Representação matemática do comportamento intra-anual do NDVI no Bioma Caatinga

Filho, Rivaildo da Silva Ramos; Vasconcelos, Rochele Sheila; Galvão, Carlos de Oliveira; Cunha, John; Rufino, Iana Alexandra Alves

doi:10.5902/1980509837279

Cited by 5 publications

(5 citation statements)

References 18 publications

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“…Variations in rainfall distributions and volumes may have caused changes in vegetation cover, surface temperature, and evapotranspiration of the land portions observed in this study. Predominant vegetation of the Caatinga biome is quickly responsive to rainfall regimes, reducing foliage in the dry period (through deciduousness) and gaining biomass by the arrival of a new rainy period, which is considered a condition of defense and physiological adaptation of these highly efficient plants [102,103].…”

Section: Rainfall Variability In Land Cover Classesmentioning

confidence: 99%

“…The first three imaging dates in the study showed that, on average, 52.26% of the territorial area of the region had 0 to 25% vegetation cover (Figure 6a-c), revealing the direct effects of low rainfall volumes resulting from the dry season on native vegetation. Under these conditions, variations in NDVI values are strongly linked to biomass production [102]. In studies carried out in the Caatinga, Cunha et al [22], Leivas et al [21], and Leivas et al [104] reported that monitoring large-scale variations of water indicators and vegetation status is of crucial importance to minimize the adverse effects of climate and land use changes on mixed agroecosystems.…”

Section: Vegetation Cover Indices Of the Municipalitymentioning

confidence: 99%

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Using Remote Sensing to Quantify the Joint Effects of Climate and Land Use/Land Cover Changes on the Caatinga Biome of Northeast Brazilian

et al. 2022

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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 (VC). 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 VC 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 ETa rates (~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.

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Section: Rainfall Variability In Land Cover Classesmentioning

confidence: 99%

Section: Vegetation Cover Indices Of the Municipalitymentioning

confidence: 99%

Using Remote Sensing to Quantify the Joint Effects of Climate and Land Use/Land Cover Changes on the Caatinga Biome of Northeast Brazilian

et al. 2022

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“…The imaging period (June) matches the rainy season, when there are a great herb layer and significant presence of vegetation leaf canopy, thus contributing to higher NDVI levels. Another important factor that should be considered in the Caatinga environment is the seasonal rainfall distribution, which plays a great role on the regional water balance, hence soil moisture content, thus directly influencing NDVI (Arraes et al, 2012;Silva Filho et al, 2020).…”

Section: Resultsmentioning

confidence: 99%

Monitoring of biome degradation in the northeastern semi-arid region, Brazil

Silva

Montenegro

Lopes

et al. 2020

Rev. Bras. Geog. Fis.

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Degradation of Caatinga biome has created desertification processes in several areas, inducing big microclimate and surface changes. Therefore, it is fundamental develop research methods capable of identifying areas under degradation process. Satellite images in different spatial, temporal, radiometric and spectral resolutions are being used to monitor big areas from several biomes worldwide. The objective of this study was to evaluate and quantify the degree of degradation and preservation of the Caatinga biome, using geoprocessing methods and remote sensing products , using surface data and Landsat-8 images for 2013, 2014 and 2015. Remote sensing methods were used to estimate the Normalized Difference Vegetation Index (NDVI), surface albedo (α) and Moving Standard Deviation Index (MDSI). The results showed that the vegetation indexes and the techniques of degradation and change detection satisfactorily identified the behavior of the surrounding vegetation in the study area, standing out as good indices for degradation processes in the semiarid. It was concluded that change detection and classification by decision tree methods were efficient in the identif ication of anthropized areas during the experimental period.

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“…The biomass of the old stands, however, was lower than those of most other dry forests, which usually had more than 72 Mg ha −1 (Read and Lawrence 2003;Raherison and Grouzis 2005;Vargas et al 2008;Raharimalala et al 2012;Becknell and Powers 2014). Low water availability is the probable cause of the low biomass in Brazilian dry forests, the closest to the equator with the highest potential evapotranspiration (Silva Filho et al 2020). The biomass of the humid forests was within the ranges reported elsewhere (Fonseca et al 2011;Poorter et al 2016;Stas et al 2017) for both young (76 to 100 Mg ha −1 ) and old stands (100 to 334 Mg ha −1 ), except for the low biomass of the young stand of the montane forest.…”

Section: Biomass and Densitymentioning

confidence: 96%

Contributions of Leguminosae to young and old stands of neotropical forests under different environmental conditions

Costa

Sampaio

Araújo

et al. 2021

Annals of Forest Science

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& Key message Potentially nodulating Leguminosae species had high density and biomass in young stands of forests in Northeast Brazil, except in a dry forest on a low-fertility soil. & Context Leguminosae species, especially potentially nodulating ones, appear to be important components of tropical secondary forests, although information is still scarce concerning their contributions to richness and biomass under different environmental conditions. & Aims To evaluate the contribution of Leguminosae to the aboveground biomass and density of young and old forest stands in six sites, with different climate and soil conditions, in northeastern Brazil. & Methods The biomass of plants was estimated using allometric equations in ten plots in one young and one old forest stand in each site. Leguminosae were separated into nodulating and non-nodulating species based on literature. & Results Leguminosae, mainly nodulating species, displayed the largest number of species among all families and the largest biomass and density in young stands. There was more similarity in Leguminosae species composition between young and old stands in dry than in humid forests. & Conclusion Nodulating species make considerable contributions to the biomass of the initial successional stages of forests in Northeast Brazilconfirming the importance of the family for natural forest regeneration, especially in dry environments.

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Representação matemática do comportamento intra-anual do NDVI no Bioma Caatinga

Cited by 5 publications

References 18 publications

Using Remote Sensing to Quantify the Joint Effects of Climate and Land Use/Land Cover Changes on the Caatinga Biome of Northeast Brazilian

Using Remote Sensing to Quantify the Joint Effects of Climate and Land Use/Land Cover Changes on the Caatinga Biome of Northeast Brazilian

Monitoring of biome degradation in the northeastern semi-arid region, Brazil

Contributions of Leguminosae to young and old stands of neotropical forests under different environmental conditions

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