Using Remote Sensing to Quantify the Joint Effects of Climate and Land Use/Land Cover Changes on the Caatinga Biome of Northeast Brazilian
Caatinga biome, located in the Brazilian semi-arid region, is the most populous semi-arid region in the world, causing intensification in land degradation and loss of biodiversity over time. The main objective of this paper is to determine and analyze the changes in land cover and use, over time, on...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-04-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/14/8/1911 |
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| author | Alexandre Maniçoba da Rosa Ferraz Jardim George do Nascimento Araújo Júnior Marcos Vinícius da Silva Anderson dos Santos Jhon Lennon Bezerra da Silva Héliton Pandorfi José Francisco de Oliveira-Júnior Antônio Heriberto de Castro Teixeira Paulo Eduardo Teodoro João L. M. P. de Lima Carlos Antonio da Silva Junior Luciana Sandra Bastos de Souza Emanuel Araújo Silva Thieres George Freire da Silva |
| author_facet | Alexandre Maniçoba da Rosa Ferraz Jardim George do Nascimento Araújo Júnior Marcos Vinícius da Silva Anderson dos Santos Jhon Lennon Bezerra da Silva Héliton Pandorfi José Francisco de Oliveira-Júnior Antônio Heriberto de Castro Teixeira Paulo Eduardo Teodoro João L. M. P. de Lima Carlos Antonio da Silva Junior Luciana Sandra Bastos de Souza Emanuel Araújo Silva Thieres George Freire da Silva |
| author_sort | Alexandre Maniçoba da Rosa Ferraz Jardim |
| collection | DOAJ |
| description | Caatinga biome, located in the Brazilian semi-arid region, is the most populous semi-arid region in the world, causing intensification in land degradation and loss of biodiversity over time. The main objective of this paper is to determine and analyze the changes in land cover and use, over time, on the biophysical parameters in the Caatinga biome in the semi-arid region of Brazil using remote sensing. Landsat-8 images were used, along with the Surface Energy Balance Algorithm for Land (SEBAL) in the Google Earth Engine platform, from 2013 to 2019, through spatiotemporal modeling of vegetation indices, i.e., leaf area index (LAI) and vegetation cover (V<sub>C</sub>). Moreover, land surface temperature (LST) and actual evapotranspiration (ET<sub>a</sub>) in Petrolina, the semi-arid region of Brazil, was used. The principal component analysis was used to select descriptive variables and multiple regression analysis to predict ET<sub>a</sub>. The results indicated significant effects of land use and land cover changes on energy balances over time. In 2013, 70.2% of the study area was composed of Caatinga, while the lowest percentages were identified in 2015 (67.8%) and 2017 (68.7%). Rainfall records in 2013 ranged from 270 to 480 mm, with values higher than 410 mm in 46.5% of the study area, concentrated in the northern part of the municipality. On the other hand, in 2017 the lowest annual rainfall values (from 200 to 340 mm) occurred. Low vegetation cover rate was observed by LAI and V<sub>C</sub> values, with a range of 0 to 25% vegetation cover in 52.3% of the area, which exposes the effects of the dry season on vegetation. The highest LST was mainly found in urban areas and/or exposed soil. In 2013, 40.5% of the region’s area had LST between 48.0 and 52.0 °C, raising ET<sub>a</sub> rates (~4.7 mm day<sup>−1</sup>). Our model has shown good outcomes in terms of accuracy and concordance (coefficient of determination = 0.98, root mean square error = 0.498, and Lin’s concordance correlation coefficient = 0.907). The significant increase in agricultural areas has resulted in the progressive reduction of the Caatinga biome. Therefore, mitigation and sustainable planning is vital to decrease the impacts of anthropic actions. |
| first_indexed | 2024-03-09T13:03:24Z |
| format | Article |
| id | doaj.art-0c0fd66bc15942d3b175aa3570f48c6a |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-09T13:03:24Z |
| publishDate | 2022-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-0c0fd66bc15942d3b175aa3570f48c6a2023-11-30T21:51:30ZengMDPI AGRemote Sensing2072-42922022-04-01148191110.3390/rs14081911Using Remote Sensing to Quantify the Joint Effects of Climate and Land Use/Land Cover Changes on the Caatinga Biome of Northeast BrazilianAlexandre Maniçoba da Rosa Ferraz Jardim0George do Nascimento Araújo Júnior1Marcos Vinícius da Silva2Anderson dos Santos3Jhon Lennon Bezerra da Silva4Héliton Pandorfi5José Francisco de Oliveira-Júnior6Antônio Heriberto de Castro Teixeira7Paulo Eduardo Teodoro8João L. M. P. de Lima9Carlos Antonio da Silva Junior10Luciana Sandra Bastos de Souza11Emanuel Araújo Silva12Thieres George Freire da Silva13Department of Agricultural Engineering, Federal Rural University of Pernambuco, Recife 52171-900, BrazilDepartment of Agricultural Engineering, Federal Rural University of Pernambuco, Recife 52171-900, BrazilDepartment of Agricultural Engineering, Federal Rural University of Pernambuco, Recife 52171-900, BrazilDepartment of Agricultural Engineering, Federal Rural University of Pernambuco, Recife 52171-900, BrazilDepartment of Agricultural Engineering, Federal Rural University of Pernambuco, Recife 52171-900, BrazilDepartment of Agricultural Engineering, Federal Rural University of Pernambuco, Recife 52171-900, BrazilInstitute of Atmospheric Sciences, Federal University of Alagoas, Maceió 57072-970, BrazilWater Resources Department, Federal University of Sergipe, São Cristóvão 49100-000, BrazilDepartment of Agronomy, Federal University of Mato Grosso do Sul, Chapadão do Sul 79560-000, BrazilMARE—Marine and Environmental Sciences Centre, University of Coimbra, 3000-456 Coimbra, PortugalDepartment of Geography, State University of Mato Grosso (UNEMAT), Sinop 78555-000, BrazilAcademic Unit of Serra Talhada, Federal Rural University of Pernambuco, Serra Talhada 56909-535, BrazilDepartment of Forest Sciences, Federal Rural University of Pernambuco, Recife 52171-900, BrazilDepartment of Agricultural Engineering, Federal Rural University of Pernambuco, Recife 52171-900, BrazilCaatinga biome, located in the Brazilian semi-arid region, is the most populous semi-arid region in the world, causing intensification in land degradation and loss of biodiversity over time. The main objective of this paper is to determine and analyze the changes in land cover and use, over time, on the biophysical parameters in the Caatinga biome in the semi-arid region of Brazil using remote sensing. Landsat-8 images were used, along with the Surface Energy Balance Algorithm for Land (SEBAL) in the Google Earth Engine platform, from 2013 to 2019, through spatiotemporal modeling of vegetation indices, i.e., leaf area index (LAI) and vegetation cover (V<sub>C</sub>). Moreover, land surface temperature (LST) and actual evapotranspiration (ET<sub>a</sub>) in Petrolina, the semi-arid region of Brazil, was used. The principal component analysis was used to select descriptive variables and multiple regression analysis to predict ET<sub>a</sub>. The results indicated significant effects of land use and land cover changes on energy balances over time. In 2013, 70.2% of the study area was composed of Caatinga, while the lowest percentages were identified in 2015 (67.8%) and 2017 (68.7%). Rainfall records in 2013 ranged from 270 to 480 mm, with values higher than 410 mm in 46.5% of the study area, concentrated in the northern part of the municipality. On the other hand, in 2017 the lowest annual rainfall values (from 200 to 340 mm) occurred. Low vegetation cover rate was observed by LAI and V<sub>C</sub> values, with a range of 0 to 25% vegetation cover in 52.3% of the area, which exposes the effects of the dry season on vegetation. The highest LST was mainly found in urban areas and/or exposed soil. In 2013, 40.5% of the region’s area had LST between 48.0 and 52.0 °C, raising ET<sub>a</sub> rates (~4.7 mm day<sup>−1</sup>). Our model has shown good outcomes in terms of accuracy and concordance (coefficient of determination = 0.98, root mean square error = 0.498, and Lin’s concordance correlation coefficient = 0.907). The significant increase in agricultural areas has resulted in the progressive reduction of the Caatinga biome. Therefore, mitigation and sustainable planning is vital to decrease the impacts of anthropic actions.https://www.mdpi.com/2072-4292/14/8/1911tropical dry forestsurface energy balanceBrazilian semi-aridSEBALactual evapotranspiration |
| spellingShingle | Alexandre Maniçoba da Rosa Ferraz Jardim George do Nascimento Araújo Júnior Marcos Vinícius da Silva Anderson dos Santos Jhon Lennon Bezerra da Silva Héliton Pandorfi José Francisco de Oliveira-Júnior Antônio Heriberto de Castro Teixeira Paulo Eduardo Teodoro João L. M. P. de Lima Carlos Antonio da Silva Junior Luciana Sandra Bastos de Souza Emanuel Araújo Silva Thieres George Freire da Silva Using Remote Sensing to Quantify the Joint Effects of Climate and Land Use/Land Cover Changes on the Caatinga Biome of Northeast Brazilian Remote Sensing tropical dry forest surface energy balance Brazilian semi-arid SEBAL actual evapotranspiration |
| title | Using Remote Sensing to Quantify the Joint Effects of Climate and Land Use/Land Cover Changes on the Caatinga Biome of Northeast Brazilian |
| title_full | Using Remote Sensing to Quantify the Joint Effects of Climate and Land Use/Land Cover Changes on the Caatinga Biome of Northeast Brazilian |
| title_fullStr | Using Remote Sensing to Quantify the Joint Effects of Climate and Land Use/Land Cover Changes on the Caatinga Biome of Northeast Brazilian |
| title_full_unstemmed | Using Remote Sensing to Quantify the Joint Effects of Climate and Land Use/Land Cover Changes on the Caatinga Biome of Northeast Brazilian |
| title_short | Using Remote Sensing to Quantify the Joint Effects of Climate and Land Use/Land Cover Changes on the Caatinga Biome of Northeast Brazilian |
| title_sort | using remote sensing to quantify the joint effects of climate and land use land cover changes on the caatinga biome of northeast brazilian |
| topic | tropical dry forest surface energy balance Brazilian semi-arid SEBAL actual evapotranspiration |
| url | https://www.mdpi.com/2072-4292/14/8/1911 |
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