scholarly journals Jurnal Penginderaan Jauh Dan Pengolahan Data Citra Digital (JPJDDD) Periode 2016-2020: Sebuah Analisis Bibliometrik

2021 ◽  
Vol 2 (1) ◽  
pp. 49-60
Author(s):  
Rochani Nani Rahayu
Keyword(s):  
Remote Sensing ◽  
Bibliometric Analysis ◽  
Landsat 8 ◽  
Research Topics ◽  
Data Source ◽  
Female Writers ◽  
The City

Abstract Bibliometric analysis was carried out on the Jurnal Penginderaan Jauh Dan Pengolahan Data Digital (JPJPDCD) 2016-2020, to find out: 1) published articles; 2) authorship patterns; 3) Degree of collaboration; 4) The gender of the author; 5) The most productive writer; 6) Author's institution; 7) The author's city of work, 8) Research topics. The data source used is accessed from http://jurnal.lapan.go.id/index.php/jurnal_inderaja. The research objective variables were recorded. The results showed that 57 articles were published by 179 authors. There are 9 individually written articles, and 48 collaborative articles. The degree of collaboration is 0.84. 117 male authors and 62 female writers. Bogor Agricultural University (IPB) appeared 11 times, and LAPAN appeared 127 times. DKI appeared 136 times, followed by Bogor 11 times and Yogyakarta 9 times. A total of 259 keywords have been used. Remote sensing is a keyword that appears 9 times, Landsat 8 appears 7 times, Dissemination, Landsat, Mangrove and Hyperspectral each appear 3 times. It was concluded that there were more articles written in collaboration than articles written individually. Male writers are more dominant than women. Sartono Marpaung (LAPAN) is the most productive writer with 5 titles. Ten universities and 7 agencies disseminate articles through JPJPDD. IPB and LAPAN are the biggest contributors. DKI is the city where the most researchers work. Most research topics are related to remote sensing. Abstrak Dilalukan analisis bibliometrik terhadap Jurnal Penginderaan Jauh Dan Pengolahan Data Citra Digital (JPJPDCD) 2016-2020, untuk mengetahui: 1) Artikel yang dipublikasikan ; 2) Pola kepengarangan; 3) Derajat kolaborasi; 4) Jenis kelamin penulis; 5) Penulis terproduktif; 6) Institusi penulis;7) Kota penulis bekerja, 8) Topik penelitian.  Sumber data yang digunakan diakses dari  http://jurnal.lapan.go.id/index.php/jurnal_inderaja. Dilakukan pencatatan terhadap variabel tujuan penelitian. Hasil penelitian menunjukkan bahwa diterbitkan 57 artikel oleh 179 penulis. Artikel yang ditulis secara individu berjumlah 9 judul, dan  yang ditulis secara kolaborasi sebanyak 48 judul. Derajat kolaborasi adalah 0,84. Penulis laki-laki 117 orang, dan penulis perempuan 62 orang. Institut Pertanian Bogor  (IPB) muncul  11 kali, dan LAPAN muncul 127 kali. DKI muncul 136 kali, diikuti Bogor 11 kali dan Yogyakarta 9 kali. Sebanyak 259 kata kunci telah digunakan. Remote sensing merupakan kata kunci yang muncul sebanyak 9 kali,  Landsat 8 muncul  7 kali, Dissemination, Landsat, Mangrove dan Hyperspectral masing-masing muncul 3 kali. Disimpulkan bahwa artikel yang ditulis berkolaborasi lebih banyak dibandingkan artikel yang ditulis individual. Penulis laki-laki lebih dominan dari perempuan. Sartono Marpaung (LAPAN) merupakan penulis terproduktif dengan tulisan 5 judul. Sepuluh perguruan tinggi dan 7 instansi  mendiseminasikan artikel melalui JPJPDD. IPB dan LAPAN merupakan kontributor terbanyak. DKI merupakan kota tempat bekerja peneliti terbanyak. Topik penelitian terbanyak adalah yang berkaitan dengan remote sensing.

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 Rapid remote sensing assessment of landscape-scale impacts from the California Camp Fire

2019 ◽  
Author(s):  
Jeffrey Chambers ◽  
Caralyn Gorman ◽  
Yanlei Feng ◽  
Margaret Torn ◽  
Jared Stapp
Keyword(s):  
Remote Sensing ◽  
Fire Spread ◽  
Early Morning ◽  
Landsat 8 ◽  
Spread Rate ◽  
Additional Information ◽  
Regional Impacts ◽  
Rapid Spread ◽  
Surrounding Landscape ◽  
The City

The Camp Fire rapidly spread across a landscape in Butte County, California, toward the city of Paradise in the early morning hours of 8 November 2018. Here we provide a set of initial tools and analyses that are useful to a variety of stakeholders, including: (1) a visualization app for GOES 16 data and the surrounding landscape showing the rapid spread of the fire from 6:37-10:47 a.m. local time; (2) processed Landsat 8 images for before, during, and after the fire, along with a tool for visualizing regional impacts; (3) a timeline of fire spread from ignition over the first four hours; and (4) a description of a potential early warning app that could make use of existing data, visualization, and analysis tools, to provide additional information for effective evacuation of communities threatened by rapidly moving wildfires. Using these tools we estimate that, over the first hour, the Camp Fire was consuming ~200 ha/minute of vegetation with a linear spread rate of 14 km over the fire’s first 25 minutes, or ~33km/hr. We briefly discuss broader use of remote sensing and geospatial analysis for fire research and risk management.

The Earth’s surface remote sensing methods used to explore heat islands in the city of Tyumen

2021 ◽  
Vol 977 (11) ◽  
pp. 40-50
Author(s):  
I.D. Akhmedova ◽  
L.D. Sulkarnaeva ◽  
N.V. Zherebyatieva ◽  
A.V. Petukhova
Keyword(s):  
Remote Sensing ◽  
Satellite Data ◽  
Landsat 8 ◽  
Heat Island ◽  
Heat Islands ◽  
Four Seasons ◽  
Remote Sensing Methods ◽  
The City

The authors present the results of mapping the “heat island” surface in the city of Tyumen and determining its spatial and seasonal manifestations using the Landsat-8 satellite data. Geothermic scenes of four seasons were obtained and analyzed

scholarly journals Rapid remote sensing assessment of landscape-scale impacts from the California Camp Fire

2019 ◽  
Author(s):  
Jeffrey Chambers ◽  
Caralyn Gorman ◽  
Yanlei Feng ◽  
Margaret Torn ◽  
Jared Stapp
Keyword(s):  
Remote Sensing ◽  
Fire Spread ◽  
Early Morning ◽  
Landsat 8 ◽  
Spread Rate ◽  
Additional Information ◽  
Regional Impacts ◽  
Rapid Spread ◽  
Surrounding Landscape ◽  
The City

The Camp Fire rapidly spread across a landscape in Butte County, California, toward the city of Paradise in the early morning hours of 8 November 2018. Here we provide a set of initial tools and analyses that are useful to a variety of stakeholders, including: (1) a visualization app for GOES 16 data and the surrounding landscape showing the rapid spread of the fire from 6:37-10:47 a.m. local time; (2) processed Landsat 8 images for before, during, and after the fire, along with a tool for visualizing regional impacts; (3) a timeline of fire spread from ignition over the first four hours; and (4) a description of a potential early warning app that could make use of existing data, visualization, and analysis tools, to provide additional information for effective evacuation of communities threatened by rapidly moving wildfires. Using these tools we estimate that, over the first hour, the Camp Fire was consuming ~200 ha/minute of vegetation with a linear spread rate of 14 km over the fire’s first 25 minutes, or ~33km/hr. We briefly discuss broader use of remote sensing and geospatial analysis for fire research and risk management.

scholarly journals Análise multitemporal de uso, ocupação e cobertura da terra na zona Leste da cidade de Caxias/Maranhão/Brasil

2021 ◽  
Vol 14 (3) ◽  
pp. 1415
Author(s):  
Patricia Barbosa Pereira ◽  
Hikaro Kayo de Brito Nunes ◽  
Francisco De Assis da Silva Araújo
Keyword(s):  
Remote Sensing ◽  
Land Cover ◽  
Urban Area ◽  
Thematic Mapper ◽  
Landsat 8 ◽  
Landsat 8 Oli ◽  
Land Occupation ◽  
Multi Temporal ◽  
Landsat 5 Tm ◽  
The City

Com o avanço da quantidade de habitantes no espaço urbano surgem novas formas de modificações no ambiente, e, assim, há o favorecimento da intensificação do processo de antropização, como a supressão da cobertura vegetal, a descaracterização do relevo e danos aos cursos d’água. Frente a isso, o objetivo deste estudo é analisar e quantificar, em escala multitemporal, a dinâmica de uso, ocupação e cobertura da terra da cidade de Caxias/MA com foco na zona Leste por meio de ferramentas obtidas junto ao Sensoriamento Remoto. A metodologia utilizada foi pesquisa bibliográfica, documental e cartográfica. Os mapas temáticos foram confeccionados através da interpretação de imagens obtidas dos satélites Landsat 5 TM (Thematic Mapper) para o ano de 2000 e o Landsat 8 OLI (Operational Land Imager) para 2017, por meio do plugin SCP (Semi-Automatic Classification) do software QGIS 2.18.8. Com os resultados obtidos, constatou-se que, a vegetação secundária continuou representando a maior área, apesar da área urbana ter crescido (de 33% a 35%). Isso é caraterizado devido à grande área verde no bairro Pai Geraldo e no bairro Baixinha onde está localizada uma fazenda. Diante dos dados e com as etapas de sensoriamento remoto, de campo e de laboratório, este estudo representou uma análise de uso, ocupação e cobertura da terra ocorrida, onde, a partir dela constatou-se as mais diversas atividades desenvolvidas na área, relacionando, ainda, com distintos riscos e impactos socioambientais. Assim, reforça-se a necessidade de novos estudos e a contribuição do sensoriamento remoto para o alcance dos objetivos.  Analyze multi-temporal the dynamics of use, land occupation and coverage the on east Zone of the city of Caxias/MA/Maranhão/Brazil  A B S T R A C TWith the advancement of the amount of people in the urban area there are new forms of changes in environment, and thus there favoring intensifying anthropization process as suppression of vegetation, the relief adulteration and damage to water courses. Faced with this, the general objective of this study was to analyze in multi-temporal scale, the dynamics of use, land occupation and coverage of the city of Caxias/MA with a focus on east Zone East through tools obtained from the Remote Sensing. The methodology used was literature, documentary and cartographic. Thematic maps were made by interpreting images obtained from the Landsat 5 TM (Thematic Mapper) satellites for the year 2000 and the Landsat 8 OLI (Operational Land Imager) for 2017, using the SCP (Semi-Automatic Classification) plugin of the QGIS software 2.18.8. Through the results obtained, it was found that in the zona Leste secondary vegetation continued to represent the largest area, despite the urban area having grown (from 33% to 35%). It is characterized because of the large green area in the Pai Geraldo district and Baixinha where it is located a farm. In the face and the remote sensing steps, field and laboratory, this study represents an analysis of use, occupation and land cover occurred in two areas of the city of Caxias/MA where, from there it was found the most diverse activities in the area, also with different risks and environmental impacts. Thus, it reinforces the need for further studies and remote sensing to the achievement of goals.Keywords: land cover; remote sensing; East zone; Caxias/MA.

scholarly journals Determinación de la temperatura de la superficie terrestre mediante imágenes Landsat 8: Estudio comparativo de algoritmos sobre la ciudad de Granada

2021 ◽  
pp. 1
Author(s):  
David Hidalgo-García
Keyword(s):  
Land Surface ◽  
Single Channel ◽  
Geographical Location ◽  
Landsat 8 ◽  
Ambient Temperatures ◽  
Analysis Process ◽  
High Pollution ◽  
Data Source ◽  
Error Bias ◽  
The City

<p>The use of satellite images has become, in recent decades, one of the most common ways to determine the Land Surface Temperature (LST). One of them is through the use of Landsat 8 images that requires the use of single-channel (MC) and two-channel (BC) algorithms. In this study, the LST of a medium-sized city, Granada (Spain) has been determined over a year by using five Landsat 8 algorithms that are subsequently compared with ambient temperatures. Few studies compare the data source with the seasonal variations of the same metropolis, which together with its geographical location, high pollution and the significant thermal variations it experiences make it a suitable place for the development of this research. As a result of the statistical analysis process, the regression coefficients R<sup>2</sup>, mean square error (RMSE), mean error bias (MBE) and standard deviation (SD) were obtained. The average results obtained reveal that the LST derived from the BC algorithms (1.0 °C) are the closest to the ambient temperatures in contrast to the MC (-5.6 °C), although important variations have been verified between the different zones of the city according to its coverage and seasonal periods. Therefore, it is concluded that the BC algorithms are the most suitable for recovering the LST of the city under study.</p>

scholarly journals ESTIMATIVA DE ÍNDICE DE QUALIDADE AMBIENTAL DA CIDADE DE UBERLÂNDIA POR MEIO DE IMAGENS DE SATÉLITE

2020 ◽  
Vol 16 (01) ◽  
pp. 59-74
Author(s):  
Dayanne Vieira de Oliveira ◽  
Lisbeth Segovia Materano ◽  
Jorge Luís Silva Brito
Keyword(s):  
Remote Sensing ◽  
Surface Temperature ◽  
Environmental Quality ◽  
Vegetation Index ◽  
Environmental Indicators ◽  
Landsat 8 ◽  
Toma De Decisiones ◽  
Para Determinar ◽  
Sentinel 2A ◽  
The City

O uso das geotecnologias e suas aplicações com o uso do Sensoriamento Remoto e dos SIG contribuem para o avanço no conhecimento da dinâmica da paisagem, sendo uma ótima ferramenta devido a aspectos de fácil visualização e rapidez para auxiliar na tomada de decisões. O presente trabalho tem o objetivo de testar um método de estimativa da qualidade ambiental usando quatro indicadores ambientais derivados de imagens de satélite na cidade de Uberlândia/MG: TS, NDVI, SAVI e NSI. Para isto foram utilizados para determinar a TS uma imagem do satélite Landsat8, correlacionado com índices de vegetação NDVI, SAVI e NSI obtidos a partir de imagens Sentinel-2A processados no ILWIS versão 3.4. Os resultados mostraram que NDVI e SAVI estão correlacionados um com o outro e correspondem com a quantidade de vegetação, enquanto NSI e TS são correlacionados com as áreas de maior proporção de área construída. Embora a qualidade ambiental seja determinada por um grande número de variáveis, os dados obtidos nas imagens de satélite mostraram-se eficaz na estimativa da qualidade ambiental, sendo uma importante ferramenta de rápido acesso para obter informações espaço-temporal dos fatores ambientais urbanos e contribuir para o planejamento e aplicação das políticas públicas. Palavras-chave: Qualidade Ambiental. Índices de vegetação. Temperatura superficial. Sensoriamento Remoto.   ESTIMATION OF THE ENVIRONMENTAL QUALITY INDEX OF THE CITY OF UBERLÂNDIA USING REMOTE SENSING ABSTRACT The use of geotechnologies and their applications with remote sensing and geographic information systems (GIS) have been widely used in recent years and contribute much to the advance in the knowledge of the landscape dynamics, being an excellent tool due to the aspects of easy visualization and speed to aid in decision making. In this context, the present work aims to develop and test a method for estimating environmental quality using four environmental indicators derived from satellite images for the city of Uberlândia/MG: TS (Surface Temperature), NDVI (Vegetation Difference Index Normalized), SAVI (Soil-Adjusted Vegetation Index) and NSI (Normalized Soil Difference Index). For this purpose, an image of the Landsat 8 satellite was used to determine the TS, correlating with the NDVI, SAVI and NSI indices obtained from a Sentinel-2A image, processed in the GIS ILWIS 3.4. The results show that NDVI and SAVI are correlated with each other, while NSI and TS are correlated with areas of higher anthropic construction. Although the environmental quality is determined by a large number of variables, the data obtained through remote sensing show potential in the estimation of environmental quality indices, being a quick access tool to obtain spatio-temporal information of urban environmental factors, contributing to the planning and implementation of public policies. Keywords: Environmental Quality. Vegetation Indexes. Surface Temperature. Remote Sensing.   ESTIMACIÓN DEL ÍNDICE DE CALIDAD AMBIENTAL DE LA CIUDAD DE UBERLÂNDIA POR MEIO DE IMÁGENES SATELITALES RESUMEN El uso de geotecnologias y sus aplicaciones con la teledetección y los sistemas de información geográfica han sido muy utilizados en los últimos años y contribuyen para el avance en el conocimiento de la dinámica del paisaje, siendo una optima herramienta debido a los aspectos de fácil visualización y rapidez para auxiliar en la toma de decisiones. En este contexto, el presente trabajo tiene como objetivo, desarrollar y probar un método de estimación de calidad ambiental usando cuatro indicadores ambientales derivados de imágenes satelitales para la cuidad de Uberlândia/MG:TS (Temperatura superficial), NDVI (Índice de Vegetación de Diferencia Normalizada), SAVI (Índice de Vegetación Ajustado al Suelo) y NSI (Índice de Diferencia Normalizada de Suelo). Para esto fueron utilizados para determinar la TS una imagen del satélite Landsat 8, correlacionando con los Índices NDVI, SAVI y NSI obtenidos de una imagen del Sentinel-2A, procesados en el SIG ILWIS 3.4. Los resultados muestran que NDVI y SAVI están correlacionados uno con el otro, en tanto NSI y TS son correlacionados con las áreas de mayor proporción construcción antrópica. A pesar de que la calidad ambiental sea determinada por un gran número de variables, los datos obtenidos mediante teledetección muestran potencialidad en la estimación de índices de calidad ambiental, siendo una herramienta de rápido acceso para obtener informaciones espacio-temporales de los factores ambientales urbanos, pudiendo contribuir a la planificación y aplicación de las políticas públicas. Palabras clave: Calidad Ambiental. Índices de Vegetación. Temperatura Superficial. Teledetección.

Landscape Change in the Steppe of Algeria South-West Using Remote Sensing

2018 ◽  
Vol 18 (1) ◽  
pp. 41-52
Author(s):  
Tayeb Sitayeb ◽  
Ishak Belabbes
Keyword(s):  
Remote Sensing ◽  
Social Systems ◽  
Bare Soil ◽  
Climatic Conditions ◽  
Landscape Dynamics ◽  
Landsat 8 ◽  
Natural Ecosystems ◽  
Stipa Tenacissima ◽  
Steppe Species ◽  
Sparse Vegetation

Abstract Landscape dynamics is the result of interactions between social systems and the environment, these systems evolving significantly over time. climatic conditions and biophysical phenomena are the main factors of landscape dynamics. Also, currently man is responsible for most changes affecting natural ecosystems. The objective of this work is to study the dynamics of a typical landscape of western Algeria in time and space, and to map the distribution of vegetation groups constitute the vegetation cover of this ecosystem. as well as using a method of monitoring the state of a fragile ecosystem by remote sensing to understand the processes of changes in this area. The steppe constitutes a large arid area, with little relief, covered with low and sparse vegetation. it lies between the annual isohyets of 100 to 400 mm, subjected to a very old human exploitation with an activity of extensive breeding of sheep, goats, and camels. Landsat satellite data were used to mapping vegetation groups in the Mecheria Steppe at a scale of 1: 300,000. Then, a comparison was made between the two maps obtained by a classification of Landsat-8 sensor Operational Land Imager (OLI) acquired on March 18, 2014, and Landsat-5 sensor Thematic Mapper (TM) acquired on April 25, 1987. The results obtained show the main changes affecting the natural distribution of steppe species, a strong change in land occupied by the Stipa tenacissima steppe with 65% of change, this steppe is replaced by Thymelaea microphylla, Salsola vermiculata, lygeum spartum and Peganum harmala steppe. an absence from the steppe Artemisia herba-alba that has also been replaced by the same previous steppes species. The groups with Quercus ilex and Juniperus phoenicea are characterized by a strong regression that was lost 60% of its global surface and transformed by steppe to stipa tenacissima and bare soil.

Random Forest (RF) and Artificial Neural Network (ANN) Algorithms for LULC Mapping

2020 ◽  
Vol 38 (4A) ◽  
pp. 510-514
Author(s):  
Tay H. Shihab ◽  
Amjed N. Al-Hameedawi ◽  
Ammar M. Hamza
Keyword(s):  
Neural Network ◽  
Remote Sensing ◽  
Artificial Neural Network ◽  
Random Forest ◽  
Satellite Image ◽  
Landsat 8 ◽  
Optical Remote Sensing ◽  
Data Set ◽  
Artificial Neural ◽  
Artificial Neural Network Ann

In this paper to make use of complementary potential in the mapping of LULC spatial data is acquired from LandSat 8 OLI sensor images are taken in 2019.  They have been rectified, enhanced and then classified according to Random forest (RF) and artificial neural network (ANN) methods. Optical remote sensing images have been used to get information on the status of LULC classification, and extraction details. The classification of both satellite image types is used to extract features and to analyse LULC of the study area. The results of the classification showed that the artificial neural network method outperforms the random forest method. The required image processing has been made for Optical Remote Sensing Data to be used in LULC mapping, include the geometric correction, Image Enhancements, The overall accuracy when using the ANN methods 0.91 and the kappa accuracy was found 0.89 for the training data set. While the overall accuracy and the kappa accuracy of the test dataset were found 0.89 and 0.87 respectively.

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.

Sign in / Sign up

Export Citation Format

Share Document