Course Overview:
This intensive five day course provides the foundation for: Building GIS databases and performing analysis in ArcGIS.
Participants shall learn how to create GIS databases and manage their data in a GIS databases. In addition, they will learn the general guidelines of performing all types of analysis. The course will offer an understanding of the types of analysis that can be performed in ArcGIS desktop environment, the kind of questions that each type answers and the tools used to perform each type. The course will be delivered through presentations, practical exercises and lesson reviews. Esri ArcGIS desktop application will be used in this course.
The programme is designed to help you use GIS to solve spatial related problems and challenges, from disaster analysis, development and policy planning.
Course Goals:
After successfully completing this course, you will have acquired an understanding of Esri’s geodatabase format and performing spatial analysis in ArcGIS Desktop platform. These new skills include:
• Building GIS databases
• Managing spatial and non-spatial datasets in a geodatabase
• An in-depth understanding of ArcGIS analysis workflow and its application in answering specific analysis questions
• Building geoprocessing models to automate the analysis process
• Sharing geoprocessing results
Software Used:
The following software licenses or applications are used in this course:
• ArcGIS Desktop 10.7 (Advanced)
Course Materials:
Each student will receive:
1. Course manuals and training data
2. ArcGIS 10.7 evaluation license
Advanced GIS using QGIS
Period: 5 Days
Course Outline:
Day 1
Spatial Data Preparation
- Elements of Spatial data
- Metadata
- Vector vs Raster data
Spatial data Storage
Methods of data storage
Introduction to geo-databases
Day 2:
Geo-Databases
- Types of geodatabase
- Data Access from Geodatabase
Data Relationships
- Joins
- Intersects
Day 3:
Advanced spatial Analysis
- Proximity Analysis
- Overlay Analysis
- Statistical Analysis
Data Symbology & Classification
- Layer Styles
- Data classes
Day 4:
Introduction to raster data
- Sources of Raster data
- Raster data analysis
- Overlay analysis
- Suitability Analysis
Day 5:
Analyzing spatial relationships
Sharing GIS Solutions
Course Recap
Course Conclusion
In these courses, the trainees will be provided with:
- Daily exercises will be done after the training for the day
- Power Point presentations for the day
- Written guides, where necessary
- 12 hrs support (During the day)
Web mapping is the process of using maps delivered by geographical information systems (GIS) on the internet through client- server architecture.
Web mapping usually involves a web browser to consume services.
These services include serving interactive maps, GIS data and location based services.
Participants will learn how to prepare and share geographic information so that it can effectively be used by colleagues, decision-makers, and non-GIS audiences.
The course will focus on:
– Web Mapping Technology,
– Web Mapping architecture, application and tools.
The goal of this training course is to introduce users to the concept of web mapping.
This course will cover the following topics
Day 1:
Web GIS Basics
Basics of Web GIS Architecture
Web Services and Mashups
An introduction / Review of ArcGIS Online
Day 2:
Basics of Web programing and development:
HTML, JavaScript and CSS.
Day 3:
Spatial Databases: Postgres-Postgis spatial database
Day 4:
Publishing map services on Geoserver
Day 5:
Consuming map services and sharing data:
Introduction to open source and proprietary web mapping API’s and scripting environments.
Software/Applications to be used
– Text editor / Notepad++
– Qgis v 2.8+
– Postgres
– Tomcat
– Geoserver
– ArcGIS (Desktop& Server where applicable)
The objective of this hands-on course is to teach Data Analysis and Statistics in a practical manner to enable you solve any complex Analysis with ease using R programming.
The training will take 5 days comprising of presentations and practical sessions facilitated by our team of data experts.
The R-studio software will be used for the training.
Course Outline:
Day One: Course Introduction
- Presentation on understanding and analyzing big data
- Overview on basics of R-studio software
- Installation of R software and packages to be used throughout the training
- Overview of the data used for practice and training
Day Two: Data Quality Check and Exploration
- Overview of dlookr package for data diagnosis, exploration and transformation
- Calculating descriptive statistics, testing normality in continuous data
- Use of diagnosis function to run data quality checks and generate data diagnosis report
- Visualization of the data using plots i.e box plots, scatter and bar charts
Day Three: Correlation and Regression Analysis
- Use of correlation coefficient to determine a relationship between continuous variables using correlation function and other correlation test e.g Pearson and Spearman test.
- Visualization of the correlation matrix using plots
- Regression analysis for modeling relationship between variables using simpler linear regression and multiple linear regression model
- Interpretation of results and visualization of the results using plots
Day Four: Simulation and Statistical Tests
- Data simulation
- Use of commonly used statistical tests to measure significance of data. E.g. One sample and two sample-Test, Chi-Squared Test, and Shapiro
- Explore more tests
Day Five: Working with Real Data
- Correlation analysis
- Modeling
- Accuracy assessment
- Presentation
Course Conclusion
Course Evaluation by the participants
Award of Certificates
This course aims at providing a complete field to office mobile mapping workflow to the participants. Participants shall use their mobile devices (Mobile Phones and GPS) to collect data, load the data into GIS and create maps from data collected. The course will enable the participants to also edit existing databases in the field and creating new data using field data collection techniques (Kobo and ODK).
MODULE I
• General Introduction to Mobile Data gathering
• Data and types of Data
• Introduction to ODK collect and Kobo Collect
• Data aggregation, storage and dissemination using ODK and Kobo Collect
• Types of questions
Preparing the mobile phone for data collection
• Installing applications: ODK Collect
• Configuring the device (Mobile Phones)
• Uploading the form into the mobile devices
(Hands-on Exercise)
MODULE II
Basic Survey Authoring
Intermediate Survey Authoring
Advanced Survey Authoring
• Conditional Survey Branching
• Grouping questions
• Making dynamic calculations
MODULE III: Hosting and Exporting survey data (Online)
Introduction to the server side component of ODK
• ODK Aggregate
• Kobo Toolbox
Hosting Survey Data (Configuring a local server)
• Configuring ODK Aggregate on a local server
• Ona account registration
Downloading data
• Manual download (ODK Briefcase)
• Using the online server interface (ona.io)
Hands-on Exercise (Practical with a sample questionnaire)
ANALYSIS
ODK and GIS data conversion
Exporting data to Fusion tables using
Hand-on Exercise
Course Summary
Discussion on the Choice of Platform
Considerations for Integrating Mobile Data Gathering Tools into the Project
