Assessing vegetation variability and trends in north-eastern Brazil using AVHRR and MODIS NDVI time series
Desertification is a challenge in north-eastern Brazil (NEB) that needs to be understood to develop sustainable land-use strategies. This study analyses regional vegetation dynamics in NEB and the compatibility of two NDVI data sets to support future desertification assessment studies in the semi-ar...
Gespeichert in:
| Veröffentlicht in: | European journal of remote sensing 2013-01, Vol.46 (1), p.40-59 |
|---|---|
| Hauptverfasser: | , , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 59 |
|---|---|
| container_issue | 1 |
| container_start_page | 40 |
| container_title | European journal of remote sensing |
| container_volume | 46 |
| creator | Schucknecht, Anne Erasmi, Stefan Niemeyer, Irmgard Matschullat, Jörg |
| description | Desertification is a challenge in north-eastern Brazil (NEB) that needs to be understood to develop sustainable land-use strategies. This study analyses regional vegetation dynamics in NEB and the compatibility of two NDVI data sets to support future desertification assessment studies in the semi-arid Caatinga biome. Vegetation variability and trends in NEB are analysed for 1982-2006, based on monthly AVHRR (GIMMS) NDVI data. The GIMMS data are compared with MODIS NDVI for the overlapping period 2001-2006. Existing statistical methods are applied and existing NDVI analyses in NEB expanded in respect to vegetation trend analysis and data set comparison. |
| doi_str_mv | 10.5721/EuJRS20134603 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_crossref_primary_10_5721_EuJRS20134603</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2200895131</sourcerecordid><originalsourceid>FETCH-LOGICAL-c353t-d1eafd681356430dd10b31cd9a65e6a48c568c4dab0a6352d6382595c6df5aff3</originalsourceid><addsrcrecordid>eNptkM1PAjEQxTdGEwl69N7E82o_tt3dIwIKBiUB5boZtl0sWVpsuxj8613BgybOZebwe-9lXhRdEXzDU0puh83jbE4xYYnA7CTqUJrmcUp5cvrrPo8uvV_jdjKM0yzvROue98p7bVZop1YqQNDWoB04DUtd67BHYCQKThnpkTbIWBfeYgU-KGfQnYNPXaPmoO8tRrPZAX-aDsZz9DxYjFHQG4W8clr5i-isgtqry5_djV7vhy_9UTyZPoz7vUlcMs5CLImCSoqMMC4ShqUkeMlIKXMQXAlIspKLrEwkLDEIxqkULKM856WQFYeqYt3o-ui7dfa9UT4Ua9s400YWlLaf55ww0lLxkSqd9d6pqtg6vQG3Lwguvhst_jTa8tmR16aybgMf1tWyCLCvrascmFL7gv0v_QLF3nuI</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2200895131</pqid></control><display><type>article</type><title>Assessing vegetation variability and trends in north-eastern Brazil using AVHRR and MODIS NDVI time series</title><source>DOAJ Directory of Open Access Journals</source><source>Access via Taylor & Francis (Open Access Collection)</source><creator>Schucknecht, Anne ; Erasmi, Stefan ; Niemeyer, Irmgard ; Matschullat, Jörg</creator><creatorcontrib>Schucknecht, Anne ; Erasmi, Stefan ; Niemeyer, Irmgard ; Matschullat, Jörg</creatorcontrib><description>Desertification is a challenge in north-eastern Brazil (NEB) that needs to be understood to develop sustainable land-use strategies. This study analyses regional vegetation dynamics in NEB and the compatibility of two NDVI data sets to support future desertification assessment studies in the semi-arid Caatinga biome. Vegetation variability and trends in NEB are analysed for 1982-2006, based on monthly AVHRR (GIMMS) NDVI data. The GIMMS data are compared with MODIS NDVI for the overlapping period 2001-2006. Existing statistical methods are applied and existing NDVI analyses in NEB expanded in respect to vegetation trend analysis and data set comparison.</description><identifier>ISSN: 2279-7254</identifier><identifier>EISSN: 2279-7254</identifier><identifier>DOI: 10.5721/EuJRS20134603</identifier><language>eng</language><publisher>Cagiari: Taylor & Francis</publisher><subject>Aridity ; Atlantic Forest ; BFAST ; Cerrado ; Datasets ; Desertification ; Land use ; MODIS ; Normalized Difference Vegetation Index ; precipitation ; Regional development ; Statistical methods ; time series decomposition ; Trend analysis ; Trends ; Vegetation</subject><ispartof>European journal of remote sensing, 2013-01, Vol.46 (1), p.40-59</ispartof><rights>2013 The Author(s). Published by Taylor & Francis. 2013</rights><rights>2013 The Author(s). Published by Taylor & Francis. This work is licensed under the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c353t-d1eafd681356430dd10b31cd9a65e6a48c568c4dab0a6352d6382595c6df5aff3</citedby><cites>FETCH-LOGICAL-c353t-d1eafd681356430dd10b31cd9a65e6a48c568c4dab0a6352d6382595c6df5aff3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.tandfonline.com/doi/pdf/10.5721/EuJRS20134603$$EPDF$$P50$$Ginformaworld$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.tandfonline.com/doi/full/10.5721/EuJRS20134603$$EHTML$$P50$$Ginformaworld$$Hfree_for_read</linktohtml><link.rule.ids>314,780,784,864,27502,27924,27925,59143,59144</link.rule.ids></links><search><creatorcontrib>Schucknecht, Anne</creatorcontrib><creatorcontrib>Erasmi, Stefan</creatorcontrib><creatorcontrib>Niemeyer, Irmgard</creatorcontrib><creatorcontrib>Matschullat, Jörg</creatorcontrib><title>Assessing vegetation variability and trends in north-eastern Brazil using AVHRR and MODIS NDVI time series</title><title>European journal of remote sensing</title><description>Desertification is a challenge in north-eastern Brazil (NEB) that needs to be understood to develop sustainable land-use strategies. This study analyses regional vegetation dynamics in NEB and the compatibility of two NDVI data sets to support future desertification assessment studies in the semi-arid Caatinga biome. Vegetation variability and trends in NEB are analysed for 1982-2006, based on monthly AVHRR (GIMMS) NDVI data. The GIMMS data are compared with MODIS NDVI for the overlapping period 2001-2006. Existing statistical methods are applied and existing NDVI analyses in NEB expanded in respect to vegetation trend analysis and data set comparison.</description><subject>Aridity</subject><subject>Atlantic Forest</subject><subject>BFAST</subject><subject>Cerrado</subject><subject>Datasets</subject><subject>Desertification</subject><subject>Land use</subject><subject>MODIS</subject><subject>Normalized Difference Vegetation Index</subject><subject>precipitation</subject><subject>Regional development</subject><subject>Statistical methods</subject><subject>time series decomposition</subject><subject>Trend analysis</subject><subject>Trends</subject><subject>Vegetation</subject><issn>2279-7254</issn><issn>2279-7254</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2013</creationdate><recordtype>article</recordtype><sourceid>0YH</sourceid><sourceid>8G5</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNptkM1PAjEQxTdGEwl69N7E82o_tt3dIwIKBiUB5boZtl0sWVpsuxj8613BgybOZebwe-9lXhRdEXzDU0puh83jbE4xYYnA7CTqUJrmcUp5cvrrPo8uvV_jdjKM0yzvROue98p7bVZop1YqQNDWoB04DUtd67BHYCQKThnpkTbIWBfeYgU-KGfQnYNPXaPmoO8tRrPZAX-aDsZz9DxYjFHQG4W8clr5i-isgtqry5_djV7vhy_9UTyZPoz7vUlcMs5CLImCSoqMMC4ShqUkeMlIKXMQXAlIspKLrEwkLDEIxqkULKM856WQFYeqYt3o-ui7dfa9UT4Ua9s400YWlLaf55ww0lLxkSqd9d6pqtg6vQG3Lwguvhst_jTa8tmR16aybgMf1tWyCLCvrascmFL7gv0v_QLF3nuI</recordid><startdate>20130101</startdate><enddate>20130101</enddate><creator>Schucknecht, Anne</creator><creator>Erasmi, Stefan</creator><creator>Niemeyer, Irmgard</creator><creator>Matschullat, Jörg</creator><general>Taylor & Francis</general><general>Taylor & Francis Ltd</general><scope>0YH</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7TG</scope><scope>7XB</scope><scope>8FD</scope><scope>8FK</scope><scope>8G5</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>H8D</scope><scope>KL.</scope><scope>L7M</scope><scope>M2O</scope><scope>MBDVC</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>Q9U</scope></search><sort><creationdate>20130101</creationdate><title>Assessing vegetation variability and trends in north-eastern Brazil using AVHRR and MODIS NDVI time series</title><author>Schucknecht, Anne ; Erasmi, Stefan ; Niemeyer, Irmgard ; Matschullat, Jörg</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c353t-d1eafd681356430dd10b31cd9a65e6a48c568c4dab0a6352d6382595c6df5aff3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2013</creationdate><topic>Aridity</topic><topic>Atlantic Forest</topic><topic>BFAST</topic><topic>Cerrado</topic><topic>Datasets</topic><topic>Desertification</topic><topic>Land use</topic><topic>MODIS</topic><topic>Normalized Difference Vegetation Index</topic><topic>precipitation</topic><topic>Regional development</topic><topic>Statistical methods</topic><topic>time series decomposition</topic><topic>Trend analysis</topic><topic>Trends</topic><topic>Vegetation</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Schucknecht, Anne</creatorcontrib><creatorcontrib>Erasmi, Stefan</creatorcontrib><creatorcontrib>Niemeyer, Irmgard</creatorcontrib><creatorcontrib>Matschullat, Jörg</creatorcontrib><collection>Access via Taylor & Francis (Open Access Collection)</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Technology Research Database</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Research Library (Alumni Edition)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>Aerospace Database</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Research Library</collection><collection>Research Library (Corporate)</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>ProQuest Central Basic</collection><jtitle>European journal of remote sensing</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Schucknecht, Anne</au><au>Erasmi, Stefan</au><au>Niemeyer, Irmgard</au><au>Matschullat, Jörg</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Assessing vegetation variability and trends in north-eastern Brazil using AVHRR and MODIS NDVI time series</atitle><jtitle>European journal of remote sensing</jtitle><date>2013-01-01</date><risdate>2013</risdate><volume>46</volume><issue>1</issue><spage>40</spage><epage>59</epage><pages>40-59</pages><issn>2279-7254</issn><eissn>2279-7254</eissn><abstract>Desertification is a challenge in north-eastern Brazil (NEB) that needs to be understood to develop sustainable land-use strategies. This study analyses regional vegetation dynamics in NEB and the compatibility of two NDVI data sets to support future desertification assessment studies in the semi-arid Caatinga biome. Vegetation variability and trends in NEB are analysed for 1982-2006, based on monthly AVHRR (GIMMS) NDVI data. The GIMMS data are compared with MODIS NDVI for the overlapping period 2001-2006. Existing statistical methods are applied and existing NDVI analyses in NEB expanded in respect to vegetation trend analysis and data set comparison.</abstract><cop>Cagiari</cop><pub>Taylor & Francis</pub><doi>10.5721/EuJRS20134603</doi><tpages>20</tpages><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 2279-7254 |
| ispartof | European journal of remote sensing, 2013-01, Vol.46 (1), p.40-59 |
| issn | 2279-7254 2279-7254 |
| language | eng |
| recordid | cdi_crossref_primary_10_5721_EuJRS20134603 |
| source | DOAJ Directory of Open Access Journals; Access via Taylor & Francis (Open Access Collection) |
| subjects | Aridity Atlantic Forest BFAST Cerrado Datasets Desertification Land use MODIS Normalized Difference Vegetation Index precipitation Regional development Statistical methods time series decomposition Trend analysis Trends Vegetation |
| title | Assessing vegetation variability and trends in north-eastern Brazil using AVHRR and MODIS NDVI time series |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-27T06%3A26%3A36IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Assessing%20vegetation%20variability%20and%20trends%20in%20north-eastern%20Brazil%20using%20AVHRR%20and%20MODIS%20NDVI%20time%20series&rft.jtitle=European%20journal%20of%20remote%20sensing&rft.au=Schucknecht,%20Anne&rft.date=2013-01-01&rft.volume=46&rft.issue=1&rft.spage=40&rft.epage=59&rft.pages=40-59&rft.issn=2279-7254&rft.eissn=2279-7254&rft_id=info:doi/10.5721/EuJRS20134603&rft_dat=%3Cproquest_cross%3E2200895131%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2200895131&rft_id=info:pmid/&rfr_iscdi=true |