Séries Temporais do Índice NDVI na Avaliação do Comportamento Sazonal do Aquífero Rio Claro

Teramoto, Elias Hideo; Benjumea, Maria Teresa; Gonçalves, Roger; Kiang, Chang Hung

doi:10.14393/rbcv70n3-45986

Cited by 2 publications

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“…In turn, the lowest values are mostly related to pasture areas, which have fasciculate roots. This makes them suffer more from the lack of water in the dry period, emphasizing the importance of vegetation in the basin area (Teramoto et al, 2018;Vale;Da Costa;Da Silva Pimentel, 2021). The values displayed in the histograms allows to identify a reduction in pixel reflectance from 1985 to 2018, from 0.5 to 0.4.…”

Section: Resultsmentioning

confidence: 99%

Technology and policy integration: modelling morphometric characterization and land use change using artificial neural networks in the western amazon

Pereira

Peixoto

Cesconetto

et al. 2022

Rev. Bras. Geog. Fis.

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This study aims to analyze in an integrated way the application of morphometric indices elaborated in geographic information systems and aspects of environmental management of water resources for the Micro Watershed of Garças River, located in the state of Rondônia. It used images with Digital Elevation Models (DEM) obtained by TOPODATA and Landsat 8 images obtained by INPE (the Brazilian Institute for Space Research). Subsequently, with the aid of the QGIS 2.18.0 software, the watershed was delimited, the NDVI and the slope were calculated and, based on initial data, morphometric characteristics were calculated. The watershed has an area of 1621.101 km², perimeter of 438.661 km and length of 82.04 km, with altimetry ranging from 77.8 to 177.8 meters, and form factor of 0.24, which characterizes a rectangular shape, indicating that the basin has a low propensity for floods. NDVI ranged from 0.187 to 0.49, and it has a coverage area of native vegetation superior to that of anthropized areas. Thus, the watershed morphometric study, together with data on use and occupation, provide essential elements for the planning of actions to be carried out in the watershed.

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Section: Resultsmentioning

confidence: 99%

Technology and policy integration: modelling morphometric characterization and land use change using artificial neural networks in the western amazon

Pereira

Peixoto

Cesconetto

et al. 2022

Rev. Bras. Geog. Fis.

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“…Vegetation indices can be used to demonstrate the performance of vegetation in terms of soil protection seasonally and not just classify it according to the type of cover. It is very important to determine land use and land cover (C factor), using vegetation indices seasonally (Benavidez et al 2018) as a function of changes in vegetation cover throughout the year (Teramoto et al 2018) and water availability (Becerra et al 2009). Along these lines, some studies have used vegetation indices to model EF (Garófalo and Ferreira 2015;Santos 2018).…”

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confidence: 99%

Analysis of seasonal environmental fragility using the normalized difference vegetation index (NDVI) and soil loss estimation in the Urutu watershed, Brazil.

Oliveira

Vick

Bacani

2023

Preprint

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Land use intensification has contributed to the emergence of impacts on the environment such as soil loss, silting of watercourses, and biodiversity reduction, among others. Using models that can seasonally diagnose environmental damage is of fundamental importance in territorial planning and management. This work aimed to analyze the seasonal Environmental Fragility (EF) from the autumn of 2019 to the summer of 2020 using the soil loss estimate. To do this, data such as slope, erodibility, erosivity and the normalized difference vegetation index (NDVI) were used. Statistical tests were also applied to assess the significance level of the models in the seasonal evaluation, as well as in the validation based on ground truth points. The results showed that there is seasonal differentiation in the EF and in the soil loss estimation, in which NDVI and erosivity are two of the main responsible factors. Spring was the one that resulted in the largest area classified as high EF (27%) and with an estimated soil loss of 0.3733 t.ha-1month-3. The summer presented the highest soil loss estimation with an average value of 0.4393 t.ha-1month-3. Autumn (0.07683 t.ha-1month-3) and winter (0.0569 t.ha-1month-3) showed the lowest rates of soil loss and the largest areas classified in the low class of EF, as a result, mainly, of the erosivity of the rains. The results indicated by the seasonal models of EF and soil loss were validated through erosion points using spatial statistics tests.

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Séries Temporais do Índice NDVI na Avaliação do Comportamento Sazonal do Aquífero Rio Claro

Cited by 2 publications

References 0 publications

Technology and policy integration: modelling morphometric characterization and land use change using artificial neural networks in the western amazon

Technology and policy integration: modelling morphometric characterization and land use change using artificial neural networks in the western amazon

Analysis of seasonal environmental fragility using the normalized difference vegetation index (NDVI) and soil loss estimation in the Urutu watershed, Brazil.

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