Mapping landscape-scale peatland degradation using airborne lidar and multispectral data

This is the final version. Available on open access from Springer via the DOI in this recordContext An increased interest in the restoration of peatlands for delivering multiple benefits requires a greater understanding of the extent and location of natural and artificial features that contribute to degradation. Objectives We assessed the utility of multiple, fine-grained remote sensing datasets for mapping peatland features and associated degraded areas at a landscape-scale. Specifically, we developed an integrated approach to identify and quantify multiple types of peatland degradation including: anthropogenic drainage ditches and peat cuttings; erosional gullies and bare peat areas. Methods Airborne LiDAR, CASI and aerial image datasets of the South West UK, were combined to identify features within Dartmoor National Park peatland area that contribute to degradation. These features were digitised and quantified using ArcGIS before appropriate buffers were applied to estimate the wider ecohydrologically affected area. Results Using fine-scale, large-extent remotely sensed data, combined with aerial imagery enabled key features within the wider expanse of peatland to be successfully identified and mapped at a resolution appropriate to future targeted restoration. Combining multiple datasets increased our understanding of spatial distribution and connectivity within the landscape. An area of 29 km2 or 9.2% of the Dartmoor peatland area was identified as significantly and directly ecohydrologically degraded. Conclusions Using a combination of fine-grained remotely sensed datasets has advantages over traditional ground survey methods for identification and mapping of anthropogenic and natural erosion features at a landscape scale. The method is accurate, robust and cost-effective particularly given the remote locations and large extent of these landscapes, facilitating effective and targeted restoration planning, management and monitoring.Dartmoor National Park AuthorityDartmoor Peatland PartnershipDuchy of CornwallEnvironment AgencyForestry CommissionMinistry of DefenceNatural EnglandSouth West partnership for Environmental and Economic Prosperity (SWEEP)South West WaterNatural Environment Research Council (NERC

Indicadores para medir la erosión de los suelos por acción de la lluvia: Una revisión con énfasis en la estabilización masiva y control de las tasas de erosión.

Soil erosion leads to a series of impacts, inside and outside the ecosystem that in tur n are related to the productive capacity of the soil and the depletion of nutrients. This document gives us a vision of the state of soil loss due to water erosion, framed in a set of selected ecosystem service indicators (ES) that include supply and demand indicators that represent the three main supplier, regulatory and sociocultural categories. The choice of appropriate indicators and their calculation is presented using the example of class ES "massive stabilization and control of erosion rates" and "control of soil erosion water". Nearly natural ecosystems often resist erosion to a greater extent than areas in use, whose erosion rates depend on natural parameters and factors related to use. The main indicator captures the protective effect of ecosystems against soil loss, calculated from the difference in annual losses and the rate of hypothetical erosion without vegetation. The objective is to show the development of indicators with a focus on stakeholder participation and adopt regulatory processes that help counteract the effects of soil erosion.La erosión del suelo conlleva a una serie de impactos, dentro y fuera del ecosistema que a su vez se encuentran relacionados con la capacidad productiva del suelo y el agotamiento de los nutrientes. Este documento nos brinda una visión del estado de la pérdida del suelo por la erosión hídrica, enmarcado en un conjunto de indicador es de servicios ecosistémicos seleccionados (ES) que comprenden indicadores de ofer ta y demanda que representan los tres principales categorías proveed oras, regulador as y socioculturales. La elección de los indicadores adecuados y su cálculo se presenta utilizando el ejemplo de la clase ES "estabilización masiva y control de las tasas de erosión" y el "control del agua de erosión del suelo". Los ecosistemas casi naturales a menudo resisten la erosión en mayor medida que las áreas en uso, cuyas tasas de erosión dependen de parámetros naturales y factores relacionados con el uso. El indicador principal, captura el efecto protector de los ecosistemas contr a pérdida de suelo, calculada a partir de la diferencia de las pérdidas anuales y la tasa de ero sión hipotética sin vegetación. El objetivo es mostrar el desarrollo de indicadores con un enfoque de participación de los interesados y adoptar procesos regulatorios que ayuden a contrarrestar los efectos de la erosión en los suelos

Application of terrestrial laser scanning to quantify surface changes in restored and degraded blanket bogs

Many recognised areas of blanket bog are degraded, but the inventory and rate of loss of blanket bog globally is not fully known. Rapid identification of the rate and drivers of erosion and peat loss in blanket bogs more widely could inform localised approaches to protection and restoration of these important ecosystems. This study developed the application of Terrestrial Laser Scanning (TLS) to quantify the rate of surface change in restored and degraded blanket bogs by adopting a single scan strategy with fixed ground markers for repeat scanner location and fixed reference markers for scan alignment. Three recently mapped and remote areas of blanket bog in the Cantabrian Mountains (northern Spain) were scanned in May 2017 and July 2017 with a portable TLS (FARO X330) and 3D change in exposed peat surfaces was determined using a mesh to cloud (M2C) algorithm. The mean resolution of scan data across the sites was <3 mm, and where reference markers remained visible the maximum error of scan alignment was <1 mm, increasing to 6.5 mm where markers were obscured or lost. The rate of erosion determined over two months at Zalama (a protected blanket bog where reference markers were not disturbed) was -5.9 ± 4.6 mm (mean ± SD), but significantly higher (p < 0.001) rates of erosion and peat loss were determined for two unprotected blanket bogs under grazing regimes at Ilsos de Zalama (-22.9 ± 20.5 mm) and Collado de Hornaza (-35.7 ± 37 mm). This rate of change is already equal to the mean annual rate of erosion reported for bare peat in England and Wales (22.4–23.1 mm yr-1) and for Scotland (36.3 mm yr-1). This study demonstrates that portable TLS units can be used to make rapid assessment of surface change (erosion and peat loss) in blanket bog and indicates that trampling by cattle and horses is significantly increasing the rate of peat surface change in unprotected blanket bog in north Spain. This technique has direct application for peatlands under grazing regimes globally, and further installation of fences around blanket bog in northern Spain may be required imminently to reduce the loss of peat, the associated carbon store and priority habitat

Automated earthwork detection using topological persistence

For thousands of years, humans have altered the movement of water through construction of earthworks. These earthworks remain in landscapes, where they continue to alter hydrology, even where structures have long since been abandoned. Management of lands containing earthworks requires an understanding of how the earthworks impact hydrology and knowledge of where the structures are located in the landscape. Various methods for detecting topographic features exist in the literature, including a set of rule and threshold-based techniques and machine learning methods. These tools are either labor-intensive or require special pre-processing or a priori assumptions about structures that limit generalizability. Here, we test a topological analysis tool called “persistence” to determine if it is useful for earthwork detection in rangelands. We found that persistence can be used to detect earthworks with 83% precision and 64% accuracy. Breached berms and berms with significant upslope sedimentation are most likely not to be detected using persistence. These results indicate that persistence can be useful for terrain analysis, and it has the potential to substantially reduce manual effort in feature detection by identifying regions where berms may be found

QUANTIFYING GULLY EROSION IN WEST TENNESSEE USING HIGH RESOLUTION LIDAR DATA

This research demonstrates the use of Light Detection and Ranging (LIDAR) for detailed measurement of volume change and erosional and depositional processes within a small gully and assessing the impact of digital elevation model (DEM) resolution on these measurements. The study site is an active gully in Meeman-Shelby Forest State Park in Tennessee, USA. DEMs were derived from an airborne LIDAR survey and multiple terrestrial LIDAR scans. DEM differences were used to quantify gross volumes of erosion and deposition within the gully over a three year period and a 49 day period. Analysis of the airborne LIDAR point cloud indicated that approximately 10,000 m3 of material eroded from the bluff since the gully was formed between 1969 and 1973. A total volume of 615.8 m3 of material was discharged from the gully between January 2012 (the airborne LIDAR survey) and December 2014 (the first terrestrial LIDAR survey). The surveys using the terrestrial laser scanner generated two 2 cm DEMs representing the gully terrain change during a short period of 49 days between December 2014 and February 2015. The comparison of these two DEMs indicates an estimated 2.1 m3 of material was imported into the gully with 11.5 m3 of gross erosion and 13.6 m3 of gross deposition. The DEM scale analysis indicates that turning points exist in the trends of erosion and deposition estimates at 0.18 m and 0.28 m resolutions, respectively. These turning points represent the resolutions at which the accuracy of erosion and deposition measurements begin to deteriorate and are revealed by examining the strength of linear fits to data points on either side of the turning point. The analyses described in this thesis offer insight into the benefits and challenges of using LIDAR to study gully morphology and serve as a starting point for continuously monitoring of gully development processes taking place within the pool gully at very fine scales

The potential of geospatial technology for monitoring peatland environments

There have been significant advances in the spectral and spatial resolution of data collected from spaceborne, airborne and terrestrial based geospatial technologies over the past 20 years. In sensitive peatland ecosystems, the non-intrusive application of these technologies offers great potential to improve vegetation monitoring and topographical mapping. This paper discusses the potential of geospatial technologies for monitoring vegetation, mapping natural erosion features and assessing artificial drainage with reference to two peatland sites in England. Earth Observation (EO) data can now provide colour imagery with spatial resolution comparable to conventional aerial photography. Enhanced spectral resolution of spaceborne sensors has also increased the accuracy of automated image classification for bog vegetation and EO data may challenge the relevance of conventional aerial photography in landscape-scale assessment. Ultra-high resolution data achievable from Unmanned Aerial Vehicle (UAV) and Terrestrial Laser Scanner (TLS) technologies are providing unprecedented levels of detail from remote sensing. UAV imagery now provides the possibility of identifying individual plants which greatly increases a researcher’s ability to map vegetation from aerial imagery. UAV derived elevation data, combined with the capability of TLS, provide enhanced resolution of gully and artificial drain morphology compared to airborne LiDAR and allow a new approach for quantifying erosion. These technologies provide opportunities to extend traditional surveys over far larger areas than was previously possible and can assist both in targeting areas for future restoration and in monitoring of subsequent change. Traditional survey methods will however maintain an important role in assessing many aspects of peatlands, as they not only provide information to verify remotely sensed data, but are currently the only method that can ‘see’ underneath peatland vegetation

Utilisation des données d'élévation LiDAR à haute résolution pour la cartographie numérique du matériel parental des sols

Les connaissances sur la morphologie de la Terre sont essentielles à la compréhension d’une variété de processus géomorphologiques et hydrologiques. Des avancées récentes dans le domaine de la télédétection ont significativement fait progresser notre habilité à se représenter la surface de la Terre. Parmi celles-ci, les données d’élévation LiDAR permettent la production de modèles numériques d’altitude (MNA) à haute résolution sur de grands territoires. Le LiDAR est une avancée technologique majeure permettant aux scientifiques de visualiser en détail la morphologie de la Terre et de représenter des reliefs peu prononcés, et ce, même sous la canopée des arbres. Une telle avancée technologique appelle au développement de nouvelles approches innovantes afin d’en réaliser le potentiel scientifique. Dans ce contexte, le présent travail vise à développer deux approches de cartographie numérique utilisant des données d’élévation LiDAR et servant à l’évaluation de la composition du sous-sol. La première approche à être développée utilise la localisation de crêtes de plage identifiées sur des MNA LiDAR afin de modéliser l’étendue maximale de la mer de Champlain, une large paléo-mer régionalement importante. Cette approche nous a permis de cartographier avec précision les 65 000 km2 autrefois inondés par la mer. Ce modèle sert à l’évaluation de la distribution des sédiments marins et littoraux dans les basses-terres du Saint-Laurent. La seconde approche utilise la relation entre des échantillons de matériel parental des sols (MPS) et des attributs topographiques dérivés de données LiDAR afin de cartographier à haute résolution et à une échelle régionale le MPS sur le Bouclier canadien. Pour ce faire, nous utilisons une approche novatrice combinant l’analyse d’image orientée-objet (AIOO) avec une classification par arbre décisionnel. Cette approche nous a permis de produire une carte du MPS à haute résolution sur plus de 185 km2 dans un environnement hétérogène de post-glaciation. Les connaissances issues de la production de ces deux modèles ont permis de conceptualiser la composition du sous-sol dans les régions limitrophes entre les basses-terres du Saint-Laurent et le Bouclier canadien. Ce modèle fournit aux chercheurs et aux gestionnaires de ressources des connaissances détaillées sur la géomorphologie de cette région et contribue à l’amélioration de notre capacité à saisir les services écosystémiques et à prédire les aléas environnementaux liés aux processus du sous-sol.Knowledge of the earth’s morphology is essential to the understanding of many geomorphic and hydrologic processes. Recent advancements in the field of remote sensing have significantly improved our ability to assess the earth’s surface. From these, LiDAR elevation data permits the production of high-resolution digital elevation models (DEMs) over large areas. LiDAR is a major technological advance as it allows geoscientists to visualize the earth’s morphology in high detail, even allowing us to resolve low-relief landforms in forested areas where the surface is obstructed by vegetation cover. Such a technological advance calls for the development of new and novel approaches to realize the scientific potential of this new spatial data. In this context, the present work aims to develop two digital mapping approaches that use LiDAR elevation data for assessing the earth’s subsurface composition. The first approach to be developed uses the location of low-relief beach ridges observed on LiDAR-derived DEMs to map the extent of a large and regionally important paleo-sea, the Champlain Sea. This approach allowed us to accurately map the 65,000 km2 area once inundated by sea water. The model serves to the assessment of the distribution of marine and littoral sediments in the St. Lawrence Lowlands. The second approach uses the relationship between field-acquired samples of soil parent material (SPM) and LiDAR-derived topographic attributes to map SPM at high-resolution and at a regional scale on the Canadian Shield. To do so, we used a novel approach that combined object-based image analysis (OBIA) with a classification tree algorithm. This approach allowed us to produce a fine-resolution 185 km2 map of SPM in a heterogeneous post-glaciation Precambrian Shield setting. The knowledge obtained from producing these two models allowed us to conceptualize the subsurface composition at the limit between the St. Lawrence Lowlands and the Canadian Shield. This insight provides researchers and resource managers with a more detailed understanding of the geomorphology of this area and contributes to improve our capacity to grasp ecosystem services and predict environmental hazards related to subsurface processes

Identification, geo-hydromorphological assessment and the state of degradation of the southernmost blanket bogs in Europe

Blanket bogs are a globally rare type of ombrotrophic peatland internationally recognised for long-term terrestrial carbon storage, the potential to serve as carbon sinks and habitat provision. The majority of recognised areas of this habitat in Europe are found in the United Kingdom and Ireland, but the rarer examples found in Spain represent the southernmost continental edge-of-range. However, gaps in the peatland inventory suggest that a number of blanket bogs in the Cantabrian Mountains (northern Spain) are not recognised and are at increased threat of loss. This study identifies and provides geo-hydromorphological classification for 14 unrecorded blanket bogs and one protected blanket bog located between the administrative regions of Cantabria and Castilla y León. Peat depth surveys and carbon analysis of peat cores were used to determine the amount of carbon stored within the newly identified blanket bogs and the current rate, and drivers, of peatland degradation were examined using remote sensing techniques. A total extent of blanket bog covering 44.45 ha (>40 cm peat depth) containing more than 500,000 m3 of peat and an estimated 44.88 ± 3.31 kt C was mapped. Approximately 30.8% of the surface of blanket bogs examined was exposed peat, and even in the protected site, exposed peat surfaces are losing a minimum of 1.7 t C m-2 yr-1. The presence of livestock in unprotected sites is increasing the rate of erosion by over five times, and without protection exposed peat surfaces are releasing as much as 3.84 t C m-2 yr-1. The peatlands identified in this research extend the known limit of blanket bogs in Europe farther south than previously recorded and represent 10.5% of blanket bog currently recognised and protected in Spain. The range of anthropogenic pressures currently acting on peatlands in the Cantabrian Mountains, specifically livestock and windfarms, indicates that without protection these important landforms and stored carbon may be lost. An urgent update of European peatland inventories is thus required to preserve these valuable carbon stores and potential carbon sinks

Generación y análisis de modelos digitales de elevación generados con vehículos aéreos no tripulados para la determinación de nanocuencas de alta precisión.

La presente investigación analiza la precisión de los modelos digitales de elevación generados con vehículos aéreos no tripulados (VANT o dron) por medio de la ejecución de vuelos programados con dos softwares diferentes (denominados A y B) de control de vuelo no tripulado. Las imágenes obtenidas por los vehículos aéreos tienen rangos entre 70 y 80% de superposición, la altura de vuelo en todos los casos es de 200 m. Para realizar los vuelos se utilizó un dron DJI Phantom 4 y DJI Phantom 3 Profesional, en un área de estudio de 129 Ha. Los datos capturados en campo, se procesaron con un software fotogramétrico digital para productos fotográficos, del cual se obtuvieron productos digitales como el modelo tridimensional, la nube densa de puntos, la superficie de malla, el ortomosaico y el Modelo Digital de Elevación (MDE). Se generaron 4 MDE´s con datos obtenidos en campo y se definieron Puntos de control Terrestre (PCT) utilizando dos diferentes equipos GPS manual y GPS RTK de doble frecuencia. El objetivo de investigación se centró en determinar cuál combinación de software, VANT y GPS poseen una mayor precisión en el cálculo de la ubicación de los puntos tridimensional y que tenga el menor margen de error. Los resultados de las diferentes combinaciones de los equipos y configuraciones antes descritas indican que los datos recabados con el software B y con los PCT tomados en campo con el GPS de doble frecuencia RTK presentan mejores resultados, cuyos errores promedio son de 0.97823 m en XY, 0.03234 m en Z y 0.615 pix. Paralelamente se realizó un análisis de las ventajas y desventajas que presenta el uso de ambos softwares de control de vuelo en la generación de imágenes útiles para la generación de MDE. Con esta información se procedió de generar el MDE con menor error y que tiene un nivel de resolución muy superior a las actuales fuentes oficiales de MDE en México finalmente se generó la red de flujo superficial en un Sistema de Información Geográfica (SIG) para demostrar una importante utilidad del uso de esta tecnología

Using high-resolution topography for spatial prioritisation of gully erosion management across catchments of the Great Barrier Reef, Australia

The Great Barrier Reef (GBR) running along ~2 000km of the north-eastern coast of Australia is a UNESCO World Heritage site and is the largest living structure on Earth. The GBR is at the forefront of environmental issues currently faced by Australia, with significant economic, environmental, social, and cultural value. Terrigenous fine sediment affects water quality in the GBR and contributes to the degradation of significant marine environments. Gully erosion is believed to be an important contributor of this fine sediment, and this has garnered recent attention from the Australian Government. A key challenge to managing gully erosion across catchments of the GBR is the large scale of the combined area (>400 000 km2). Recent advances in Light Detection and Ranging (LiDAR) have enabled generation of high-resolution (~1 m) digital elevation models (DEMs) over large areas. Over recent years airborne LiDAR data captures have covered many areas of the GBR catchments, with ~50 000 km2 of topography data with a spatial resolution of 1 m or finer. This newly available source of high-resolution data presents an opportunity to map and predict locations of gully erosion across large areas, reducing the need for time-consuming fieldwork. However, there is a need for further development of suitable methods to exploit this data. The core aim of this PhD has been to develop a set of tools and algorithms for using high-resolution topography data to map gullies and areas susceptible to future gully erosion. Novel analysis methods were developed into open-source computer programs with a general focus on creating resources to assist researchers and practitioners managing and assessing gully erosion over large areas. The overall approach is split into to two broad categories of analysis. The first focuses on gully management at small scales (tens of square kilometres), and the second focuses on large scales (hundreds to thousands of square kilometres). The algorithms developed from each of the two halves are designed to work in unison to prioritise gully erosion management first at large scales and subsequently at small scales. This PhD has developed and assessed novel methods for using high-resolution topography data to map and predict gully erosion across catchments of the GBR. A core focus has been on proposing 'standard' methods for computing the required inputs for topographic models of gully occurrence in the landscape. The broader goal of this was to help move the field closer to a set of tools that allow researchers to readily compare model results between landscapes and regions free of bias introduced by variations in sampling procedures. This work has highlighted the potential benefit of using high-resolution topography, particularly airborne LiDAR, but that consistency with methodologies is key to enabling comparisons across landscapes. The methods developed also have applications to other environments, particularly semi-arid regions, and have all been developed in open-source programming languages to help facilitate adoption. Results from applying two different topographic models of gullies showed that land clearing and a transition from natural forests to agricultural landscapes has likely led to increased gullying across catchments of the GBR. This finding is consistent with other studies globally and provides important context for gully management priorities in this region