scholarly journals ÍNDICE DE VEGETAÇÃO POR DIFERENÇA NORMALIZADA ASSOCIADO ÀS VARIÁVEIS PLUVIOMÉTRICAS PARA A SUB-BACIA DO RIO ESPINHARAS – PB/RN

Nativa ◽  
2021 ◽  
Vol 9 (1) ◽  
pp. 106-114
Author(s):  
Ewerton Medeiros Simões ◽  
Joedla Rodrigues de Lima ◽  
Izaque Francisco Candeia de Mendonça
Keyword(s):  
Rainy Season ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Progressive Increase ◽  
Limiting Factor ◽  
Landsat 8 ◽  
Dry Period ◽  
Rainy Period ◽  
Brazilian Semiarid ◽  
Weather Stations

No semiárido brasileiro, onde se insere o bioma caatinga, a precipitaçãos é um dos fator limitante para seu desenvolvimento sócioeconômico e ambiental, este estudo avaliou a correlação existente entre o nível de cobertura vegetal e as variáveis pluviométricas locais, considerando a climatologia de 2005 e 2015, utilizando-se imagens dos sensores TM e OLI dos satélites Landsat 5 e Landsat 8, respectivamente. O ano de 2005 apresentou maiores valores de NDVI em relação a 2015, com valores máximos de 0,71 e 0,78 no período seco e úmido, respectivamente. No ano de 2015, os valores máximos são de 0,64 e 0,61, para o período seco e úmido, respectivamente. Os maiores valores foram observados no período chuvoso de 2005, nas áreas de influência das estações meteorológicas de Matureia, Salgadinho e Areia de Baraúnas. No período seco, nota-se a baixa variabilidade dos valores de NDVI, sendo as maiores leituras observadas nas estações de Matureia, Salgadinho e Teixeira. As estações que apresentaram as maiores reduções nos valores de NDVI de 2005 para 2015, no período chuvoso, foram Matureia, Santa Teresinha e Salgadinho, com reduções de 41,9%, 38,2% e 32,7%, respectivamente. As correlações mais significativas foram estabelecidas para os períodos secos. As menores correlações foram verificadas no período chuvoso. A elevação dos níveis pluviométricos na região não implicou o aumento progressivo nos valores de NDVI. Palavras-chave: semiárido; geoprocessamento; índice de vegetação normalizada.   Normalized difference vegetation index associated with pluviometric variables for Espinharas River sub-basin - PB/RN States   ABSTRACT: In the Brazilian semiarid, where the caatinga biome is inserted, precipitation is a limiting factor for its socioeconomic and environmental development, This study evaluated the correlation between the level of vegetation cover and the local rainfall variables, considering the climatology of 2005 and 2015, using images from the TM and OLI sensors of the Landsat 5 and Landsat 8 satellites, respectively. The year 2005 presented higher NDVI values compared to 2015, with maximum values of 0.71 and 0.78 in the dry and wet periods, respectively. In 2015, the maximum values are 0.64 and 0.61, for the dry and wet periods, respectively. The highest values were observed in the rainy period of 2005, in the weather stations of Matureia, Salgadinho and Areia de Baraúnas. In the dry period, the low variability of NDVI values is noted, with the highest readings observed in the Matureia, Salgadinho and Teixeira platforms. The platforms that showed the greatest reductions in NDVI values from 2005 to 2015, in the rainy season, were Matureia, Santa Teresinha and Salgadinho, with reductions of 41.9%, 38.2% and 32.7%, respectively. The most significant correlations were established for the dry periods. The smallest correlations were found in the rainy season. The increase in rainfall levels in the region did not imply a progressive increase in NDVI values. Keywords: semiarid; geoprocessing; normalized difference vegetation index.

TEMPERATURA DE SUPERFÍCIE E A RELAÇÃO COM O ÍNDICE DE VEGETAÇÃO POR DIFERENÇA NORMALIZADA (NDVI) NA MICROBACIA DO RIO DA BATATEIRAS, CRATO-CE

2019 ◽  
Vol 21 (2) ◽  
pp. 1310-1320
Author(s):  
Cícera Celiane Januário da Silva ◽  
Vinicius Ferreira Luna ◽  
Joyce Ferreira Gomes ◽  
Juliana Maria Oliveira Silva
Keyword(s):  
Remote Sensing ◽  
Surface Temperature ◽  
Temperature Measurement ◽  
Rainy Season ◽  
Satellite Images ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Landsat 8 ◽  
Low Density ◽  
Difference Map

O objetivo do presente trabalho é fazer uma comparação entre a temperatura de superfície e o Índice de Vegetação por Diferença Normalizada (NDVI) na microbacia do rio da Batateiras/Crato-CE em dois períodos do ano de 2017, um chuvoso (abril) e um seco (setembro) como também analisar o mapa de diferença de temperatura nesses dois referidos períodos. Foram utilizadas imagens de satélite LANDSAT 8 (banda 10) para mensuração de temperatura e a banda 4 e 5 para geração do NDVI. As análises demonstram que no mês de abril a temperatura da superfície variou aproximadamente entre 23.2ºC e 31.06ºC, enquanto no mês correspondente a setembro, os valores variaram de 25°C e 40.5°C, sendo que as maiores temperaturas foram encontradas em locais com baixa densidade de vegetação, de acordo com a carta de NDVI desses dois meses. A maior diferença de temperatura desses dois meses foi de 14.2°C indicando que ocorre um aumento da temperatura proporcionado pelo período que corresponde a um dos mais secos da região, diferentemente de abril que está no período de chuvas e tem uma maior umidade, presença de vegetação e corpos d’água que amenizam a temperatura.Palavras-chave: Sensoriamento Remoto; Vegetação; Microbacia.                                                                                  ABSTRACTThe objective of the present work is to compare the surface temperature and the Normalized Difference Vegetation Index (NDVI) in the Batateiras / Crato-CE river basin in two periods of 2017, one rainy (April) and one (September) and to analyze the temperature difference map in these two periods. LANDSAT 8 (band 10) satellite images were used for temperature measurement and band 4 and 5 for NDVI generation. The analyzes show that in April the surface temperature varied approximately between 23.2ºC and 31.06ºC, while in the month corresponding to September, the values ranged from 25ºC and 40.5ºC, and the highest temperatures were found in locations with low density of vegetation, according to the NDVI letter of these two months. The highest difference in temperature for these two months was 14.2 ° C, indicating that there is an increase in temperature provided by the period that corresponds to one of the driest in the region, unlike April that is in the rainy season and has a higher humidity, presence of vegetation and water bodies that soften the temperature.Key-words: Remote sensing; Vegetation; Microbasin.RESUMENEl objetivo del presente trabajo es hacer una comparación entre la temperatura de la superficie y el Índice de Vegetación de Diferencia Normalizada (NDVI) en la cuenca Batateiras / Crato-CE en dos períodos de 2017, uno lluvioso (abril) y uno (Septiembre), así como analizar el mapa de diferencia de temperatura en estos dos períodos. Las imágenes de satélite LANDSAT 8 (banda 10) se utilizaron para la medición de temperatura y las bandas 4 y 5 para la generación de NDVI. Los análisis muestran que en abril la temperatura de la superficie varió aproximadamente entre 23.2ºC y 31.06ºC, mientras que en el mes correspondiente a septiembre, los valores oscilaron entre 25 ° C y 40.5 ° C, y las temperaturas más altas se encontraron en lugares con baja densidad de vegetación, según el gráfico NDVI de estos dos meses. La mayor diferencia de temperatura de estos dos meses fue de 14.2 ° C, lo que indica que hay un aumento en la temperatura proporcionada por el período que corresponde a uno de los más secos de la región, a diferencia de abril que está en la temporada de lluvias y tiene una mayor humedad, presencia de vegetación y cuerpos de agua que suavizan la temperatura.Palabras clave: Detección remota; vegetación; Cuenca.

scholarly journals Evaluation of the Consistency of Simultaneously Acquired Sentinel-2 and Landsat 8 Imagery on Plastic Covered Greenhouses

2020 ◽  
Vol 12 (12) ◽  
pp. 2015 ◽  
Author(s):  
Manuel Ángel Aguilar ◽  
Rafael Jiménez-Lao ◽  
Abderrahim Nemmaoui ◽  
Fernando José Aguilar ◽  
Dilek Koc-San ◽  
...  
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Coefficient Of Determination ◽  
Landsat 8 ◽  
Surface Reflectance ◽  
Remote Sensing Techniques ◽  
Image Pairs ◽  
Study Sites ◽  
High Level ◽  
Sentinel 2

Remote sensing techniques based on medium resolution satellite imagery are being widely applied for mapping plastic covered greenhouses (PCG). This article aims at testing the spectral consistency of surface reflectance values of Sentinel-2 MSI (S2 L2A) and Landsat 8 OLI (L8 L2 and the pansharpened and atmospherically corrected product from L1T product; L8 PANSH) data in PCG areas located in Spain, Morocco, Italy and Turkey. The six corresponding bands of S2 and L8, together with the normalized difference vegetation index (NDVI), were generated through an OBIA approach for each PCG study site. The coefficient of determination (r2) and the root mean square error (RMSE) were computed in sixteen cloud-free simultaneously acquired image pairs from the four study sites to evaluate the coherence between the two sensors. It was found that the S2 and L8 correlation (r2 > 0.840, RMSE < 9.917%) was quite good in most bands and NDVI. However, the correlation of the two sensors fluctuated between study sites, showing occasional sun glint effects on PCG roofs related to the sensor orbit and sun position. Moreover, higher surface reflectance discrepancies between L8 L2 and L8 PANSH data, mainly in the visible bands, were always observed in areas with high-level aerosol values derived from the aerosol quality band included in the L8 L2 product (SR aerosol). In this way, the consistency between L8 PANSH and S2 L2A was improved mainly in high-level aerosol areas according to the SR aerosol band.

scholarly journals Periphytic algae dynamics in lentic ecosystems in the Brazilian semiarid

2016 ◽  
Vol 77 (3) ◽  
pp. 495-505 ◽  
Author(s):  
R. S. Cordeiro ◽  
J. E. L. Barbosa ◽  
G. Q. Lima Filho ◽  
L. G. Barbosa
Keyword(s):  
Aquatic Macrophytes ◽  
Soluble Reactive Phosphorus ◽  
Algal Community ◽  
Aquatic Communities ◽  
Dry Period ◽  
Rainy Period ◽  
Brazilian Semiarid ◽  
High Concentrations ◽  
Reactive Phosphorus ◽  
Reduced Density

Abstract The hydrological periods drive the structure and organization of aquatic communities in semiarid regions. We hypothesize that a decrease of the precipitation during the dry period will favor the development of the periphytic algal community, leading to higher richness and density in this period. To test this hypothesis, we investigated the changes in the periphytic algal community structure in three shallow and eutrophic ecosystems of the Brazilian semiarid. The sampling was performed between 2007 and 2010 at two-mensal intervals. The sampling of periphytic algal was performed in aquatic macrophytes and rocks. The abiotic variables were analyzed simultaneously. Dominance in diatoms, cyanobacteria and chlorophytes, respectively, was observed in two periods. In the dry period, waters were alkaline and had high concentrations of nitrate and total phosphorus associated with the highest densities of Bacillariophyceae. In the rainy period the water was warmer, oxygenated and high concentrations of ammonia and soluble reactive phosphorus with diatoms remained dominant but with reduced density, while cyanobacteria and chlorophytes increased. Overall, periphytic algal community composition no responded to changes in the hydrological periods. However, the hydrological periods altered the dynamics of periphytic algal community, supported by the alternation of the most representative classes (diatoms and cyanobacteria) between the hydrologic periods. Our data suggest that the morphometric and chemical and physical characteristics of lentic aquatic ecosystems studied were more important in the dynamics of periphytic algal community than the hydrological periods and types of substrates.

ANALISIS PERBANDINGAN METODE NORMALIZED VEGETATION INDEX DAN MAXIMUM LIKELIHOOD CLASSIFICATION UNTUK ANALISIS RUANG TERBUKA HIJAU (Studi Kasus di Kota Pekalongan, Jawa Tengah)

2021 ◽  
pp. 513
Author(s):  
Mohammad Slamet Sigit Prakoso ◽  
Rizki Dwi Safitri
Keyword(s):  
Maximum Likelihood ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Landsat 8 ◽  
Landsat 8 Oli ◽  
Maximum Likelihood Classification

Ruang Terbuka Hijau (RTH) adalah suatu tempat yang luas dan terbuka yang dimaksudkan untuk penghijauan suatu kota, di mana di dalamnya ditumbuhi pepohonan. Dalam analisis ruang terbuka hijau dapat menggunakan beberapa metode, di antaranya yaitu metode Normalized Difference Vegetation Index (NDVI) dan metode Maximum Likelihood Classification. Tujuan penelitian ini untuk mengetahui perbedaan hasil dari analisis metode NDVI dan Maximum Likelihood Classification yang digunakan untuk mengetahui ruang terbuka hijau di Kota Pekalongan. Metode yang digunakan pada penelitian ini yaitu dengan menggunakan metode NDVI dan metode Maximum Likelihood Classification. Data yang digunakan yaitu Citra Landsat 8 OLI. Pengolahan data menggunakan software Arcgis 10.3. Hasil dari pengolahan berupa peta ruang terbuka hijau dari masing - masing metode. Secara kuantitatif dari hasil perhitungan luas metode NDVI, luas permukiman sebesar 3.016,53 ha, persawahan 609,39 ha, hutan kota 573,3 ha, dan badan air seluas 482,04 ha. Sedangkan untuk metode Maximum Likelihood Classification didapatkan hasil luas permukiman 2.278,26 ha, persawahan 1.141,83 ha, hutan kota 738,18 ha, dan badan air seluas 522,99 ha. Berdasarkan luasan RTH terhadap luas Kota Pekalongan, pada metode NDVI sebesar 25,2%, sedangkan untuk metode Maximum Likelihood Classification sebesar 40,1%. Dari hasil analisis diperoleh perbedaan luasan yang cukup signifikan yaitu pada luasan persawahan dan permukiman. Perbedaan hasil analisis terjadi akibat perbedaan klasifikasi warna citra pada saat pengolahan data.

scholarly journals ESTIMASI PRODUKSI PADI DENGAN ANALISIS CITRA SATELIT LANDSAT 8 DI KABUPATEN KLUNGKUNG PROVINSI BALI

2018 ◽  
Vol 12 (1) ◽  
pp. 93
Author(s):  
Made Arya Bhaskara Putra ◽  
I Wayan Nuarsa ◽  
I Wayan Sandi Adnyana
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Satellite Image ◽  
Image Data ◽  
Research Area ◽  
Rice Production ◽  
Landsat 8 ◽  
Estimation Model ◽  
Accuracy Test ◽  
Accuracy Level

Rice crop is one of the important commodities that must always be available, so estimation of rice production becomes very important to do before harvesting time to know the food availability. The technology that can be used is remote sensing technology using Landsat 8 Satellite. The aims of this study were (1) to obtain the model of estimation of rice production with Landsat 8 image analysis, and (2) to know the accuracy of the model that obtained by Landsat 8. The research area is located in three sub-districts in Klungkung regency. Analysis in this research was conducted by single band analysis and analysis of vegetation index of satellite image of Landsat 8. Estimation model of rice production was developed by finding the relationship between satellite image data and rice production data. The final stage is the accuracy test of the rice production estimation model, with t test and regression analysis. The results showed: (1) estimation of rice production can be calculated between 67 to 77 days after planting; (2) there was a positive correlation between NDVI (Normalized Difference Vegetation Index) vegetation index value with rice yield; (3) the model of rice production estimation is y = 2.0442e1.8787x (x is NDVI value of Landsat 8 and y is rice production); (4) The results of the model accuracy test showed that the obtained model is suitable to predict rice production with accuracy level is 89.29% and standard error of production estimation is + 0.443 ton/ha. Based on research results, it can be concluded that Landsat 8 Satellite image can be used to estimate rice production and the accuracy level is 89.29%. The results are expected to be a reference in estimating rice production in Klungkung Regency.

scholarly journals Consideration of NDVI thematic changes in density analysis and floristic composition of Wadi Yalamlam, Saudi Arabia

2018 ◽  
Vol 7 (4) ◽  
pp. 297-306 ◽  
Author(s):  
Amal Y. Aldhebiani ◽  
Mohamed Elhag ◽  
Ahmad K. Hegazy ◽  
Hanaa K. Galal ◽  
Norah S. Mufareh
Keyword(s):  
Saudi Arabia ◽  
Vegetation Cover ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Remote Sensing Data ◽  
Floristic Composition ◽  
Water Source ◽  
Shannon Index ◽  
Landsat 8 ◽  
Main Stream

Abstract. Wadi Yalamlam is known as one of the significant wadis in the west of Saudi Arabia. It is a very important water source for the western region of the country. Thus, it supplies the holy places in Mecca and the surrounding areas with drinking water. The floristic composition of Wadi Yalamlam has not been comprehensively studied. For that reason, this work aimed to assess the wadi vegetation cover, life-form presence, chorotype, diversity, and community structure using temporal remote sensing data. Temporal datasets spanning 4 years were acquired from the Landsat 8 sensor in 2013 as an early acquisition and in 2017 as a late acquisition to estimate normalized difference vegetation index (NDVI) changes. The wadi was divided into seven stands. Stands 7, 1, and 3 were the richest with the highest Shannon index values of 2.98, 2.69, and 2.64, respectively. On the other hand, stand 6 has the least plant biodiversity with a Shannon index of 1.8. The study also revealed the presence of 48 different plant species belonging to 24 families. Fabaceae (17 %) and Poaceae (13 %) were the main families that form most of the vegetation in the study area, while many families were represented by only 2 % of the vegetation of the wadi. NDVI analysis showed that the wadi suffers from various types of degradation of the vegetation cover along with the wadi main stream.

scholarly journals A new method for estimating of evapotranspiration and surface soil moisture from optical and thermal infrared measurements: the simplified triangle

2020 ◽  
Author(s):  
Toby N. Carlson ◽  
George Petropoulos
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Heat Fluxes ◽  
Surface Model ◽  
Landsat 8 ◽  
Simple Method ◽  
Practical Applications ◽  
Infrared Measurements

Earth Observation (EO) provides a promising approach towards deriving accurate spatiotemporal estimates of key parameters characterizing land surface interactions, such as latent (LE) and sensible (H) heat fluxes as well as soil moisture content. This paper proposes a very simple method to implement, yet reliable to calculate evapotranspiration fraction (EF) and surface moisture availability (Mo) from remotely sensed imagery of Normalized Difference Vegetation Index (NDVI) and surface radiometric temperature (Tir). The method is unique in that it derives all of its information solely from these two images. As such, it does not depend on knowing ancillary surface or atmospheric parameters, nor does it require the use of a land surface model. The procedure for computing spatiotemporal estimates of these important land surface parameters is outlined herein stepwise for practical application by the user. Moreover, as the newly developedscheme is not tied to any particular sensor, it can also beimplemented with technologically advanced EO sensors launched recently or planned to be launched such as Landsat 8 and Sentinel 3. The latter offers a number of key advantages in terms of future implementation of the method and wider use for research and practical applications alike.

scholarly journals Assessment of vegetal cover changes using Normalized Difference Vegetation Index (NDVI) and subtractive (NDVI) time-series, Karbala province, Iraq

2018 ◽  
Vol 15 (35) ◽  
pp. 133-141
Author(s):  
Israa J. Muhsin
Keyword(s):  
Satellite Images ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Landsat 8 ◽  
Gap Filling ◽  
Economic Resource ◽  
Detection Techniques ◽  
Similar Region ◽  
Ndvi Time Series ◽  
Vegetal Cover

Karbala province regarded one part significant zones in Iraq and considered an economic resource of vegetation such as trees of fruits, sieve and other vegetation. This research aimed to utilize Normalized Difference Vegetation index (NDVI) and Subtracted (NDVI) for investigating the current vegetation cover at last four decay. The Normalized Difference Vegetation Index (NDVI) is the most extensively used satellite index of vegetation health and density. The primary goals of this research are gather a gathering of studied area (Karbala province) satellite images in sequence time for a similar region, these image captured by Landsat (TM 1985, TM 1995, ETM+ 2005 and Landsat 8 OLI (Operational Land Imager) 2015. Preprocessing such gap filling consider being vital stride has been implied on the defected image which captured in Landsat 2005 and isolate the regions of studied region. The Assessment vegetal cover changes of the studied area in this paper has been implemented using Normalized Difference Vegetation Index (NDVI), Green Normalized Difference Vegetation Index (GNDVI) and change detection techniques such as Subtracted (NDVI) method also have been used to detect the change in vegetal cover of the studied region. Many histogram and statistical properties were illustrated has been computed. From The results shows there are increasing in the vegetal cover from 1985 to 2015.

scholarly journals Spatio-temporal variability of biophysical parameters of irrigated maize using orbital remote sensing

2021 ◽  
Vol 42 (4) ◽  
pp. 2181-2202
Author(s):  
Taiara Souza Costa ◽  
◽  
Robson Argolo dos Santos ◽  
Rosângela Leal Santos ◽  
Roberto Filgueiras ◽  
...  
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Crop Coefficient ◽  
Coefficient Of Determination ◽  
Landsat 8 ◽  
Crop Evapotranspiration ◽  
Biophysical Parameters ◽  
Planting Dates ◽  
Maize Crop ◽  
Spatio Temporal

This study proposes to estimate the actual crop evapotranspiration, using the SAFER model, as well as calculate the crop coefficient (Kc) as a function of the normalized difference vegetation index (NDVI) and determine the biomass of an irrigated maize crop using images from the Operational Land Imager (OLI) and Thermal Infrared (TIRS) sensors of the Landsat-8 satellite. Pivots 21 to 26 of a commercial farm located in the municipalities of Bom Jesus da Lapa and Serra do Ramalho, west of Bahia State, Brazil, were selected. Sowing dates for each pivot were arranged as North and South or East and West, with cultivation starting firstly in one of the orientations and subsequently in the other. The relationship between NDVI and the Kc values obtained in the FAO-56 report (KcFAO) revealed a high coefficient of determination (R2 = 0.7921), showing that the variance of KcFAO can be explained by NDVI in the maize crop. Considering the center pivots with different planting dates, the crop evapotranspiration (ETc) pixel values ranged from 0.0 to 6.0 mm d-1 during the phenological cycle. The highest values were found at 199 days of the year (DOY), corresponding to around 100 days after sowing (DAS). The lowest BIO values occur at 135 DOY, at around 20 DAS. There is a relationship between ETc and BIO, where the DOY with the highest BIO are equivalent to the days with the highest ETc values. In addition to this relationship, BIO is strongly influenced by soil water availability.

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.

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