NDVI and meteorological data as indicators of the Pampa biome natural grasslands growth

Fontana, Denise Cybis; Junges, Amanda Heemann; Bremm, Carolina; Schaparini, Laura Pigatto; Mengue, Vagner Paz; Wagner, Ana Paula; Carvalho, Paulo César de Faccio

doi:10.1590/1678-4499.2017222

Cited by 10 publications

(10 citation statements)

References 21 publications

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“…Also, in Pampa Biome the difference between the minimum and maximum ET is greater than in Barrax. According to Fontana et al, (2018) this variability influences all types of vegetation growth and, in the Pampa biome, causes variations in the forage availability to the animals throughout the seasons and also years. Rubert et al, (2018) have also analyzed the Pampa biome ET by eddy co-variance and have concluded that this biome presented strong seasonality of evapotranspiration, with the highest evapotranspiration rates in the summer season, where the vegetation was in active growth and, therefore, had higher biomass production.…”

Section: Resultsmentioning

confidence: 99%

“…That is why NDVI can be used as indicators of the vegetation growth and development and are associated with the subtropical climate prevailing in the region. (Fontana et al, 2018).…”

Section: Variablementioning

confidence: 99%

“…Ecosystems evapotranspiration (ET) has been quantified around the world by different methodologies to understand the energy balance and hydrological cycle and its variation, mostly to control of the evolution of climate change. In this way, the Pampa biome has been characterized by the quantification of ET and its relationship with environmental variables, especially when it comes to the validation of ET by remote sensing (Fontana et al, 2018;Monteiro et al, 2014;Rubert et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Pampa Biome Environmental Particularities Regarding to Energy Balance

Rocha

Käfer

Skokovic

et al. 2020

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. Ecosystem evapotranspiration (ET) has been quantified around the world by different methodologies to understand the energy balance, especially to control the evolution of climate change. It is known that the vegetation of the pampa biome is natural grasslands, it has a large variety of species (flora and fauna), however is it different in the environmental aspects related to the energy balance when compared to the grassland cultivated? In this study the objective was to analyze the environmental differences of the Pampa Biome related to the energy balance in comparison with the pastures cultivated in Barrax, Spain. In the first one the minimum daily ET is 0.99 mm/day, while in the second is 1.57 mm/day. However, the highest differences between the sites occur during the summer period, in the maximum daily ET, the maximum is 16.25 mm/day in Pampa and in Barrax is 7.31 mm/day. The results of this study have indicated that the characteristics of the Pampa biome, both in terms of soil and climatic issues and land use, generate differences in the energy balance when compared to similar vegetation in other regions of the world.

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Section: Resultsmentioning

confidence: 99%

“…That is why NDVI can be used as indicators of the vegetation growth and development and are associated with the subtropical climate prevailing in the region. (Fontana et al, 2018).…”

Section: Variablementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Pampa Biome Environmental Particularities Regarding to Energy Balance

Rocha

Käfer

Skokovic

et al. 2020

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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“…In contrast, the winter season had the lowest values (Figures 2c and d). Fontana et al (2018) commented that this is a typical behaviour of the predominant subtropical climate in the region of Pampa biome. The authors also pointed out that winter is the critical season for cattle ranching, since the lower biomass accumulation and consequently lower NDVI values are conditioned by solar radiation and air temperature decrease.…”

Section: Spatial Distribution Of Lst Ndvi and Surface Albedomentioning

confidence: 95%

“…Although there are a considerable number of studies on the seasonal variations of Pampa biome vegetation along with climate variables, vegetation-LST relationship is not properly addressed on the literature. Most researches focused on air temperature data in conjunction with IVs or applied LST standard products (Fontana et al 2018;Moreira et al 2019), which present known limitations (Mukherjee et al 2014;Simó et al 2016).…”

Section: Introductionmentioning

confidence: 99%

Seasonal Assessment of Surface Temperature With Normalized Vegetation Index and Surface Albedo Over Pampa Biome

Käfer

Rocha

Diaz

et al. 2020

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. Land surface temperature (LST) governs many biophysical processes at the land-atmosphere interface and the relationship vegetation-LST has been the premise of many studies. This paper purposed to correlate LST with normalized difference vegetation index (NDVI) and surface albedo in the grasslands of Pampa biome during winter and summer seasons. Four Landsat 8 scenes with clear-sky conditions were acquired from the US Geological Survey website and NDVI and surface albedo were calculated. Afterwards, LST was obtained using Split-window (SW) algorithm. Results showed that LST in winter season exhibited less variations between pixels in comparison to summer, where the heterogeneity of the environment is significantly more detectable. LST retrieved from Landsat 8 data was consistent with the actual temperature measured in the field, with differences varying between 1–1.6 K. The LST-Vegetation relationship in the Pampa grasslands varies with the season so that caution must be taken in assuming a regular behaviour between LST and remote sensing vegetation variables, such as empirical relationships that are widely used in many scientific fields.

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Precision livestock farming applied to grazingland monitoring and management—A review

et al. 2023

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To meet the expected demand for food while protecting animal welfare, environmental sustainability, and profitability, animal production efficiency must improve. Improvements in grazinglands management techniques can impact livestock production efficiency. The current stage of artificial intelligence development, mainly machine learning techniques, remote sensing (RS), and precision agriculture technologies, automatizes data collection and raises the monitoring capacity to support on‐farm decision‐making. This literature review presents current developments in precision livestock farming (PLF) applied to grazinglands monitoring and management, demonstrates some knowledge gaps, and discusses potential solutions of grazinglands management issues. Although the implementation of precision technologies in grazing systems is advancing rapidly, challenges, such as lack of reliable reference data and low variability of datasets used to calibrate models, are examples of constraints to be addressed in future studies. More effort in terms of relationship strengthening between farmers and researchers, benefits elucidation, cooperation among professionals with different expertise, and software or app development must be directed to make the knowledge accessible and largely implemented in field conditions.

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NDVI and meteorological data as indicators of the Pampa biome natural grasslands growth

Cited by 10 publications

References 21 publications

Pampa Biome Environmental Particularities Regarding to Energy Balance

Pampa Biome Environmental Particularities Regarding to Energy Balance

Seasonal Assessment of Surface Temperature With Normalized Vegetation Index and Surface Albedo Over Pampa Biome

Precision livestock farming applied to grazingland monitoring and management—A review

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