SPATIO-TEMPORAL VARIABILITY OF VEGETATION CONDITION IN IRRIGATED AGRICULTURE THROUGH SENTINEL-2A IMAGES
Given the importance of irrigation in a scenario which is highlighted by the increasing demand for food, it is increasingly necessary to adopt techniques that allow proper monitoring of irrigated areas in order to observe the dynamics of crop conditions. This is possible, in a fast way and with low...
Gespeichert in:
Veröffentlicht in: | Revista brasileira de agricultura irrigada 2017-01, Vol.11 (6), p.1884 |
---|---|
Hauptverfasser: | , , , , , |
Format: | Artikel |
Sprache: | por |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | |
---|---|
container_issue | 6 |
container_start_page | 1884 |
container_title | Revista brasileira de agricultura irrigada |
container_volume | 11 |
creator | Rayssa Balieiro Ribeiro Filgueiras, Roberto Alves Ramos, Maria Camila Laura Thebit de Almeida Tarcila Neves Generoso Luane Inês Brito Monteiro |
description | Given the importance of irrigation in a scenario which is highlighted by the increasing demand for food, it is increasingly necessary to adopt techniques that allow proper monitoring of irrigated areas in order to observe the dynamics of crop conditions. This is possible, in a fast way and with low cost, using remote sensing techniques. In this context, this study aimed to evaluate, with the help of remote sensing, spatial and temporal variability of vegetation conditions for an area irrigated by center pivot to support the management of irrigated agriculture. It was used a series of Sentinel 2A images, from March to July 2016. The images were subjected to pre-processing to be subsequently performed the analysis of vegetation through of the indexes NDVI (Normalized Difference Vegetation Index) and VCI (Vegetation Condition Index). The use of remote sensing in this study allowed the monitoring of the variability of vegetation condition, and the vegetation indexes were sensitive to variations of force, and, therefore, constituting an important source of information in decision-making for irrigation management. |
format | Article |
fullrecord | <record><control><sourceid>proquest</sourceid><recordid>TN_cdi_proquest_journals_1963058096</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>1963058096</sourcerecordid><originalsourceid>FETCH-proquest_journals_19630580963</originalsourceid><addsrcrecordid>eNqNissKwjAQRYMgWLT_EHBdSFvtYxnrmA7ERtJpwZW4UKGIr-j_W8UPEC6cC-cMmBfmWRSkSZqPmO9cJ4QI41kUi8Rjp3ojCU1AsN4YKzVvpUW5QI205WbFW1BAn6LihamW-H3Yz1pUkmDJpbJYNJoaC5xKaxpV8hoqwgp0EEmOa6mgnrDhcX92B__HMZuugIoyuD2u99fBPXfd9fW49GoX5kks5pno8V_1BptTPbw</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1963058096</pqid></control><display><type>article</type><title>SPATIO-TEMPORAL VARIABILITY OF VEGETATION CONDITION IN IRRIGATED AGRICULTURE THROUGH SENTINEL-2A IMAGES</title><source>EZB-FREE-00999 freely available EZB journals</source><creator>Rayssa Balieiro Ribeiro ; Filgueiras, Roberto ; Alves Ramos, Maria Camila ; Laura Thebit de Almeida ; Tarcila Neves Generoso ; Luane Inês Brito Monteiro</creator><creatorcontrib>Rayssa Balieiro Ribeiro ; Filgueiras, Roberto ; Alves Ramos, Maria Camila ; Laura Thebit de Almeida ; Tarcila Neves Generoso ; Luane Inês Brito Monteiro</creatorcontrib><description>Given the importance of irrigation in a scenario which is highlighted by the increasing demand for food, it is increasingly necessary to adopt techniques that allow proper monitoring of irrigated areas in order to observe the dynamics of crop conditions. This is possible, in a fast way and with low cost, using remote sensing techniques. In this context, this study aimed to evaluate, with the help of remote sensing, spatial and temporal variability of vegetation conditions for an area irrigated by center pivot to support the management of irrigated agriculture. It was used a series of Sentinel 2A images, from March to July 2016. The images were subjected to pre-processing to be subsequently performed the analysis of vegetation through of the indexes NDVI (Normalized Difference Vegetation Index) and VCI (Vegetation Condition Index). The use of remote sensing in this study allowed the monitoring of the variability of vegetation condition, and the vegetation indexes were sensitive to variations of force, and, therefore, constituting an important source of information in decision-making for irrigation management.</description><identifier>EISSN: 1982-7679</identifier><language>por</language><publisher>Fortaleza: Instituto de Pesquisa e Inovação na Agricultura Irrigada - INOVAGRI</publisher><subject>Agricultural economics ; Agricultural management ; Agriculture ; Decision making ; Detection ; Dynamics ; Irrigated areas ; Irrigation ; Low cost ; Normalized difference vegetative index ; Remote monitoring ; Remote sensing ; Spatial distribution ; Temporal variations ; Variability ; Vegetation</subject><ispartof>Revista brasileira de agricultura irrigada, 2017-01, Vol.11 (6), p.1884</ispartof><rights>Copyright Instituto de Pesquisa e Inovação na Agricultura Irrigada - INOVAGRI 2017</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,777,781</link.rule.ids></links><search><creatorcontrib>Rayssa Balieiro Ribeiro</creatorcontrib><creatorcontrib>Filgueiras, Roberto</creatorcontrib><creatorcontrib>Alves Ramos, Maria Camila</creatorcontrib><creatorcontrib>Laura Thebit de Almeida</creatorcontrib><creatorcontrib>Tarcila Neves Generoso</creatorcontrib><creatorcontrib>Luane Inês Brito Monteiro</creatorcontrib><title>SPATIO-TEMPORAL VARIABILITY OF VEGETATION CONDITION IN IRRIGATED AGRICULTURE THROUGH SENTINEL-2A IMAGES</title><title>Revista brasileira de agricultura irrigada</title><description>Given the importance of irrigation in a scenario which is highlighted by the increasing demand for food, it is increasingly necessary to adopt techniques that allow proper monitoring of irrigated areas in order to observe the dynamics of crop conditions. This is possible, in a fast way and with low cost, using remote sensing techniques. In this context, this study aimed to evaluate, with the help of remote sensing, spatial and temporal variability of vegetation conditions for an area irrigated by center pivot to support the management of irrigated agriculture. It was used a series of Sentinel 2A images, from March to July 2016. The images were subjected to pre-processing to be subsequently performed the analysis of vegetation through of the indexes NDVI (Normalized Difference Vegetation Index) and VCI (Vegetation Condition Index). The use of remote sensing in this study allowed the monitoring of the variability of vegetation condition, and the vegetation indexes were sensitive to variations of force, and, therefore, constituting an important source of information in decision-making for irrigation management.</description><subject>Agricultural economics</subject><subject>Agricultural management</subject><subject>Agriculture</subject><subject>Decision making</subject><subject>Detection</subject><subject>Dynamics</subject><subject>Irrigated areas</subject><subject>Irrigation</subject><subject>Low cost</subject><subject>Normalized difference vegetative index</subject><subject>Remote monitoring</subject><subject>Remote sensing</subject><subject>Spatial distribution</subject><subject>Temporal variations</subject><subject>Variability</subject><subject>Vegetation</subject><issn>1982-7679</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><recordid>eNqNissKwjAQRYMgWLT_EHBdSFvtYxnrmA7ERtJpwZW4UKGIr-j_W8UPEC6cC-cMmBfmWRSkSZqPmO9cJ4QI41kUi8Rjp3ojCU1AsN4YKzVvpUW5QI205WbFW1BAn6LihamW-H3Yz1pUkmDJpbJYNJoaC5xKaxpV8hoqwgp0EEmOa6mgnrDhcX92B__HMZuugIoyuD2u99fBPXfd9fW49GoX5kks5pno8V_1BptTPbw</recordid><startdate>20170101</startdate><enddate>20170101</enddate><creator>Rayssa Balieiro Ribeiro</creator><creator>Filgueiras, Roberto</creator><creator>Alves Ramos, Maria Camila</creator><creator>Laura Thebit de Almeida</creator><creator>Tarcila Neves Generoso</creator><creator>Luane Inês Brito Monteiro</creator><general>Instituto de Pesquisa e Inovação na Agricultura Irrigada - INOVAGRI</general><scope>3V.</scope><scope>7QH</scope><scope>7UA</scope><scope>7X2</scope><scope>8FE</scope><scope>8FH</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>CLZPN</scope><scope>DWQXO</scope><scope>F1W</scope><scope>H96</scope><scope>HCIFZ</scope><scope>L.G</scope><scope>M0K</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope></search><sort><creationdate>20170101</creationdate><title>SPATIO-TEMPORAL VARIABILITY OF VEGETATION CONDITION IN IRRIGATED AGRICULTURE THROUGH SENTINEL-2A IMAGES</title><author>Rayssa Balieiro Ribeiro ; Filgueiras, Roberto ; Alves Ramos, Maria Camila ; Laura Thebit de Almeida ; Tarcila Neves Generoso ; Luane Inês Brito Monteiro</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-proquest_journals_19630580963</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>por</language><creationdate>2017</creationdate><topic>Agricultural economics</topic><topic>Agricultural management</topic><topic>Agriculture</topic><topic>Decision making</topic><topic>Detection</topic><topic>Dynamics</topic><topic>Irrigated areas</topic><topic>Irrigation</topic><topic>Low cost</topic><topic>Normalized difference vegetative index</topic><topic>Remote monitoring</topic><topic>Remote sensing</topic><topic>Spatial distribution</topic><topic>Temporal variations</topic><topic>Variability</topic><topic>Vegetation</topic><toplevel>online_resources</toplevel><creatorcontrib>Rayssa Balieiro Ribeiro</creatorcontrib><creatorcontrib>Filgueiras, Roberto</creatorcontrib><creatorcontrib>Alves Ramos, Maria Camila</creatorcontrib><creatorcontrib>Laura Thebit de Almeida</creatorcontrib><creatorcontrib>Tarcila Neves Generoso</creatorcontrib><creatorcontrib>Luane Inês Brito Monteiro</creatorcontrib><collection>ProQuest Central (Corporate)</collection><collection>Aqualine</collection><collection>Water Resources Abstracts</collection><collection>Agricultural Science Collection</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Natural Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>Latin America & Iberia Database</collection><collection>ProQuest Central Korea</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>SciTech Premium Collection</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><collection>Agricultural Science Database</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><jtitle>Revista brasileira de agricultura irrigada</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Rayssa Balieiro Ribeiro</au><au>Filgueiras, Roberto</au><au>Alves Ramos, Maria Camila</au><au>Laura Thebit de Almeida</au><au>Tarcila Neves Generoso</au><au>Luane Inês Brito Monteiro</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>SPATIO-TEMPORAL VARIABILITY OF VEGETATION CONDITION IN IRRIGATED AGRICULTURE THROUGH SENTINEL-2A IMAGES</atitle><jtitle>Revista brasileira de agricultura irrigada</jtitle><date>2017-01-01</date><risdate>2017</risdate><volume>11</volume><issue>6</issue><spage>1884</spage><pages>1884-</pages><eissn>1982-7679</eissn><abstract>Given the importance of irrigation in a scenario which is highlighted by the increasing demand for food, it is increasingly necessary to adopt techniques that allow proper monitoring of irrigated areas in order to observe the dynamics of crop conditions. This is possible, in a fast way and with low cost, using remote sensing techniques. In this context, this study aimed to evaluate, with the help of remote sensing, spatial and temporal variability of vegetation conditions for an area irrigated by center pivot to support the management of irrigated agriculture. It was used a series of Sentinel 2A images, from March to July 2016. The images were subjected to pre-processing to be subsequently performed the analysis of vegetation through of the indexes NDVI (Normalized Difference Vegetation Index) and VCI (Vegetation Condition Index). The use of remote sensing in this study allowed the monitoring of the variability of vegetation condition, and the vegetation indexes were sensitive to variations of force, and, therefore, constituting an important source of information in decision-making for irrigation management.</abstract><cop>Fortaleza</cop><pub>Instituto de Pesquisa e Inovação na Agricultura Irrigada - INOVAGRI</pub><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | EISSN: 1982-7679 |
ispartof | Revista brasileira de agricultura irrigada, 2017-01, Vol.11 (6), p.1884 |
issn | 1982-7679 |
language | por |
recordid | cdi_proquest_journals_1963058096 |
source | EZB-FREE-00999 freely available EZB journals |
subjects | Agricultural economics Agricultural management Agriculture Decision making Detection Dynamics Irrigated areas Irrigation Low cost Normalized difference vegetative index Remote monitoring Remote sensing Spatial distribution Temporal variations Variability Vegetation |
title | SPATIO-TEMPORAL VARIABILITY OF VEGETATION CONDITION IN IRRIGATED AGRICULTURE THROUGH SENTINEL-2A IMAGES |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-21T00%3A35%3A49IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=SPATIO-TEMPORAL%20VARIABILITY%20OF%20VEGETATION%20CONDITION%20IN%20IRRIGATED%20AGRICULTURE%20THROUGH%20SENTINEL-2A%20IMAGES&rft.jtitle=Revista%20brasileira%20de%20agricultura%20irrigada&rft.au=Rayssa%20Balieiro%20Ribeiro&rft.date=2017-01-01&rft.volume=11&rft.issue=6&rft.spage=1884&rft.pages=1884-&rft.eissn=1982-7679&rft_id=info:doi/&rft_dat=%3Cproquest%3E1963058096%3C/proquest%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=1963058096&rft_id=info:pmid/&rfr_iscdi=true |