Multi-scale Geographical Analysis of Global Change

Research Group Leader: Francisco Javier Martínez Vega (Senior Scientist)

Members:

Alumni in the last 10 years:

 

The generation of geographical information from remote sensing and GIS provides a unique opportunity to manage and analyze spatial events and processes in relation to Climate Change. To understand its causes and mitigate its adverse effects, this technology supports decision making through accurate, repetitive, consistent, specific, and quick data. In this context, our research group seeks to train scientists and advance in Climate Change knowledge through the application of Geographic Information Technologies at multiple scales. From local comprehensive field campaigns to global satellite observations, the goal is to comprehend how climate change affects the physical environment and human activities. Our research lines focus on:

  • Environmental Remote Sensing: From a multiscalar approach we estimate key biophysical vegetation variables in terrestrial ecosystems and agricultural land, including leaf area index, canopy water content, leaf pigments and nitrogen content. Field sampling of these variables validate estimates from field, UAV, airborne and satellite, multi and hyper spectral sensors.
  • Protected Areas: We develop indicators to assess and monitor the sustainability of terrestrial and marine protected areas and their surroundings. An integrated perspective considers the four sustainability pillars: environment, society, economy and governance. The implementation of semi-experimental BACI type designs intend to determinate the effectiveness of the protect areas or their networks according to multiple socio-environment aspects. We also study which variables influence their sustainability that are key for the biodiversity conservation. To do this, we generate spatially explicit, updated and useful information for territorial planners and managers, public decision-makers, scientist and the public in general.
  • Wildfires: We model multitemporal wildfire human risk and their explanatory factors through different techniques: logistic regression (LR), generalized linear models (GLM) and maximum entropy models (Maxent). Land use-land cover changes, along with climate factors and other human components registered in the Mediterranean regions in the last decades, help explaining wildfire occurrence. We analyze the urban-forest, agricultural-forest and grassland-forest interfaces as indirect drivers of fire occurrence related with Land Use-Land Cover (LULC). Analysis of future LULC scenarios allow to predict how fire occurrence will evolve in the next decades.

The research group manages spectro-radiometry and environmental remote sensing laboratory SpecLab since 2007 that provides instrumental and logistic support to our work and to other CSIC and external research groups. Since 2004, we are part of GEOLAB, an associated unit between University of Alcala’s Department of Geography and CSIC’s Institute of Economy, Geography and Demography. Our objective is to carry out joint research projects using Geographic Information Technologies, collaborate in fieldwork campaigns for the continuous monitoring of environmental variables, share the available research equipment and data, and participate in postgraduate courses.

 

Related sites:

Current projects:

Past projects:

Instituto de Economía, Geografía y Demografía (IEGD)

Dept. of Applied Economics and Geography