Development of burned area algorithms on a global scale
- ALONSO CAÑAS, ITZIAR
- Emilio Chuvieco Salinero Director
Universitat de defensa: Universidad de Alcalá
Fecha de defensa: 01 de de febrer de 2016
- M. Pilar Martín Isabel President/a
- Francisco Javier Salas Rey Secretari
- María Inmaculada Aguado Suárez Vocal
- José Miguel Pereira Chávez Vocal
- Kevin Tansey Vocal
Tipus: Tesi
Resum
This manuscript contains the research work entitled “Development of Burned Area algorithms on a global scale”. This work was developed and funded in the framework of the fire_cci project within the European Space Agency’s Climate Change Initiative programme. The PhD aim was to obtain an algorithm to retrieve burned areas (BA) on a global scale from the MERIS sensor. The document is structured in the following chapters: Chapter 1: Introduction: this chapter aims at putting in context the global relevance of fire and of accessing information on burned areas. The methods to characterize fire from space and the state of the art are reviewed here. Chapter 2: Objectives: the aim of this chapter is to introduce the context of the PhD research as well as a more detailed description of the thesis objectives. Chapter 3: BA algorithm development and testing: in this chapter an overview of general considerations required to build the algorithm is included. The methods developed and tested to obtain the algorithm to detect burned areas will be presented. Since results from these tests helped shaping the algorithm final configuration, the structure in this thesis is not separated in methods and results. Instead, results from the different phases of the algorithm are introduced in this chapter. Chapter 4: BA product assessment: burned area global estimates for years 2006 to 2008 obtained with the MERIS algorithm developed are included here. Results analysis, validation and inter-comparison with other BA products are introduced in this chapter. Chapter 5: Discussion: analysis and discussion on the steps taken to develop the algorithm, results obtained and limitations found are included in this section. Chapter 6: Conclusions and perspectives: main outcomes and lessons learned from the development of this algorithm as well as the way forward are introduced in this chapter. The first two scientific publications result of this work are included in Annex 2 and Annex 3. Annex 2 is a paper published in Remote Sensing of Environment containing the main algorithm developments. Annex 3 is a paper submitted and accepted with minor corrections to Geofocus – Revista Internacional de Ciencia y Tecnología de la Información Geográfica. It summarises the main improvements made on version 1 that lead to version 2 of the algorithm. The main achievement of the work carried out within this thesis is the development of the first algorithm based on MERIS data to obtain BA on a global scale, at higher resolution than the current BA collections, and improving the quality of existing European BA collections. Although the algorithm presents some limitations and future work is still needed to improve current results, the interest stands now on obtaining a longer time series, and on ensuring the continuity of these measurements, to monitor BA and to use this information in the context of climate change. In fact, this algorithm will be the basis for computing the full MERIS BA time series for the second phase of the fire_cci project (2002 to 2012). It will also prepare for the upcoming generations of the European Space Agency BA products, particularly for those based on Sentinel-3 OLCISLSTR sensors. The algorithm will also be adapted to other sensors, such as MODIS bands 1 and 2, with higher spatial resolution and revisit time. The availability of alternative BA time series would complement existing BA products, providing more robust estimations and improvements in the uncertainty characterisation of BA inputs for climate models. Furthermore, different BA products can provide diverse regional accuracies and therefore, merging outputs from global synthesis may greatly improve the way BA trends are currently characterised