scholarly journals Quantification and Analysis of Impervious Surface Area in the Metropolitan Region of São Paulo, Brazil

2019 ◽  
Vol 11 (8) ◽  
pp. 944 ◽  
Author(s):  
Fernando Kawakubo ◽  
Rúbia Morato ◽  
Marcos Martins ◽  
Guilherme Mataveli ◽  
Pablo Nepomuceno ◽  
...  
Keyword(s):  
Surface Area ◽  
Vegetation Index ◽  
Impervious Surface ◽  
Sao Paulo ◽  
Metropolitan Region ◽  
Integrated Analysis ◽  
Landsat 8 ◽  
São Paulo ◽  
Impervious Surface Area ◽  
Pixel Scale

The growing intensity of impervious surface area (ISA) is one of the most striking effects of urban growth. The expansion of ISA gives rise to a set of changes on the physical environment, impacting the quality of life of the human population as well as the dynamics of fauna and flora. Hence, due to its importance, the present study aimed to examine the ISA distribution in the Metropolitan Region of São Paulo (MRSP), Brazil, using satellite imagery from the Landsat-8 Operational Land Imager (OLI) instrument. In contrast to other investigations that primarily focus on the accuracy of the estimate, the proposal of this study is—besides generating a robust estimate—to perform an integrated analysis of the impervious-surface distribution at pixel scale with the variability present in different territorial units, namely municipalities, sub-prefecture and districts. The importance of this study is that it strengthens the use of information related to impervious cover in the territorial planning, providing elements for a better understanding and connection with other spatial attributes. Reducing the dimensionality of the dataset (visible, near-infrared and short-wave infrared bands) by Karhune–Loeve analysis, the first three principal components (PCs) contained more than 99% of the information present in the original bands. Projecting PC1, PC2 and PC3 onto a series of two-dimensional (2D) scatterplots, four endmembers—Low Albedo (Dark), High Albedo (Substrate), Green Vegetation (GV) and Non-Photosynthetic Vegetation (NPV)—were visually selected to produce the unmixing estimates. The selected endmembers fitted the model well, as the propagated error was consistently low (root-mean-square error = 0.005) and the fraction estimates at pixel scale were found to be in accordance with the physical structures of the landscape. The impervious surface fraction (ISF) was calculated by adding the Dark and Substrate fraction imagery. Reconciling the ISF with reference samples revealed the estimates to be reliable (R2 = 0.97), regardless of an underestimation error (~8% on average) having been found, mostly over areas with higher imperviousness rates. Intra-pixel variability was combined with the territorial units of analysis through a modification of the Lorenz curve, which permitted a straightforward comparison of ISF values at different reference scales. Good adherence was observed when the original 30-m ISF was compared to a resampled 300-m ISF, but with some differences, suggesting a systematic behavior with the degradation of pixel resolution tending to underestimate lower fractions and overestimate higher ones; furthermore, discrepancies were bridged with the increase of scale analysis. The analysis of the IFS model also revealed that, in the context of the MRSP, gross domestic product (GDP) has little potential for explaining the distribution of impervious areas on the municipality scale. Finally, the ISF model was found to be more sensitive in describing impervious surface response than other well-known indices, such as Normalized Difference Vegetation Index (NDVI) and Normalized Difference Built-up Index (NDBI).

scholarly journals Planejamento Ambiental Urbano: a Relação entre a Cobertura Vegetal e Temperatura Superficial na Cidade de São Carlos, São Paulo, Brasil

2021 ◽  
Vol 10 (2) ◽  
pp. 116-131
Author(s):  
Vitor Augusto Luizari Camacho Camacho ◽  
Luiz Eduardo Moschini
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Sao Paulo ◽  
Landsat 8 ◽  
São Paulo

A rápida expansão urbana das cidades brasileiras modificou a paisagem natural alterando as condições ambientais e climáticas, a partir disso os estudos que envolvem planejamento urbano, meio ambiente e geotecnologias apresentam soluções as novas demandas. O objetivo deste trabalho consiste em analisar a relação entre a cobertura vegetal e a temperatura da superfície da cidade de São Carlos, São Paulo, Brasil. Foi utilizado imagens do satélite Landsat-8, por meio das técnicas de processamento digital de imagem e sensoriamento remoto. Para a temperatura da superfície foi utilizado a banda 10 (termal) e para a cobertura vegetal as bandas 4 (vermelho) e 5 (infravermelho próximo) pelo índice de vegetação NDVI (Normalized Difference Vegetation Index). O trabalho foi realizado no sistema de informação geográfica QGIS. Como analise foram determinados os coeficientes de correlação e determinação entre os índices a partir de pontos de controle no perímetro urbano. Como resultado foi possível observar uma forte correlação negativa entre cobertura vegetal e temperatura da superfície. Áreas com as maiores temperaturas (37,4°C) estiveram associadas a ausência de vegetação, ao alto grau de adensamento construtivo e impermeabilização do solo. Estudos como este reforçam a importância da cobertura vegetal em áreas urbanas para o controle térmico e bem-estar das populações residentes diante do crescente efeito das mudanças climáticas que afetam os centros urbanos. Propostas e ações de mitigação devem fazer parte de um conjunto de políticas públicas aplicadas as cidades, pensando de forma sistêmica e dinâmica.

scholarly journals The climatic rhythm and blooms of cyanobacteria in a tropical reservoir in São Paulo, Brazil

2014 ◽  
Vol 74 (1) ◽  
pp. 72-78 ◽  
Author(s):  
I Ogashawara ◽  
JA Zavattini ◽  
JG Tundisi
Keyword(s):  
Water Quality ◽  
Meteorological Data ◽  
Polar Front ◽  
Sao Paulo ◽  
Cyanobacterial Blooms ◽  
Metropolitan Region ◽  
Integrated Analysis ◽  
Limiting Factor ◽  
São Paulo ◽  
Tropical Reservoir

The present study sought to develop a methodology to analyse water quality based on the concepts and methods of climate and climatology. Accordingly, we attempted to relate hydro- and limnometeorological techniques and methodologies to a rhythmic analysis technique developed within the context of the Brazilian geographical climatology. Our goal was to assess and analyse cyanobacterial blooms, the main index of water quality for the reservoirs of the “Alto Tietê” Basin and, consequently, the Metropolitan Region of São Paulo, an area of high environmental complexity due to its high degree of development and high population density. The meteorological data used were collected by the Institute of Astronomy, Geophysics and Atmospheric Sciences at the University of São Paulo meteorological station, and the limnological data were collected through the Hydrological Monitoring System implemented by SABESP in the Billings and Guarapiranga Reservoirs and the laboratory of the same entity. The rhythmic and integrated analysis showed that the process of cyanobacterial blooms is dependent on a combination of meteorological factors as temperature and wind intensity that may disrupt the stability of the reservoir, providing the conditions necessary for the development of cyanobacteria during the stabilisation process. The pace of the Atlantic Polar Front Entrance during the winter in São Paulo is a limiting factor for the growth of cyanobacteria because of their high frequency, thus maintaining the balance of the reservoir throughout this period. The weather types those could cause a instability in the water column were: Cold Front entrance (66.67%), conflict between masses (22.22%) and the Tropical Instability Line (11.11%). The possibility for prevention and forecasting periods advise when these reservoirs should not be used, mainly with regard to recreational activities.

scholarly journals A satellite-based investigation into the algae bloom variability in large water supply urban reservoirs during COVID-19 lockdown

2021 ◽  
Author(s):  
Enner Alcantara ◽  
Keyla Coimbra ◽  
Igor Ogashawara ◽  
Thanan Rodrigues ◽  
Jose Mantovani ◽  
...  
Keyword(s):  
Water Supply ◽  
Water Use ◽  
Sao Paulo ◽  
Metropolitan Region ◽  
Treated Wastewater ◽  
Landsat 8 ◽  
São Paulo ◽  
Environmental Consequences ◽  
First Case ◽  
The Impact

Abstract Here we report the first case study of the significant algae blooming in large reservoirs in relation to the COVID-19 lockdown in Sao Paulo, Brazil. Chlorophyll-a (Chl-a) and phycocyanin (PC) concentrations were analyzed in the Guarapiranga and Billings reservoirs, which supply daily water use for over 20 million people and receives treated wastewater. We employed field-calibrated Sentinel 2 MSI and Landsat 8 OLI images to map the spatial patterns of Chl-aand PC over the two period: before (April, August and October 2019) and more than a month after the lockdown in Sao Paulo due to the rapid spread of the COVID-19 in Brazil (April 2020). We found a significant increase in algae blooming (both Chl-a and PC) in both reservoirs in April 2020, compared to the same month of 2019. We show that the episodic algae blooming is strongly related to the increased inflows of the residential wastewater from the surrounding watersheds, because the household water use has increased ~3.2% in April 2020, while the runoff into the reservoirs driven by the rainfall was much lower in 2020 compared to the previous year for the same month. In the case of Guarapiranga Reservoir, PC increased nearly 500% in April 2020 compared to April 2019. Given the importance of Billings and Guarapiranga reservoirs for the water supply of the Metropolitan Region of Sao Paulo (MRSP), the abrupt occurrence of cyanobacteria blooms related to the state’s lockdown should be considered a major concern for public and environmental health of the region. Although several environmental consequences have been reported due to the COVID-19 worldwide, this study is the first to report the impact of COVID-19 on the trophic state in the tropical reservoirs.

scholarly journals SENSORIAMENTO REMOTO APLICADO A MODELAGEM DE PRODUTIVIDADE DA CULTURA DA CANA-DE-AÇÚCAR

2019 ◽  
Vol 34 (2) ◽  
pp. 263-270
Author(s):  
Victor Costa Leda ◽  
Aline Kuramoto Golçalves ◽  
Natalia da Silva Lima
Keyword(s):  
Remote Sensing ◽  
Vegetation Index ◽  
Sao Paulo ◽  
Coefficient Of Determination ◽  
Landsat 8 ◽  
São Paulo ◽  
Vegetation Indexes ◽  
Production Area ◽  
Remote Sensing Techniques ◽  
Sugarcane Productivity

SENSORIAMENTO REMOTO APLICADO A MODELAGEM DE PRODUTIVIDADE DA CULTURA DA CANA-DE-AÇÚCAR   VICTOR COSTA LEDA1, ALINE KURAMOTO GOLÇALVES2, NATALIA DA SILVA LIMA3   1 Departamento de Solos e Recursos Ambientais, Universidade Paulista “Júlio de Mesquita Filho” – Unesp, Fazenda Experimental Lageado, Avenida Universitária, nº 3780, Altos do Paraíso, CEP 18610-034, Botucatu, São Paulo, Brasil, [email protected]. 2 Departamento de Solos e Recursos Ambientais, Universidade Paulista “Júlio de Mesquita Filho” – Unesp, Fazenda Experimental Lageado, Avenida Universitária, nº 3780, Altos do Paraíso, CEP 18610-034, Botucatu, São Paulo, Brasil, [email protected]. 3 Departamento de Solos e Recursos Ambientais, Universidade Paulista “Júlio de Mesquita Filho” – Unesp, Fazenda Experimental Lageado, Avenida Universitária, nº 3780, Altos do Paraíso, CEP 18610-034, Botucatu, São Paulo, Brasil, [email protected].   RESUMO: O trabalho objetivou modelar as correlações de produtividade da cana-de-açúcar com índices de vegetação obtidos por meio de análise de imagens orbitais. Para análise, foram elaborados modelos matemáticos que expliquem a produtividade da cana-de-açúcar por meio das técnicas de geoprocessamento e sensoriamento remoto. O experimento foi realizado na área de produção comercial da Agrícola Rio Claro, parceira do grupo Zilor, que está localizada nos municípios de Lençóis Paulista e Pratânia, SP. A área ocupa aproximadamente 6000 ha, com altimetrias variando entre 600 e 700 m. Foi constatado que as modelagens foram satisfatórias, variando o coeficiente de determinação entre 0,15 a 0,97, sendo que, em períodos de colheita com elevados coeficientes de determinação, podem geralmente ser encontradas áreas de forma aglomerada, o que sugere uma menor incidência de variáveis. Enquanto áreas que apresentaram coeficientes de determinação baixos, podem ser explicadas devido a fatores como, dispersão dos talhões na área, classes de solo, precipitação e variedades da cultura, provavelmente distintos.   Palavras-chaves: índices de vegetação, Landsat 8, regressão linear múltipla.   REMOTE SENSING FOR THE SUGARCANE PRODUCTIVITY MODELING   ABSTRACT: The aim of this study was to model the sugarcane productivity correlations with vegetation indexes obtained through orbital image analysis. From the analysis was elaborated      mathematical models to explain sugarcane productivity through geoprocessing and remote sensing techniques. The experiment was carried out in the commercial production area of Agrícola Rio Claro, a partner of the Zilor group, located in the municipalities of Lençóis Paulista and Pratânia, SP, with approximately 6,000 hectares, with altimetry varying between 600 and 700 meters. It was verified that the modeling was satisfactory, varying the coefficient of determination between 0,15 and 0,97. Once      in periods with high determination coefficients, areas of agglomerated form can usually be found, which suggests a lower incidence of variables. While, in periods with low determination coefficients, can be explain due to listed factors that occurred as dispersion of the stands in the area, classes of soil, precipitation and probably different varieties of the crop.   Keywords: vegetation index, landsat8, multiple linear regression.

scholarly journals VEGETATION COVERAGE AND IMPERVIOUS SURFACE AREA ESTIMATED BASED ON THE ESTARFM MODEL AND REMOTE SENSING MONITORING

2018 ◽  
Vol IV-3 ◽  
pp. 113-119
Author(s):  
Rongming Hu ◽  
Shu Wang ◽  
Jiao Guo ◽  
Liankun Guo
Keyword(s):  
Remote Sensing ◽  
Surface Area ◽  
Temporal Resolution ◽  
Remote Sensing Data ◽  
Impervious Surface ◽  
Vegetation Coverage ◽  
Landsat 8 ◽  
Spatiotemporal Resolution ◽  
Impervious Surface Area ◽  
Sensing Data

Impervious surface area and vegetation coverage are important biophysical indicators of urban surface features which can be derived from medium-resolution images. However, remote sensing data obtained by a single sensor are easily affected by many factors such as weather conditions, and the spatial and temporal resolution can not meet the needs for soil erosion estimation. Therefore, the integrated multi-source remote sensing data are needed to carry out high spatio-temporal resolution vegetation coverage estimation. Two spatial and temporal vegetation coverage data and impervious data were obtained from MODIS and Landsat 8 remote sensing images. Based on the Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM), the vegetation coverage data of two scales were fused and the data of vegetation coverage fusion (ESTARFM FVC) and impervious layer with high spatiotemporal resolution (30 m, 8 day) were obtained. On this basis, the spatial variability of the seepage-free surface and the vegetation cover landscape in the study area was measured by means of statistics and spatial autocorrelation analysis. The results showed that: 1) ESTARFM FVC and impermeable surface have higher accuracy and can characterize the characteristics of the biophysical components covered by the earth's surface; 2) The average impervious surface proportion and the spatial configuration of each area are different, which are affected by natural conditions and urbanization. In the urban area of Xi'an, which has typical characteristics of spontaneous urbanization, landscapes are fragmented and have less spatial dependence.

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