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Monitoring forest conditions in a protected Mediterranean coastal area by the analysis of multiyear NDVI data
The operational utilization of remote sensing techniques for monitoring terrestrial ecosystems is often constrained by problems of under-sampling in space and time, particularly in heterogeneous and unstable Mediterranean environments. The current work deals with the use of the NOAA-AVHRR and Landsa...
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Published in: | Remote sensing of environment 2004-02, Vol.89 (4), p.423-433 |
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container_title | Remote sensing of environment |
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creator | Maselli, Fabio |
description | The operational utilization of remote sensing techniques for monitoring terrestrial ecosystems is often constrained by problems of under-sampling in space and time, particularly in heterogeneous and unstable Mediterranean environments. The current work deals with the use of the NOAA-AVHRR and Landsat-TM/ETM+ images to produce long-term NDVI data series characterising coniferous and broadleaved forests in a protected coastal area in Tuscany (Central Italy). Two methods to extract NDVI values of relatively small vegetated areas from NOAA-AVHRR data were first evaluated by comparison to estimates from higher resolution Landsat-TM/ETM+images. The optimal method was then applied to multitemporal AVHRR data series to derive 10-day NDVI profiles of coniferous and broadleaved forests over a 15-year period (1986–2000). Trend analyses performed on these data series showed that notable NDVI decreases occurred during the study period, particularly for the coniferous forest in summer and early fall. Further analysis carried out on local meteorological measurements led to identify the likely causes of these negative trends in contemporaneous winter rainfall decreases which were significantly correlated with the found NDVI variations. |
doi_str_mv | 10.1016/j.rse.2003.10.020 |
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Further analysis carried out on local meteorological measurements led to identify the likely causes of these negative trends in contemporaneous winter rainfall decreases which were significantly correlated with the found NDVI variations.</description><subject>Animal, plant and microbial ecology</subject><subject>Applied geophysics</subject><subject>AVHRR</subject><subject>Biological and medical sciences</subject><subject>Coniferous and broadleaved forests</subject><subject>Earth sciences</subject><subject>Earth, ocean, space</subject><subject>Exact sciences and technology</subject><subject>Fundamental and applied biological sciences. Psychology</subject><subject>General aspects. 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Psychology</topic><topic>General aspects. Techniques</topic><topic>Internal geophysics</topic><topic>NDVI</topic><topic>Rainfall</topic><topic>Teledetection and vegetation maps</topic><topic>TM/ETM</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Maselli, Fabio</creatorcontrib><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>Ecology Abstracts</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</collection><collection>Technology Research Database</collection><collection>Aerospace Database</collection><collection>Advanced Technologies Database with Aerospace</collection><jtitle>Remote sensing of environment</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Maselli, Fabio</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Monitoring forest conditions in a protected Mediterranean coastal area by the analysis of multiyear NDVI data</atitle><jtitle>Remote sensing of environment</jtitle><date>2004-02-29</date><risdate>2004</risdate><volume>89</volume><issue>4</issue><spage>423</spage><epage>433</epage><pages>423-433</pages><issn>0034-4257</issn><eissn>1879-0704</eissn><coden>RSEEA7</coden><abstract>The operational utilization of remote sensing techniques for monitoring terrestrial ecosystems is often constrained by problems of under-sampling in space and time, particularly in heterogeneous and unstable Mediterranean environments. The current work deals with the use of the NOAA-AVHRR and Landsat-TM/ETM+ images to produce long-term NDVI data series characterising coniferous and broadleaved forests in a protected coastal area in Tuscany (Central Italy). Two methods to extract NDVI values of relatively small vegetated areas from NOAA-AVHRR data were first evaluated by comparison to estimates from higher resolution Landsat-TM/ETM+images. The optimal method was then applied to multitemporal AVHRR data series to derive 10-day NDVI profiles of coniferous and broadleaved forests over a 15-year period (1986–2000). Trend analyses performed on these data series showed that notable NDVI decreases occurred during the study period, particularly for the coniferous forest in summer and early fall. 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source | ScienceDirect Freedom Collection 2022-2024 |
subjects | Animal, plant and microbial ecology Applied geophysics AVHRR Biological and medical sciences Coniferous and broadleaved forests Earth sciences Earth, ocean, space Exact sciences and technology Fundamental and applied biological sciences. Psychology General aspects. Techniques Internal geophysics NDVI Rainfall Teledetection and vegetation maps TM/ETM |
title | Monitoring forest conditions in a protected Mediterranean coastal area by the analysis of multiyear NDVI data |
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