Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Assessing Vegetation Decline due to Pollution from Waste Cycle Activities by a Multitemporal Remote-Sensing Approach

Version 1 : Received: 15 November 2021 / Approved: 16 November 2021 / Online: 16 November 2021 (11:39:44 CET)

How to cite: Mancino, G.; Console, R.; Greco, M.; Iacovino, C.; Trivigno, M.L.; Falciano, A. Assessing Vegetation Decline due to Pollution from Waste Cycle Activities by a Multitemporal Remote-Sensing Approach. Preprints 2021, 2021110289 (doi: 10.20944/preprints202111.0289.v1). Mancino, G.; Console, R.; Greco, M.; Iacovino, C.; Trivigno, M.L.; Falciano, A. Assessing Vegetation Decline due to Pollution from Waste Cycle Activities by a Multitemporal Remote-Sensing Approach. Preprints 2021, 2021110289 (doi: 10.20944/preprints202111.0289.v1).

Abstract

The work consisted in identifying possible effects from heavy metals (HMs) pollution due to waste disposal activities in three potentially polluted sites located in Basilicata (Italy), where a release of pollutants with values over the thresholds allowed by the Italian legislation was detected. The potential variations in the physiological efficiency of vegetation have been analyzed through the multitemporal processing of satellite images. In detail, Landsat 5 Thematic Mapper (TM) and Landsat 8 Operational Land Imager (OLI) images were used to calculate the Normalized Difference Vegetation Index (NDVI) trend over the years. Then, the multitemporal trends were analyzed using the median of Theil-Sen, a non-parametric estimator particularly suitable for the treatment of remote sensing data, being able to minimize the outlier effects due to exogenous factors. Finally, the subsequent application of the Mann-Kendall test on the trends identified by Theil-Sen slope allowed the evaluation of trends significance and, therefore, the areas characterized by the effects of contamination on vegetation. The application of the procedure to the three survey sites led to the exclusion of the presence of significant effects of HMs contamination on the vegetation surrounding the sites during the years of waste disposal activities.

Keywords

vegetation decline; multitemporal satellite; time series; remote sensing; Landsat; Theil-Sen estimator; Mann-Kendall test; pollution; heavy metals

Subject

EARTH SCIENCES, Environmental Sciences

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