Environmental degradation of vegetation cover and water bodies in the semiarid region of the Brazilian Northeast via cloud geoprocessing techniques applied to orbital data

Silva, Jhon Lennon Bezerra da; Moura, Geber Barbosa de Albuquerque; Silva, Marcos Vinícius da; Oliveira‐Júnior, José Francisco de; Jardim, Alexandre Maniçoba da Rosa Ferraz; Refati, Daiana Caroline; Lima, Ricardo da Cunha Correia; Carvalho, Ailton Alves de; Ferreira, Maria Beatriz Rocha; Brito, José Ivaldo Barbosa de; Guedes, Roni Valter de Souza; Lopes, Pabrício Marcos Oliveira; Nóbrega, Ranyére Silva; Pandorfi, Héliton; Bezerra, Alan Cézar; Batista, Pedro Henrique Dias; Jesus, Fernanda Lâmede Ferreira de; Sanches, Arthur Carniato; Santos, Rodrigo Couto

doi:10.1016/j.jsames.2022.104164

Cited by 14 publications

(21 citation statements)

References 65 publications

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“…The study was also followed over time by images from the Sentinel-2A/MSI satellite from the Multispectral Instrument (MSI) sensor, Level-2A processing (Table 2), where geospatial analysis was developed based on indicator indices sensitive to soil spectral change conditions. Highlighting the Normalized Difference Vegetation Index (NDVI) [53][54][55][56], Normalized Difference Moisture Index (NDMI_GAO), and the Normalized Difference Water Index (NDWI_GAO) [57,58]. The estimation of vegetation indices was conducted using multispectral surface reflectance bands obtained from the Sentinel-2A/MSI satellite.…”

Section: Orbital Data Of Satellite (From Sentinel-2a/msi)mentioning

confidence: 99%

“…The NDVI using sentinel orbital images was estimated for the reason between the difference of the multispectral bands of near-infrared reflectance (r NIR 1 ) and the red band (r RED ) by the sum of the same. The NDVI varies between −1 and 1 and can be determined according to Equation (1) [54][55][56]61].…”

Section: Orbital Data Of Satellite (From Sentinel-2a/msi)mentioning

confidence: 99%

“…Similarly, the NDMI_GAO and NDWI_GAO indices have been utilized to monitor productivity, soil moisture, and water availability for plants. Low NDWI_GAO values may indicate dry conditions or water stress, while higher values may suggest an adequate water supply [56,85].…”

Section: Satellite Data Analysis (Sentinel-2a/msi)mentioning

confidence: 99%

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Geotechnologies in Biophysical Analysis through the Applicability of the UAV and Sentinel-2A/MSI in Irrigated Area of Common Beans: Accuracy and Spatial Dynamics

de Oliveira,

de Castro,

Sousa

et al. 2024

Remote Sensing

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The applicability of remote sensing enables the prediction of nutritional value, phytosanitary conditions, and productivity of crops in a non-destructive manner, with greater efficiency than conventional techniques. By identifying problems early and providing specific management recommendations in bean cultivation, farmers can reduce crop losses, provide more accurate and adequate diagnoses, and increase the efficiency of agricultural resources. The aim was to analyze the efficiency of vegetation indices using remote sensing techniques from UAV multispectral images and Sentinel-2A/MSI to evaluate the spectral response of common bean (Phaseolus vulgaris L.) cultivation in different phenological stages (V4 = 32 DAS; R5 = 47 DAS; R6 = 60 DAS; R8 = 74 DAS; and R9 = 89 DAS, in 99 days after sowing—DAS) with the application of doses of magnesium (0, 250, 500, and 1000 g ha−1). The field characteristics analyzed were mainly chlorophyll content, productivity, and plant height in an experimental area by central pivot in the midwest region of Brazil. Data from UAV vegetation indices served as variables for the treatments implemented in the field and were statistically correlated with the crop’s biophysical parameters. The spectral response of the bean crop was also detected through spectral indices (NDVI, NDMI_GAO, and NDWI_GAO) from Sentinel-2A/MSI, with spectral resolutions of 10 and 20 m. The quantitative values of NDVI from UAV and Sentinel-2A/MSI were evaluated by multivariate statistical analysis, such as principal components (PC), and cophenetic correlation coefficient (CCC), in the different phenological stages. The NDVI and MCARI vegetation indices stood out for productivity prediction, with r = 0.82 and RMSE of 330 and 329 kg ha−1, respectively. The TGI had the best performance in terms of plant height (r = 0.73 and RMSE = 7.4 cm). The best index for detecting the relative chlorophyll SPAD content was MCARI (r = 0.81; R2 = 0.66 and RMSE = 10.14 SPAD), followed by NDVI (r = 0.81; R2 = 0.65 and RMSE = 10.19 SPAD). The phenological stage with the highest accuracy in estimating productive variables was R9 (Physiological maturation). GNDVI in stages R6 and R9 and VARI in stage R9 were significant at 5% for magnesium doses, with quadratic regression adjustments and a maximum point at 500 g ha−1. Vegetation indices based on multispectral bands of Sentinel-2A/MSI exhibited a spectral dynamic capable of aiding in the management of bean crops throughout their cycle. PCA (PC1 = 48.83% and PC2 = 39.25%) of the satellite multiple regression model from UAV vs. Sentinel-2A/MSI presented a good coefficient of determination (R2 = 0.667) and low RMSE = 0.12. UAV data for the NDVI showed that the Sentinel-2A/MSI samples were more homogeneous, while the UAV samples detected a more heterogeneous quantitative pattern, depending on the development of the crop and the application of doses of magnesium. Results shown denote the potential of using geotechnologies, especially the spectral response of vegetation indices in monitoring common bean crops. Although UAV and Sentinel-2A/MSI technologies are effective in evaluating standards of the common bean crop cycle, more studies are needed to better understand the relationship between field variables and spectral responses.

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Section: Orbital Data Of Satellite (From Sentinel-2a/msi)mentioning

confidence: 99%

Section: Orbital Data Of Satellite (From Sentinel-2a/msi)mentioning

confidence: 99%

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Geotechnologies in Biophysical Analysis through the Applicability of the UAV and Sentinel-2A/MSI in Irrigated Area of Common Beans: Accuracy and Spatial Dynamics

de Oliveira,

de Castro,

Sousa

et al. 2024

Remote Sensing

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“…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%

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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“…The rapid and disorderly growth of urbanization results in the heat islands, which are pockets of heated air present in the urban environment, caused by greater absorption of radiation, due to the capacity that the different building materials that make up the urban structure have to exchanging energy with the sun. The solar radiation absorbed by these materials is converted into heat waves, being retained and raising the temperature of the environments causing thermal discomfort, which can be mitigated by the inclusion of green areas (Amorim, 2017;Peng et al, 2020;Silva, 2023).…”

Section: Introductionmentioning

confidence: 99%

Evaluation of thermal and optical properties measurements of paspalum in modular green roof in a tropical environment

Ferreira

Lopes²,

Silva³

et al. 2023

Rev. Bras. Geog. Fis.

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Artigo recebido em 01/10/2022 e aceito em 06/02/2023 R E S U M O O objetivo desta pesquisa foi avaliar a utilização de medições de propriedades térmicas e ópticas na caracterização do Gênero Paspalum para utilização em telhados verdes num ambiente tropical. O experimento foi conduzida na Universidade Federal Rural de Pernambuco -UFRPE de Maio a Junho de 2019. Foi avaliado o número de dezesseis acessos de Paspalum com hábitos de crescimento vertical ou prostrado. Em condições simuladas de um telhado verde, foram avaliadas: Índice de Vegetação Ajustada ao Solo (SAVI); temperatura das folhas (L) e do dossel (C) por termometria (TM); e por termografia (TG). O coeficiente de determinação (R 2 ) entre SAVI e a área de cobertura dos acessos foi de 0,84, e com matéria verde (R 2 = 0,73) e matéria seca (R 2 = 0,56). Não foi observada diferença significativa entre os acessos de Paspalum para a medição da temperatura da folha por TM e TG, e para o dossel TM. No entanto, foi observada uma diferença significativa entre a TG do dossel dos acessos de Paspalum, com temperaturas do dossel mais baixas nos acessos com hábito de crescimento vertical do que nos acessos com hábito prostado. A relação entre as técnicas mostrou valores elevados de coeficiente de determinação para TML com TGL (R 2 = 0,85) e TMC com TGC (R 2 = 0,91). Conclui-se que, o SAVI pode ser utilizado para estimar capacidade de área de cobertura vegetal dos acessos. As temperaturas das folhas e das copas podem ser usadas como indicação de déficit hídrico nos acessos de Paspalum, utilizando tanto o termómetro de infravermelhos (mais acessível) como a câmara termográfica. A termografia do dossel também pode ser utilizada para avaliar o desempenho térmico dos telhados verdes. As imagens termográficas indicaram que os acessos de Paspalum de hábitos de crescimento verticais podem proporcionar um melhor conforto térmico. Palavras-chave: Infravermelho; termografia; termometria; SAVI; fenotipagem; melhoramento de plantas. Evaluation of thermal and optical properties measurements of paspalum in modular green roof in a tropical environment A B S T R A C TThe objective was to evaluate the use of thermal and optical properties measurements in the characterization of the genus Paspalum for use on green roofs in a tropical environment. The experiment was conducted at the Universidade Federal Rural de Pernambuco -UFRPE from May to June 2019. The number of sixteen Paspalum accessions with prostrate and upright growth habits was evaluated. In a simulated modular green roof were evaluated: Soil-Adjusted Vegetation Index (SAVI); leaf (L) and canopy (C) temperature by thermometry (TM); and by thermography (TG). The determination coefficient (R 2 ) between SAVI and the coverage area are of 0.84, with green matter (R 2 = 0.73) and dry matter (R 2 = 0.56). No significant difference was observed between the accessions for leaf temperature measure by TM and TG, and for canopy TM. Nevertheless, significant difference to canopy TG were observed, with lower canopy temperatures in accessions w...

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Environmental degradation of vegetation cover and water bodies in the semiarid region of the Brazilian Northeast via cloud geoprocessing techniques applied to orbital data

Cited by 14 publications

References 65 publications

Geotechnologies in Biophysical Analysis through the Applicability of the UAV and Sentinel-2A/MSI in Irrigated Area of Common Beans: Accuracy and Spatial Dynamics

Geotechnologies in Biophysical Analysis through the Applicability of the UAV and Sentinel-2A/MSI in Irrigated Area of Common Beans: Accuracy and Spatial Dynamics

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

Evaluation of thermal and optical properties measurements of paspalum in modular green roof in a tropical environment

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