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 representing […]
Advanced Raster Data: Solutions
Below are the solutions to these exercises on “Advanced Raster Data.” #################### # # # Exercise 1 # # # #################### ## Create a folder named data-raw inside the working directory to place downloaded data if(!dir.exists(“./data-raw”)) dir.create(“./data-raw”) ## If you run into download problems try changing: method = “wget” download.file(“https://raw.githubusercontent.com/joaofgoncalves/R_exercises_raster_tutorial/master/data/LT8_PNPG_MultiBand.zip”, “./data-raw/LT8_PNPG_MultiBand.zip”, method = “auto”) # […]
Advanced Techniques With Raster Data – Part 3: Exercises
Background In this post, the ninth of the geospatial processing series with raster data, I will focus on interpolating and modeling air surface temperature data recorded at weather stations. For this purpose I will explore regression-kriging (RK), a spatial prediction technique commonly used in geostatistics that combines a regression of the dependent variable (air temperature […]
Advanced Techniques With Raster Data – Part 2: Supervised Classification
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 […]
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 […]
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 […]
Exercises With Raster Data (Part 1 and 2)
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 representing […]
Exercises With Raster Data: Solutions (Part 1 and 2)
Below are the solutions to these exercises on Raster Data Analysis (Part 1 and 2). #################### # # # Exercise 1 # # # #################### library(raster) ## Create a folder named data-raw inside the working directory to place downloaded data if(!dir.exists(“./data-raw”)) dir.create(“./data-raw”) ## If you run into download problems try changing: method = “wget” download.file(“https://raw.githubusercontent.com/joaofgoncalves/R_exercises_raster_tutorial/master/data/srtm_pnpg.zip”, […]
Spatial Data Analysis: Introduction to Raster Processing (Part 2)
Background In the second part of this tutorial series on spatial data analysis using the raster package, we will explore new functionalities, namely: Raster algebra Cropping Reprojection and resampling We will also introduce a new type of object named RasterStack, which, in its essence, is a collection of RasterLayer objects with the same spatial extent, […]