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Identification of early abandonment in cropland through radar‐based coherence data and application of a Random‐Forest model

Authors: Wouter Meijninger; Berien Elbersen; Michiel Eupen; Stephan Mantel; Pilar Ciria; Andrea Parenti; Marina Sanz Gallego; +3 Authors

Identification of early abandonment in cropland through radar‐based coherence data and application of a Random‐Forest model

Abstract

AbstractIn the context of increased pressures on land for food and non‐food production, it is relevant to understand better, which land resources have become unused and abandoned and where these lands are. Data on where these lands are and what their extend is are not collected in regular statistics. In this paper, we present an approach to detect signs of abandonment in cropping land using radar coherence data. The methodology was tested in the Spanish regions of Albacete and Soria where agricultural land abandonment is a common process. The results show that land abandonment detection using radar coherence data works well for the region of Albacete in arable lands. The radar‐based analysis is a relatively simple method to detect land abandonment in an early to longer term state and can therefore be applied once developed and tested further in other regions to larger areas of the EU where land abandonment is serious and needs monitoring and policy response. The applicability of the method to Soria and Emilia Romagna (Italy) regions shows that there are still challenges to overcome to make the method more widely applicable for detecting land abandonment in other environmental zones of Europe. Lack of reliable training and validation data, like Land Parcel Identification Systems data, in regions is one of the challenges in this respect.

Countries
Netherlands, Italy
Keywords

abandoned lands; radar coherence; satellite remote sensing; unused lands, satellite remote sensing, TJ807-830, Energy industries. Energy policy. Fuel trade, Renewable energy sources, unused lands, radar coherence, abandoned lands, HD9502-9502.5

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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    7
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    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
7
Top 10%
Average
Top 10%
Green
gold