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Biblioteca(s): |
Epagri-Sede. |
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Data corrente: |
27/12/2022 |
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Data da última atualização: |
27/12/2022 |
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Tipo da produção científica: |
Artigo em Anais de Congresso / Nota Técnica |
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Autoria: |
GIEHL, A. L. |
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Título: |
Bovinocultura - Agosto 2022. |
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Ano de publicação: |
2022 |
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Fonte/Imprenta: |
Boletim Agropecuário, Florianópolis, n. 111, p. 41-44, 2022. |
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Idioma: |
Português |
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Conteúdo: |
O presente documento apresenta a análise conjuntural do mercado e da produção de bovinos em Santa Catarina. O mesmo constitui-se em parte integrante do Boletim Agropecuário da Epagri/Cepa referente ao mês de agosto/2022 (Boletim n. 111). |
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Thesagro: |
Análise de mercado; bovinocultura; bovinos; carne bovina; conjuntura; preços. |
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Categoria do assunto: |
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Marc: |
LEADER 00748naa a2200193 a 4500
001 1133028
005 2022-12-27
008 2022 bl uuuu u00u1 u #d
100 1 $aGIEHL, A. L.
245 $aBovinocultura - Agosto 2022.$h[electronic resource]
260 $c2022
520 $aO presente documento apresenta a análise conjuntural do mercado e da produção de bovinos em Santa Catarina. O mesmo constitui-se em parte integrante do Boletim Agropecuário da Epagri/Cepa referente ao mês de agosto/2022 (Boletim n. 111).
650 $aAnálise de mercado
650 $abovinocultura
650 $abovinos
650 $acarne bovina
650 $aconjuntura
650 $apreços
773 $tBoletim Agropecuário, Florianópolis$gn. 111, p. 41-44, 2022.
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Epagri-Sede (Epagri-Sede) |
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Biblioteca(s): |
Epagri-Sede. |
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Data corrente: |
12/04/2016 |
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Data da última atualização: |
12/04/2016 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
Internacional - B |
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Autoria: |
EBERHARDT, I. D. R.; SCHULTZ, B.; RIZZI, R.; SANCHES, I. D.; FORMAGGIO, A. R.; ATZBERGER, C.; MELLO, M. P.; IMMITZER, M.; TRABAQUINI, K.; FOSCHIERA, W.; LUIZ, A. J. B. |
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Título: |
Cloud Cover Assessment for Operational Crop Monitoring Systems in Tropical Areas. |
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Ano de publicação: |
2016 |
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Fonte/Imprenta: |
Remote Sensing, Suiça, v. 8, n. 3, p. 219-233, 2016. |
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Idioma: |
Inglês |
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Conteúdo: |
The potential of optical remote sensing data to identify, map and monitor croplands is well recognized. However, clouds strongly limit the usefulness of optical imagery for these applications. This paper aims at assessing cloud cover conditions over four states in the tropical and sub-tropical Center-South region of Brazil to guide the development of an appropriate agricultural monitoring system based on Landsat-like imagery. Cloudiness was assessed during overlapping four months periods to match the typical length of crop cycles in the study area. The percentage of clear sky occurrence was computed from the 1 km resolution MODIS Cloud Mask product (MOD35) considering 14 years of data between July 2000 and June 2014. Results showed high seasonality of cloud occurrence within the crop year with strong variations across the study area. The maximum seasonality was observed for the two states in the northern part of the study area (i.e., the ones closer to the Equator line), which also presented the lowest averaged values (15%) of clear sky occurrence during the main (summer) cropping period (November to February). In these locations, optical data faces severe constraints for mapping summer crops. On the other hand, relatively favorable conditions were found in the southern part of the study region. In the South, clear sky values of around 45% were found and no significant clear sky seasonality was observed. Results underpin the challenges to implement an operational crop monitoring system based solely on optical remote sensing imagery in tropical and sub-tropical regions, in particular if short-cycle crops have to be monitored during the cloudy summer months. To cope with cloudiness issues, we recommend the use of new systems with higher repetition rates such as Sentinel-2. For local studies, Unmanned Aircraft Vehicles (UAVs) might be used to augment the observing capability. Multi-sensor approaches combining optical and microwave data can be another option. In cases where wall-to-wall maps are not mandatory, statistical sampling approaches might also be a suitable alternative for obtaining useful crop area information. MenosThe potential of optical remote sensing data to identify, map and monitor croplands is well recognized. However, clouds strongly limit the usefulness of optical imagery for these applications. This paper aims at assessing cloud cover conditions over four states in the tropical and sub-tropical Center-South region of Brazil to guide the development of an appropriate agricultural monitoring system based on Landsat-like imagery. Cloudiness was assessed during overlapping four months periods to match the typical length of crop cycles in the study area. The percentage of clear sky occurrence was computed from the 1 km resolution MODIS Cloud Mask product (MOD35) considering 14 years of data between July 2000 and June 2014. Results showed high seasonality of cloud occurrence within the crop year with strong variations across the study area. The maximum seasonality was observed for the two states in the northern part of the study area (i.e., the ones closer to the Equator line), which also presented the lowest averaged values (15%) of clear sky occurrence during the main (summer) cropping period (November to February). In these locations, optical data faces severe constraints for mapping summer crops. On the other hand, relatively favorable conditions were found in the southern part of the study region. In the South, clear sky values of around 45% were found and no significant clear sky seasonality was observed. Results underpin the challenges to implement an operational crop monito... Mostrar Tudo |
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Palavras-Chave: |
agriculture monitoring; clear sky coverage; crop classification; MODIS. |
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Categoria do assunto: |
Z Localizações Geográficas |
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Marc: |
LEADER 02971naa a2200289 a 4500
001 1124955
005 2016-04-12
008 2016 bl uuuu u00u1 u #d
100 1 $aEBERHARDT, I. D. R.
245 $aCloud Cover Assessment for Operational Crop Monitoring Systems in Tropical Areas.$h[electronic resource]
260 $c2016
520 $aThe potential of optical remote sensing data to identify, map and monitor croplands is well recognized. However, clouds strongly limit the usefulness of optical imagery for these applications. This paper aims at assessing cloud cover conditions over four states in the tropical and sub-tropical Center-South region of Brazil to guide the development of an appropriate agricultural monitoring system based on Landsat-like imagery. Cloudiness was assessed during overlapping four months periods to match the typical length of crop cycles in the study area. The percentage of clear sky occurrence was computed from the 1 km resolution MODIS Cloud Mask product (MOD35) considering 14 years of data between July 2000 and June 2014. Results showed high seasonality of cloud occurrence within the crop year with strong variations across the study area. The maximum seasonality was observed for the two states in the northern part of the study area (i.e., the ones closer to the Equator line), which also presented the lowest averaged values (15%) of clear sky occurrence during the main (summer) cropping period (November to February). In these locations, optical data faces severe constraints for mapping summer crops. On the other hand, relatively favorable conditions were found in the southern part of the study region. In the South, clear sky values of around 45% were found and no significant clear sky seasonality was observed. Results underpin the challenges to implement an operational crop monitoring system based solely on optical remote sensing imagery in tropical and sub-tropical regions, in particular if short-cycle crops have to be monitored during the cloudy summer months. To cope with cloudiness issues, we recommend the use of new systems with higher repetition rates such as Sentinel-2. For local studies, Unmanned Aircraft Vehicles (UAVs) might be used to augment the observing capability. Multi-sensor approaches combining optical and microwave data can be another option. In cases where wall-to-wall maps are not mandatory, statistical sampling approaches might also be a suitable alternative for obtaining useful crop area information.
653 $aagriculture monitoring
653 $aclear sky coverage
653 $acrop classification
653 $aMODIS
700 1 $aSCHULTZ, B.
700 1 $aRIZZI, R.
700 1 $aSANCHES, I. D.
700 1 $aFORMAGGIO, A. R.
700 1 $aATZBERGER, C.
700 1 $aMELLO, M. P.
700 1 $aIMMITZER, M.
700 1 $aTRABAQUINI, K.
700 1 $aFOSCHIERA, W.
700 1 $aLUIZ, A. J. B.
773 $tRemote Sensing, Suiça$gv. 8, n. 3, p. 219-233, 2016.
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