Aplicação de Sensoriamento Remoto na análise das mudanças da vegetação de campos de altitude no Pantanal usando dados multitemporais Landsat. e2321497
Due to the cold climate and altitude, to identify trends in the dynamic vegetation and the main factors that contribute to changes in vegetation cover in grassland areas is essential to understand climate change in mountainous regions. Landsat-8 OLI and Landsat-1 MSS images from 1973 to 2022 of Mor...
| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Universidade Estadual de Ponta Grossa
2023-04-01
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| Series: | Terr@ Plural |
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| Online Access: | https://revistas.uepg.br/index.php/tp/article/view/21497/209209217539 |
| _version_ | 1797346548944732160 |
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| author | Dhonatan Diego Pessi Normandes Matos da Silva Camila Leonardo Mioto Domingos Sávio Barbosa Rodrigo Martins Moreira Mateus Antonio Gums Gomes Alfredo Marcelo Grigio Vinicius de Oliveira Ribeiro Marco Antonio Diodato Antonio Conceição Paranhos Filho |
| author_facet | Dhonatan Diego Pessi Normandes Matos da Silva Camila Leonardo Mioto Domingos Sávio Barbosa Rodrigo Martins Moreira Mateus Antonio Gums Gomes Alfredo Marcelo Grigio Vinicius de Oliveira Ribeiro Marco Antonio Diodato Antonio Conceição Paranhos Filho |
| author_sort | Dhonatan Diego Pessi |
| collection | DOAJ |
| description | Due to the cold climate and altitude, to identify trends in the dynamic vegetation and the main factors that contribute to changes in vegetation cover in grassland areas is essential to understand climate change in mountainous regions. Landsat-8 OLI and Landsat-1 MSS images from 1973 to 2022 of Morraria do Urucum and Serra do Amolar were pre-processed in the GEE cloud platform and QGIS. The resampling method per pixel in the scale of values defined for vegetation Campos de Altitude was used to show changes in vegetation cover and its dynamics through the NDVI index. In both study areas, a continuous trend of significant reduction of vegetation in highland grasslands was observed over 50 years. The average decrease was 49% for Urucum (less 2,164 hectares) and 43% for Amolar (less 3,959 hectares). The use of GHG to obtain remote sensing data combined with temporal image analysis offers the potential to quickly perceive trends in large-and small-scale vegetation cover change |
| first_indexed | 2024-03-08T11:35:03Z |
| format | Article |
| id | doaj.art-242e23a25df543fdb3dd76cca4b4f209 |
| institution | Directory Open Access Journal |
| issn | 1982-095X |
| language | English |
| last_indexed | 2024-03-08T11:35:03Z |
| publishDate | 2023-04-01 |
| publisher | Universidade Estadual de Ponta Grossa |
| record_format | Article |
| series | Terr@ Plural |
| spelling | doaj.art-242e23a25df543fdb3dd76cca4b4f2092024-01-25T13:02:25ZengUniversidade Estadual de Ponta GrossaTerr@ Plural1982-095X2023-04-0117e232149710.5212/TerraPlural.v.17.2321497.003Aplicação de Sensoriamento Remoto na análise das mudanças da vegetação de campos de altitude no Pantanal usando dados multitemporais Landsat. e2321497Dhonatan Diego Pessi 0https://orcid.org/0000-0003-0781-785XNormandes Matos da Silva 1https://orcid.org/0000-0002-4631-9725Camila Leonardo Mioto 2https://orcid.org/0000-0002-6951-9527Domingos Sávio Barbosa 3https://orcid.org/0000-0001-6793-0956Rodrigo Martins Moreira 4https://orcid.org/0000-0001-6794-6026Mateus Antonio Gums Gomes 5https://orcid.org/0000-0001-7905-6653Alfredo Marcelo Grigio 6https://orcid.org/0000-0002-2094-9710Vinicius de Oliveira Ribeiro 7https://orcid.org/0000-0002-4373-1132Marco Antonio Diodato 8https://orcid.org/0000-0002-9088-836XAntonio Conceição Paranhos Filho 9https://orcid.org/0000-0002-9838-5337Universidade Federal de Mato Grosso do Sul, UFMS, Campo Grande, MS, BrasilUniversidade Federal de Rondonópolis, UFR, Rondonópolis, MT, BrasilUniversidade Federal de Rondonópolis, UFR, Rondonópolis, MT, BrasilUniversidade Federal de Rondonópolis, UFR, Rondonópolis, MT, BrasilUniversidade Federal de Rondônia, UNIR, Porto Velho, RO, BrasilUniversidade Federal de Rondônia, UNIR, Porto Velho, RO, BrasilUniversidade do Estado do Rio Grande do Norte, UERN, Natal, RN, BrasilUniversidade Estadual de Mato Grosso do Sul, UEMS, Dourados, MS, BrasilUniversidade Federal Rural do Semi-Árido, UFERSA, Mossoró, RN, BrasilUniversidade Federal de Mato Grosso do Sul, UFMS, Campo Grande, MS, BrasilDue to the cold climate and altitude, to identify trends in the dynamic vegetation and the main factors that contribute to changes in vegetation cover in grassland areas is essential to understand climate change in mountainous regions. Landsat-8 OLI and Landsat-1 MSS images from 1973 to 2022 of Morraria do Urucum and Serra do Amolar were pre-processed in the GEE cloud platform and QGIS. The resampling method per pixel in the scale of values defined for vegetation Campos de Altitude was used to show changes in vegetation cover and its dynamics through the NDVI index. In both study areas, a continuous trend of significant reduction of vegetation in highland grasslands was observed over 50 years. The average decrease was 49% for Urucum (less 2,164 hectares) and 43% for Amolar (less 3,959 hectares). The use of GHG to obtain remote sensing data combined with temporal image analysis offers the potential to quickly perceive trends in large-and small-scale vegetation cover changehttps://revistas.uepg.br/index.php/tp/article/view/21497/209209217539mountainous vegetationnatural habitatsconservationecosystem monitoring |
| spellingShingle | Dhonatan Diego Pessi Normandes Matos da Silva Camila Leonardo Mioto Domingos Sávio Barbosa Rodrigo Martins Moreira Mateus Antonio Gums Gomes Alfredo Marcelo Grigio Vinicius de Oliveira Ribeiro Marco Antonio Diodato Antonio Conceição Paranhos Filho Aplicação de Sensoriamento Remoto na análise das mudanças da vegetação de campos de altitude no Pantanal usando dados multitemporais Landsat. e2321497 Terr@ Plural mountainous vegetation natural habitats conservation ecosystem monitoring |
| title | Aplicação de Sensoriamento Remoto na análise das mudanças da vegetação de campos de altitude no Pantanal usando dados multitemporais Landsat. e2321497 |
| title_full | Aplicação de Sensoriamento Remoto na análise das mudanças da vegetação de campos de altitude no Pantanal usando dados multitemporais Landsat. e2321497 |
| title_fullStr | Aplicação de Sensoriamento Remoto na análise das mudanças da vegetação de campos de altitude no Pantanal usando dados multitemporais Landsat. e2321497 |
| title_full_unstemmed | Aplicação de Sensoriamento Remoto na análise das mudanças da vegetação de campos de altitude no Pantanal usando dados multitemporais Landsat. e2321497 |
| title_short | Aplicação de Sensoriamento Remoto na análise das mudanças da vegetação de campos de altitude no Pantanal usando dados multitemporais Landsat. e2321497 |
| title_sort | aplicacao de sensoriamento remoto na analise das mudancas da vegetacao de campos de altitude no pantanal usando dados multitemporais landsat e2321497 |
| topic | mountainous vegetation natural habitats conservation ecosystem monitoring |
| url | https://revistas.uepg.br/index.php/tp/article/view/21497/209209217539 |
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