https://geosmartdecisions.co.uk/contact daily 0.75 2021-09-29 https://geosmartdecisions.co.uk/home daily 1.0 2025-06-18 https://images.squarespace-cdn.com/content/v1/60c75cbab577382c5e7fb4a5/9108d5de-d81d-4c47-8efd-c58fe4c8fb3f/IMG_9193.jpeg Home - Services At GSD, we provide GIS support to the planning and forestry sectors as well as carry out surveys, collect and analyse spatial data and provide maps across a range of environmental and land management applications. https://geosmartdecisions.co.uk/our-story-so-far daily 0.75 2025-06-19 https://images.squarespace-cdn.com/content/v1/60c75cbab577382c5e7fb4a5/53cd4b2a-7f9a-41a9-8252-7cd776dbf315/IMG_1477.jpeg https://geosmartdecisions.co.uk/team daily 0.75 2025-06-19 https://images.squarespace-cdn.com/content/v1/60c75cbab577382c5e7fb4a5/62685d4c-5211-4e22-96db-e70f4d826363/IMG_0078.jpeg Team https://images.squarespace-cdn.com/content/v1/60c75cbab577382c5e7fb4a5/3ad30a9d-a539-48ab-8962-2066da09d5d6/IMG_3133.jpeg Team https://images.squarespace-cdn.com/content/v1/60c75cbab577382c5e7fb4a5/9862836f-df3e-4f73-bd3c-60d051d72bd9/IMG_4512.jpeg Team https://geosmartdecisions.co.uk/work-with-us daily 0.75 2022-02-10 https://geosmartdecisions.co.uk/research-and-education daily 0.75 2021-09-23 https://images.squarespace-cdn.com/content/v1/60c75cbab577382c5e7fb4a5/1631022323946-UQFMCYOWVNK1YRQ63X0X/cs4esd.jpg Research and Education https://images.squarespace-cdn.com/content/v1/60c75cbab577382c5e7fb4a5/1631043067564-YEZ6W38DEXKQZC9U9089/IMG_1697.jpg Research and Education https://images.squarespace-cdn.com/content/v1/60c75cbab577382c5e7fb4a5/1631043143448-L7ZJJ5KHNVWRY9GDDWNB/FromTomi.jpg Research and Education https://geosmartdecisions.co.uk/pemba daily 0.75 2024-01-19 https://images.squarespace-cdn.com/content/v1/60c75cbab577382c5e7fb4a5/1627468185044-H3QV218EOTBHUJU6JLUR/pemba1.png Mapping Island Reefs - Mapping Island Reefs GSD was contracted to create satellite derived bathymetry models (SDB) and benthic habitat models for an island close to Tanzania using depth and habitat field survey data together with satellite Earth Observation (EO) imagery. Data used included freely available and atmospherically corrected Sentinel-2 (S2) imagery (10 m spatial resolution) and WorldView3 imagery from Maxar. Satellite Derived Bathymetry (SDB) modelling is a method of surveying shallow waters using satellite imagery. This method of bathymetry can reduce the movement of staff and equipment which can save costs. This SDB was carried out using a custom Python script developed by GSD for several similar bathymetry projects but for which the parameters can be customised for a particular location, imagery or client need. For the benthic habitat mapping, indices and transformation of image bands were computed to reduce the error that derives from water depth on spectral values. GSD utilised Scikit-Learn's Random Forest classification algorithm to perform the habitat mapping. Again a custom-developed GSD python script was used. The outputs provided included figures showing the SDB for the study sites and figures showing the modelled benthic habitat at the study sites. The data was also provided in formats that could be used locally by our client. 3D visualisations of the bathymetry were created and these could be draped over satellite or map imagery. This enabled the client to both explore the data in a very intuitive way. The products that GSD delivered were used to inform our client’s Marine Protected Area Management Plan. The maps will help to record changes in the areas over time and provide a good visual aid to present to the wider stakeholders when discussing why it is so important to protect these marine environments. https://geosmartdecisions.co.uk/peat-surveys daily 0.75 2024-01-19 https://images.squarespace-cdn.com/content/v1/60c75cbab577382c5e7fb4a5/1626180121252-E4V4CJUOPWPK23NQ0WV3/PeatSurvey.jpg https://geosmartdecisions.co.uk/orthorectification daily 0.75 2024-01-19 https://images.squarespace-cdn.com/content/v1/60c75cbab577382c5e7fb4a5/1626180349116-KS0EYKTUZDVFEFV53KBX/orthorectification.jpeg Forestry - Spatial Data Management - FORESTRY - SPATIAL DATABASE MANAGEMENT GSD has successfully delivered many contracts over the last five years to NRW to enhance and add value to their in house forestry compartment database. GSD provides GIS support to update and analyse the Welsh Government Woodland Estate (WGWE) forestry database using a bespoke module for ESRI’s ArcMap as well as a range of open-source software. Forester Web training and input has also recently begun. Much of the work involves liaising with the clients' foresters and planners as well as liaising with and coordinating GSD’s specialist surveyors. This work is critical for our clients' forest resource planning programme and for maintaining their UK Woodland Assurance Standard (UKWAS) accreditation. The work involves inspecting satellite imagery to improve the clients' forestry datasets and identifying anomalies within the data. Our team of experienced woodland field surveyors will survey areas and collect data that GSD analysts will then input into NRW’s database. GSD has introduced innovative ways to both improve accuracy and decrease the time taken to find discrepancies in the delivery of this project. This has included introducing using mobile apps for field data collection. Regular updates are provided to the client in the form of reports and maps some of which have been automated to decrease the time taken and to ensure consistency. https://geosmartdecisions.co.uk/3keel daily 0.75 2024-01-19 https://images.squarespace-cdn.com/content/v1/60c75cbab577382c5e7fb4a5/1631885728358-3SYEZVCAV4HNEIHB1J8U/slope-failure-web-2.png Understanding the Impacts of Climate Change - UNDERSTANDING THE IMPACTS OF CLIMATE CHANGE Climate change has the potential to impact all forms of current day life, however it will also have a huge and, until now, unquantified impact upon historic, iconic and culturally significant sites across the UK. That is why GSD were contracted to partner with sustainability advisors to develop what has been called a “game changer” map, estimating the relative risks to countryside locations, monuments, coastlines and historical sites across the Wales, Northern Island and England. To provide this information at a local scale, a hex grid was created to enable zonal statistics on climate related data to be drawn and identify locally specific risks that would enable the client to take specific action to protect sites. This grid was derived using the specific site locations that struck a balance between conflating data at appropriate scales and providing localised levels of detail. Finally, to fully visualise the results and enable optimal engagement for the client with stakeholders and partners, the map was developed into an online web mapping tool. This dataset was then populated with existing data on climate change related events, encompassing as many impacts as possible, ranging from heat, humidity, flood risk, slope stability, coastal erosion, soil heave and storm frequency. Analysis was then conducted into how these events would change into the future, providing data on the 2020 and future (2060) risks to individual sites. This was calculated using a worst-case model of no intervention on current emission rates. The important findings of this analysis has shown that; 71% of the sites could face medium-high risks from climate change related impacts by 2060. A rise from 30% in 2020. Sites in the highest risk category will more than double, from 1453 in 2020, to 3861 in 2060. Heat and Humidity will be the largest threats, particularly in the South East, whilst storm damage, landslides and flooding will also become more common and widespread. One third of sites will expect to see >15 days a year with temperatures over 30 degrees Celsius. The results of this project provided the client with a “flagging tool”, which aids their observations of sites and allows early intervention to mitigate any damage that may be caused by the changing climatic conditions. This further allows landowners and councils to come together with a joined-up approach to dealing with arising problems, such as slowing water runoff, peat bog or river restoration and natural shade construction. Since the initial project GSD have worked with the client to be able to provide data for different climate related threats for other organisations working with sites across the UK. Having parts of the processing already automated meant that we could provide the new datasets quickly and efficiently. The mapping tool can be found at https://nationaltrust.maps.arcgis.com/apps/webappviewer/index.html?id=0bc569747210413a8c8598535a6b36e1 https://geosmartdecisions.co.uk/dwd-regener8-esco daily 0.75 2024-01-19 https://images.squarespace-cdn.com/content/v1/60c75cbab577382c5e7fb4a5/1626795805883-CE2LRTRAN1X8IA5WSGBK/image.png https://geosmartdecisions.co.uk/ztv daily 0.75 2024-01-19 https://images.squarespace-cdn.com/content/v1/60c75cbab577382c5e7fb4a5/1626205531681-YWU97WM97F98WPYBOKC2/ztv.png Visibility Assessment - Sensitive Landscapes - VISIBILITY ASSESSMENT - SENSITIVE LANDSCAPES Zone of Theoretical Visibility (ZTV) mapping offers a model of the landscape surfaces that are visible from an observation point. It is often a very important aspect of the environmental planning process. Natural Resource Wales (NRW) instructed Geo Smart Decisions to create and present strategic evidence on the visibility of National Parks and Areas of Outstanding Natural Beauty AONB) to their surrounding landscapes in Wales. The key and majority audience for this work are those considering visual impact issues for strategic planning purposes. The approach applied uses computer GIS software (‘Geographical Information Systems’) to compute viewsheds or ‘Zones of Theoretical Visibility’ (ZTVs) in nine Designated Landscapes with settings in Wales, these were: Snowdonia National Park, Brecon Beacons National Park, Pembrokeshire Coast National Park, Wye Valley AONB (partly in Wales), Shropshire Hills AONB (wholly in England), Llŷn AONB, Clwydian Range and Dee Valley AONB, Gower AONB and Anglesey AONB. ZTV calculation can provide a binary (visible or non-visible) product delineating regions theoretically visible for a human observer located at specific vantage points. Secondly, for regions that are not directly visible to the human observer, an estimate of the height (above ground level) required for an object to become visible can also be created. ZTV analysis can either be carried out on a single observer point, or the combination of many. When undertaking the latter analysis, binary viewsheds can become cumulative, combining the visible areas from all observer points. The cumulate viewshed can subsequently form heatmaps, showing regions visible from multiple observer points located throughout the landscape. Whilst the models assume a ‘bare earth’, i.e., ones that do not contain surface features such a vegetation artificial structures, they do account for factors such as atmospheric aerosol conditions and the curvature of the earth resulting in broad yet strategic estimates. To create these data, observer points had to first be generated across the landscapes within and surrounding national parks and areas of outstanding natural beauty. In typical ZTV deployments, these points are selected manually, based on the location development. However, due to the project’s national scale, comprising of nine specific areas and their surrounding regions, a method for automatically generating observer points at critical locations had to be developed. The points were derived utilising the topographic features extracted from the digital elevation model used in the ZTV calculation to identify observer points that identified the total viewable area with the least number of points. To refine this methodology, extensive testing was conducted refining the appropriate number of points, the resolution of the DEM and various available ZTV algorithms, working closely with the client to create a bespoke model that identified regions that corresponded with previous work. The resultant method generated thousands of observer points, for which, multiple ZTVs were computed to identify visible areas, estimates of heights required to become visible, and visibility heatmaps. To further enhance the project, GSD also provided analysis specific to NRW’s LANDMAP Visual and Sensory aspect areas. This then provided NRW with complete coverage of theoretical visibility over an entire country, alongside a national visual impact model for protected areas in a first-of-its-kind product. Project outputs and the final report are in the public domain and can be obtained from NRW. https://geosmartdecisions.co.uk/urban-tree-canopy daily 0.75 2024-01-19 https://images.squarespace-cdn.com/content/v1/60c75cbab577382c5e7fb4a5/1626205896004-OCB9PHKORQA3KQZ8N5OE/UTC2.jpg Quantifying Urban Tree Canopy using GIS - QUANTIFIYING URBAN TREE CANOPY USING GIS This Wales-wide project was assigned to GSD by Natural Resources Wales (NRW) and looked to update the data held on Wales’ Urban Tree Canopy Cover by comparing data with updated aerial imagery. From specifications set by the client, processes were created for a consistent approach to the analysis and quality assurance of the data created across a team of five analysts. Our technical lead kept in regular contact with the rest of the team, monitoring progress and regularly reporting on progress with our client. The data were processed using a custom GSD python script and open-source GIS tools. Quality assurance and consistency checks were carried out regularly by the technical lead using a range of different approaches developed at the start of the project; these evolved as the project developed and in response to the clients' needs. At the end of the project, GSD summarised the results of the project and recommendations for future processes in a final report that is now available from NRW and is in the public domain.. https://geosmartdecisions.co.uk/neom daily 0.75 2024-01-19 https://images.squarespace-cdn.com/content/v1/60c75cbab577382c5e7fb4a5/1626206193792-VQV5MFDBOOIODTRNFVRR/neom.png Multi-Temporal Earth Observation to Map Vegetation Dynamics in KSA - MULTI-TEMPORAL EARTH OBSERVATION TO MAP VEGETATION DYNAMICS IN KSA GSD was tasked with providing remotely sensed analysis for a very large region of Saudi Arabia for this confidential client. The goals of this project were to provide historical vegetation analysis as well as an assessment of current land cover patterns. This project contained a variety of challenges, from identifying vegetation cover in desert conditions, to mapping them coherently through time. To achieve these goals, the entire Landsat satellite archive was used, spanning 30 years of data collection. To analyse this very large dataset, annual composites of the region were created to ensure cloud free images with minimal aerosol presence. From these, a variety of optical indices and band data were analysed in a pixel stack, allowing highlights in trend changes in vegetation productivity and extent to be extracted. This was then modelled to identify hotspots of vegetation change, high productive areas and trends were identified in order to predict future change. From this analysis, both map-based and spatial dataset products were created that condensed the large amount of processed data into interpretable products with respect to planning and conservation applications. To compliment this, a modern-day land cover map was also created using higher resolution Sentinel-2 data. Works here focused on the identification of ‘speculative’ land covers, with no training data available to train a specific model. Here, methods were developed to identify distinct terrestrial and marine extents using the spectral data, as well as elevation and other radar-derived products. https://geosmartdecisions.co.uk/dahari daily 0.75 2024-01-19 https://images.squarespace-cdn.com/content/v1/60c75cbab577382c5e7fb4a5/1626207019413-2O0RC3UUFDEWJ96U9E2O/dahari.png Island Land-Cover Mapping - ISLAND LAND-COVER MAPPING GSD has in house experts experienced in identifying land cover from remotely sensed data - satellite Earth Observation. GSD tackled this task over a multitude of spatial and temporal scales. At GSD we pride ourselves in keeping abreast with the latest mapping techniques, to stay on the cutting edge of remote sensing and provide the highest quality with upmost confidence in our results. In the case of this project mapping in the Comoros Islands, the goals of this project were to create and deploy a mapping framework that could accurately map the technically challenging terrain to identify in particular both natural and disturbed forest types. This was to be achieved using a framework that was solely built on utilising freely available satellite data. To achieve these aims, GSD consulted with the client to build a method from the ground up, discussing the land cover types they were aiming to map and how best this might be done at different scales. GSD then worked to build a training data library so that a machine learning classifier could be deployed for optimum identification of land covers. To overcome the unique challenges when mapping the tropical and high rainfall forests of the study area, GSD first explored the available satellite platforms, from optical, radar and lidar. Here GSD incorporated multiple sensors together, to provide a more consistent product that mitigated against single sensor inhibition. As well as this, GSD also developed seasonal compositing techniques to create high quality cloud free optical images. This satellite data was then used to train a high-performance machine learning classifier, to accurately identify forest classes and provide mapping products that could be used for client analysis. https://geosmartdecisions.co.uk/frp daily 0.75 2024-01-19 https://images.squarespace-cdn.com/content/v1/60c75cbab577382c5e7fb4a5/1626206631121-EKAGWMOIUXGWPT5OC651/FRP.jpg GIS and Mobile Mapping for Forest Resource Planning - GIS AND MOBILE MAPPING FOR FOREST RESOURCE PLANNING Forest Resource Plans (FRP) are used by Natural Resources Wales (NRW) to support the delivery of sustainable forest management using an ecosystem approach. They set out long-term objectives and are the basis for 10-year programmes of work. The plans are a requirement for forest certification and form the basis for regulatory approval for the work required. They are a key tool for supporting communication with stakeholders. GSD associates are expert foresters and we worked closely utilising our GIS expertise to produce an FRP for NRW in the North Wales region. To do this, we started by reviewing the existing plans for the forest taking into regard any relevant policies, legislation and guidance. Next, we carried out a detailed silvicultural survey on the forest using our extensive forestry experience. Throughout the process, various maps and reports were created that were required by our clients. To make sure that the maps generated matched the reports generated for other plans we carefully copied the styling and formatting used. Once the initial field work and assessment of existing datasets was carried out and maps produced using GSD GIS consultants, both internal (to our client) and external stakeholders were engaged with for the consultation stage. The results from this then fed into the final plan for the forest. From this, GSD and Associates then developed the final FRP Objectives, relating to the different aspects and areas of the forest. https://geosmartdecisions.co.uk/jubail-island daily 0.75 2024-01-19 https://images.squarespace-cdn.com/content/v1/60c75cbab577382c5e7fb4a5/1626207250562-JVGFHPKGHYB6BM0NONH9/jubail_island.png Island Habitat Mapping UAE - ISLAND HABITAT MAPPING UAE GSD sourced and pre-processed very high resolution spatial data (2 m x 2 m pixel sizes) imagery for this detailed habitat mapping project. After atmospherically correcting the imagery using python scripting and open source libraries, training data was generated in close consultation with the client and was used to generate habitat models, which were then discussed iteratively with the client. There were mangroves on site which were of high conservation value and as the client was developing a residential development with a focus on maintaining the in situ biodiversity, mapping the extent and condition of these was of significant interest to the client. GSD’s work expanded to a focussed study, on the mangrove habitat, using spectral indices to explore the condition of the mangrove and its resilience on site. The aim of this second piece of work was to use satellite imagery to assess whether there is a relationship between mangrove health, using NDVI (a spectral index called Normalised Difference Vegetation Index) as a proxy, and percentage of time mangrove areas are inundated. The expected relationship tested was that healthy mangrove displayed higher NDVI values where inundation times were relatively high. This was investigated using data on a pixel by pixel basis. Mangrove areas from the Jubail habitat map were used to extract the NDVI values of only the mangroves. The areas were converted to points and at each of the point locations the NDVI and the inundation value from the inundation dataset was extracted. Areas of mangroves that were smaller than 300 m2 were removed from the analysis; since they are most likely to have an influence from the soil reflectance. The resulting areas were converted to points, inundation and NDVI values were extracted, values were plotted and statistics were produced. These larger areas were also analysed by extracting the minimum, maximum, median, modal, and mean NDVI and inundation values for each area rather than using each point within the area. This assessed correlation between the mangrove health and inundation time on a larger scale, thereby reducing influences of soil reflectance and the difference with the spatial resolution of the inundation model. https://geosmartdecisions.co.uk/the-world-islands daily 0.75 2024-01-19 https://images.squarespace-cdn.com/content/v1/60c75cbab577382c5e7fb4a5/1626207416841-LEA5K58OI80ZJSS944CX/the_world_islands.png Water Quality - The World Islands - WATER QUALITY - THE WORLD ISLANDS GSD used satellite Earth Observation to analyse freely available satellite imagery to contribute to our client’s understanding of patterns in water quality both in the local area and in the region. This was to enable a more informed assessment of the risk of algal blooms occurring in close proximity. The work was split into three main areas, that which considered MODIS satellite data for the region, that which used Landsat imagery to investigate turbidity and chlorophyll concentrations and that which used Sentinel 2 satellite imagery to model the spatial variations of chlorophyll-a and turbidity. The main remote sensing instruments that have been designed to measure chl-a are SeaWiFS and MODIS. SeaWiFS was designed to primarily quantify chlorophyll produced by marine phytoplankton; however, this stopped collecting data in December 2010. MODIS has been providing many ocean water quality products since 2002 including: total suspended sediments (TSS), sea surface temperature (SST), and Chlorophyll-a (chl-a). Both satellites are used for regional-to-global monitoring of chl-a and thus have a coarse spatial resolution (1-4 km). Data from these missions are freely available from the USGS. GSD’s work on this project utilised the Normalised Difference Chlorophyll Index (NDCI) applying this to Sentinel-2 imagery. https://geosmartdecisions.co.uk/services-overview daily 0.75 2025-06-18 https://images.squarespace-cdn.com/content/v1/60c75cbab577382c5e7fb4a5/1627467463607-WKNWP8TAAHXQWCIYUOSV/ZTV1+%281%29.png Services Overview https://images.squarespace-cdn.com/content/v1/60c75cbab577382c5e7fb4a5/1627467548269-GJ7DW0QQUN3F8D32OR85/orthorectification.jpeg Services Overview https://images.squarespace-cdn.com/content/v1/60c75cbab577382c5e7fb4a5/1627467608466-GYUP5Q1L56DYRQXZ1H5I/neom.png Services Overview https://images.squarespace-cdn.com/content/v1/60c75cbab577382c5e7fb4a5/1627467807152-XRQ1NOV671SS4R4YWENS/dwd3.png Services Overview https://images.squarespace-cdn.com/content/v1/60c75cbab577382c5e7fb4a5/1627468146825-Y3NV57LI08GPQICLL8X6/UTC.jpeg Services Overview https://images.squarespace-cdn.com/content/v1/60c75cbab577382c5e7fb4a5/1627468325847-N8G7OFS7I4SROFIJBII1/Phantom4.jpg Services Overview https://images.squarespace-cdn.com/content/v1/60c75cbab577382c5e7fb4a5/1631043729686-NFH8ZJ1N7ZCGGFWMO9FM/IMG_1697.jpg Services Overview https://images.squarespace-cdn.com/content/v1/60c75cbab577382c5e7fb4a5/1632412836899-F5FBY5MWVTRC8CTMC76E/michael-roach-TqlmoxKO1R8-unsplash.jpg Services Overview https://images.squarespace-cdn.com/content/v1/60c75cbab577382c5e7fb4a5/61695cda-f869-4277-9654-6a8f2443d8a3/PeatSite_B_SurveyArea_10_Image8.jpg Services Overview https://geosmartdecisions.co.uk/echoes daily 0.75 2021-09-23 https://images.squarespace-cdn.com/content/v1/60c75cbab577382c5e7fb4a5/1631042704336-YV4WP5P9CTFOLC0DEH0E/IMG_1697.jpg ECHOES Ringed Curlew. Photo: Rachel Taylor, BTO https://images.squarespace-cdn.com/content/v1/60c75cbab577382c5e7fb4a5/1631042831631-IJ2I3IRIUN3XCX9UWUH7/BTO-2019-B11-Edmund-Fellowes--1880_2_original_GWFG+%281%29.jpg ECHOES - Make it stand out Greenland White-fronted Goose. 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