Geostatistics – III

By |

Many environmental variables such as temperature, rainfall, air pollutants, and soil nutrients are measured at sampled point locations. We often need to estimate these variables at one of more unsampled locations. Geostatistics provide tools and techniques to carry out this task.

In a series of three workshops, we will cover the basics of Geostatistics. In this third workshop, we will combine the material we covered in the first two workshops and develop the geostatistical modeling approach. This is mainly a lecture style workshop, but will include an example in R. The material will also help you understand the basics of Gaussian Process Regression, a commonly used modeling technique in Machine Learning.

Geostatistics – II

By |

Many environmental variables such as temperature, rainfall, air pollutants, and soil nutrients are measured at sampled point locations. We often need to estimate these variables at one of more unsampled locations. Geostatistics provide tools and techniques to carry out this task.

In a series of three workshops, we are covering the basics of Geostatistics. In this second workshop, we will focus on covariance and variogram, and their estimation in the context of geostatistical modeling. This is mainly a lecture style workshop, but we will also execute some examples in R. The material will also help you understand the basics of Gaussian Process Regression, a commonly used modeling technique in Machine Learning.

Geostatistics – I

By |

Many environmental variables such as temperature, rainfall, air pollutants, and soil nutrients are measured at sparsely sampled point locations. We often need to estimate these variables at one of more unsampled locations. Geostatistics provide tools and techniques to carry out this task.

In a series of three workshops, we will cover the basics of Geostatistics. In this first workshop we will understand the idea of stationary random fields, positive definite functions, and the fundamental building blocks of Gaussian random fields. This is mainly a lecture style workshop, but we will also execute some examples in R. The material will also help you understand the foundations of Gaussian Process Regression, a commonly used technique in Machine Learning and AI.

GIS Fundamentals – Understanding and manipulating elevation data

By |

Elevation data can come in the form of point (e.g. from LiDAR), digital elevation model (DEM), or triangulated irregular network (TIN). In this workshop we will focus on DEM and TIN. We will learn about each model and related data structure, their relative strengths, the kind of information they provide, and how to obtain downstream derived information. This is a lecture-style workshop and the primary focus will be about understanding the two models. However, we will also see examples in ArcGIS or QGIS

Participants should know GIS and be familiar with vector and raster data.

GIS Fundamentals – Height and Vertical Datum

By |

Understanding how heights are measured and recorded in GIS systems are essential for many applied tasks such as modeling flood risk due to sea level rise. In this workshop we will understand vertical datums, the concept of height, and what do terms like orthometric height and ellipsoid height mean. This will be a lecture-style workshop with a focus on conceptual details.

Participants should know basic GIS and should be familiar with horizontal datums.

GIS Fundamentals – Spatial Database, PostGIS

By |

PostGIS, built on top of PostgreSQL, is the most powerful open-source relational database for managing spatial data. In this workshop we will cover the basic concept of spatial databases, learn about setting PostGIS, and understand how PostGIS can help us manage large volumes of vector data spread over multiple tables and geometries efficiently.  We will also touch upon topics such as spatial indexing and the capabilities of PostGIS for other data models for 2-D GIS such as the network and raster data model.

GIS Fundamentals – (Map visualization – II)

By |

This workshop will further develop the material covered on mapping in the first workshop a few weeks back. We will focus on basic cartography principles for map-making and explore the functionalities of R and QGIS for making production-quality bi-variate static and dynamic choropleth maps. We will also explore the functionalities of leaflet, a powerful library, to create web maps and add extra information about more than two variables.

Participants should have some familiarity with R, but exposure to QGIS is not required.

GIS Fundamentals – (PostGIS-II)

By |

This workshop will further develop the material covered on spatial databases in the first workshop a few weeks back. PostGIS is the most widely used spatial database and is built on top of PostgreSQL, a powerful open source relational database. The focus of this workshop is to exploit PostGIS to deal with big vector data, and use familiar tools in R to reduce the burden to learn SQL.

This is a hands-on workshop. Please make sure that you have PostgreSQL installed along with pgAdmin.

Participants should be familiar with vector data processing in R.

GIS Fundamentals – VI (Map visualization)

By |

This is the sixth workshop in a series of workshops we are offering this semester on the fundamentals of GIS. Each workshop covers one or two key elements of GIS and is self-contained. The focus is on conceptual details that can provide sufficient preparation for applications, but we will also touch upon the technical aspects.

This workshop will cover basic concepts and tools available in QGIS and R for visualizing vector spatial data as single and bi-variate static choropleth maps. We will focus on basic cartography principles for map-making and explore the functionalities of R and QGIS for making production-quality maps.

Participants should have some familiarity with R, but exposure to QGIS is not required.

GIS Fundamentals – V (Spatial Database – PostGIS)

By |

This is the fifth workshop in a series of workshops we are offering this semester on the fundamentals of GIS. Each workshop covers one or two key elements of GIS and is somewhat self-contained. The focus is on conceptual details that can provide sufficient preparation for applications, but we will also touch upon the technical aspects.

In this workshop we will cover the basic concepts of spatial databases and learn about setting up and using PostGIS, an open source spatial database built on top of PostgreSQL, along with R for vector data analysis. We will also touch upon topics such as spatial indexing, query processing and the capabilities of PostGIS for other data models such as the network and raster data model. This is a hands-on workshop and the instructor will use a Mac machine. If you intend to use a Windows or Linux machine please get in touch with the instructor before the workshop at manishve@umich.edu.