Remote Sensing-Based Estimation of Below-Ground Sediment Carbon in Seagrass Habitats of Bahrain Waters

This study investigates the role of seagrass habitats in carbon sequestration by quantifying sediment carbon and seagrass coverage in Bahrain’s coastal waters. Recognised as significant carbon sinks, seagrass ecosystems are crucial for marine biodiversity and climate change mitigation. The study uses a twofold approach: assessing sediment carbon content variation across sampling points and estimating seagrass cover with remote sensing techniques using Sentinel-2 and Landsat 8 data. The accuracy of remote sensing-based models for estimating sediment carbon in seagrass is evaluated. Findings show higher sediment carbon concentrations in southern sites and an increase in average sediment carbon content in 2019, despite declines in seagrass coverage and stored sediment carbon. The Landsat 8-based model proved more accurate than the Sentinel-2-based model. This research highlights the importance of preserving seagrass habitats for carbon sequestration, contributing valuable data to global blue carbon reservoirs and informing future conservation strategies and climate change mitigation efforts

Radar backscatter modelling of forests using a macroecological approach

This thesis provides a new explanation for the behaviour of radar backscatter of forests using vegetation structure models from the field of macroecology. The forests modelled in this work are produced using allometry-based ecological models with backscatter derived from the parameterisation of a radiative transfer model. This work is produced as a series of papers, each portraying the importance of macroecology in defining the forest radar response. Each contribution does so by incorporating structural and dynamic effects of forest growth using one of two allometric models to expose variations in backscatter as a response to vertical and horizontal forest profiles. The major findings of these studies concern the origin of backscatter saturation effects from forest SAR surveys. In each work the importance of transition from Rayleigh to Optical scattering, combined with the scaling effects of forest structure, is emphasised. These findings are administered through evidence including the transition’s emergence as the region of dominant backscatter in a vertical profile (according to a dominant canopy scattering layer), also through the existence of a two trend backscatter relationship with volume in the shape of the typical “saturation curve” (in the absence of additional attenuating factors). The importance of scattering regime change is also demonstrated through the relationships with volume, basal area and thinning. This work’s findings are reinforced by the examination of the relationships between forest height and volume, as collective values, providing evidence to suggest the non-uniqueness of volume-toheight relationships. Each of the studies refer to growing forest communities not single trees, so that unlike typical studies of radar remote sensing of forests the impact of the macroecological structural aspects are more explicit. This study emphasises the importance of the overall forest structure in producing SAR backscatter and how backscatter is not solely influenced by electrical properties of scatteres or the singular aspects of a tree but also by the collective forest parameters defining a dynamically changing forest

Temperate Grassland Afforestation Dynamics in the Aguapey Valuable Grassland Area between 1999 and 2020:Identifying the Need for Protection

Temperate grasslands are considered the most endangered terrestrial ecosystem worldwide; the existent areas play a key role in biodiversity conservation. The Aguapey Valuable Grassland Area (VGA), one of the most well-preserved temperate grassland areas within Argentina, is currently threatened by the anthropogenic expansion of exotic tree plantations. Little is known about the impacts of afforestation over temperate grassland landscape structures; therefore, the aim of this study is to characterize Aguapey VGA landscape structural changes between 1999 and 2020 based on remotely sensed data. This involves the generation of land cover maps for four annual periods based on unsupervised classification of Landsat 5 TM and 8 OLI images, the estimation of landscape metrics, and the transition analysis between land cover types and annual periods. The area covered by temperate grassland is shown to have decreased by almost 22% over the 20 year-period studied, due to the expansion of tree plantation cover. The afforestation process took place mainly between 1999 and 2007 in the northern region of the Aguapey VGA, which led first to grassland perforation and subsequently to grassland attrition; however, Aguapey’s cultural tradition of cattle ranching could have partially inhibited the expansion of exotic trees over the final years of the study. The evidence of grassland loss and fragmentation within the Aguapey VGA should be considered as an early warning to promote the development of sustainable land use policies, mainly focused towards the Aguapey VGA’s southern region where temperate grassland remains the predominant land cover type

Long Wavelength SAR Backscatter Modelling Trends as a Consequence of the Emergent Properties of Tree Populations

www.mdpi.com/journal/remotesensin

Investigating the Role of Cover-Crop Spectra for Vineyard Monitoring from Airborne and Spaceborne Remote Sensing

The monitoring of grape quality parameters within viticulture using airborne remote sensing is an increasingly important aspect of precision viticulture. Airborne remote sensing allows high volumes of spatial consistent data to be collected with improved efficiency over ground-based surveys. Spectral data can be used to understand the characteristics of vineyards, including the characteristics and health of the vines. Within viticultural remote sensing, the use of cover-crop spectra for monitoring is often overlooked due to the perceived noise it generates within imagery. However, within viticulture, the cover crop is a widely used and important management tool. This study uses multispectral data acquired by a high-resolution uncrewed aerial vehicle (UAV) and Sentinel-2 MSI to explore the benefit that cover-crop pixels could have for grape yield and quality monitoring. This study was undertaken across three growing seasons in the southeast of England, at a large commercial wine producer. The site was split into a number of vineyards, with sub-blocks for different vine varieties and rootstocks. Pre-harvest multispectral UAV imagery was collected across three vineyard parcels. UAV imagery was radiometrically corrected and stitched to create orthomosaics (red, green, and near-infrared) for each vineyard and survey date. Orthomosaics were segmented into pure cover-cropuav and pure vineuav pixels, removing the impact that mixed pixels could have upon analysis, with three vegetation indices (VIs) constructed from the segmented imagery. Sentinel-2 Level 2a bottom of atmosphere scenes were also acquired as close to UAV surveys as possible. In parallel, the yield and quality surveys were undertaken one to two weeks prior to harvest. Laboratory refractometry was performed to determine the grape total acid, total soluble solids, alpha amino acids, and berry weight. Extreme gradient boosting (XGBoost v2.1.1) was used to determine the ability of remote sensing data to predict the grape yield and quality parameters. Results suggested that pure cover-cropuav was a successful predictor of grape yield and quality parameters (range of R2 = 0.37–0.45), with model evaluation results comparable to pure vineuav and Sentinel-2 models. The analysis also showed that, whilst the structural similarity between the both UAV and Sentinel-2 data was high, the cover crop is the most influential spectral component within the Sentinel-2 data. This research presents novel evidence for the ability of cover-cropuav to predict grape yield and quality. Moreover, this finding then provides a mechanism which explains the success of the Sentinel-2 modelling of grape yield and quality. For growers and wine producers, creating grape yield and quality prediction models through moderate-resolution satellite imagery would be a significant innovation. Proving more cost-effective than UAV monitoring for large vineyards, such methodologies could also act to bring substantial cost savings to vineyard management