Global change caused by human activity (e.g., land fragmentation, deforestation, pollution, anthropization of natural landscapes) has several effects on the biomes of the Earth, leading to alterations in the functioning of ecological systems. In this context, remote sensing represents an important tool to assess ecosystem changes, as it allows to collect a huge amount of data at different temporal and spatial resolutions concerning various compartments of the Earth system (land, ocean, atmosphere, and cryosphere). This information can be used to estimate precipitation patterns, global temperatures, snow cover and aerosol concentrations. The aim of this work is to exploit this wide availability of data to display the ecosystem changes using a new visualization method: the helical graphs. The helical graphs represent the change of a variable over time, reporting on the y-axis its moving averages and on the x-axis its rates of change. These new charts were tested on the NDVI index retrieved from Google Earth Engine (https://earthengine.google.com/) to visualize trends on selected biomes of the Earth (tropical and boreal forests). The results show that the helical graphs are a useful tool to highlight trends that might not be easily detected in a time series. In conclusion, the helical graphs can have a lot of application in ecology, especially exploiting the wide amount of data available thanks to the remote sensing.

Helical graphs to visualize the NDVI temporal variation of forest vegetation in an open source space

Di Musciano M.;
2023-01-01

Abstract

Global change caused by human activity (e.g., land fragmentation, deforestation, pollution, anthropization of natural landscapes) has several effects on the biomes of the Earth, leading to alterations in the functioning of ecological systems. In this context, remote sensing represents an important tool to assess ecosystem changes, as it allows to collect a huge amount of data at different temporal and spatial resolutions concerning various compartments of the Earth system (land, ocean, atmosphere, and cryosphere). This information can be used to estimate precipitation patterns, global temperatures, snow cover and aerosol concentrations. The aim of this work is to exploit this wide availability of data to display the ecosystem changes using a new visualization method: the helical graphs. The helical graphs represent the change of a variable over time, reporting on the y-axis its moving averages and on the x-axis its rates of change. These new charts were tested on the NDVI index retrieved from Google Earth Engine (https://earthengine.google.com/) to visualize trends on selected biomes of the Earth (tropical and boreal forests). The results show that the helical graphs are a useful tool to highlight trends that might not be easily detected in a time series. In conclusion, the helical graphs can have a lot of application in ecology, especially exploiting the wide amount of data available thanks to the remote sensing.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11697/205114
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