HIGH RESOLUTION REMOTE SENSING FOR LANDSCAPE-SCALE RESTORATION OF PEATLAND

RELEVANCE & SCIENTIFIC VALUE Upland peatlands offer vital ecosystem services from carbon storage, biodiversity, water provision, flood protection, aesthetic/recreational value, to economic value from grouse shooting and grazing. Due to historic and current atmospheric pollution, inappropriate land management and wildfires, large areas of peatlands are degraded. Peatlands restoration is one of the main tools to adress government PSA targets for biodiversity, soil and water protection in uplands. Restoration is of crucial importance to protect UK soil carbon stores, as more than 50% of UK soil carbon is stored in peat and is rapidly lost. Restoration efforts have started to restore bare peat at a landscape scale in the UK; the Moors for the Future Partnership (MFF) is revegetating 5km2 of bare peat within the Peak District. Monitoring is of pivotal importance to judge the success of the restoration, but traditional approaches with field-based permanent plots surveys are insufficient in terms of time and resource commitment. Natural England (NE) wish to explore remote sensing (RS) as an alternative, so are funding the CASE element via MFF. Key issues are to what extent can RS provide information on habitat condition (% cover, species composition) for reseeded peat soils, and how feasible is this in operational terms. AIM The project addresses the key problem of upscaling from permanent plots to landscape. It will evaluate the ability of high spatial and spectral resolution RS to distinguish between moorland restoration treatments and monitor changes over time using the case study of the Moors for the Future restoration programme in the Peak District National Park. The special case of remote sensing of sparse vegetation growth on peat soils offers a stimulating and feasible PhD topic. RESEARCH QUESTIONS 1. How well can 'restoration classes' (age-treatment of reseeding, gully blocks, key species) be distinguished on archive airborne hyperspectral images, aerial photographs and high resolution satellite images? 2. How accurately can plot data can be upscaled to classify restoration classes using a SPECIM (AISA Eagle/Hawk) airborne hyperspectral image & simulated satellite images? 3. How accurately can plot data can be upscaled to estimate key vegetation condition variables (e.g. % cover and presence of key species)? What are the thresholds? This presents a new challenge as the reflectance of peat and live plants are similar, unlike less organic soils. 4. What are the optimal times in the phenological cycle for image acquisition and how feasible is it to use hyperspectral data to monitor over time? 5. What are the costs, benefits, feasibility and geographic transferability of alternative images for operational monitoring? What are the critical sensor requirements for operational monitoring from space? BENEFITS OF THE COLLABORATION NE/MFF will gain an evaluation of the feasibility of using high spatial & spectral resolution RS to monitor peatland restoration. For the student, policy-relevance will be maximised. NE/MFF will provide expertise in ecology, access to key databases and excellent knowledge transfer facilities. AB has a CASE student with whom the student can work. AB and JM have a research collaboration spanning 5 years. EQUIPMENT MFF will provide dGPS. A spectroradiometer will be loaned from NERC-FSF & Sheffield. Manchester has the image processing facilities required and a Spatial Data Research Officer. SUPERVISION AB (MFF) will provide specialist training in habitat survey and knowledge transfer, JM in remote sensing. JM was PI for 3 sets of airborne data for the Peak District and supervised a PhD on RS of peat (awarded 2007). She serves on the Steering Committee of NERC's Ariborne Research & Survey Facility. The student will work in a strong research environment of >160 PhD students (93% completion rate). S/he will take part in the School's well-established research skills training programme