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Other ORP type . 2018
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Remote sensing for monitoring and mapping land productivity in Italy. A rapid assessment methodology

Authors: Borfecchia, F.; De Cecco, L.; De Felice, M.; Sciortino, M.;

Remote sensing for monitoring and mapping land productivity in Italy. A rapid assessment methodology

Abstract

Presentiamo una metodologia basata sul telerilevamento per una rapida valutazione dello stato e delle tendenze della produttività del territorio (LP) a livello nazionale e subnazionale. Questa metodologia mira a sostenere le politiche ambientali nazionali e internazionali per raggiungere l'obiettivo di Land Degradation Neutrality nel quadro dell'Agenda 2030 delle Nazioni Unite e degli Obiettivi di sviluppo sostenibile. Il lavoro è stato eseguito utilizzando l'indice NDVI (Normalized Difference Vegetation Index) della NASA-MODIS come indicatore proxy dello stato e della tendenza di LP. Lo stato LP è stato identificato dalla media e dalla deviazione standard dei valori annuali LP 2000-2015. I trend di LP delle serie annuali sono state calcolate utilizzando i test Mann-Kendall (MK) e Contextual Mann-Kendal (CMK). La quantità di terreno con trend crescenti e decrescenti è stata valutata assumendo il livello di significatività del 95% nelle aree ove la qualità del dati NDVI è affidabile. L'area di trend LP crescenti e decrescenti è stimata per il territorio nazionale e per diverse coperture del suolo. Le variazioni di LP positive osservate sono sicumente correlate alla progressiva rinaturalizzazione del territorio in seguito alla diminuzione delle attività agricole e all'aumento delle precipitazioni nella stagione invernale nel periodo di riferimento. La diminuzione di LP ha interessato aree molto limitate correlate a variazioni delle precipitazioni stagionali e/o delle attività umane. I comuni maggiormente interessati dal declino o dall'aumento di LP vengono identificati allo scopo di individuare le aree ove possibilmente effettuare specifiche attività di monitoraggio e convalida future.

We present a remote sensing-based methodology for rapid assessment of status and trends of Land Productivity (LP) at national and sub-national scales. This methodology aims at supporting environmental national and international policies to achieve the Land Degradation Neutrality target in the framework of the UN Agenda 2030 and the Sustainable Development Goals. The work was performed in Italy using the NASA-MODIS Normalized Difference Vegetation Index (NDVI) as proxy indicator of LP status and trend. LP status was identified by mean and standard deviation of 2000-2015 yearly LP values. LP trends of the yearly time series were computed using Mann-Kendall (MK) and Contextual MK (CMK) tests. The amount of land with valid increasing and decreasing trends is estimated assuming the 95% significance level of trends in the areas with good pixel reliability. The area of increasing and decreasing LP are estimated for the national territory and for different land covers. The widespread observed positive LP variations were correlated to the progressive renaturalization of lands subsequent to the decrease of agricultural activities and increasing precipitation trends in the winter season. LP decrease affected very limited areas and hot spots were correlated to changes of seasonal precipitation and human activities. The municipalities most affected by LP decline or increase are identified for future monitoring and validation activities.

Country
Italy
Keywords

NDVI, Land productivity, NDVI;Land productivity;Remote sensing, Remote sensing

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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!
0
Average
Average
Average