气候变化领域集成服务门户(CCPortal): Using Remote Sensing to Quantify the Joint Effects of Climate and Land Use/Land Cover Changes on the Caatinga Biome of Northeast Brazilian

CCPortal

DOI	10.3390/rs14081911
	Using Remote Sensing to Quantify the Joint Effects of Climate and Land Use/Land Cover Changes on the Caatinga Biome of Northeast Brazilian
	Jardim, Alexandre Manicoba da Rosa Ferraz; Araujo Junior, George do Nascimento; da Silva, Marcos Vinicius; dos Santos, Anderson; da Silva, Jhon Lennon Bezerra; Pandorfi, Heliton; de Oliveira-Junior, Jose Francisco; Teixeira, Antonio Heriberto de Castro; Teodoro, Paulo Eduardo; de Lima, Joao L. M. P.; da Silva Junior, Carlos Antonio; de Souza, Luciana Sandra Bastos; Silva, Emanuel Araujo; Silva, Thieres George Freire da
发表日期	2022
EISSN	2072-4292
卷号	14 期号:8
英文摘要	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-C). Moreover, land surface temperature (LST) and actual evapotranspiration (ETa) 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 ETa. 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-C 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 degrees C, raising ETa rates (similar to 4.7 mm day(-1)). 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.
英文关键词	tropical dry forest; surface energy balance; Brazilian semi-arid; SEBAL; actual evapotranspiration
语种	英语
WOS研究方向	Environmental Sciences ; Geosciences, Multidisciplinary ; Remote Sensing ; Imaging Science & Photographic Technology
WOS类目	Science Citation Index Expanded (SCI-EXPANDED) ; Social Science Citation Index (SSCI)
WOS记录号	WOS:000787398600001
来源期刊	REMOTE SENSING
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/280965
作者单位	Universidade Federal Rural de Pernambuco (UFRPE); Universidade Federal Rural de Pernambuco (UFRPE); Universidade Federal de Alagoas; Universidade Federal de Sergipe; Universidade Federal de Mato Grosso do Sul; Universidade de Coimbra; Universidade de Coimbra; Universidade do Estado de Mato Grosso; Universidade Federal Rural de Pernambuco (UFRPE)
推荐引用方式 GB/T 7714	Jardim, Alexandre Manicoba da Rosa Ferraz,Araujo Junior, George do Nascimento,da Silva, Marcos Vinicius,et al. Using Remote Sensing to Quantify the Joint Effects of Climate and Land Use/Land Cover Changes on the Caatinga Biome of Northeast Brazilian[J],2022,14(8).
APA	Jardim, Alexandre Manicoba da Rosa Ferraz.,Araujo Junior, George do Nascimento.,da Silva, Marcos Vinicius.,dos Santos, Anderson.,da Silva, Jhon Lennon Bezerra.,...&Silva, Thieres George Freire da.(2022).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,14(8).
MLA	Jardim, Alexandre Manicoba da Rosa Ferraz,et al."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 14.8(2022).