Early Identification of Land Degradation Hotspots in Complex Bio-Geographic Regions

Remote Sensing

Maria Lanfredi³  Rosa Coppola³  Tiziana Simoniello³  Rosa Coluzzi³  Mariagrazia D𠆞milio³  Vito Imbrenda³  Maria Macchiato²  Arnon Karnieli¹  Ioannis Gitas¹ 

[1] IMAA-CNR (Institute of Methodologies for Environmental Analysis-Italian National Research Council), C. da Santa Loja, 85050 Tito Scalo (PZ), Italy;;Department of Physics, University of Naples Federico II, Monte Sant’ Angelo, 80126 Naples, Italy; E-Mail:;IMAA-CNR (Institute of Methodologies for Environmental Analysis-Italian National Research Council), C. da Santa Loja, 85050 Tito Scalo (PZ), Italy; E-Mails:

关键词: vegetation degradation;    local climate;    Mediterranean landscape;    bio-geographic complexity;    Landsat;    NDVI;   

DOI  :  10.3390/rs70608154

来源: mdpi

【 摘 要 】

The development of low-cost and relatively simple tools to identify emerging land degradation across complex regions is fundamental to plan monitoring and intervention strategies. We propose a procedure that integrates multi-spectral satellite observations and air temperature data to detect areas where the current status of local vegetation and climate shows evident departures from the mean conditions of the investigated region. Our procedure was tested in Basilicata (Italy), which is a typical bio-geographic example of vulnerable Mediterranean landscape. We grouped Landsat TM/ETM+ NDVI and air temperature (T) data by vegetation cover type to estimate the statistical distributions of the departures of NDVI and T from the respective land cover class means. The pixels characterized by contextual left tail NDVI values and right tail T values that persisted in time (2002–2006) were classified as critical to land degradation. According to our results, most of the critical areas (88.6%) corresponded to forests affected by erosion and to riparian buffers that are shaped by fragmentation, as confirmed by aerial and in-situ surveys. Our procedure enables cost-effective screenings of complex areas able to identify raising hotspots that require urgent and deeper investigations.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland.