Space-time evaluation of physical parameters around the Barra do Juá/Pernambuco dam from Landsat-8 Images

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DOI:

https://doi.org/10.5902/2179460X73974

Keywords:

Remote sensing, Physical parameters, Digital image processing

Abstract

Remote sensing makes it possible to identify in real time changes in the earth's surface resulting from various natural phenomena and anthropic processes. The quantification of physical parameters obtained from remote sensing data is of great importance in environmental studies around water dams. Favoring the establishment of sustainable use and occupations, especially in the caatinga biome. This study aims to evaluate the space-time behavior of physical parameters (Normalized Difference Index – NDVI, Surface Albedo and Surface Temperature) in the surroundings of the Barra do Juá Dam/Pernambuco from technical data of remote sensing. Images from the Landsat-8 satellite OLI and TIRS sensors acquired from 2013 to 2021 through the Google Earth Engine cloud platform were used. Analyzes were based on time series interpretation, zonal statistics and linear regression. The spatial dynamics and the dry period influenced the physical parameters. Native vegetation showed the highest NDVI values in relation to exposed soil. Albedo and surface temperature showed inverse values to the NDVI, with lower values for native vegetation.The physical parameters studied showed a seasonal behavior for the years 2013 to 2021, showing an environmental relationship with climate dynamics and vegetative development as a result of water availability in the semi-arid region.

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Author Biographies

Admilson da Penha Pacheco, Universidade Federal de Pernambuco

Physicist with a Master's degree in Remote Sensing from the National Institute for Space Research (INPE) and a PhD in Geophysics from the University of São Paulo - USP/Astronomical and Geophysical Institute - IAG; Post-Doctorate at the Institute of Earth Sciences at the University of Minho/Portugal (2019); Full Professor at the Federal University of Pernambuco (UFPE/Department of Cartographic and Surveying Engineering); Coordination and Participation in Research and Development Projects (CNPq, FINEPE, FACEPE, ANEEL, ANA, CHESF, FUNDAJ), working in the areas of Applied Geophysics, Environment, Remote Sensing and Image Processing of Natural and Artificial Materials.

Camila Roberta Ribeiro de Souza, Universidade Federal de Pernambuco

Cartography and Surveyor Engineer from the Federal University of Pernambuco (UFPE). She works in the area of Geoprocessing, Digital Image Processing, Remote Sensing with an emphasis on geospatial data quality, environmental monitoring and natural disasters.

Juarez Antonio da Silva Júnior, Universidade Federal de Pernambuco

Cartographer and Surveyor Engineer from the Federal University of Pernambuco (UFPE). He works in the area of Geoprocessing, Digital Image Processing, Remote Sensing with an emphasis on geospatial data quality, environmental monitoring and natural disasters. I have experience with Multispectral, SAR, Hyperspectral and Lidar images. In the professional field, he was a geoprocessing and cartography analyst for the implementation of wind farms in the semiarid northeastern region and a geoprocessing analyst for the implementation of an environmental sanitation database in the municipality of Recife-PE.

References

ALBUQUERQUE, E. M.; ANDRADE, S. C. P.; MORAIS, H. F.; DINIZ, J. M. T.; SANTOS, C. A. C. Análise do comportamento do NDVI e NDWI sob diferentes intensidades pluviométricas no município de Souza-PB. Revista Estudos Geoambientais, [s. l.] v. 1 n. 1, 2014. Disponível em: https://periodicos.ufpb.br/index.php/geo/article/view/17986. Acesso em: 27 jan. 2022.

ALVES, J. M. B.; SILVA, E. M. da; ARAÚJO, F. C. de; SILVA, L. L. da. Um Estudo de Focos de Calor no Bioma Caatinga e suas Relações com Variáveis Meteorológicas. Revista Brasileira de Meteorologia, [S.L.], v. 36, n. 3, p. 513-527, set. 2021. DOI: http://dx.doi.org/10.1590/0102-77863630015.

ALTMAN, N.; KRZYWINSKI, M. Simple linear regression. Nature Methods, 12 (11): 999–1000, 2015. DOI: https://doi.org/10.1038/nmeth.3627.

APAC – Agência Pernambucana de Águas e Climas. Plano Estadual de Recursos Hídricos (PERH/PE): Pernambuco. 2019. Disponível em: www.apac.pe.gov.br. Acesso em: 27 jan. 2022.

ARAÚJO, A. L; SILVA, M. T.; SILVA, B. B. S.; COSTA, C. A.; DANTAS, M. Análise das Mudanças de Parâmetros Biofísicos Sobre o Nordeste Brasileiro de 2002 a 2011 com Dados Modis. Revista Brasileira de Meteorologia, 33(44): 589-599, 2018. DOI: https://doi.org/10.1590/0102-7786334002.

ARRAES, F. D. D. Dinâmica do balanço de energia na bacia hidráulica do açude Orós e suas adjacências. 2010. 89 p. Dissertação (Mestrado em Engenharia Agrícola) - Universidade Federal do Ceará, Fortaleza-CE, 2010. Disponível em: http://repositorio.ufc.br/handle/riufc/18599. Acesso em: 27 jan. 2022

CAETANO, R.; SILVA, T. B.; CASTRO, D. R. de; BENFICA, N. S. Uso de índices espectrais na caracterização da cobertura vegetal em região de Caatinga do Semiárido Baiano. Revista de Geociências do Nordeste, [S.l.], v. 8, n. 2, p. 28-43, 18 ago. 2022. DOI: http://dx.doi.org/10.21680/2447-3359.2022v8n2id26864.

CRUZ NETO, J. F da; JARDIM, A. M. R. F.; SOUZA, L. S. B. de; SILVA, T. G. F da. Desertification: an overview of processes and concepts, based on the application of orbital indices through remote sensing. Research, Society and Development, [S. l.] v. 10. N. 11, p. e585101119950, 2021. DOI: https://doi.org/10.33448/rsd-v10i11.19950.

CUNHA, J.; NÓBREGA, R. L. B.; RUFINO, I.; ERASMI, S.; GALVÃO, C.; Valente, F. Surface albedo as a proxy for land-cover clearing in seasonally dry forests: Evidence from the Brazilian Caatinga. Remote Sensing of Environment, v. 238, p. 111250. 2020. DOI: https://doi.org/10.1016/j.rse.2019.111250.

ERMIDA, S. L.; SOARES, P.; MANTAS, V.; FRANK-M, G.; TRIGO, I. F. Google Earth Engine Open-Source Code for Land Surface Temperature Estimation from the Landsat Series. Remote Sensing. V. 12, p. 1471, 2020. DOI: https://doi.org/10.3390/rs12091471.

FAO. Organización de las Naciones Unidas para la Alimentación y la Agricultura. Trabajo estratégico de la FAO para contribuir a la erradicación del hambre y la malnutrición, 2017. Disponível em: http://www.fao.org/3/a-i6431s.pdf. Acesso em: 29 jan. 2022.

FENG, M.; SEXTON, J. O.; HUANG, C.; MASEK, J. G.; VERMOTE, E. F.; GAO, F.; NARASIMHAN, R.; CHANNAN, S.; WOLFE, R. E.; TOWNSHEND, J. R. Global Surface refl ectance products from Landsat: Assessment using coincident MODIS observations. Remote Sensing of Environment, v. 134, p.276-293, 2013. DOI: https://doi.org/10.1016/j.rse.2013.02.031.

GUO, L.; SUN, X.; FU, P.; SHI, T.; DANG, L.; CHEN, Y.; LINDERMAN, M.; ZHANG, G.; ZHANG, Y.; JIANG, Q. Mapping soil organic carbon stock by hyperspectral and time-series multispectral remote sensing images in low-relief agricultural areas. Geoderma, [S.l.], v. 398, p. 115118, 2021. DOI: http://dx.doi.org/10.1016/j.geoderma.2021.115118.

HASHIM, B. M. ; MALIKI, A. A. ; SULTAN, M. A.; SHAHID, S. ; YASEEN, Z. M.. Effect of land use land cover changes on land surface temperature during 1984–2020: A case study of Baghdad city using landsat image. Natural Hazards, 112(2), 1223-1246, 2022. DOI: https://doi.org/10.1007/s11069-022-05224-y.

HE, J.; ZHAO, W.; LI, A.; WEN, F.; YU, D. The impact of the terrain effect on land surface temperature variation based on Landsat-8 observations in mountainous areas International Journal of Remote Sensing, 40, 1808–1827, 2018 DOI: https://doi.org/10.1080/01431161.2018.1466082

HUETE, A. R.; LIU, H. Q. An error and sensitivity analysis of the atmospheric-and soil-correcting variants of the NDVI for the MODIS-EOS. IEEE Transactions on Geoscience and Remote Sensing, v. 32, n.4, p. 897-905, 1994. DOI: 10.1109/36.298018.

JESUS, J. B.de; KUPLICH, T. M.; BARRETO, Í. D. de C.; ROSA, C. N. da; HILLEBRAND, F. L. Temporal and phenological profiles of open and dense Caatinga using remote sensing: response to precipitation and its irregularities. Journal of Forestry Research, [S.L.], v. 32, n. 3, p. 1067-1076, 2021. DOI: http://dx.doi.org/10.1007/s11676-020-01145-3.

KHORRAMI, B.; GUNDUZ, O.; PATEL, N.; GHOUZLANE, S.; NAJJAR, M. Land Surface Temperature Anomalies in Response to Changes in Forest Cover, International Journal of Engineering and Geosciences. v. 4 n. 3, p. 149-156, 2019. DOI: https://doi.org/10.26833/ijeg.549944.

LIANG, S. Narrowband to Broadband Conversions of Land Surface Albedo I: Algorithms. Remote Sensing of Environment, v. 76, n. 2 p. 213–238, 2001. DOI: https://doi.org/10.1016/S0034-4257(00)00205-4.

LI, Z.; ERB, A.; SUN, Q.; LIU, Y.; SHUAI, Y.; WANG, Z.; BOUCHER, P.; SCHAAF, C. Preliminary Assessment of 20-m Surface Albedo Retrievals from Sentinel-2A Surface Reflectance and MODIS/VIIRS Surface Anisotropy Measures. Remote Sensing of Environment, v. 217, p.352–365, 2018. DOI: https://doi.org/10.1016/j.rse.2018.08.025.

LIMA, J. F.; OLIVEIRA, L. M. M.; FARIAS, A. A. M.; SILVA, B. B. RODRIGUES, D, F. B.; MONTENEGRO, S. M G L. Geotecnologia para Caracterização do Albedo e Temperatura da Superfície no Sertão de Pernambuco, Brasil. Anuário do Instituto de Geociências, v. 44, p. 35481, 2021. DOI: https://doi.org/10.11137/1982-3908_2021_44_35481.

LIU, Y., TIAN, J., LIU, R., DING, L. Influences of Climate Change and Human Activities on NDVI Changes in China. Remote Sensing, v. 13, p. 4326, 2021. DOI: https://doi.org/10.3390/rs13214326.

LUCENA, L. R.; STOSIC, T. Temperatura do nordeste brasileiro via análise de lacunaridade. Sigmae, 2013; 2: 76-80. Disponível em: https://publicacoes.unifal-mg.edu.br/revistas/index.php/sigmae/article/view/211/pdf. Acesso em: 27 jan. 2022.

MAPBIOMAS. 2022. Disponível em: https://mapbiomas.org/a-cada-ano-brasil-queima-area-maior-que-a-inglaterra. Acesso em: 29 de junho de 2022.

NAEGELI, K.; DAMM, A.; HUSS, M.; WULF, H.; SCHAEPMAN, M.; HOELZLE, M. Cross-Comparison of Albedo Products for Glacier Surfaces Derived from Airborne and Satellite (Sentinel-2 and Landsat 8) Optical Data. Remote Sensing. v. 9 n. 2, p. 110, 2017. DOI: https://doi.org/10.3390/rs9020110.

PERNAMBUCO. Secretaria de Ciência, Tecnologia e Meio Ambiente. Atlas de bacias hidrográficas de Pernambuco. Recife, 2006. p. 90-91.

PINTO, C. T.; PONZONI, F. J.; BARRIENTOS, C.; MATTAR, C.; ARTIGAS, A. S.; CASTRO, R. Spectral and atmospheric characterization of a site at atacama desert for earth observation sensor calibration. IEEE Geoscience and Remote Sensing Letters, v. 12, n. 11,p. 2227-2231, 2015. DOI: 10.1109/LGRS.2015.2460454.

REIS, E. Estatística Descritiva. 7a Edição, ISBN: 978-972-618-476-8. Lisboa: Edições Sílabo. 2017, 248p..

SANTOS, C. A. C. dos; SILVA, M. V. G.; SILVA, M. T.; SANTOS, C. F. A.; BEZERRA, B. G.; MEDEIROS, S. de S. Obtenção de Parâmetros Ambientais na Região Semiárida da Paraíba por Dados MODIS, Revista Brasileira de Meteorologia, 2017; [S.l.], v. 32, n. 4, p. 633-647. DOI: http://dx.doi.org/10.1590/0102-7786324011.

SILVA, C. V. S.; SILVA, J. L. B. da; MOURA, G. B. de A.; LOPES, P. M. O.; NASCIMENTO, C. R.; SILVA, L. C. da. Monitoramento da cobertura vegetal por sensoriamento remoto no semiárido brasileiro através de índices de vegetação. Nativa, 2019; [S.l.], v. 7, n. 6, p. 708. DOI: http://dx.doi.org/10.31413/nativa.v7i6.7646.

SILVA, L. C. da; SILVA, J. L. B. da; MOURA, G. B. de A.; SILVA, D. A. de O.; LOPES, P. M. O.; NASCIMENTO, C. R.; SILVA, M. V. da; BATISTA, P. H. D.. Índices biofísicos e o saldo de radiação à superfície via sensoriamento remoto no semiárido pernambucano. Journal Of Environmental Analysis And Progress, [S.L.], v. 6, n. 1, p. 012-023, 28 jan. 2021. DOI: http://dx.doi.org/10.24221/jeap.6.1.2021.2876.012-023.

SILVA, D. A. de O.; LOPES, P. M. O.; MOURA, G. B. de A.; SILVA, Ê. F. de F. e; SILVA, J. L. B. da; BEZERRA, A. C.. Evolução Espaço-Temporal do Risco de Degradação da Cobertura Vegetal de Petrolina-PE. Revista Brasileira de Meteorologia, [S.l.], v. 34, n. 1, p. 89-99, mar. 2019. FapUNIFESP (SciELO). DOI: http://dx.doi.org/10.1590/0102-7786334018.

SILVA FILHO, R. da; VASCONCELOS, R. S.; GALVÃO, C. de O.; CUNHA, J. E. de B. L.; RUFINO, I. A. A.. Representação matemática do comportamento intra-anual do NDVI no Bioma Caatinga. Ciência Florestal, [S.L.], v. 30, n. 2, p. 473, jun. 2020. DOI: http://dx.doi.org/10.5902/1980509837279

SOUZA, A. M.; SILVA, C. S.; BEZERRA, B. G. Caatinga Albedo Preserved and Replaced by Pasture in Northeast Brazil. Atmosphere, [S.L.], v. 12, n. 12, p. 1622, 2021. DOI: http://dx.doi.org/10.3390/atmos12121622.

UNCCD, United Nations Convention to Combat Desertification. 2012. Disponível em: www.unccd.int. Acesso em: 06 de out.de 2016.

USGS, Landsat 8 Data Users Handbook. Department of the Interior U.S. Geological Survey. 2019. Disponível em: https://www.usgs.gov/landsat-missions/landsat-8-data-users-handbook. Acesso em: Set. 7, 2022.

WANG, Z.; SCHAAF, C. B.; SUN, Q.; SHUAI, Y.; ROMÁN, M. O. Capturing Rapid Land Surface Dynamics with Collection V006 MODIS BRDF/NBAR/Albedo (MCD43) Products. Remote Sensing of Environment, v. 207, p. 50–64, 2018. DOI: https://doi.org/10.1016/j.rse.2018.02.001

WEBB, EE, LORANTY, MM, LICHSTEIN, JW. Surface Water, Vegetation, and Fire as Drivers of the Terrestrial Arctic-Boreal Albedo Feedback. Environmental Research Letters, v. 16, n. 8, p. 084046, 2021. DOI: 10.1088/1748-9326/ac14ea.

XU, H. Q.; HUANG, S. L. A Comparative Study on the Calibration Accuracy of Landsat 8 Thermal 831 Infrared Sensor Data. Spectroscopy and Spectral Analysis, v. 36, n. 6, p.1941-1948, 2016.

ZHANG, P. P.; CAI, Y. P.; YANG, W.; YI, Y. Y.; YANG, Z. F.; FU, Q. Contributions of climatic and anthropogenic drivers to vegetation dynamics indicated by NDVI in a large dam-reservoir-river system. Journal of Cleaner Production. v. 256, p. 120477, 2020. DOI: https://doi.org/10.1016/j.jclepro.2020.120477

ZHANG, X.; JIAO, Z.; ZHAO, C.; QU, Y.; LIU, Q.; ZHANG, H.; TONG, Y.; WANG, C.; LI, S.; GUO, J. Review of Land Surface Albedo: Variance Characteristics, Climate Effect and Management Strategy. Remote Sensing, v. 14, n. 6, p. 1382, 2022. DOI: https://doi.org/10.3390/rs14061382

ZANTER, K.; Department of the interior, U.S. Geological Survey. Landsat 4-7 surface reflectance (LEDAPS). Product Guide. Version 2.0. 2019, EROS, Sioux Falls, South Dakota. Disponível em: https://www.usgs.gov/media/files/landsat-4-7-surface-reflectance-code-ledaps product-guide. Acesso em: September 7, 2022.

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2023-12-12

How to Cite

Pacheco, A. da P., Souza, C. R. R. de, & Silva Júnior, J. A. da. (2023). Space-time evaluation of physical parameters around the Barra do Juá/Pernambuco dam from Landsat-8 Images. Ciência E Natura, 45, e34. https://doi.org/10.5902/2179460X73974

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Vol. 45 (2023): Continuous Publication

Section

Geography

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