Monitoramento Espaço-Temporal do Risco de Degradação Ambiental e Desertificação por Sensoriamento Remoto em Região Semiárida

Silva, Jhon Lennon Bezerra da; Moura, Geber Barbosa de Albuquerque; Lopes, Pabrício Marcos Oliveira; Silva, Ênio Farias de França e; Ortiz, Pedro Francisco Sanguino; Silva, Douglas Alberto de Oliveira; Silva, Marcos Vinícius da; Guedes, Roni Valter de Souza

doi:10.26848/rbgf.v13.2.p544-563

Cited by 11 publications

(7 citation statements)

References 30 publications

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“…The numerical values aim to stabilize atmospheric variations, minimizing the residual effects and impacts of aerosols in the study area. Soil Adjusted Vegetation Index (SAVI) was estimated following the same pattern as the determination of NDVI, and especially based on the adjustment factor (L) to the effects and soil conditions of the study area, as mentioned earlier in the main highlights of EVI, according to Equation ( 4) [11,26,49,51,61,73,76,77]:…”

Section: Orbital Data From Terra and Aqua Satellites (Modis Sensor)mentioning

confidence: 99%

“…At a global level, the intensification of extreme climate change events mainly affects rainfall rates, driving severe droughts. In addition, the impacts caused by human activities also accelerate and lead to significant changes [3][4][5][6], with emphasis for semiarid areas of Brazil, such as the Northeast Region (NEB) and Brazilian Semiarid Region, where studies on the detection of vulnerabilities related to environmental degradation processes and soil desertification, based on radiation and energy balance components, help to understand the dynamics of these factors over time [7][8][9][10][11][12][13][14][15][16].…”

Section: Introductionmentioning

confidence: 99%

“…It is necessary to understand the processes of surface energy balance, as well as to comprehend the spectral behavioral pattern of vegetation through biophysical parameters and energy fluxes, such as vegetation indices, albedo and surface temperature, and mainly evapotranspiration. These aspects are fundamental for adequate planning of water and soil conservation projects [11,14,15,26,28,51]. In this regard, research focused on the development and improvement of models of the evapotranspiration of native vegetation and agricultural areas stands out [12,49,[52][53][54].…”

Section: Introductionmentioning

confidence: 99%

“…Evapotranspiration is also strongly linked to irrigated agriculture, being essential for the management and adequate dimensioning of irrigation projects in a sector that demands and consumes high water capacity. For beyond this planning, there are more effective and sustainable management measures for water resources in arid and semiarid regions [11,23,50,[54][55][56][57].…”

Section: Introductionmentioning

confidence: 99%

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Geospatial Insights into Aridity Conditions: MODIS Products and GIS Modeling in Northeast Brazil

Silva,

Jardim

et al. 2024

Hydrology

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Northeast Brazil (NEB), particularly its semiarid region, represents an area highly susceptible to the impacts of climate change, including severe droughts, and intense anthropogenic activities. These stresses may be accelerating environmental degradation and desertification of soil in NEB. The main aim of this study was to gain geospatial insights into the biophysical parameters of surface energy balance and actual evapotranspiration on a multi-temporal scale, aiming to detect and analyze the spectral behavioral patterns of areas vulnerable to degradation processes, based on thematic maps at the surface, for NEB and mainly the semiarid region of NEB from 2000 to 2019. Geospatial data from 8-day MODIS sensor products were used, such as surface reflectance (Terra/MOD09A1 and Aqua/MYD09A1), surface temperature (Terra/MOD11A2 and Aqua/MYD11A2), and actual evapotranspiration (Terra/MOD16A2 and Aqua/MYD16A2), version 6. Therefore, in this study, pixel-to-pixel values were processed by calculating the average pixel statistics for each year. From the reflectance product, digital processing of the surface albedo and spectral vegetation indices was also carried out, using computational programming scripts and machine learning algorithms developed via the Google Earth Engine (GEE) platform. The study also presents a seasonal analysis of these components and their relationships over 20 years. Through vegetation indices and statistical correlations, a new predictive model of actual evapotranspiration was developed. The quantitative and spatiotemporal spectral patterns of the parameters were assessed through descriptive statistics, measures of central tendency and dispersion, and statistical error analyses and correlation indices. Thematic maps highlighted the pixel-to-pixel results, with patterns of high temperature distribution mainly in the central and northeastern part of NEB and the semiarid region of NEB, highlighting the formation of persistent heat islands over time. Meanwhile, in these areas, the maps of actual evapotranspiration showed a drastic reduction due to the lesser availability of energy. Over time, the semiarid region of NEB presented areas with little and/or no vegetation cover, which were highly well-defined between the years 2012 and 2019, confirming that these areas are extremely vulnerable to degradation and desertification processes due to significant loss of vegetative and water resilience. The components of energy balance were highly interconnected to climatological and environmental conditions, showing the severe results of drought and accentuation of the water deficit in NEB, presenting a greater condition of aridity in the semiarid region of NEB over time.

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Section: Orbital Data From Terra and Aqua Satellites (Modis Sensor)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Geospatial Insights into Aridity Conditions: MODIS Products and GIS Modeling in Northeast Brazil

Silva,

Jardim

et al. 2024

Hydrology

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“…Já as divergências quanto à área máxima das massas d'água também pode ter sido influenciada pela diferença nas datas de aquisição das imagens e a dinâmica dos reservatórios no semiárido (Silva et al, 2020(Silva et al, , 2019. Os valores máximos de área classificados pelos índices e bancos de dados se refere ao Açude Chapéu, um dos principais reservatórios da bacia de estudo.…”

Section: Anaunclassified

Comparison of the area of water masses in a hydrographic basin using spectral indices and MapBioma’s classification

Lourenço

Carvalho

Almeida

et al. 2021

Jour. Hypers. Rem. Sensg.

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Information surveys about water resources availability present in a basin is essential for its multiple use planning. In this context, the purpose of this study was to evaluate the reservoirs area in a semi-arid hydrographic basin, comparing information obtained from spectral indices with data from the MapBiomas classification. The study was carried out in the contribution basin of the Chapéu reservoir, in the Brígida River Basin, Pernambuco State. To assess the area of water masses in the basin, data from the classification carried out by the MapBiomas project -collection 5, referring to the year 2019, were used. The NDWI and MNDWI indices were also applied to images from the Sentinel-2 Satellite, referring to the year 2019, to determine the areas of reservoirs in the basin. The information from the indexes was vectored to obtain the polygons of each reservoir and calculate their respective areas. The use of the NDWI and MNDWI spectral indices for the identification of water bodies provided similar areas for the Chapéu reservoir, the main reservoir in the study basin, approaching the volume values obtained with the local monitoring of the reservoir. The assessment of water masses in the basin based on spectral indices and the MapBiomas classification provided information on the masses with high spatial resolution, enabling the identification of bodies in the basin, and it could be used as a tool for monitoring water resources.

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Application of fuzzy-AHP method for desertification assessment in Sabzevar area of Iran

Dastorani

2022

Nat Hazards

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Monitoramento Espaço-Temporal do Risco de Degradação Ambiental e Desertificação por Sensoriamento Remoto em Região Semiárida

Cited by 11 publications

References 30 publications

Geospatial Insights into Aridity Conditions: MODIS Products and GIS Modeling in Northeast Brazil

Geospatial Insights into Aridity Conditions: MODIS Products and GIS Modeling in Northeast Brazil

Comparison of the area of water masses in a hydrographic basin using spectral indices and MapBioma’s classification

Application of fuzzy-AHP method for desertification assessment in Sabzevar area of Iran

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