Browsing by Author "Massetti, Andrea"
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- Mapping and assessing land cover/land use and aboveground carbon stocks rapid changes in small oceanic islands' terrestrial ecosystems: A case study of Madeira Island, Portugal (2009–2011)Publication . Massetti, Andrea; Gil, Artur José FreireSmall islands face environmental issues directly or indirectly related to land cover/land use changes (LCLUC), such as natural hazards, climate change, loss of biodiversity and proliferation of invasive alien species, some of which are caused by direct human exploitation. A Land Cover/Land Use Change (LCLUC) detection approach based on PCA and vegetation indices derived from low cost high-resolution RapidEye multispectral satellite data and available vegetation maps was developed to assess vegetated/forested aboveground carbon stocks and their changes in Madeira Island, Portugal, for the period between December 2009 and August 2011 due to catastrophic events occurred in 2010. During this period, the identified LCLUC revealed a relevant decrease of vegetated areas (especially those dominated by native/endemic communities) substituted by increases of non-vegetated and human-managed vegetated/forested areas. In particular, there was a decrease of 2% of vegetated areas, 30% of which were represented by native/endemic vegetation. The largest and most accurate LCLUC detected were used to estimate changes in aboveground biomass carbon (AGC) stocks. In 2010 more than 25,000 Mg of AGC stocks may have been released. Both relevant LCLUC and AGC stocks depletion in such short period of time may have been strongly enhanced by two catastrophic events that affected Madeira in February (flashflood and landslides) and August 2010 (wildfires). This straightforward and cost-effective methodological approach may be successfully applied in remote territories such as islands or mountainous areas, where the logistic and economic costs associated to periodic and standard airborne remote sensing campaigns for mapping, assessing and monitoring aboveground biomass carbon stocks are generally unaffordable for most decision-makers and land managers in these territories.
- The spectralrao-monitoring Python package : A RAO's Q diversity index-based application for land-cover/land-use change detection in multifunctional agricultural areasPublication . Tassi, Andrea; Massetti, Andrea; Gil, Artur José FreireMonitoring multifunctional agricultural areas is paramount to ensure their cost-effective management. The remote sensing-based detection of land-cover/land-use (LCLU) changes and analysis of vegetation dynamics constitute a relevant indicator to support robust monitoring schemes, allowing the control of agri-environmental conditions and enforcing related measures and policies. The Rao's Q diversity index (RaoQ) is frequently used to measure functional diversity in ecology, thanks to the textural analysis of the environment. This paper aims to develop and provide an open-source Python application whose workflow may constitute a RaoQ-based LCLU change monitoring tool for multifunctional agricultural areas. Here, a use case is presented for detecting and mapping LCLU changes leveraging the free and open access Landsat 8 (L8) satellite data. The workflow is organized in four main stages: (1) data processing; (2) Normalized Difference Vegetation Index (NDVI) calculation; (3) RaoQ calculation; and (4) detection and mapping of LCLU changes through thresholding of RaoQ. Three methodological approaches were developed (RaoC – “classic” RaoQ; RaoMD – “multidimensional” RaoQ, and “classic + multidimensional” RaoQ) with overall accuracies ranging from 0.88 to 0.92. An example of an agri-environmental monitoring decision-support framework based on spectralrao-monitoring is presented. The application is easily reproducible, and the code is fully available and utilizable with other sensors at different resolutions to support monitoring other types of agricultural areas.