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Registro Completo |
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Biblioteca(s): |
Embrapa Agricultura Digital. |
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Data corrente: |
24/08/2022 |
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Data da última atualização: |
25/08/2022 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
TORO, A. P. S. G. D.; WERNER, J. P. S.; REIS, A. A. dos; ESQUERDO, J. C. D. M.; ANTUNES, J. F. G.; COUTINHO, A. C.; LAMPARELLI, R. A. C.; MAGALHÃES, P. S. G.; FIGUEIREDO, G. K. D. A. |
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Afiliação: |
FEAGRI/UNICAMP; FEAGRI/UNICAMP; UNICAMP; JULIO CESAR DALLA MORA ESQUERDO, CNPTIA, FEAGRI/UNICAMP; JOAO FRANCISCO GONCALVES ANTUNES, CNPTIA; ALEXANDRE CAMARGO COUTINHO, CNPTIA; UNICAMP; UNICAMP; FEAGRI/UNICAMP. |
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Título: |
Evaluation of early season mapping of integrated crop livestock systems using Sentinel-2 data. |
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Ano de publicação: |
2022 |
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Fonte/Imprenta: |
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, v. 43, B3, p. 1335-1340, 2022. |
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DOI: |
https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-1335-2022 |
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Idioma: |
Inglês |
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Notas: |
Edition of proceedings of the 2022 edition of the XXIVth ISPRS Congress, Nice, France. |
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Conteúdo: |
ABSTRACT. Various approaches were developed considering the need to increase agricultural productivity in cultivated areas without more deforestation, such as the Integrated Crop livestock systems (ICLS). The ICLS could be composed of annual crops followed by pastureland with the presence of cattle. Due to the high temporal dynamic of rotation between crops over the season, monitoring these areas is a big challenge. Also, agricultural organizations worldwide highlight the need for early-season maps for this kind of work. In this context, this study evaluated the potential of open data (Sentinel-2) data to map ICLS areas. The performance of two classifiers was evaluated: one of Machine Learning (random forest) and the other of Deep Learning (LSTM). Three different time windows of data were tested (Entire season, 180 days, and 120 days). Using the RF classifier, it was possible to achieve satisfactory results (Overall accuracy higher than 80%) for the early season (180 days). However, further studies are needed to explain better the lower(when compared to Random Forest) accuracy achieved by LSTM net (0.79 % for 180 days) and compare the results achieved here with results for a study area with different rates of cloud cover. |
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Palavras-Chave: |
Agricultura regenerativa; Aprendizado profundo; Crop identification; Floresta aleatória; Identificação de culturas; LSTM; Random forest; Regenerative agriculture. |
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Thesagro: |
Sensoriamento Remoto. |
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Thesaurus Nal: |
Remote sensing. |
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Categoria do assunto: |
-- |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/doc/1145714/1/AP-Evalution-early-season-2022.pdf
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Marc: |
LEADER 02542naa a2200361 a 4500
001 2145714
005 2022-08-25
008 2022 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.5194/isprs-archives-XLIII-B3-2022-1335-2022$2DOI
100 1 $aTORO, A. P. S. G. D.
245 $aEvaluation of early season mapping of integrated crop livestock systems using Sentinel-2 data.$h[electronic resource]
260 $c2022
500 $aEdition of proceedings of the 2022 edition of the XXIVth ISPRS Congress, Nice, France.
520 $aABSTRACT. Various approaches were developed considering the need to increase agricultural productivity in cultivated areas without more deforestation, such as the Integrated Crop livestock systems (ICLS). The ICLS could be composed of annual crops followed by pastureland with the presence of cattle. Due to the high temporal dynamic of rotation between crops over the season, monitoring these areas is a big challenge. Also, agricultural organizations worldwide highlight the need for early-season maps for this kind of work. In this context, this study evaluated the potential of open data (Sentinel-2) data to map ICLS areas. The performance of two classifiers was evaluated: one of Machine Learning (random forest) and the other of Deep Learning (LSTM). Three different time windows of data were tested (Entire season, 180 days, and 120 days). Using the RF classifier, it was possible to achieve satisfactory results (Overall accuracy higher than 80%) for the early season (180 days). However, further studies are needed to explain better the lower(when compared to Random Forest) accuracy achieved by LSTM net (0.79 % for 180 days) and compare the results achieved here with results for a study area with different rates of cloud cover.
650 $aRemote sensing
650 $aSensoriamento Remoto
653 $aAgricultura regenerativa
653 $aAprendizado profundo
653 $aCrop identification
653 $aFloresta aleatória
653 $aIdentificação de culturas
653 $aLSTM
653 $aRandom forest
653 $aRegenerative agriculture
700 1 $aWERNER, J. P. S.
700 1 $aREIS, A. A. dos
700 1 $aESQUERDO, J. C. D. M.
700 1 $aANTUNES, J. F. G.
700 1 $aCOUTINHO, A. C.
700 1 $aLAMPARELLI, R. A. C.
700 1 $aMAGALHÃES, P. S. G.
700 1 $aFIGUEIREDO, G. K. D. A.
773 $tThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences$gv. 43, B3, p. 1335-1340, 2022.
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Registro original: |
Embrapa Agricultura Digital (CNPTIA) |
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Registro Completo
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Biblioteca(s): |
Embrapa Semiárido. |
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Data corrente: |
18/02/2021 |
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Data da última atualização: |
12/01/2023 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
A - 1 |
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Autoria: |
SILVA, T. G. F. da; QUEIROZ, M. G. de; ZOLNIER, S.; SOUZA, L. S. B. de; SOUZA, C. A. A. de; MOURA, M. S. B. de; ARAUJO, G. G. L. de; STEIDLE NETO, A. J.; SANTOS, T. S. dos; MELO, A. L. de; CRUZ NETO, J. F. da; SILVA, M. J. da; ALVES, H. K. M. N. |
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Afiliação: |
Thieres George Freire da Silva; Maria Gabriela de Queiroz; Sérgio Zolnier; Luciana Sandra Bastos de Souza; Carlos André Alves de Souza; MAGNA SOELMA BESERRA DE MOURA, CPATSA; GHERMAN GARCIA LEAL DE ARAUJO, CPATSA; Antonio Jose Steidle Neto; Thalyta Soares dos Santos; Andre Laurênio de Melo; José Francisco da Cruz Neto; Marcelo Jose da Silva; Hygor Kristoph Muniz Nunes Alves. |
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Título: |
Soil properties and microclimate of two predominant landscapes in the Brazilian semiarid region: comparison between a seasonally dry tropical forest and a deforested area. |
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Ano de publicação: |
2021 |
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Fonte/Imprenta: |
Soil and Tillage Research, v. 207, mar. 2021. |
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DOI: |
https://doi.org/10.1016/j.still.2020.104852 |
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Idioma: |
Inglês |
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Conteúdo: |
The Brazilian semiarid region has been subjected to strong man-made actions since the 1970s, which have resulted in landscape transformation. The scientific literature presents several studies on the soil properties or microclimate of different types of landscapes; however, less attention was having been paid to the surface contrast between native vegetation and bare soil. The objective of this research was to evaluate the soil properties and microclimate of two common landscapes in the Brazilian semiarid region, a seasonally dry tropical forest (Caatinga) and a deforested area. Soil and microclimate data were obtained from two sites, both located in the State of Pernambuco, Brazil. Soil samples were collected on six dates and from layers, and microclimate variables were measured for three years. Soil properties and microclimatic data were evaluated using the MannWhitney test, as well as regression and principal component analysis. Successive years of agricultural practices affected the bulk density, promoting an increase in the total porosity of the soil in the deforested area site. In addition, changes were verified in the magnitude of many chemical properties (pH, P, K+, Mg2+, Cu2+, Fe, Mn, Zn2+ and Ca2+), indicating soil degradation. Compared with the Caatinga forest site, the minimum air temperature was 2.3 ◦C, and the maximum vapor pressure deficit was 7% higher in the deforested area site, and it is very likely that Caatinga removal there will lead to a reduction in precipitation. The results suggest that Caatinga vegetation removal followed by agricultural practices and subsequent land abandonment promotes significant changes in soil properties and the microclimate, which can contribute to advances in desertification and affects agricultural activities in the Brazilian semiarid region. MenosThe Brazilian semiarid region has been subjected to strong man-made actions since the 1970s, which have resulted in landscape transformation. The scientific literature presents several studies on the soil properties or microclimate of different types of landscapes; however, less attention was having been paid to the surface contrast between native vegetation and bare soil. The objective of this research was to evaluate the soil properties and microclimate of two common landscapes in the Brazilian semiarid region, a seasonally dry tropical forest (Caatinga) and a deforested area. Soil and microclimate data were obtained from two sites, both located in the State of Pernambuco, Brazil. Soil samples were collected on six dates and from layers, and microclimate variables were measured for three years. Soil properties and microclimatic data were evaluated using the MannWhitney test, as well as regression and principal component analysis. Successive years of agricultural practices affected the bulk density, promoting an increase in the total porosity of the soil in the deforested area site. In addition, changes were verified in the magnitude of many chemical properties (pH, P, K+, Mg2+, Cu2+, Fe, Mn, Zn2+ and Ca2+), indicating soil degradation. Compared with the Caatinga forest site, the minimum air temperature was 2.3 ◦C, and the maximum vapor pressure deficit was 7% higher in the deforested area site, and it is very likely that Caatinga removal there will lead to a reductio... Mostrar Tudo |
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Palavras-Chave: |
Degradação do solo; Evasão; Mudanças nos nutrientes do solo; Terras agrícolas. |
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Thesagro: |
Caatinga; Clima; Degradação Ambiental; Solo; Uso da Terra. |
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Thesaurus NAL: |
Climate. |
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Categoria do assunto: |
P Recursos Naturais, Ciências Ambientais e da Terra |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/221231/1/Soil-properties-and-microclimate-2021.pdf
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Marc: |
LEADER 03074naa a2200397 a 4500
001 2130062
005 2023-01-12
008 2021 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.1016/j.still.2020.104852$2DOI
100 1 $aSILVA, T. G. F. da
245 $aSoil properties and microclimate of two predominant landscapes in the Brazilian semiarid region$bcomparison between a seasonally dry tropical forest and a deforested area.$h[electronic resource]
260 $c2021
520 $aThe Brazilian semiarid region has been subjected to strong man-made actions since the 1970s, which have resulted in landscape transformation. The scientific literature presents several studies on the soil properties or microclimate of different types of landscapes; however, less attention was having been paid to the surface contrast between native vegetation and bare soil. The objective of this research was to evaluate the soil properties and microclimate of two common landscapes in the Brazilian semiarid region, a seasonally dry tropical forest (Caatinga) and a deforested area. Soil and microclimate data were obtained from two sites, both located in the State of Pernambuco, Brazil. Soil samples were collected on six dates and from layers, and microclimate variables were measured for three years. Soil properties and microclimatic data were evaluated using the MannWhitney test, as well as regression and principal component analysis. Successive years of agricultural practices affected the bulk density, promoting an increase in the total porosity of the soil in the deforested area site. In addition, changes were verified in the magnitude of many chemical properties (pH, P, K+, Mg2+, Cu2+, Fe, Mn, Zn2+ and Ca2+), indicating soil degradation. Compared with the Caatinga forest site, the minimum air temperature was 2.3 ◦C, and the maximum vapor pressure deficit was 7% higher in the deforested area site, and it is very likely that Caatinga removal there will lead to a reduction in precipitation. The results suggest that Caatinga vegetation removal followed by agricultural practices and subsequent land abandonment promotes significant changes in soil properties and the microclimate, which can contribute to advances in desertification and affects agricultural activities in the Brazilian semiarid region.
650 $aClimate
650 $aCaatinga
650 $aClima
650 $aDegradação Ambiental
650 $aSolo
650 $aUso da Terra
653 $aDegradação do solo
653 $aEvasão
653 $aMudanças nos nutrientes do solo
653 $aTerras agrícolas
700 1 $aQUEIROZ, M. G. de
700 1 $aZOLNIER, S.
700 1 $aSOUZA, L. S. B. de
700 1 $aSOUZA, C. A. A. de
700 1 $aMOURA, M. S. B. de
700 1 $aARAUJO, G. G. L. de
700 1 $aSTEIDLE NETO, A. J.
700 1 $aSANTOS, T. S. dos
700 1 $aMELO, A. L. de
700 1 $aCRUZ NETO, J. F. da
700 1 $aSILVA, M. J. da
700 1 $aALVES, H. K. M. N.
773 $tSoil and Tillage Research$gv. 207, mar. 2021.
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Embrapa Semiárido (CPATSA) |
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