Project Highlights:

  • Mapping desert sands and features with satellite and GIS technology
  • Modelling complex dune field patterns at multiple scales
  • Reconstructing the environment in the context of human migration



Active sand seas are present in many arid environments across the globe. Normally associated with hot, dry conditions their location, extent and dune forms, are key indicators of past and current environmental processes. Dune patterns are known to develop over timescales of thousands of years, and as such they document past geomorphic and climatic situations. A better understanding of these relationships can help increase our knowledge of dune form controls and interpretation of stratigraphic evidence to reconstruct past climatic conditions.

In any one sand sea the morphological classification of dunes often varies spatially, a firm indication that at more localised scales there is a deeply complex mix between climatic and geomorphic processes, with bedform patterns developing due to self-organisation.

Transitions between different dune types are not well understood, particularly where there is frequent but intermittent fluvial activity in a predominantly aeolian environment. As a result, spatial distribution of dune-form, is a function of these disturbances both temporally and spatially. The boundary controls need to be assessed as they ultimately affect the evolution of dune field form in the sand seas.

In central Saudi Arabia, extensive sand seas that are on the margins of current weather systems such as the Indian monsoon, are likely to be highly sensitive to localised controls and longer term climatic change. The project aims to connect the present relationships between different dune forms and environmental processes to better understand the local controls embedded within the regional climate and test how far these processes can be simulated with a dune development model. The project will involve satellite-derived data mapping the variation in dune forms and local topographic characteristics. Using this evidence a dune model will then be run to simulate dune development under single and multiple, local and regional conditions from source to sink.

This research will provide key information for palaeo-environmental reconstruction in a region where little is known about climatic changes, ever more relevant because central Saudi Arabia has been elevated in importance for the facilitation of historical human migration.

Figure 1: SandSea – Central KSA


Digital elevation data GDEM and MODIS images will be used to map the extent and mineral characteristics of the sand seas in central Saudi Arabia. Collected samples will be analysed and the findings will drive the dune formation simulation model

MODIS imagery will be used to spectrally identify the sand sea boundaries using image classification techniques and to identify spectral variations caused by subtle mineralogical changes. The images will also be used to assist with the DEM work to identify dune types and extent.

The DEM data, GIS and statistical techniques will be applied to: (i) identify and map geomorphic patterns (ii) look for underlying structural differences in and under the sand sea using the technique ‘back stripping’, (iii) interpolation to model the underlying geological structures (iv) map the hydrological patterns and morphology around the sand sea to identify local controls in the region; (v) identify and model complex dune patterns.

The dune simulation model will be run at multiple scales to reconstruct sand movement under different climate regimes to better understand the potential of the region to facilitate human migration.

Training and Skills

The student will gain training in analysis of remote sensing data, specific GIS techniques, and understanding and recognising desert sand dune features. In addition, the development and use of a cellular automata dune model.

Students will also receive training in the communication of science to academics as well as the general public, students, media etc. using a range of formats such as presentations, publications, interviews, social media and so forth.


Year 1: Literature review. Download MODIS images and DEM. Pre-process images and image processing to define study area and build data set of of study site. GIS analysis ofDEM for (i-iv method). Submit manuscript to international conference.

Year 2: Complete GIS, Image processing of MODIS for mineralogical mapping, geochemical analysis of lab results. Set upand run dune model simulations. Preparemanuscriptfor publication. Submit abstract for international conference.

Year 3: Critically appraise results. Present at conference. Finalise paper. Write up thesis.

Partners and collaboration (including CASE)

Partners offer a range of skills including geological, palaeoenvironmental, modelling, Remote sensing, GIS and field experience of the study area.

Sue McLaren is a reader in Geography at the University of Leicester and has a vast experience of dryland environments

Joerg Kaduk is a senior lecturer in Environmental modelling at the University of Leicester and is experienced with a range of software modelling techniques.

Andrew Bradley is a Research Fellow at Nottingham University, and is an experienced remote sensing and GIS analyst.

Ahmed Al Dughairi is a lecturer at the University of Qassim in central Saudi Arabia and has extensive field knowledge of the area.

Further Details

Dr S McLaren sjm11@le.ac.uk