GEOG2750 Earth Observation & GIS of the Physical Environment 20 Credit Level 2 Module Louise Mackay & Steve Carver Module Information See also http://www.geog.leeds.ac.uk/courses/level2/geog2750/index.html Week 14 GEOG2750 – Earth Observation & GIS of the Physical Environment 1 Module Outline • Runs Semester 1 & 2. • Semester 1: Earth Observation of the Physical Environment – Louise Mackay • Semester 2: GIS of the Physical Environment – Steve Carver • Two complimentary technologies for monitoring & understanding the Earths physical environment Week 14 GEOG2750 – Earth Observation & GIS of the Physical Environment 2 GIS Aims On completion of semester 2 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 3. 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. Week 14 GEOG2750 – Earth Observation & GIS of the Physical Environment 3 GIS Objectives 1. Identify principles and functional issues pertaining to physical geography applications of GIS; 2. Examine and review specific application areas where GIS is a useful tool; 3. Investigate techniques provided by GIS which have particular relevance to physical geography applications and problem solving; and 4. Identify and address problem areas such as data sources, modelling, error and uncertainty. Week 14 GEOG2750 – Earth Observation & GIS of the Physical Environment 4 Overall 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 Earth observation and GIS to problems in physical geography; – Critique and evaluate the applicability of Earth observation and GIS in relation to physical geography applications; and – Demonstrate a high level of skill in the application of Earth observation & GIS software to the solving of environmental problems. Week 14 GEOG2750 – Earth Observation & GIS of the Physical Environment 5 Dates & Times • GIS – Semester 2: – 10 x 1hr lectures, Monday 10-11am, Geography Lecture Theatre – 10 x 2hr practicals, Tuesday 3-5pm or Friday 9am-1pm, Textiles G34 Computer Lab Week 14 GEOG2750 – Earth Observation & GIS of the Physical Environment 6 Module Assessment Semester 2 - GIS • 5 practical worksheets contributing 5% each to the final module mark • 1 x 1hr exam (short answer) at the end of the semester (2 questions from 5) contributing 25% of module mark Overall assessment based on: • 10 Practicals = 50% of final module mark (5 x Earth Observation = 25% done already last semester) • 2 exams = 50% of final module mark (Earth Observation = 25% done already last semester) Week 14 GEOG2750 – Earth Observation & GIS of the Physical Environment 7 GIS Syllabus – Semester 2 (Weeks) 14. Introduction to GIS for environmental applications 15. Spatial & Temporal variability and environmental data 16. Error & Uncertainty 17. Interpolation of environmental data 18. Principles of grid-based modelling 19. Terrain modelling: the basics 20. Reading week 21. Terrain modelling: applications 22. Hydrological modelling 23. Environmental assessment 24. Making Decisions Week 14 GEOG2750 – Earth Observation & GIS of the Physical Environment 8 Lecture 11 Introduction to GIS for environmental applications • Outline – what makes physical geography applications of GIS different? – environmental science and management – the role of GIS? Week 14 GEOG2750 – Earth Observation & GIS of the Physical Environment 9 What makes physical 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 Week 14 GEOG2750 – Earth Observation & GIS of the Physical Environment 10 From this… …to this Week 14 GEOG2750 – Earth Observation & GIS of the Physical Environment 11 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’ Week 14 GEOG2750 – Earth Observation & GIS of the Physical Environment 12 Spatio-temporal scales of operation • Variety of spatial and temporal scales: – micro scale - meso scale - macro scale – e.g. Hydrology – – now - sec - min - day - year - century - etc. e.g. Climatology Week 14 Micro : runoff plots, infiltrometer, hillslope Meso: sub-catchment, headwaters, reach Macro: whole catchment, region, watershed Seconds: Minutes: Day: Year: Millennium: Wind speeds Incoming solar radiation Anabatic/katabatic winds Annual temperature variation Glacial/interglacial periodicity GEOG2750 – Earth Observation & GIS of the Physical Environment 13 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 Week 14 GEOG2750 – Earth Observation & GIS of the Physical Environment 14 Question… • How can sampling strategies be matched to spatio-temporal scales? Week 14 GEOG2750 – Earth Observation & GIS of the Physical Environment 15 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 Week 14 GEOG2750 – Earth Observation & GIS of the Physical Environment 16 Sampling theory DEM Cell size 1 Cell size 2 1 wavelength Rate amplitude Time Week 14 GEOG2750 – Earth Observation & GIS of the Physical Environment 17 Question… • How do we choose appropriate sampling frequencies? Week 14 GEOG2750 – Earth Observation & GIS of the Physical Environment 18 Advantages of GIS • GIS is good at… – handling spatial data – visualisation of spatial data – integrating spatial data – framework for: analysis and modelling decision support Week 14 GEOG2750 – Earth Observation & GIS of the Physical Environment 19 (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 Week 14 GEOG2750 – Earth Observation & GIS of the Physical Environment 20 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 Week 14 specialist programming languages (e.g. AML and Avenue) universal programming languages (e.g. Java and Visual Basic) access to source code (e.g. GRASS) GEOG2750 – Earth Observation & GIS of the Physical Environment 21 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) Week 14 GEOG2750 – Earth Observation & GIS of the Physical Environment 22 NELUP Week 14 GEOG2750 – Earth Observation & GIS of the Physical Environment 23 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 Week 14 GEOG2750 – Earth Observation & GIS of the Physical Environment 24 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) Week 14 GEOG2750 – Earth Observation & GIS of the Physical Environment 25 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) Week 14 GEOG2750 – Earth Observation & GIS of the Physical Environment 26 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 Week 14 GEOG2750 – Earth Observation & GIS of the Physical Environment 27 Useful web links • NELUP web site – http://www.ncl.ac.uk/wrgi/wrsrl/projects/nelup/ nelup.html Week 14 GEOG2750 – Earth Observation & GIS of the Physical Environment 28 Next week… • Spatial and temporal variability and environmental data – general characteristics of environmental data – environmental data sources – toward integrated databases • Practical: Using Digimap to access OS data products Week 14 GEOG2750 – Earth Observation & GIS of the Physical Environment 29