Analysis of the Phenology Dynamics of Brazilian Caatinga Species With Ndvi Time Series

Silva, Claudionor Ribeiro da; Machado, Sérgio Luís Dias; Araújo, Aracy Alves de; Abreu, Carlos Alberto Matias de

doi:10.1590/01047760201824012487

Cited by 6 publications

(11 citation statements)

References 18 publications

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“…This proves the influence of random factors on the time series, i.e. irregular variations in vegetation cover and exposed areas of soil occurred due to unexpected events such as burning and deforestation (SILVA et al, 2018).…”

Section: Resultsmentioning

confidence: 71%

“…Analysis of historical data from the IBGE showed that in 2004 101,986 m 3 were extracted, 103,515 m 3 in 2005, and 106,620 m 3 in 2006 (INSTITUTO BRASILEIRO DE GEOGRAFIA E STATÍSTICA, 2010), which favoured desertification, since exposure of the soil intensified the erosion process and other factors of soil and plant degradation. These factors acted continuously over the years, resulting in the formation of vegetation with reflectance patterns below 0.40 in the near infrared, with less capacity to respond to rainy periods and, therefore, classified as desertified (CUNHA et al, 2019;LANDIM;SILVA;ALMEIDA, 2011;OLIVEIRA FILHO et al, 2019).…”

Section: Resultsmentioning

confidence: 99%

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Detecting desertification in different years and rainfall regimes by 2D Scatter Plot

Santos

Teixeira

Terra

et al. 2021

Revista Ciência Agronômica

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The desertification process causes soil degradation and a reduction in vegetation. The absence of visualisation techniques and the broad spatial and temporal dimension of the data hampers the identification of desertification and rapid decision-making by multidisciplinary teams. The 2D Scatter Plot is a two-dimensional visual analysis of reflectances in the red (630 -690 nm) and nearinfrared (760 -900 nm) bands to visualise the spectral response of the vegetation. The hypothesis of this study is that visualising the reflectances of the vegetation by means of a 2D scatter plot will allow desertification to be inferred. The aim of this study was to identify desertified areas and characterise the spatial and temporal dynamics of the vegetation and soil during dry (DP) and rainy (RP) periods between 2000 and 2008, using a 2D scatter plot. The 2D scatter plot generated by the Envi ® 4.8 software and the reflectances in bands 3 and 4 of the TM5 sensor were used within communities in the Irauçuba hub (Ceará, Brazil). The concentration densities of the near-infrared reflectances of the vegetation pixels were observed. Each community presented pixel concentrations with reflectances of less than 0.4 (40%) during each of the periods under evaluation, indicating little vegetation development, with further degradation caused by deforestation, the use of fire and overgrazing. The 2D scatter plot was able to show vegetation with low reflectance in the near infrared during both dry and rainy periods between 2000 and 2008, thereby inferring the occurrence of desertification.

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Section: Resultsmentioning

confidence: 71%

Section: Resultsmentioning

confidence: 99%

Detecting desertification in different years and rainfall regimes by 2D Scatter Plot

Santos

Teixeira

Terra

et al. 2021

Revista Ciência Agronômica

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show abstract

“…Caatinga biome is a Brazilian formation forest with xerophytic plants, some different ecoregions (ANTUNES et al, 2014;APGAUA et al, 2014;ANDRADE et al, 2015;MENINO et al, 2015;SILVA et al, 2018), with high evapotranspiration, and concentrated rainfall in a short period.…”

Section: Introductionmentioning

confidence: 99%

“…In addition, in Caatinga biome area, is common the disordered anthropogenic actions and climate changes, causing processes such as the loss of biodiversity and desertification (ANTUNES et al, 2014;APGAUA et al, 2014;ANDRADE et al, 2015;MENINO et al, 2015;DRUMOND et al, 2016;SILVA et al, 2018). Walter et al (2019) describes that Caatinga biome area it covers about 53.1% of the territory of the Northeast region of the country, which represents about 882,081 km 2 and more than 20 million people living in this vast location (FERREIRA & CUNHA, 2013).…”

Section: Introductionmentioning

confidence: 99%

“…Currently, there are some efforts to promote a sustainable production of forest essences from Caatinga biome, for example, studies in seedling formation (ANTUNES et al, 2014;ANDRADE et al, 2015;MENINO et al, 2015), bioecology (APGAUA et al, 2014), morphology (LOUREIRO et al, 2013), satellite analyses (SILVA et al, 2018), and thermal image (DIAS JÚNIOR, et al, 2019). However, for some species in Caatinga species have dormancy and this fact can be disturbing the forest production and this fact is poorly studied (Medeiros et al, 2005) or are recommendation the acid treatments to improve the germination to broken the seed resistance in Euphorbiaceae family (LOUREIRO et al, 2013).…”

Section: Introductionmentioning

confidence: 99%

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ULTRASOUND AND WATER IMMERSION TO PROMOTING VIGOR IN SEEDS AND SEEDLINGS OF Cnidoscolus quercifolius

Ferreira¹,

Oliveira²,

Pérez-Marin³

2021

BIOFIX

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Time series analysis of the enhanced vegetation index to detect coffee crop development under different irrigation systems

Silva

Alves

Sáfadi

et al. 2021

J. Appl. Rem. Sens.

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The coffee crop spectral behavior identification throughout its cycle can contribute to its development monitoring under pest incidence. We aim to identify coffee development through time signatures of enhanced vegetation index (EVI), as well as to evaluate the use of seasonal autoregressive integrated moving average (SARIMA) models to identify coffee trees spectrum-time patterns under different irrigation management and design future scenarios. Three coffee fields were selected under different irrigation systems, whose EVI data of 8 years were obtained from the moderate resolution image spectroradiometer sensor. Each coffee crop model was subjected to residual autocorrelation test and classified according to information criteria, while its accuracy was assessed by means of prediction error measures and agreement index. The estimated and observed EVI values were similar, even for the predicted year. However, in agricultural years during which coffee diseases occurred, the crops showed vegetative vigor below the expected. We concluded that SARIMA models enabled the establishment of a reliable spectral signature expected for coffee crop, which could help with crop management defining, regardless of the irrigation system adopted. Based on the evaluation of divergence between expected and observed spectral signatures, early signs of coffee underdevelopment were detected, which could reduce economic loss risks on its commercial chain.

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Analysis of the Phenology Dynamics of Brazilian Caatinga Species With Ndvi Time Series

Cited by 6 publications

References 18 publications

Detecting desertification in different years and rainfall regimes by 2D Scatter Plot

Detecting desertification in different years and rainfall regimes by 2D Scatter Plot

ULTRASOUND AND WATER IMMERSION TO PROMOTING VIGOR IN SEEDS AND SEEDLINGS OF Cnidoscolus quercifolius

Time series analysis of the enhanced vegetation index to detect coffee crop development under different irrigation systems

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