Contact Dr Daniel Simms
- Tel: +44 (0) 1234 750111
- Email: d.m.simms@cranfield.ac.uk
- ORCID
Areas of expertise
- Digital Agriculture
- Monitoring and Environmental Informatics
- Natural Capital
Background
Daniel Simms graduated from the University of Plymouth in 2000 and worked as a GIS technician for Jacobs Babtie before studying for an MSc in Geographical Information Management at Cranfield. After working as the Spatial Data Manager for Kent County Council, he returned to Cranfield in 2004 to work on a UK Government project on illicit crop monitoring. The project delivered science-based support for decision makers through the integration of multi-resolution satellite and airborne imagery, digital photogrammetry, ground data collection and analysis. During the 6 year project he gained field experience in the operation and deployment of satellite receiving stations, collection of aerial photography and crop data.
Since 2009 Dr Simms has been involved in projects supporting the UNODC in monitoring of illicit crops; the dissemination of soil and terrain data through open web standards as part of the European contribution to a Global Soil Observing System (eSoter); and the integration of spatial hazard datasets based on future projections of extreme weather events as part of the CREW (Community Resilience to Extreme Weather) interdisciplinary project.
Current activities
Dr Daniel Simms is a specialist in applied remote sensing and GIS, researching the integration of imagery and spatial data for land and agricultural information
His interests are in the area of applied remote sensing for improved land and agricultural information. He is currently researching crop detection and cultivation estimation from field to regional scale through the integration of satellite and aerial imagery with ancillary spatial datasets. Of particular interest is the development of methodologies for deriving accurate and timely information from remotely sensed data with a minimal requirement for ground-based sampling.
Dr Simms lectures on the Geographical Information Management MSc Programme and has delivered training in remote sensing and GIS techniques to Afghan nationals under UN-sponsored capacity building projects, and ground data collection for the UK component of the 2013 EU LUCAS survey.
Clients
UK Government
United Nations Office on Drugs and Crime
EPSRC (Engineering and Physical Sciences Research Council)
EUFP7 (EU Framework Programme 7)
ETI (Energy Technologies Institute)
Magellium
DMC International Imaging Ltd
Commodity traders
Publications
Articles In Journals
- Toumasis N, Simms D, Rust W, Harris JA, White JR, .... (2024). Emerging resilience metrics in an intensely managed ecological system. Ecological Engineering, 200
- Okyere FG, Cudjoe DK, Virlet N, Castle M, Riche AB, .... (2024). Hyperspectral imaging for phenotyping plant drought stress and nitrogen interactions using multivariate modeling and machine learning techniques in wheat. Remote Sensing, 16(18)
- Joshi N, Simms DM & Burgess PJ. (2024). Automating the derivation of sugarcane growth stages from Earth observation time series. Remote Sensing, 16(22)
- van der Plas TL, Geikie ST, Alexander DG & Simms DM. (2023). Multi-stage semantic segmentation quantifies fragmentation of small habitats at a landscape scale. Remote Sensing, 15(22)
- Okyere FG, Cudjoe DM, Sadeghi-Tehran P, Virlet N, Riche AB, .... (2023). Machine learning methods for automatic segmentation of images of field-and glasshouse-based plants for high-throughput phenotyping. Plants, 12(10)
- Okyere FG, Cudjoe D, Sadeghi-Tehran P, Virlet N, Riche AB, .... (2023). Modeling the spatial-spectral characteristics of plants for nutrient status identification using hyperspectral data and deep learning methods. Frontiers in Plant Science, 14
- Simms DM, Hamer AM, Zeiler I, Vita L & Waine TW. (2023). Mapping agricultural land in Afghanistan’s opium provinces using a generalised deep learning model and medium resolution satellite imagery. Remote Sensing, 15(19)
- Sanzo-Miró M, Simms DM, Rezwan FI, Terry LA & Alamar MC. (2023). An integrated approach to control and manage potato black dot disease: a review. American Journal of Potato Research, 100(5)
- Beale J, Grabowski RC, Lokidor PL, Vercruysse K & Simms DM. (2022). Vegetation cover dynamics along two Himalayan rivers: drivers and implications of change. Science of The Total Environment, 849(November)
- Hamer AM, Simms DM & Waine TW. (2021). Replacing human interpretation of agricultural land in Afghanistan with a deep convolutional neural network. International Journal of Remote Sensing, 42(8)
- Simms DM. (2020). Fully convolutional neural nets in-the-wild. Remote Sensing Letters, 11(12)
- Hamer A, Simms D & Waine T. (2020). Using deep learning to transfer knowledge between satellite datasets for automated agricultural land discrimination in Afghanistan.
- Campbell S, Simmons RW, Rickson RJ, Waine T & Simms DM. (2018). Using Near-Surface Photogrammetry Assessment of Surface Roughness (NSPAS) to assess the effectiveness of erosion control treatments applied to slope forming materials from a mine site in West Africa. Geomorphology, 322
- Simms DM, Waine TW & Taylor JC. (2017). Improved estimates of opium cultivation in Afghanistan using imagery-based stratification. International Journal of Remote Sensing, 38(13)
- Snapir B, Simms DM & Waine TW. (2017). Mapping the expansion of galamsey gold mines in the cocoa growing area of Ghana using optical remote sensing. International Journal of Applied Earth Observation and Geoinformation, 58
- Simms DM, Waine TW, Taylor JC & Brewer TR. (2016). Image segmentation for improved consistency in image-interpretation of opium poppy. International Journal of Remote Sensing, 37(6)
- Waine TW, Simms DM, Taylor JC & Juniper GR. (2014). Towards improving the accuracy of opium yield estimates with remote sensing. International Journal of Remote Sensing, 35(16)
- Simms DM, Waine TW, Taylor JC & Juniper GR. (2014). The application of time-series MODIS NDVI profiles for the acquisition of crop information across Afghanistan. International Journal of Remote Sensing, 35(16)
- Pourabdollah A, Leibovici DG, Simms DM, Tempel P, Hallett SH, .... (2012). Towards a standard for soil and terrain data exchange: SoTerML. Computers & Geosciences, 45
- Taylor JC, Waine TW, Juniper GR, Simms DM & Brewer TR. (2010). Survey and monitoring of opium poppy and wheat in Afghanistan: 2003-2009. Remote Sensing Letters, 1(3)
