Riparian vegetation NDVI dynamics and its relationship with climate, surface water and groundwater

Fu, Baihua; Burgher, Isabela

doi:10.1016/j.jaridenv.2014.09.010

Cited by 158 publications

(98 citation statements)

References 37 publications

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“…A retirada de boa parte da vegetação contribui para o aumento do assoreamento do rio e da quantidade de sólidos em suspensão, já que a mata ciliar diminui a erosão do solo e aumenta a taxa de infiltração. O despejo de lixo e esgoto doméstico também eleva o valor da turbidez [14].…”

Section: Resultsunclassified

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Water Quality of Igarapé Pau-Cheiroso and the Process of Urbanization of The Municipality Igarapé-Açu

Uchôa-Bordallo¹,

DeSouza²,

Santos-Silva³

et al. 2017

ITEGAM- Journal of Engineering and Technology for Industrial Applications (Itegam-Jetia)

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The objective was to evaluate the water quality of the Pau-Cheiroso igarapé, Igarapé-Açu/PA, through physicochemical parameters and to make the comparison with the acceptable values established by the legislation. Ten points were selected and divided into areas of riparian forest and urban area. The determinations were performed in April, June, August, October and December of 2015 and February of 2016. It was observed that the pH averages were below 6, the minimum value allowed in class II waters; The values of turbidity oscillated within the maximum allowed value; The values of dissolved oxygen did not present above the acceptable minimum of 5 mg L -1 ; And the temperature did not vary significantly between the points and between the collections. It was possible to distinguish two distinct groups through the multivariate analysis, observing the influence of the removal of riparian forest, by the urbanization process, on the water quality of the Pau-Cheiroso stream.Key Words: water quality, urbanization process, environmental management. Qualidade da água do igarapé pau-cheiroso e o processo de urbanização doMunicípio Igarapé-Açu/PA RESUMO O objetivo foi avaliar a qualidade da água do igarapé Pau-Cheiroso, Igarapé-Açu/PA, através de parâmetros físico-químicos e realizar a comparação com os valores aceitáveis estabelecidos pela legislação. Foram selecionados 10 pontos e divididos em área de mata ciliar e em área urbana. As determinações foram realizadas nos meses de abril, junho, agosto, outubro e dezembro de 2015 e fevereiro de 2016. Observou-se que as médias de pH se encontraram abaixo de 6, valor mínimo permitido em águas de classe II; os valores de turbidez oscilaram dentro do valor máximo permitido; os valores de oxigênio dissolvido não se apresentaram acima do mínimo aceitável de 5 mg L -1 ; e a temperatura não variou significativamente entre os pontos e entre as coletas. Foi possível distinguir através da análise multivariada dois grupos distintos, observando a influência da retirada da mata ciliar, pelo processo de urbanização, na qualidade da água do igarapé Pau-Cheiroso.Palavras Chaves: qualidade da água, processo de urbanização, gestão ambiental. I. INTRODUÇÃOA água pode ser considerada um recurso abundante, relativamente para as necessidades atuais. No passado era visto como bem infinito impossível de acabar, mas os tempos mudaram e a água é hoje o recurso mais importante para a vida, sendo caracterizada como finito para o consumo humano. A importância da água não está relacionada apenas às suas funções na natureza, mas ao papel que exerce na saúde, economia e qualidade de vida humana [1].A proximidade com a água foi um fator preponderante no crescimento e desenvolvimento das civilizações e das cidades atuais que utilizam a mesma para seus diversos fins. Ambientes aquáticos são utilizados em todo o mundo com distintas finalidades, entre as quais se destacam o abastecimento de água (doméstico e industrial), a geração de energia, a irrigação, a

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Section: Resultsunclassified

“…A chuva aumenta o volume dos rios, aumentando assim a quantidade de oxigênio introduzida. A quantidade de matéria orgânica e o consumo de oxigênio por plantas e animais também influenciam na quantidade de oxigênio reduzido [14,15].…”

Section: Resultsunclassified

Water Quality of Igarapé Pau-Cheiroso and the Process of Urbanization of The Municipality Igarapé-Açu

Uchôa-Bordallo¹,

DeSouza²,

Santos-Silva³

et al. 2017

ITEGAM- Journal of Engineering and Technology for Industrial Applications (Itegam-Jetia)

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“…They explored vegetative drought in the region and found rainfall (or lack thereof) as the dominant causative factor in the event. Fu and Burgher [38] found that the maximum temperature primarily splits NDVI values, followed by previous rainfall and then inter-flood dry period and resulting groundwater levels and suggested that warmer months required more rain compared to cooler months to attain similar mean NDVI values in areas of high NDVI such as riparian zones, likely due to higher local evaporation. Inter-flood dry periods were also found to be important for maintenance of NDVI levels, especially when rainfall is limited.…”

Section: Hydrologic Parameters and Their Relationship With Ndvimentioning

confidence: 99%

“…Another contributing factor in NDVI dynamics is the groundwater level. Shallower groundwater levels tend to enhance NDVI and thereby vegetation greenness primarily due to the wetter environment [38]. Wang et al [39] examined spatial responses of NDVI to precipitation and temperature during a 9-year period (1989)(1990)(1991)(1992)(1993)(1994)(1995)(1996)(1997).…”

Section: Hydrologic Parameters and Their Relationship With Ndvimentioning

confidence: 99%

Optical Cloud Pixel Recovery via Machine Learning

et al. 2017

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Remote sensing derived Normalized Difference Vegetation Index (NDVI) is a widely used index to monitor vegetation and land use change. NDVI can be retrieved from publicly available data repositories of optical sensors such as Landsat, Moderate Resolution Imaging Spectro-radiometer (MODIS) and several commercial satellites. Studies that are heavily dependent on optical sensors are subject to data loss due to cloud coverage. Specifically, cloud contamination is a hindrance to long-term environmental assessment when using information from satellite imagery retrieved from visible and infrared spectral ranges. Landsat has an ongoing high-resolution NDVI record starting from 1984. Unfortunately, this long time series NDVI data suffers from the cloud contamination issue. Though both simple and complex computational methods for data interpolation have been applied to recover cloudy data, all the techniques have limitations. In this paper, a novel Optical Cloud Pixel Recovery (OCPR) method is proposed to repair cloudy pixels from the time-space-spectrum continuum using a Random Forest (RF) trained and tested with multi-parameter hydrologic data. The RF-based OCPR model is compared with a linear regression model to demonstrate the capability of OCPR. A case study in Apalachicola Bay is presented to evaluate the performance of OCPR to repair cloudy NDVI reflectance. The RF-based OCPR method achieves a root mean squared error of 0.016 between predicted and observed NDVI reflectance values. The linear regression model achieves a root mean squared error of 0.126. Our findings suggest that the RF-based OCPR method is effective to repair cloudy pixels and provides continuous and quantitatively reliable imagery for long-term environmental analysis.

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“…At present, researchers have proposed a variety of drought indexes to reflect the degree and characteristics of drought, such as the on the NDVI; Birtwistle et al [38] found large seasonal-scale changes in the NDVI along channels, which was useful in determining when and where flow events have occurred. Fu and Burgher [39] analyzed the correlation between NDVI dynamics and climate, surface water, and groundwater. In Western China, especially in the Qinghai-Tibet Plateau, many studies have shown that the climate has changed, becoming warmer and wetter [40,41].…”

Section: Introductionmentioning

confidence: 99%

Response of Grassland Degradation to Drought at Different Time-Scales in Qinghai Province: Spatio-Temporal Characteristics, Correlation, and Implications

et al. 2017

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Grassland, as the primary vegetation on the Qinghai-Tibet Plateau, has been increasingly influenced by water availability due to climate change in last decades. Therefore, identifying the evolution of drought becomes crucial to the efficient management of grassland. However, it is not yet well understood as to the quantitative relationship between vegetation variations and drought at different time scales. Taking Qinghai Province as a case, the effects of meteorological drought on vegetation were investigated. Multi-scale Standardized Precipitation Evapotranspiration Index (SPEI) considering evapotranspiration variables was used to indicate drought, and time series Normal Difference Vegetation Index (NDVI) to indicate the vegetation response. The results showed that SPEI values at different time scales reflected a complex dry and wet variation in this region. On a seasonal scale, more droughts occurred in summer and autumn. In general, the NDVI presented a rising trend in the east and southwest part and a decreasing trend in the northwest part of Qinghai Province from 1998 to 2012. Hurst indexes of NDVI revealed that 69.2% of the total vegetation was positively persistent (64.1% of persistent improvement and 5.1% of persistent degradation). Significant correlations were found for most of the SPEI values and the one year lagged NDVI, indicating vegetation made a time-lag response to drought. In addition, one month lagged NDVI made an obvious response to SPEI values at annual and biennial scales. Further analysis showed that all multiscale SPEI values have positive relationships with the NDVI trend and corresponding grassland degradation. The study highlighted the response of vegetation to meteorological drought at different time scales, which is available to predict vegetation change and further help to improve the utilization efficiency of water resources in the study region.

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Riparian vegetation NDVI dynamics and its relationship with climate, surface water and groundwater

Cited by 158 publications

References 37 publications

Water Quality of Igarapé Pau-Cheiroso and the Process of Urbanization of The Municipality Igarapé-Açu

Water Quality of Igarapé Pau-Cheiroso and the Process of Urbanization of The Municipality Igarapé-Açu

Optical Cloud Pixel Recovery via Machine Learning

Response of Grassland Degradation to Drought at Different Time-Scales in Qinghai Province: Spatio-Temporal Characteristics, Correlation, and Implications

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