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Use of Remote Sensing for the Assessment of Farmland Biodiversity
In many countries farmland represent the most relevant type of land use. The conservation and the enhancement of biodiversity within these areas is primary objective for the achievement of sustainable management of agro-ecosystems and the level of biodiversity can be used as agri-environmental indicator. The measure of biodiversity over larger territories however, can be very expensive and time consuming. Earth observations have a rich history in characterizing and monitoring biodiversity and ecosystems. The possibility to use remotely sensed data for monitoring biodiversity was identified at the dawn of Earth observations and has been widely used for decades. Remotely sensed data can cost-effectively track changes in ecosystem distribution and status. The new generation of high-spatial and spectral resolution offers more hope for more direct monitoring of habitats and species. Recent developments in satellite remote sensing and in geographic information system (GIS) combined with user oriented computer programs allow us to use ecological principles for biodiversity characterization at landscape level more efficiently. This paper presents an approach for biodiversity characterization at landscape level using geospatial techniques. The present study hypothesizes that the complexity of the landscape is related to biological phytodiversity, and in turn phytodiversity can be considered a proxy of the overall biodiversity. The aim of the study is to estimate the farmland landscape complexity by using a remote sensing based approach. The approach has been validated in a Northern Italian agricultural area (Emilia-Romagna region). The proposed approach can provide policy makers and land use planners valuable, updated and low cost information on farmland landscape complexity and an estimate of its biodiversity. ; JRC.DDG.H.7-Land management and natural hazards
Use of Remote Sensing for the Assessment of Farmland Biodiversity
In many countries farmland represent the most relevant type of land use. The conservation and the enhancement of biodiversity within these areas is primary objective for the achievement of sustainable management of agro-ecosystems and the level of biodiversity can be used as agri-environmental indicator. The measure of biodiversity over larger territories however, can be very expensive and time consuming. Earth observations have a rich history in characterizing and monitoring biodiversity and ecosystems. The possibility to use remotely sensed data for monitoring biodiversity was identified at the dawn of Earth observations and has been widely used for decades. Remotely sensed data can cost-effectively track changes in ecosystem distribution and status. The new generation of high-spatial and spectral resolution offers more hope for more direct monitoring of habitats and species. Recent developments in satellite remote sensing and in geographic information system (GIS) combined with user oriented computer programs allow us to use ecological principles for biodiversity characterization at landscape level more efficiently. This paper presents an approach for biodiversity characterization at landscape level using geospatial techniques. The present study hypothesizes that the complexity of the landscape is related to biological phytodiversity, and in turn phytodiversity can be considered a proxy of the overall biodiversity. The aim of the study is to estimate the farmland landscape complexity by using a remote sensing based approach. The approach has been validated in a Northern Italian agricultural area (Emilia-Romagna region). The proposed approach can provide policy makers and land use planners valuable, updated and low cost information on farmland landscape complexity and an estimate of its biodiversity. ; JRC.DDG.H.7-Land management and natural hazards
Use of Remote Sensing for the Assessment of Farmland Biodiversity
GARDI Ciro (author) / ROSSI Simone (author) / SOMMER Stefan (author)
2010-03-09
Miscellaneous
Electronic Resource
English
DDC:
710
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