Using spectral indices to estimate water content and GPP in Sphagnum moss and other peatland vegetation

Peatlands provide important ecosystem services including carbon stroage and biodiversity conservation. Remote sensing shows potential for monitoring peatlands, but most off-the-shelf data produces are developed for unsaturated environments and it is unclear how well they can perform in peatland ecosystems. Sphagnum moss is an important peatland genus with specific characteristics which can affect spectral reflectance, and we hypothesized that the prevalence of Sphagnum in a peatland could affect the spectral signature of the area. This study combines results from both laboratory and field experiments to assess the relationship between spectral indices and the moisture content and GPP of peatland (blanket bog) vegetation species. The aim was to consider how well the selected indices perform under a range of conditions, and whether Sphagnum has a significant impact on the relationships tested. We found that both water indices tested (NDWI and fWBI) were sensitive to the water content changes in Sphagnum moss in the laboratory, and there was little difference between them. Most of the vegetation indices tested (the NDVI, EVI, SIPI and CIm) were found to have a strong relationship with GPP both in the laboratory and in the field. The NDVI and EVI are useful for large-scale estimation of GPP, but are sensitive to the proportion of Sphagnum present. The CIm is less affected by different species proportions and might therefore be the best to use in areas where species cover is unknown. The PRI is shown to be best suited to small-scale studies of single species

Assessing the reliability of peatland GPP measurements by remote sensing: from plot to landscape scale

Estimates of peatland carbon fluxes based on remote sensing data are a useful addition to monitoring methods in these remote and precious ecosystems, but there are questions as to whether large-scale estimates are reliable given the small-scale heterogeneity of many peatlands. Our objective was to consider the reliability of models based on Earth Observations for estimating ecosystem photosynthesis at different scales using the Forsinard Flows RSPB reserve in Northern Scotland as our study site. Three sites across the reserve were monitored during the growing season of 2017. One site is near-natural blanket bog, and the other two are at different stages of the restoration process after removal of commercial conifer forestry. At each site we measured small (flux chamber) and landscape scale (eddy covariance) CO2 fluxes, small scale spectral data using a handheld spectrometer, and obtained corresponding satellite data from MODIS. The variables influencing GPP at small scale, including microforms and dominant vegetation species, were assessed using exploratory factor analysis. A GPP model using land surface temperature and a measure of greenness from remote sensing data was tested and compared to chamber and eddy covariance CO2 fluxes; this model returned good results at all scales (Pearson’s correlations of 0.57 to 0.71 at small scale, 0.76 to 0.86 at large scale). We found that the effect of microtopography on GPP fluxes at the study sites was spatially and temporally inconsistent, although connected to water content and vegetation species. The GPP fluxes measured using EC were larger than those using chambers at all sites, and the reliability of the TG model at different scales was dependent on the measurement methods used for calibration and validation. This suggests that GPP measurements from remote sensing are robust at all scales, but that the methods used for calibration and validation will impact accuracy

Measuring peatland carbon uptake by remote sensing

Peatlands are an important ecosystem for carbon storage, due to their semi-permanent water saturated condition which inhibits decomposition. Many peatlands in the UK have been degraded through human land use to the point where they are releasing carbon, and restoration is now a priority to protect these landscapes and the carbon held within them. Most methods of monitoring peatland restoration are small-scale and expensive. Remote sensing methods, however, are large-scale and often freely available to the end user. This project considers the potential benefits of using remote sensing to estimate peatland carbon uptake, and describes experiments which answer research questions in this area. Much of the work was done within the Forsinard Flows RSPB reserve, which has a chronosequence of blanket bog sites at different stages of restoration. A laboratory experiment on the effects of drought stress on the carbon flux and spectral reflectance of Sphagnum moss was first completed. This was followed by a field experiment to assess factors affecting peatland GPP and whether these could be detected by remote sensing data. The final part of this project involved the development of a Temperature and Greenness (TG) model using remote sensing to estimate GPP across blanket bog ecosystems. The project used both flux chamber and eddy covariance techniques to measure carbon uptake and compared the results to spectral reflectance at small-scale using a hand-held spectrometer, and large-scale using satellite data from MODIS. The results from these experiments suggest that spectral indices, and models using them, can give information about Sphagnum drought stress, seasonal change in peatland vegetation, and restoration progress, and are functional at scales from a few centimetres up to one kilometre. Next steps could include calibrating the developed model for a range of sites to broaden its applicability, and further work into monitoring water table depth using remote sensin

Põhjapoolkera soode põhjaveetaseme seire täiendamine optiliste ja termiliste satelliidiandmete abil

Väitekirja elektrooniline versioon ei sisalda publikatsiooneSood on märgalad, kuhu taimede mittetäieliku lagunemise tõttu on talletunud palju turvast, , mis sisaldab suurt kogust süsinikku. Turvas on moodustunud aastatuhandete jooksul niisketes tingimustes. Inimtegevuse surve ning globaalne kliima soojenemine on põhjustanud soode kuivenemise ning seetõttu talletunud süsiniku lendumist kasvuhoonegaaside (KHG), peamiselt süsihappegaasina (CO2), mis põhjustab omakorda kliima soojenemist. Ka teised KHG-d, metaan ja naerugaas, lenduvad soodest ja nendegi puhul on olulisimaks teguriks põhjaveetaseme langus. Seetõttu on täpsem teadmine soode põhjaveetaseme muutustest olulise tähtsusega Maa kliima muutumise ennustamisel. Käesolev väitekiri annab ülevaate uuringutest, mille välitööde osa tehti Eestis Endla looduskaitsealal Männikjärve ja Linnusaare rabades, võrdlevad analüüsid aga sarnaste soodega Soomes, Rootsis, Kanadas ja USA-s. Töö peamiseks eesmärgiks oli täiendada Põhjapoolkera soode põhjaveetaseme sattelliidi-põhist kaugseiret, mille alusel hinnati tulemuste olulisust, võrreldes seda soodes tehtud kohapealsete mõõtmistega. Esmakordselt näidati, et kasutatud optiliste ja termiliste spektrite signaalid, mis on turba veesisalduse ja rohelise (kasvuperioodi) taimkatte määramise seisukohast kõige tundlikumad, , iseloomustavad usaldusväärselt soode põhjaveetaset. Täiendava uuringuga taimkatte mõjust seosele leiti vastav niiskusindeks ja selle kõige usaldusväärsemad kohad (pikslid) soodes, mis omakorda võimaldas üldistada tulemust kogu soo ulatuses. Algselt Eesti soodes välja töötatud metoodika õigustas ennast ka teistes soodes nii Euroopas kui ka Põhja-Ameerikas ning seda soovitatakse kasutada edasistes uuringutes.Peatlands are a type of wetlands, which have accumulated huge quantities of carbon as a plant matter. The accumulation of this carbon occurred in water-logged conditions and took thousands of years. Global climate change can lead to the drying of peatlands and, thus, the release of accumulated carbon in the form of greenhouse gas – carbon dioxide (CO2). Releasing CO2 into the atmosphere will amplify global climate change. Therefore, knowledge of water table depth in peatlands is essential for predicting future Earth climate. In this thesis, we present results of our four articles integrated together and they share one general aim – to improve the estimation of water table depth in Northern Hemisphere peatlands using remotely sensed information in thermal and optical spectra. We evaluated the usefulness of this information to detect the temporal and spatial changes in water table depth based on in-situ data collected in peatlands. Particularly, we used signals sensitive to moisture and green vegetation, and utilized them in several indices that indicate soil moisture conditions. In this thesis, we have determined, for the first time, that used in our study moisture index based on optical data has a strong temporal relationship with in-situ measured water table depth in peatlands. Moreover, we discussed the impact of vegetation cover on that relationship and suggested a method for selecting the most informative pixels of moisture index. In conclusion, we suggest the future perspectives of using optical-based moisture index together with challenges it might have.https://www.ester.ee/record=b536954

A Multiscale Productivity Assessment of High Andean Peatlands across the Chilean Altiplano Using 31 Years of Landsat Imagery

The high Andean peatlands, locally known as "bofedales", are a unique type of wetland distributed across the high-elevation South American Altiplano plateau. This extensive peatland network stores significant amounts of carbon, regulates local and regional hydrological cycles, supports habitats for a variety of plant and animal species, and has provided critical water and forage resources for the livestock of the indigenous Aymara communities for thousands of years. Nevertheless, little is known about the productivity dynamics of the high Andean peatlands, particularly in the drier western Altiplano region bordering the Atacama desert. Here, we provide the first digital peatland inventory and multiscale productivity assessment for the entire western Altiplano (63,705 km(2)) using 31 years of Landsat data (about 9000 scenes) and a non-parametric approach for estimating phenological metrics. We identified 5665 peatland units, covering an area of 510 km(2), and evaluated the spatiotemporal productivity patterns at the regional, peatland polygon, and individual pixel scales. The regional assessment shows that the peatland areas and peatlands with higher productivity are concentrated towards the northern part of our study region, which is consistent with the Altiplano north-south aridity gradient. Regional patterns further reveal that the last seven years (2011-2017) have been the most productive period over the past three decades. While individual pixels show contrasting patterns of reductions and gains in local productivity during the most recent time period, most of the study area has experienced increases in annual productivity, supporting the regional results. Our novel database can be used not only to explore future research questions related to the social, biological, and hydrological influences on peatland productivity patterns, but also to provide technical support for the sustainable development of livestock practices and conservation and water management policy in the Altiplano region.Open access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Simulating urban soil carbon decomposition using local weather input from a surface model

Non peer reviewe

Airborne Hyperspectral Evaluation of Maximum Gross Photosynthesis, Gravimetric Water Content, and CO2 Uptake Efficiency of the Mer Bleue Ombrotrophic Peatland

Peatlands cover a large area in Canada and globally (12% and 3% of the landmass, respectively). These ecosystems play an important role in climate regulation through the sequestration of carbon dioxide from, and the release of methane to, the atmosphere. Monitoring approaches, required to understand the response of peatlands to climate change at large spatial scales, are challenged by their unique vegetation characteristics, intrinsic hydrological complexity, and rapid changes over short periods of time (e.g., seasonality). In this study, we demonstrate the use of multitemporal, high spatial resolution (1 m(2)) hyperspectral airborne imagery (Compact Airborne Spectrographic Imager (CASI) and Shortwave Airborne Spectrographic Imager (SASI) sensors) for assessing maximum instantaneous gross photosynthesis (PGmax) in hummocks, and gravimetric water content (GWC) and carbon uptake efficiency in hollows, at the Mer Bleue ombrotrophic bog. We applied empirical models (i.e., in situ data and spectral indices) and we derived spatial and temporal trends for the aforementioned variables. Our findings revealed the distribution of hummocks (51.2%), hollows (12.7%), and tree cover (33.6%), which is the first high spatial resolution map of this nature at Mer Bleue. For hummocks, we found growing season PGmax values between 8 mu mol m(-2) s(-1) and 12. tmol m(-2) s(-1) were predominant (86.3% of the total area). For hollows, our results revealed, for the first time, the spatial heterogeneity and seasonal trends for gravimetric water content and carbon uptake efficiency for the whole bog.Peer reviewe