.rst .pdf

Contents

Welcome to our documentation…

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About us

We are a GIS and remote sensing specialist team with the mission of providing solutions to all technical issues in geographic information and geospatial data analysis for atmospheric, ocean, and land studies at various spatial and temporal scales. Besides seeking technical solution, our main goal is also to share the knowledge, information, opportunity in this field and help people getting started with their journey for doing geo data analysis more efficiently through this documentation website and our facebook page.

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This website contains three main sections: Projects, Documentations, and Lessons.

Projects

This section describes the technical solution to solve various topics including land cover classification, flood water surface extraction, forest cover, etc.

Documentations

This section describes the programming technics in different applications including LiDAR, geo-python, Google Earth Engine, machine learning and deep learning.

Lessons

This section provides full lessons to understand the basic concepts of programming and scientific data analysis using Python programming language.

Contents

Projects

• 2020
  • Phnom Penh: Urban Growth from 1988 to 2020 by Landsat Satellite Imageries
  • Sentinel-1 SAR: Cambodia Flood in October 2020
  • Cambodia Forest Cover Change 2000-2019
• 2021
  • Develop paddy area map from MODIS satellite images using machine learning
  • Indonesia project: high-resolution satellite image analysis
• 2022
  • Kano & Yoshii river: Land cover classification using machine learning
  • Mapping flood frequency in Cambodia from 1988 to 2020 using Google Earth Engine
  • Land cover classification using supervised learning method in Google Earth Engine

Documentations

• LiDAR
  • Create DEM and Hillshade from point cloud data in Python
  • Create RGB image from las file in Python
• Geo-Python
  • Read & visualize raster image using xarray
  • Classify iris dataset with random forest classifier
  • Create a subplot figure
  • Interactive geoplots in dashboard layout with Bokeh
• Google Earth Engine
  • Download DEM from SRTM90 dataset
  • Calculate monthly mean temperature from ECMWF Climate dataset
  • Calculate monthly mean precipitation from CHIRPS Daily dataset
  • Calculate water turbidity index (WTI) from Sentinel-2
• Machine Learning
  • Land Use Classification with Random Forests Classifier
• Deep Learning
  • UNET Building footprint extraction using PyTorch

Lessons

• Geospatial data analysis with Python
  • Session 1: Geometric Objects
  • Session 2: Vector Data Analysis and Map Projection
  • Session 3: Geocoding and Nearest Neighbour Analysis
  • Session 4: Geometric operation and Data classification
  • Session 5: Plotting Static and Interactive Map on Leaftlet
  • Session 6: Raster Data Analysis

Contact Info

• Email: geospatialyst@gmail.com

• Facebook page: @GeospatialystCambodia

next

2020