Online
Offline
Our Best Approaches |
Comprehensive Curriculum
Engage with interactive modules that simulate real-world scenarios for GIS applications.
Hands-on Exercices
Practice hands-on exercises using real satellite imagery and GIS tools to enhance practical skills.
Expert-led Instructions
Learn from industry experts through live sessions and detailed tutorials on spaceborne GIS.
Certification
Earn recognized certifications to validate your expertise in GIS.
Real World Case Studies
Work on case studies and projects that reflect current industry challenges and solutions.
Community Support & Networking
Join a community of professionals and peers for support and networking opportunities.
Customized Training Option
Benefit from customized training solutions designed to meet specific organizational needs.
Carrer Development Guidance
Access resources to advance your career in the spaceborne GIS field.
Explore Our Course Categories
GIS
Dive into the world of Geographic Information Systems (GIS) with our comprehensive training offerings. Whether you're a beginner seeking to understand spatial data fundamentals or an experienced professional looking to enhance your GIS skills, our courses cover a wide range of topics to suit your needs. From cartography and geospatial analysis to GIS software proficiency, embark on a journey of discovery and unlock the power of spatial data in managing natural resources.
Remote Sensing
Embark on a journey of exploration into the realm of Remote Sensing with our specialized training programs. Gain insights into cutting-edge technologies and methodologies used to extract valuable information about the Earth's surface from satellite and aerial imagery. Whether you're interested in environmental monitoring, land use classification, or disaster management, our courses offer practical skills and knowledge to propel your remote sensing expertise to new heights.
Data Analysis
Dive into our Data Analysis Training: Delve into the art and science of Data Analysis with our dynamic training courses. From introductory tutorials on statistical techniques to advanced workshops on machine learning algorithms, our comprehensive curriculum caters to learners of all levels. Whether you're aiming to master data visualization, predictive modeling, or big data analytics, our courses provide the tools and insights you need to transform raw data into actionable insights.
Why Space Borne?
Expert Faculties
Space Borne’s GIS training courses are led by industry experts with years of experience in geospatial technology. Participants benefit from in-depth, practical knowledge and insights tailored to real-world applications. The hands-on sessions and personalized mentorship prepare trainees to excel in GIS, Remote Sensing, and related fields.
Course Coverage
From beginners to advanced levels, Space Borne offers a wide range of GIS courses, including specialized topics like crop yield prediction, soil erosion mapping, and marine biodiversity assessment. Each course is structured to provide a balanced mix of theoretical understanding and practical experience using the latest GIS tools and techniques.
Tools and Technology
Training at Space Borne involves exposure to the latest GIS software, remote sensing tools, and AI/ML techniques. Participants gain experience working with state-of-the-art technologies, ensuring they are industry-ready and equipped to handle complex geospatial challenges. You work on the latest Tools of Remote Sensing here.
Flexible Learning
FAQ
Most frequent questions and answers
Space Borne provides a variety of services including GIS and remote sensing training, research programs, consulting, and customized geospatial solutions for different industries.
- These courses are beneficial for a wide range of professionals, including geographers, urban planners, environmental scientists, engineers, and anyone interested in spatial data analysis.
- Most introductory courses at Space Borne do not require specific prerequisites. However, a background in geography, environmental science, or a related field can be helpful for more advanced courses.
- Yes, Space Borne offer online courses, making it convenient for learners from around the world to access the training.
- Course durations vary, but introductory courses can typically be completed in a few weeks, while more advanced programs may span several months or even a year.
- Popular GIS software includes ArcGIS and QGIS. These tools are often taught in GIS courses to familiarize students with industry-standard software.
- Basic courses can often be completed with a standard computer. However, for more advanced coursework, access to a computer with higher processing power may be necessary.
- Yes, Space Borne provides certificates upon successful completion of their courses. These certificates can enhance your resume and career prospects.
- Yes, there is a growing demand for professionals with Remote Sensing and GIS skills in various industries, including environmental management, urban planning, agriculture, and disaster management.
Space Borne offers job placement assistance or connects students with industry contacts to help them find employment.
– Yes, many institutes offer advanced courses, diplomas, and even degree programs for those who wish to further specialize in the field.
– Career options include GIS analyst, remote sensing specialist, cartographer, urban planner, environmental consultant, and more, depending on your specialization and interests.
– Yes, many institutions and organizations actively engage in research in these fields, and you can pursue research opportunities depending on your qualifications and interests.
– You can stay informed by joining professional organizations, attending conferences, and following industry publications and blogs at our website.
– Space Borne offers scholarships or financial aid for eligible students. It’s advisable to mail us or contact us with the details.
What students Say about us
Awesome Training
The best online platform to learn GIS and Remote Sensing. State of art teaching and conceptual clarity. I recommend all the students and academicians to come and learn in this platform as the experts here take personal care to bring the best out of you and help you enhance your skills of research using GIS and remote sensing. Extremely affordable and accessible for such a highly quality capacity building.
Simply The Best
No doubt, it is the best experience for me . Enjoyed and learned a lot in a holistic environment. The style and the knowledge of the educator is totally amazing and commendable. Hoping for more such courses in future.
Best and Supportive
Best training institute and management. All the staff members are also very friendly and always ready to help for everything. lots and lots of thank to Space Borne Institute and i wish you more success.
Creative
It was a nice experience here. Sir was very cooperative with us . He clears the doubts in arcgis and explains the things thoroughly in an easy way. This is a very good institute to learn about Arcgis