scholarly journals CO2flux e temperatura da superfície edáfica em áreas de caatinga

2021 ◽  
Vol 14 (4) ◽  
pp. 1898-1908
Author(s):  
Daniel da Silva Gomes ◽  
Sabrina Kelly dos Santos ◽  
João Henrique Constantino Sales Silva ◽  
Teófilo de Medeiros Santos ◽  
Ermerson de Vasconcelos Silva ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Carbon Sequestration ◽  
Surface Temperature ◽  
Rainy Season ◽  
Dry Season ◽  
Spectral Radiance ◽  
Landsat 8 ◽  
Caatinga Vegetation ◽  
The Face ◽  
Using Data

The changes that occur in the Caatinga vegetation cover alter the incidence of solar radiation at the surface-atmosphere interface. To monitor CO2 flows, through geotechnologies, they appear as an alternative or remote sensing. Thus, the objective of this work was to determine the carbon sequestration and the surface temperature in caatinga areas in the face of seasonal variations using data from the Landsat 8 satellite OLI and TIRS sensors. The study was carried out with a scene referring to the dry season and another referring to the rainy season, in two areas, one with preserved Caatinga vegetation and the other with agricultural intervention, both in the municipality of São José de Piranhas, Paraíba. The pre-processing of the images took place from the transformation of digital numbers for spectral radiance and then for reflectance, since the processing occurred from the application of the vegetation and temperature indices, resulting in CO2flux and surface temperature. The Caatinga was greatly influenced by rainfall, directly affecting the phenology of this vegetation. The variation in temperature and CO2flux were influenced by seasonality, in the dry season there was less sequestration and higher temperatures, while in the rainy season there was greater sequestration and lower temperatures. The multiple comparison test showed that all the variables studied showed statistical differences. Temperature and CO2flux are influenced by seasonality. Multispectral remote sensing is a tool that can assist in the study of temperature dynamics and carbon sequestration in the Caatinga biome.

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 Estimation and Validation of Land Surface Temperature by using Remote Sensing & GIS for Chittoor District, Andhra Pradesh

2021 ◽  
Vol 12 (5) ◽  
pp. 607-617
Author(s):  
A. Rajani, Dr. S.Varadarajan
Keyword(s):  
Remote Sensing ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Andhra Pradesh ◽  
Temperature Data ◽  
Sensor Data ◽  
Spectral Radiance ◽  
Landsat 8 ◽  
Thermal Band

Land Surface Temperature (LST) quantification is needed in various applications like temporal analysis, identification of global warming, land use or land cover, water management, soil moisture estimation and natural disasters. The objective of this study is estimation as well as validation of temperature data at 14 Automatic Weather Stations (AWS) in Chittoor District of Andhra Pradesh with LST extracted by using remote sensing as well as Geographic Information System (GIS). Satellite data considered for estimation purpose is LANDSAT 8. Sensor data used for assessment of LST are OLI (Operational Land Imager) and TIR (Thermal Infrared). Thermal band  contains spectral bands of 10 and 11 were considered for evaluating LST independently by using algorithm called Mono Window Algorithm (MWA). Land Surface Emissivity (LSE) is the vital parameter for calculating LST. The LSE estimation requires NDVI (Normalized Difference Vegetation Index) which is computed by using Band 4 (visible Red band) and band 5 (Near-Infra Red band) spectral radiance bands. Thermal band images having wavelength 11.2 µm and 12.5 µm of 30th May, 2015 and 21st October, 2015 were processed for the analysis of LST. Later on validation of estimated LST through in-suite temperature data obtained from 14 AWS stations in Chittoor district was carried out. The end results showed that, the LST retrieved by using proposed method achieved 5 per cent greater correlation coefficient (r) compared to LST retrieved by using existing method which is based on band 10.

scholarly journals ASSESSING THE VARIATION OF THE DRY SEASON’S SURFACE TEMPERATURE IN BINH DUONG PROVINCE FROM 2002 TO 2016 BY APPLYING THERMAL REMOTE SENSING

2018 ◽  
Vol 55 (4C) ◽  
pp. 136
Author(s):  
Nguyen Huynh Anh Tuyet
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Surface Temperature ◽  
Land Surface ◽  
Urban Areas ◽  
Dry Season ◽  
Landsat 8 ◽  
Large Area ◽  
Spectral Radiation ◽  
Thermal Remote Sensing

Thermal remote sensing with its own concepts and potentials has presented a variety of applications in the atmosphere and land surface temperature (LST) variation detection. The objective of this study is to access the LST variation in the dry season of Binh Duong province for understanding the effect of land-use change on the microclimate conditions. The spectral radiation value was determined from gray-scale of thermal infrared images of Landsat 7 ETM+ and Landsat 8 OLI/TIRs, followed by the LST calculation. Results showed that the LST in dry season decreased approximately 1.5 °C over the past 15 years from 30.8 °C in the year 2002 to 29.3 °C in the year 2016, due to a large area of newly planted land of industrial trees changed into mature ones in 2016. The area, in which temperature increased corresponding to 16.6 % of the natural square, has developed rapidly with new industrial parks, urban areas, and vacant land areas. Therefore, the Government should have solutions to promote its positive side and mitigate its negative side by a suitable land-use structure in order to both develop the economic continuously and help to mitigate the climate change effects.

scholarly journals Spatial-temporal dynamics of Caatinga vegetation cover by remote sensing in the Brazilian semiarid region

DYNA ◽  
2020 ◽  
Vol 87 (215) ◽  
pp. 109-117
Author(s):  
Joez André de Moraes Rodrigues ◽  
Pabricio Marcos Oliveira Lopes ◽  
Jhon Lennon Bezerra da Silva ◽  
Hélio Lopes Araújo ◽  
Marcos Vinícios da Silva ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Leaf Area ◽  
Environmental Degradation ◽  
Vegetation Index ◽  
Temporal Dynamics ◽  
Dry Season ◽  
Semiarid Region ◽  
Landsat 8 ◽  
Caatinga Vegetation ◽  
Brazilian Semiarid

The Brazilian semiarid region is marked by water scarcity, which causes the loss of leaves from native vegetation to reduce transpiration. With the reduction of the Caatinga leaf area, the soil becomes more exposed, which makes it a great ally for environmental degradation. This study aimed to monitor and analyze the spatial-temporal dynamics of the Caatinga vegetation by orbital remote sensing in the semiarid region of Pernambuco, Brazil, in the rainy and dry season. The study was developed from Landsat-8 satellite images between the years 2013-2018. From the SEBAL algorithm, thematic maps of the biophysical parameters were determined: albedo and surface temperature, normalized difference vegetation index (NDVI), soil-adjusted vegetation index (SAVI), and leaf area index (LAI). The results show that in the dry season, there is a greater aptitude for environmental degradation to occur.

Impact of LULC Changes on LST in Rajshahi District of Bangladesh: A Remote Sensing Approach

2020 ◽  
Vol 3 (1) ◽  
pp. 11-23 ◽  
Author(s):  
Abdulla Al Kafy ◽  
Abdullah Al-Faisal ◽  
Mohammad Mahmudul Hasan ◽  
Md. Soumik Sikdar ◽  
Mohammad Hasib Hasan Khan ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Surface Temperature ◽  
Land Surface ◽  
Agricultural Land ◽  
Global Climate ◽  
Urban Expansion ◽  
Water Bodies ◽  
Landsat 8 ◽  
Lulc Changes ◽  
The Impact

Urbanization has been contributing more in global climate warming, with more than 50% of the population living in cities. Rapid population growth and change in land use / land cover (LULC) are closely linked. The transformation of LULC due to rapid urban expansion significantly affects the functions of biodiversity and ecosystems, as well as local and regional climates. Improper planning and uncontrolled management of LULC changes profoundly contribute to the rise of urban land surface temperature (LST). This study evaluates the impact of LULC changes on LST for 1997, 2007 and 2017 in the Rajshahi district (Bangladesh) using multi-temporal and multi-spectral Landsat 8 OLI and Landsat 5 TM satellite data sets. The analysis of LULC changes exposed a remarkable increase in the built-up areas and a significant decrease in the vegetation and agricultural land. The built-up area was increased almost double in last 20 years in the study area. The distribution of changes in LST shows that built-up areas recorded the highest temperature followed by bare land, vegetation and agricultural land and water bodies. The LULC-LST profiles also revealed the highest temperature in built-up areas and the lowest temperature in water bodies. In the last 20 years, LST was increased about 13ºC. The study demonstrates decrease in vegetation cover and increase in non-evaporating surfaces with significantly increases the surface temperature in the study area. Remote-sensing techniques were found one of the suitable techniques for rapid analysis of urban expansions and to identify the impact of urbanization on LST.

scholarly journals Monitoramento Espaço-Temporal da Detecção de Mudanças em Vegetação de Caatinga por Sensoriamento Remoto no Semiárido Brasileiro

2020 ◽  
Vol 13 (1) ◽  
pp. 286 ◽  
Author(s):  
Alan Cézar Bezerra ◽  
Jhon Lennon Bezerra da Silva ◽  
Douglas Alberto De Oliveira Silva ◽  
Pedro Henrique Dias Batista ◽  
Liliane Da Cruz Pinheiro ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Surface Temperature ◽  
Environmental Degradation ◽  
Vegetation Index ◽  
Digital Processing ◽  
Soil Condition ◽  
Response Patterns ◽  
Biophysical Parameters ◽  
Surface Data ◽  
Caatinga Vegetation

O sensoriamento remoto pode ser utilizado no monitoramento ambiental de parâmetros biofísicos micrometeorológicos nas regiões semiáridas do Brasil. Objetivou-se monitorar o risco da degradação ambiental através da detecção de mudanças da superfície no semiárido por sensoriamento remoto. A pesquisa foi desenvolvida através do processamento digital de imagens de satélite para Serra Talhada, Pernambuco. Foram coletados dados de superfície para subsidiar o algoritmo do balanço de energia da superfície terrestre (SEBAL) na estimativa do albedo e temperatura da superfície e o índice de vegetação ajustado as condições do solo (SAVI). Além disso, se desenvolveu mapas temáticos do grau do risco de degradação. Os mapas da degradação foram submetidos a avaliação estatística de qualidade temática, por matriz de confusão. O SAVI apresentou-se sensível à chuva, tendo na estação chuvosa os maiores valores e na estação seca os menores, período que o albedo e a temperatura apresentaram valores elevados, indicando vulnerabilidade à degradação das áreas com pouca vegetação e solo exposto. Os mapas do risco de degradação destacaram características semelhantes aos padrões de respostas do SAVI, albedo e temperatura. O monitoramento espaço-temporal dos parâmetros biofísicos e do risco de degradação permitirá o planejamento e gestão dos recursos hídricos e naturais da região semiárida. Spatial-Temporal Monitoring Detection of Changes in Caatinga Vegetation by Remote Sensing in the Brazilian Semiarid A B S T R A C TRemote sensing can be used for environmental monitoring of micrometeorological biophysical parameters in the semiarid regions of Brazil. The present investigation aimed to monitor the risk of environmental degradation by detecting surface changes in the semiarid by means of remote sensing. The research was developed through digital processing of satellite images for Serra Talhada, Pernambuco, Brazil. Surface data were collected to support the Surface Energy Balance algorithm (SEBAL) to estimate the albedo and the surface temperatures as well as the soil condition adjusted to the vegetation index (SAVI). Furthermore, thematic maps were developed for the levels of risk of degradation and statistical evaluation was performed on the thematic quality by means of confounding matrix. The SAVI was sensitive to precipitation, displaying the highest values for the rainy season and the lowest for the dry season, for which the albedo and the surface temperature presented higher values, thus indicating vulnerability to degradation in areas of scarce vegetation and exposed soil. The risk of degradation maps highlighted characteristics similar to SAVI response patterns, albedo and surface temperature. The spatiotemporal monitoring of biophysical parameters and the risk of degradation will enable both the planning and the management of water and natural resources in the semiarid region.Keywords: Agrometeorology, Caatinga, Environmental Degradation, Deforestation; Environmental Impacts.

scholarly journals Thermal Remote Sensing: A tool to Determine Temporal Land Surface Temperature in Hawassa City, Ethiopia

2020 ◽  
Author(s):  
Mikias Biazen Molla
Keyword(s):  
Remote Sensing ◽  
Standard Deviation ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Urban Expansion ◽  
Landsat 8 ◽  
Landsat 8 Oli ◽  
Thermal Remote Sensing ◽  
The City

Abstract This investigation was conducted for the estimation of the temporal land surface temperature value using thermal remote sensing of Landsat-8 (OLI) Data in Hawassa City Administration, Ethiopia. Satellite datasets of Landsat-7 (ETM+) for 22nd March 2002 and Landsat-8 (OLI) of 22nd March 2019 were taken for this study. Different algorisms were used to estimate the Normalized Difference Vegetation Index threshold from the Red and Near-Infrared band and the ground earth's surface emissivity esteem is legitimately recovered from the thermal infrared by coordinating with the outcome got from MODIS information. The land use land cover map of the city was prepared with better accuracy using the on-screen classification technique. The spatial distribution of surface temperature of the city range from 6.62°C to 22.54°C with a mean of 14.58°C and a standard deviation of 11.25 in the year of march 22nd 2002. The LST result derived from Landsat 8 for March 22nd, 2019, ranges from 11.97°C to 35.5°C with a mean of 23.735 °C and a standard deviation of 16.64. In both years the higher LST values correspond to built-up/settlement and bare/open lands of the city; whereas, lower LST values were observed in vegetation (trees/woodlot, shrubs, and grass forested) area. Urban expansion (built-up area roads, and another impervious surface), decline in vegetation levels due to deforestation and increasing population density. Increasing an evergreen tree and green space coverage, design and develop city parks and rehabilitate the existing degraded natural environments are among the recommended strategy to reduce the rate of LST.

scholarly journals Retrieval of Land Surface Temperature of Lahore Through Landsat-8 TIRS Data

2019 ◽  
Vol 10 (1) ◽  
pp. 70-77
Author(s):  
Muhammad Nasar -u-Minallah
Keyword(s):  
Radiative Transfer ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Vegetation Cover ◽  
Land Surface ◽  
Global Climate ◽  
Spectral Radiance ◽  
Landsat 8 ◽  
Barren Land ◽  
Data Continuity

Land surface temperature (LST) is an important parameter in global climate change and urban thermalenvironmental studies. The significance of land surface temperature is being acknowledged gradually and interest isincreasing in developing methodologies for the retrieval of LST from Satellite Remote Sensing (SRS) data. ThermalInfrared Sensor (TIRS) of Landsat-8 is the newest TIR sensor for the Landsat Data Continuity Mission (LDCM),offering two adjacent thermal infrared bands (10, 11), having significant beneficiary for the land surface temperatureinversion. The spectral radiance can be estimated through TIR bands 10 and 11 of Landsat-8 OLI_TIRS satellite image.In the present study, the radiative transfer equation-based method has been employed in estimating LST of Lahore andthe analysis demonstrated that estimated LST has the highest accuracy from the radiative transfer method through band10. Land Surface Emissivity (LSE) was derived with the aid of the NDVI’s threshold technique. The present studyresults show that as the built-up area increases and vegetation cover decreases in urban surface, they are linked toincrease in urban land surface temperature and conversely larger vegetation cover associated with lower urbantemperature. The output exposed that LST was high in built-up and barren land, whereas it was low in the area wherethere were more vegetation cover and water.

scholarly journals Analisis Heat Island pada Perkebunan Kelapa Sawit: Studi Kasus di Kabupaten Kayong Utara, Kalimantan Barat

2020 ◽  
Vol 8 (2) ◽  
pp. 106-115
Author(s):  
Nurul Ihsan Fawzi ◽  
Marindah Yulia Iswari
Keyword(s):  
Remote Sensing ◽  
Surface Temperature ◽  
Palm Oil ◽  
Secondary Forest ◽  
Remote Sensing Data ◽  
Primary Forest ◽  
Landsat 8 ◽  
Heat Island ◽  
Local Climate ◽  
Island Effect

Between 2000 – 2017, 3.06 million hectares of primary forest in Kalimantan have been converted into palm oil plantation. This change impacts local climate changes. This study aims is to analyze the heat island in palm oil plantation. The analytical method used surface temperature estimation through remote sensing and zonal statistics. The remote sensing data that are used is Landsat 8 images acquired on 15 July 2018 and 3 August 2019. From this research, we found that young palm oil plantations have an average IHI value of 2.1 ± 1.7oC in 2018 and 1.7 ± 1.4oC in 2019. The IHI value is close to the heat island in a built-up area. IHI for mature palm oil plantation (11-12 years) created a cool island with an intensity close to secondary forest. The decreasing value of IHI for 2018 and 2019 in palm oil plantations is due to the growth of palm oil trees, which decreases surface temperature. The implication of this research is to know heat island effect due to deforestation or land cover changes, especially change into palm oil plantations.

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