Geospatial data harmonization from regional level to european level: a usa case in forest fire data

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.Geospatial data harmonization is becoming more and more important to increase interoperability of heterogeneous data derived from various sources in spatial data infrastructures. To address this harmonization issue we present the current status of data availability among different communities, languages, and administrative scales from regional to national and European levels. With a use case in forest data models in Europe, interoperability of burned area data derived from Europe and Valencia Community in Spain were tested and analyzed on the syntactic, schematic and semantic level. We suggest approaches for achieving a higher chance of data interoperability to guide forest domain experts in forest fire analysis. For testing syntactic interoperability, a common platform in the context of formats and web services was examined. We found that establishing OGC standard web services in a combination with GIS software applications that support various formats and web services can increase the chance of achieving syntactic interoperability between multiple geospatial data derived from different sources. For testing schematic and semantic interoperability, the ontology-based schema mapping approach was taken to transform a regional data model to a European data model on the conceptual level. The Feature Manipulation Engine enabled various types of data transformation from source to target attributes to achieve schematic interoperability. Ontological modelling in Protégé helped identify a common concept between the source and target data models, especially in cases where matching attributes were not found at the schematic level. Establishment of the domain ontology was explored to reach common ground between application ontologies and achieve a higher level of semantic interoperability

Estimating the threshold of detection on tree crown defoliation using vegetation indices from UAS multispectral imagery

Periodical outbreaks of Thaumetopoea pityocampa feeding on pine needles may pose a threat to Mediterranean coniferous forests by causing severe tree defoliation, growth reduction, and eventually mortality. To cost-effectively monitor the temporal and spatial damages in pine-oak mixed stands using unmanned aerial systems (UASs) for multispectral imagery, we aimed at developing a simple thresholding classification tool for forest practitioners as an alternative method to complex classifiers such as Random Forest. The UAS flights were performed during winter 2017-2018 over four study areas in Catalonia, northeastern Spain. To detect defoliation and further distinguish pine species, we conducted nested histogram thresholding analyses with four UAS-derived vegetation indices (VIs) and evaluated classification accuracy. The normalized difference vegetation index (NDVI) and NDVI red edge performed the best for detecting defoliation with an overall accuracy of 95% in the total study area. For discriminating pine species, accuracy results of 93-96% were only achievable with green NDVI in the partial study area, where the Random Forest classification combined for defoliation and tree species resulted in 91-93%. Finally, we achieved to estimate the average thresholds of VIs for detecting defoliation over the total area, which may be applicable across similar Mediterranean pine stands for monitoring regional forest health on a large scale

Assessing FAIRness of Citizen Science Data in the Context of the Green Deal Data Space

As part of the European Data Strategy, the European Commission is working on common European data spaces, including a Green Deal Data Space (GDDS) that covers issues such as climate change, circular economy, pollution, biodiversity, and deforestation. The successful development of the EU GDDS will depend on the availability of FAIR (findable, accessible, interoperable, and reusable) data sources, including FAIR citizen science data. While the importance of FAIR principles is increasingly acknowledged within the field of citizen science, sources of FAIR data outside the biodiversity domain are generally scarce. This is contributed by the lack of end-to-end technical solutions, readily available semantic resources to support data interoperability, and centralised data repositories suited for citizen science data. To investigate the current state of play with citizen science data FAIR compliance, we conducted a review to elicit platforms, tools and standards either used by or indicated as suitable for facilitating stages of the citizen science project lifecycle. We report on the results of our review and discuss gaps that still exist to achieve citizen science data FAIRness. We also examine three data aggregation platforms identified in our review which closely align with FAIR, namely: the Global Biodiversity Information Facility, OpenStreetMap, and Sensor.Community

The use of scenarios and models to evaluate the future of nature values and ecosystem services in Mediterranean forests

Science and society are increasingly interested in predicting the effects of global change and socio-economic development on natural systems, to ensure maintenance of both ecosystems and human well-being. The Intergovernmental Platform on Biodiversity and Ecosystem Services has identified the combination of ecological modelling and scenario forecasting as key to improving our understanding of those effects, by evaluating the relationships and feedbacks between direct and indirect drivers of change, biodiversity, and ecosystem services. Using as case study the forests of the Mediterranean basin (complex socio-ecological systems of high social and conservation value), we reviewed the literature to assess (1) what are the modelling approaches most commonly used to predict the condition and trends of biodiversity and ecosystem services under future scenarios of global change, (2) what are the drivers of change considered in future scenarios and at what scales, and (3) what are the nature and ecosystem service indicators most commonly evaluated. Our review shows that forecasting studies make relatively little use of modelling approaches accounting for actual ecological processes and feedbacks between different socio-ecological sectors; predictions are generally made on the basis of a single (mainly climate) or a few drivers of change. In general, there is a bias in the set of nature and ecosystem service indicators assessed. In particular, cultural services and human well-being are greatly underrepresented in the literature. We argue that these shortfalls hamper our capacity to make the best use of predictive tools to inform decision-making in the context of global change.This work was supported by the Spanish Government through the INMODES project (grant number CGL2017-89999-C2-2-R), the ERA-NET FORESTERRA project INFORMED (grant number 29183), and the project Boscos Sans per a una Societat Saludable funded by Obra Social la Caixa (https://obrasociallacaixa.org/). AMO and AA were supported by Spanish Government through the “Juan de la Cierva” fellowship program (IJCI-2016-30349 and IJCI-2016-30049, respectively). JVRD was supported by the Government of Asturias and the FP7-Marie Curie-COFUND program of the European Commission (Grant “Clarín” ACA17-02)

Assessing spatio-temporal impacts of pine processionary moth defoliation on Mediterranean forest dynamics using UAV remote sensing

En general, aquesta tesi destaca que les últimes tècniques de teledetecció, inclòs el UAV com una tecnologia 3D alternativa, estan actualment disponibles per a combinar-se amb inspeccions de terra convencionals i anàlisis estadístiques d'acord amb les escales espacials i temporals i els tipus de defoliació. L'ús d'imatges d'UAV també pot tenir un gran potencial com un mètode rendible i alternatiu a altres dades convencionals de veritat en terra ferma per monitoritzar la salut de bosc. Concloc que els mètodes òptims de detecció i monitoratge sovint són específics per a cada plaga associat amb l'espècie d'arbres. Per tant, l'avanç en els models de predicció vinculats als serveis de l'ecosistema en el control de plagues i malalties seria prometedor per mitigar l'afectació futura als nostres boscos sota el canvi climàtic.En general, esta tesis destaca que las últimas técnicas de teledetección, incluido el UAV como una tecnología 3D alternativa, están actualmente disponibles para combinarse con inspecciones de tierra convencionales y análisis estadísticos de acuerdo con las escalas espaciales y temporales y los tipos de defoliación. El uso de imágenes de UAV también puede tener un gran potencial como un método rentable y alternativo a otros datos convencionales de verdad en tierra firme para monitorizar la salud del bosque. Concluyo que los métodos óptimos de detección y monitorización a menudo son específicos para cada plaga asociado con la especie de árboles. Por lo tanto, el avance en los modelos de predicción vinculados a los servicios del ecosistema en el control de plagas y enfermedades sería prometedor para mitigar la afectación futura a nuestros bosques bajo el cambio climático.Overall, this thesis highlights that the latest modelling and remote sensing techniques, including UAV as an alternative 3D technology, are currently available to be combined with conventional ground surveys and statistical analyses according to the spatial and temporal scales and types of defoliation. The use of UAV images may also hold great potential as an alternative cost-effective method to other conventional ground-truth data for monitoring forest health. I conclude that optimal detection and monitoring methods are often specific to each pest agent associated with host tree species. Therefore, the advancement in prediction models linked to ecosystem services in pest and disease control would be promising for mitigating the future damage to our forests under climate change

Assessing spatio-temporal impacts of pine processionary moth defoliation on Mediterranean forest dynamics using UAV remote sensing

En general, aquesta tesi destaca que les últimes tècniques de teledetecció, inclòs el UAV com una tecnologia 3D alternativa, estan actualment disponibles per a combinar-se amb inspeccions de terra convencionals i anàlisis estadístiques d'acord amb les escales espacials i temporals i els tipus de defoliació. L'ús d'imatges d'UAV també pot tenir un gran potencial com un mètode rendible i alternatiu a altres dades convencionals de veritat en terra ferma per monitoritzar la salut de bosc. Concloc que els mètodes òptims de detecció i monitoratge sovint són específics per a cada plaga associat amb l'espècie d'arbres. Per tant, l'avanç en els models de predicció vinculats als serveis de l'ecosistema en el control de plagues i malalties seria prometedor per mitigar l'afectació futura als nostres boscos sota el canvi climàtic.En general, esta tesis destaca que las últimas técnicas de teledetección, incluido el UAV como una tecnología 3D alternativa, están actualmente disponibles para combinarse con inspecciones de tierra convencionales y análisis estadísticos de acuerdo con las escalas espaciales y temporales y los tipos de defoliación. El uso de imágenes de UAV también puede tener un gran potencial como un método rentable y alternativo a otros datos convencionales de verdad en tierra firme para monitorizar la salud del bosque. Concluyo que los métodos óptimos de detección y monitorización a menudo son específicos para cada plaga asociado con la especie de árboles. Por lo tanto, el avance en los modelos de predicción vinculados a los servicios del ecosistema en el control de plagas y enfermedades sería prometedor para mitigar la afectación futura a nuestros bosques bajo el cambio climático.Overall, this thesis highlights that the latest modelling and remote sensing techniques, including UAV as an alternative 3D technology, are currently available to be combined with conventional ground surveys and statistical analyses according to the spatial and temporal scales and types of defoliation. The use of UAV images may also hold great potential as an alternative cost-effective method to other conventional ground-truth data for monitoring forest health. I conclude that optimal detection and monitoring methods are often specific to each pest agent associated with host tree species. Therefore, the advancement in prediction models linked to ecosystem services in pest and disease control would be promising for mitigating the future damage to our forests under climate change.Universitat Autònoma de Barcelona. Programa de Doctorat en Ecologia Terrestr

Trade-off analysis of accuracy and spatial resolution in strategic forest planning models

When large areas of forest are modelled, spatial detail can create excessively large databases and adversely affect the processing time. Spatial generalization can be an efficient means of aggregating polygons into blocks in strategic forest planning models. In this study, a sensitivity analysis on spatial generalization was conducted to examine the trade-off between accuracy and spatial resolution to meet the objectives of strategic planning. Five scenarios were designed by generalizing forest cover polygons into the uniform hexagon block sizes of 5, 10, 20, 50 and 100 ha. To quantitatively assess accuracy, deviations caused by spatial generalization were calculated by criteria for hexagon scenarios relative to the base case. Criteria include model inputs (area of natural disturbance type and ungulate winter range) and outputs (harvest volume, growing stock and seral stage distribution). In general, deviations in all criteria increased with the block size. Spatial resolution was also evaluated by the database size and simulation runtime. A negative relationship was observed between spatial resolution and the block size. The trade-off analysis between accuracy and spatial resolution indicated that using the smallest block size of 5 ha creates more detail than necessary. Although scenarios with the block sizes of 50 and 100 ha reduced spatial resolution significantly, the maximum deviations relative to the base case were as high as 14% and 17% in growing stock, 12% and 12% in seral stage distribution, and 6% and 21% in ungulate winter range, respectively. For this study, the preferred block size is in the range of 10-20 ha, however, in general, the preferred block size will vary depending on the importance of each criterion used in the trade-off analysis.Forestry, Faculty ofGraduat

Calibrating the Severity of Forest Defoliation by Pine Processionary Moth with Landsat and UAV Imagery

The pine processionary moth (Thaumetopoea pityocampa Dennis and Schiff.), one of the major defoliating insects in Mediterranean forests, has become an increasing threat to the forest health of the region over the past two decades. After a recent outbreak of T. pityocampa in Catalonia, Spain, we attempted to estimate the damage severity by capturing the maximum defoliation period over winter between pre-outbreak and post-outbreak images. The difference in vegetation index (dVI) derived from Landsat 8 was used as the change detection indicator and was further calibrated with Unmanned Aerial Vehicle (UAV) imagery. Regression models between predicted dVIs and observed defoliation degrees by UAV were compared among five selected dVIs for the coefficient of determination. Our results found the highest R-squared value (0.815) using Moisture Stress Index (MSI), with an overall accuracy of 72%, as a promising approach for estimating the severity of defoliation in affected areas where ground-truth data is limited. We concluded with the high potential of using UAVs as an alternative method to obtain ground-truth data for cost-effectively monitoring forest health. In future studies, combining UAV images with satellite data may be considered to validate model predictions of the forest condition for developing ecosystem service tools