Background In supervised classification, contrary to the unsupervised version, a priori defined reference class is used as additional information. This initial process determines which classes are the result of the classification. Usually, a statistical or machine-learning algorithm is used to obtain or “learn” a classification function from a set of training examples. This is then […]
Tutorials
How to plot Air Pollution Data with Openair
INTRODUCTION The openair package is specifically designed to plot air pollution data. This tutorial will give a brief introduction to many of the plotting functions in openair. This tutorial will cover the following openair functions. SummaryPlot() windRose() pollutionRose() percentileRose() timePlot() calendarPlot() SummaryPlot() The first plotting function we’ll look at is the summaryPlot(). Functions in the openair […]
Logistic Regression in Tensorflow
What is Logistic Regression? Logistic regression seeks to: Model the probability of an event occurring, depending on the values of the independent variables, which can be categorical or numerical. Estimate the probability that an event occurs for a randomly selected observation versus the probability that the event does not occur. Predict the effect of a […]
Advanced Techniques With Raster Data: Part 1 – Unsupervised Classification
Background The process of unsupervised classification (UC; also commonly known as clustering) uses the properties and moments of the statistical distribution of pixels within a feature space (ex. formed by different spectral bands) to differentiate between relatively similar groups. Unsupervised classification provides an effective way of partitioning remotely-sensed imagery in a multi-spectral feature space and […]
How to Use Environmental Data With Ropenaq
INTRODUCTION This R package is aimed at accessing the openaq API. OpenAQ is a community of scientists, software developers, and lovers of open environmental data who are building an open, real-time database that provides programmatic and historical access to air quality data. The package contains 5 functions that correspond to the 5 different types of […]
How to Use KableExtra and RMarkdown to Create Tables in PDF Documents
INTRODUCTION The goal of this tutorial is to introduce you to kableExtra, which you can use to build common complex tables and manipulate table styles. It imports the pipe %>% symbol from magrittr and verbalizes all the functions in order to permit you to add “layers” to the kable output. In combination with R Markdown, you […]
Linear Regression in Tensorflow
Linear Regression Theory Overview In statistics, linear regression is a linear approach for modeling the relationship between a scalar dependent variable, “y”, and one or more explanatory (independent) variables. The case of one independent variable is called simple linear regression. For more than one independent variable, the process is called “multiple linear regression.” The compacted […]
Spatial Data Analysis: Introduction to Raster Processing: Part 4
Background In the fourth part of this tutorial series on Spatial Data Analysis using the raster package, we will explore more functionalities, this time related to time-series analysis of raster data. For more information on raster data processing, see here, as well as the tutorial part-1, tutorial part-2, and, tutorial part-3, of this series. We […]
Spatial Data Analysis: Introduction to Raster Processing: Part-3
Background Geospatial data is becoming increasingly used to solve numerous ‘real-life’ problems (check out some examples here.) In turn, R is becoming a powerful, open-source solution to handle this type of data, currently providing an exceptional range of functions and tools for GIS and Remote Sensing Data Analysis. In particular, raster data provides support for […]
Tensorflow – Basics: Part 2
Overview In this tutorial, we will go through the basics of Tensorflow. By the end of this series, you will have the background in order to use Tensorflow for deep learning models. Tensorflow is an open source, software library for numerical computation using data flow graphs. Nodes in the graph are called ops (short for […]
