Lecture 1 GEOG2590 – GIS for Physical Geography1 GIS for Physical Geography GEOG2590 Dr Steve Carver School of Geography

Lecture 1 GEOG2590 – GIS for Physical Geography2 Introduction to module Module outline: –Convenor: Dr Steve Carver –11 x 1 hour lectures –11 x 2 hour GIS practicals Assessment: –3 x 500 word equivalent practical assignments (20% each) to be submitted in weeks 19, 22 and 24. –1 x 1 ¼ hour written examination (40%)

Lecture 1 GEOG2590 – GIS for Physical Geography3 Module outline 1. Principles of GIS for Physical Geography applications 2. Working with environmental data 3. Error and uncertainty 4. Interpolating environmental datasets 5. Grid-based modelling 6. Terrain modelling 1: the basics 7. Terrain modelling 2: applications 8. Hydrological modelling 9. Land suitability modelling 10. Spatial decision support systems 11. Reading week

Lecture 1 GEOG2590 – GIS for Physical Geography4 Aims On completion of this module students should have: 1.Knowledge of the use of GIS across a range of applications in physical geography including terrain analysis, hydrology, landscape evaluation and environmental assessment; 2.Familiarity with the use and application of the ArcGIS package; and Knowledge of environmental data sources, skills in the interpretation of spatial environmental data and an awareness of specific problems and issues relating to data quality, spatial data models and methods of interpolation.

Lecture 1 GEOG2590 – GIS for Physical Geography5 Objectives Identify principles and functional issues pertaining to physical geography applications of GIS; Examine and review specific application areas where GIS is a useful tool; Investigate techniques provided by GIS which have particular relevance to physical geography applications and problem solving; and Identify and address problem areas such as data sources, modelling, error and uncertainty

Lecture 1 GEOG2590 – GIS for Physical Geography6 Learning outcomes On completion of this module students should be able to: –demonstrate a clear knowledge and understanding of the key concepts concerning the application of GIS to problems in physical geography; –show an appreciation of the space-time variability within environmental data and what this means for GIS applications in the field; and –demonstrate a high level of skill in the application of GIS software (principally ArcGIS) to the solving of environmental problems.

Lecture 1 GEOG2590 – GIS for Physical Geography7 Lecture 1. Principles of GIS for physical geography applications Outline –what makes physical geography applications of GIS different? –environmental science and management –the role of GIS?

Lecture 1 GEOG2590 – GIS for Physical Geography8 What makes physcial geography applications of GIS different? The natural environment is… –extremely complex –highly variable (space and time) –complicated further by human action Understanding of natural systems –very basic –multiple approaches to natural science

Lecture 1 GEOG2590 – GIS for Physical Geography9 From this… …to this

Lecture 1 GEOG2590 – GIS for Physical Geography10 Spatio-temporal variation Range of variability over a range of spatial and temporal scales –variation depends on the scale of observation  e.g. vegetation (species, community, ecosystem) –sliding scale to represent both spatial and temporal variability  i.e. space from infinitesimal (zero) to infinite  i.e. time from the instantaneous to ‘for ever’

Lecture 1 GEOG2590 – GIS for Physical Geography11 Spatio-temporal scales of operation Variety of spatial and temporal scales: –micro scale - meso scale - macro scale – e.g. Hydrology  Micro: runoff plots, infiltrometer, hillslope  Meso: sub-catchment, headwaters, reach  Macro: whole catchment, region, watershed – now - sec - min - day - year - century - etc. – e.g. Climatology  Seconds:Wind speeds  Minutes:Incoming solar radiation  Day:Anabatic/katabatic winds  Year:Annual temperature variation  Millennium:Glacial/interglacial periodicity

Lecture 1 GEOG2590 – GIS for Physical Geography12 Complexity Complex nature of environmental systems makes possibility of realistic modelling seem remote Frustrated by lack of understanding –e.g. influence of human activity Variations in complexity: –most GIS applications model only 1 or 2 processes with assumptions/simplification

Lecture 1 GEOG2590 – GIS for Physical Geography13 Question… How can sampling strategies be matched to spatio-temporal scales?

Lecture 1 GEOG2590 – GIS for Physical Geography14 Sampling theory Sampling spatial processes: – the sampling frequency needs to be small enough to record local variations without undue generalisation of spatial pattern but coarse enough so as to avoid data redundancy Sampling temporal processes: – in order to record variations in temporal processes sampling frequency needs to be about half the wavelength of the process to avoid measurement bias and too much detail Sampling dependent on process(es) operating

Lecture 1 GEOG2590 – GIS for Physical Geography15 Sampling theory DEMCell size 1Cell size 2 Time Rate 1 wavelength amplitude

Lecture 1 GEOG2590 – GIS for Physical Geography16 Question… How do we choose appropriate sampling frequencies?

Lecture 1 GEOG2590 – GIS for Physical Geography17 Advantages of GIS GIS is good at… –handling spatial data –visualisation of spatial data –integrating spatial data –framework for:  analysis and modelling  decision support

Lecture 1 GEOG2590 – GIS for Physical Geography18 (dis)Advantages of GIS GIS is not so good at… –handling temporal data –visualisation of temporal data –integrating spatial and temporal data –framework for:  analysis and modelling of time dependent data  volumetric analysis  uncertainty

Lecture 1 GEOG2590 – GIS for Physical Geography19 GIS alone is not enough Integrated systems: –limited ‘off-the-shelf’ spatial analysis and modelling –framework for developing better integrated systems  GIS - image processing systems  GIS - modelling systems  GIS - statistical software –facilitated through  specialist programming languages (e.g. AML and Avenue)  universal programming languages (e.g. Java and Visual Basic)  access to source code (e.g. GRASS)

Lecture 1 GEOG2590 – GIS for Physical Geography20 Integrated systems Combined (symbiotic) systems Example: –NERC/ESRC Land Use Programme (NELUP): decision support for land use change in UK  GRASS GIS  models: hydrological (SHE), agricultural economics and ecological  Graphic User Interface (GUI)  Spatial Decision Support System (SDSS)

Lecture 1 GEOG2590 – GIS for Physical Geography21 NELUP

Lecture 1 GEOG2590 – GIS for Physical Geography22 Conclusions The physical world is complex and our understanding simple –environmental data is highly variable –implications for GIS applications GIS has important role to play in environmental science and management –handling and analysing spatial data –problems with temporal data

Lecture 1 GEOG2590 – GIS for Physical Geography23 Practical Spatial variability in environmental data Task: Investigate the spatial variability in terrain datasets and determine the effects of a) sampling strategy, and b) resolution on the data. Data: The following datasets are provided for the Leeds area –10m resolution DEM (1:10,000 OS Profile data) –50m resolution DEM (1:50,000 OS Panorama data) –10m interval contour data (1:10,000 OS Profile data)

Lecture 1 GEOG2590 – GIS for Physical Geography24 Practical Steps: 1.Display both elevation datasets in ArcMap and look for visible differences - do these result from differences in sampling strategy or resolution or both? Use the IDENTIFY tool to interrogate the images. 2.Calculate the slope (gradient) from both the 10m and 50m data – is there any ‘striping’ in the slope data and what might this be due to? (use the slope tool in ArcMap or ArcGRID to calculate slope)

Lecture 1 GEOG2590 – GIS for Physical Geography25 Learning outcomes Familiarity with scale issues especially resolution and sampling in relation to spatial variation in environmental data Experience/practice in use of analysis and display functions in ArcMap Familiarity with OS terrain model products

Lecture 1 GEOG2590 – GIS for Physical Geography26 Next week… Working with environmental data –general characteristics of environmental data –environmental data sources –toward integrated databases Practical: Using Digimap to access OS data products