Spatial Data and Software

Benjamin Leutner, Ned Horning, Duccio Rocchini and Martin Wegmann

1.1 What is Geospatial Data?

Geospatial data are information that can be pinpointed to spatially explicit locations on Earth. Most of the data you sample in ecology are of geospatial nature, regardless of whether you recorded the spatial coordinates during data collection or not. In principle, a geospatial data element consists of two parts: (1) spatial coordinates in a defined coordinate system, such as latitude and longitude; and (2) one or more values, such as a label, a physical measurement or a species observation associated with this location (Figure 1.1).

The analysis of geospatial data has been at the core of ecology since its very beginning. Answering the fundamental ecological question "What do we find where and why?" requires an explicit investigation into spatial relationships, processes and patterns.

This book will get you started with the basic geospatial analysis techniques you need to approach these questions. What is the distance to the border of the PAs? Which points are located close to a road? What degree of tree cover and how much land cover change exist in my study area? Combining the geospatial data of different sources, such as field observations and remote sensing data, will go a long way in finding answers to these questions.

1.2 Tools

Within this book we will mainly focus on two different packages of GIS-capable software: R and QGIS. Both programs are platform independent and free, including in commercial environments, due to their OS licensing under the GNU General Public License (GPL). However, for some analyses, other software packages such as GRASS (Geographic Resources Analysis Support System), SAGA (System for Automated Geoscientific Analyses) or Orfeo ToolBox (OTB) will be more appropriate, in which case we will point you to the corresponding program and function.

QGIS is a program similar to proprietary GIS packages and offers a GUI with a variety of GIS functionalities. R, on the other hand is purely based on a command-line interface (CLI) that forces you to program your own analysis in a script. While this can be less intuitive at first, it pays out quickly, at the latest when you have to redo your analysis. If you have not programmed or worked with the command line so far, you will hopefully enjoy using it after reading this book. You will have to work continuously on your coding skills and fight the frustrating bits and pieces. However, you will feel greatly rewarded having also managed to solve problems and finish off your script.

We will cover a variety of functions that will guide you from data import, generation and inspection in QGIS to more advanced data modification, analysis and visualization in R. R will be used extensively due to its statistical and spatial data manipulation capabilities.

1.2.1 QGIS

QGIS is a very user-friendly GIS available for free from http://qgis.org. It provides an appealing GUI and is the most intuitive software package used in this book – the ideal GIS to get you started with spatial analysis (Figure 1.2). The QGIS GUI is especially helpful for interactive data analysis, such as data display, digitization or map generation.

QGIS, however, is more than a simple GUI. It has fully fledged support for high-end geospatial data processing with all the functionality you would expect from a modern GIS. While you can achieve everything in the GUI, QGIS also provides a graphical model builder to generate program routines for users not familiar with a scripting language. More importantly, it also includes a scripting console for the Python programming language. Furthermore, QGIS provides interfaces to R, GRASS, SAGA and other software packages so you can use their additional functionality within QGIS.

In addition, QGIS comes with a plug-in architecture for which users have contributed a variety of extensions. The set of available extensions or plug-ins is rapidly evolving as is QGIS itself. QGIS comes with a plug-in manager that makes it easy to browse and install plug-ins from a central repository (Figure 1.3).

Some useful and recommended plug-ins include:

• GPStools: importing and modifying GPS data;

• fTools: vector analysis and management;

• OpenLayers Plugin: display of Google Earth, OpenStreetMap, Bing Maps, and so on;

• Georeferencer GDAL: georeference raster using GDAL;

• Processing: interfaces to GRASS, OTB, R, SAGA.

QGIS has a very high development pace: new releases or candidates are announced every couple of months. Three QGIS versions, 2.2, 2.3 and 2.4, were released in 2014 alone. Odd-numbered versions are development versions while even numbers indicate stable release versions.

QGIS provides an extensive online archive of help pages and tutorials. Go to Help > Help Contents or hit "F1" in QGIS and your browser will be directed to the user guide for your current version of QGIS.

SAGA, GRASS and OTD in QGIS

QGIS is increasingly capable of calling functions available in different packages. This increases the functionality of QGIS tremendously while maintaining a simple and intuitive user interface (Figure 1.4). It is a very good starting point to use SAGA, GRASS or OTB through QGIS, however, you might want to work directly with these packages at a later stage, which would allow...