scholarly journals Spatiotemporal Built-up Land Density Mapping Using Various Spectral Indices in Landsat-7 ETM+ and Landsat-8 OLI/TIRS (Case Study: Surakarta City)

2017 ◽  
Vol 98 ◽  
pp. 012006
Author(s):  
Yanuar S Risky ◽  
Yogi H Aulia ◽  
Prima Widayani
Keyword(s):  
Landsat 8 ◽  
Spectral Indices ◽  
Landsat 8 Oli ◽  
Density Mapping ◽  
Landsat 7

Delineation of burned arid landscapes using Landsat 8 OLI data: a case study of Karaganda region in Kazakhstan

2021 ◽  
pp. 1-16
Author(s):  
Andrey Karpachevskiy ◽  
Sergey Lednev ◽  
Ivan Semenkov ◽  
Anna Sharapova ◽  
Sultan Nagiyev ◽  
...  
Keyword(s):  
Landsat 8 ◽  
Landsat 8 Oli ◽  
Arid Landscapes ◽  
Karaganda Region

scholarly journals Mapping forest height using photon-counting LiDAR data and Landsat 8 OLI data: A case study in Virginia and North Carolina, USA

2020 ◽  
Vol 114 ◽  
pp. 106287
Author(s):  
Xiaoxiao Zhu ◽  
Cheng Wang ◽  
Sheng Nie ◽  
Feifei Pan ◽  
Xiaohuan Xi ◽  
...  
Keyword(s):  
North Carolina ◽  
Photon Counting ◽  
Lidar Data ◽  
Landsat 8 ◽  
Landsat 8 Oli ◽  
Forest Height

scholarly journals Integrating Landsat 7 and 8 data to improve basalt formation classification: A case study at Buon Ma Thuot region, Central Highland, Vietnam

2019 ◽  
Vol 11 (1) ◽  
pp. 901-917
Author(s):  
Ngo Van Liem ◽  
Dang Van Bao ◽  
Dang Kinh Bac ◽  
Nguyen Hieu ◽  
Do Trung Hieu ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Spectral Band ◽  
Landsat 8 ◽  
Central Highland ◽  
Band Ratios ◽  
Landsat 7 ◽  
Cenozoic Basalt ◽  
Geological Map ◽  
Geological Formations

Abstract Cenozoic basalt regions contain various natural resources that can be used for socio-economic development. Different quantitative and qualitative methods have been applied to understand the geological and geomorphological characteristics of basalt formations. Nowadays the integration of remote sensing and geographic information systems (GIS) has become a powerful method to distinguish geological formations. In this paper, authors combined satellite and fieldwork data to analyze the structure and morphology of highland geological formations in order to distinguish two main volcanic eruption episodes. Based on remote sensing analysis in this study, different spectral band ratios were generated to select the best one for basalt classification. Lastly, two spectral combinations (including band ratios 4/3, 6/2, 7/4 in Landsat 8 and 3/2, 5/1, 7/3 in Landsat 7) were chosen for the Maximum Likelihood classification. The final geological map based on the integration of Landsat 7 and 8 outcomes shows precisely the boundary of the basalt formations with the accuracy up to 93.7%. This outcome contributed significantly to the correction of geological maps. In further studies, authors suggest the integration of Landsat 7 and 8 data in geological studies and natural resource and environmental management at both local and regional scales.

scholarly journals DINÂMICA DO VOLUME, BIOMASSA E CARBONO NA MATA ATLÂNTICA POR FERRAMENTA DE DETECÇÃO DE MUDANÇAS

Nativa ◽  
2019 ◽  
Vol 7 (4) ◽  
pp. 437
Author(s):  
Ayrton Machado ◽  
Ana Paula Marques Martins ◽  
Carlos Roberto Sanquetta ◽  
Ana Paula Dalla Corte ◽  
Jaime Wojciechowski ◽  
...  
Keyword(s):  
River Basin ◽  
Atlantic Forest ◽  
Landsat 8 ◽  
South American ◽  
Landsat 8 Oli ◽  
Mata Atlântica ◽  
Landsat 7 ◽  
Mata Atlantica ◽  
Year 2000 ◽  
Iguaçu River

A Mata Atlântica é reconhecida internacionalmente como uma das maiores e mais importantes florestas tropicais do continente sul-americano e além de sua importância para a biodiversidade, esse Bioma exerce importante função no ciclo de carbono. O objetivo deste trabalho foi desenvolver e aplicar uma rotina de detecção de mudanças dos estoques de volume, biomassa e carbono de 2000 a 2015 na Bacia do Rio Iguaçu, Estado do Paraná. Foram utilizadas imagens Landsat-7 ETM+ para o ano 2000 e Landsat-8 OLI para o ano de 2015 totalizando dez cenas para cada período. Foi desenvolvido uma rotina em Python e implementado no Software ArcGIS 10.4 para realizar a automatização de um processo de cálculo de estimativa de volume, biomassa e carbono para os remanescentes de vegetação natural. Houve acréscimo de 15,21% em volume, 14,95% em biomassa, 14,96% em carbono não considerando os estágios sucessionais nem subdivisão por fitofisionomia na bacia do Rio Iguaçu.  Desta forma, concluiu-se que a região de estudo está colaborando de forma positiva para a remoção de dióxido de carbono da atmosfera.Palavras-chave: bacia do rio Iguaçu; mudanças climáticas; sequestro de carbono. DYNAMICS OF VOLUME, BIOMASS AND CARBON IN THE ATLANTIC FOREST BY A CHANGE DETECTION TOOL ABSTRACT: The Atlantic Forest is recognized internationally as one of the largest and most important tropical forests in the South American continent and besides its importance for biodiversity, this biome plays important role in the carbon cycle. The objective of this work was to develop and apply a routine of detection of changes in volume, biomass and carbon stocks from 2000 to 2015 in the Iguaçu River Basin, State of Paraná. They were used Landsat-7 ETM+ images for the year 2000 and Landsat-8 OLI images for the year 2015 totaling ten images for each period. A routine was developed in Python and implemented in ArcGIS 10.4 Software to perform the automation of a calculation process of volume, biomass and carbon estimation for the remnants of natural vegetation. There was an increase of 15.21% in volume, 14.95% in biomass, 14.96% in carbon, not considering successional stages nor subdivision by phytophysiognomy in the Iguaçu River basin. Thus concludes that the region of study is collaborating in a positive way for the removal of carbon dioxide from the atmosphere.Keywords: Iguaçu river basin; climate changes; carbon sequestration.

scholarly journals Comparison between Landsat 7 Enhanced Thematic Mapper Plus (ETM+) and Landsat 8 Operational Land Imager (OLI) Assessment of Vegetation Indices

2017 ◽  
Vol 1 (2) ◽  
pp. 355-366
Author(s):  
E. O. Makinde ◽  
A. D. Obigha
Keyword(s):  
Statistical Analysis ◽  
Land Cover ◽  
Vegetation Index ◽  
Vegetation Indices ◽  
Thematic Mapper ◽  
Landsat 8 ◽  
Landsat 8 Oli ◽  
Water Index ◽  
Landsat 7 ◽  
Index 2

The Landsat system has contributed significantly to the understanding of the Earth observation for over forty years. Since May 2013, data from Landsat 8 has been available online for download, with substantial differences from its predecessors, having an extended number of spectral bands and narrower bandwidths. The objectives of this research were majorly to carry out a cross comparison analysis between vegetation indices derived from Landsat 7 Enhanced Thematic Mapper Plus (ETM+) and Landsat 8 Operational Land Imager (OLI) and also performed statistical analysis on the results derived from the vegetation indices. Also, this research carried out a change detection on four land cover classes present within the study area, as well as projected the land cover for year 2030. The methods applied in this research include, carrying out image classification on the Landsat imageries acquired between 1984 – 2016 to ascertain the changes in the land cover types, calculated the mean values of differenced vegetation indices derived from the four land covers between Landsat 7 ETM+ and Landsat 8 OLI. Statistical analysis involving regression and correlation analysis were also carried out on the vegetation indices derived between the two sensors, as well as scatter plot diagrams with linear regression equation and coefficients of determination (R2). The results showed no noticeable differences between Landsat 7 and Landsat 8 sensors, which demonstrates high similarities. This was observed because Global Environmental Monitoring Index (GEMI), Improved Modified Triangular Vegetation Index 2 (MTVI2), Normalized Burn Ratio (NBR), Normalized Difference Vegetation Index (NDVI), Modified Normalized Difference Water Index (MNDWI), Leaf Area Index (LAI) and Land Surface Water Index (LSWI) had smaller standard deviations. However, Renormalized Difference Vegetation Index (RDVI), Anthocyanin Reflectance Index 1 (ARI1) and Anthocyanin Reflectance Index 2 (ARI2) performed relatively poorly because their standard deviations were high. the correlation analysis of the vegetation indices that both sensors had a very high linear correlation coefficient with R2 greater than 0.99. It was concluded from this research that Landsat 7 ETM+ and Landsat 8 OLI can be used as complimentary data.

scholarly journals ANALYSIS OF RELATIONSHIP BETWEEN URBAN HEAT ISLAND EFFECT AND LAND USE/COVER TYPE USING LANDSAT 7 ETM+ AND LANDSAT 8 OLI IMAGES

2016 ◽  
Vol XLI-B8 ◽  
pp. 821-828
Author(s):  
N. Aslan ◽  
D. Koc-San
Keyword(s):  
Land Use ◽  
Land Surface ◽  
Vegetation Index ◽  
Irrigated Agriculture ◽  
Time Interval ◽  
Landsat 8 ◽  
Landsat 8 Oli ◽  
Landsat Images ◽  
Study Results ◽  
Landsat 7

The main objectives of this study are (i) to calculate Land Surface Temperature (LST) from Landsat imageries, (ii) to determine the UHI effects from Landsat 7 ETM+ (June 5, 2001) and Landsat 8 OLI (June 17, 2014) imageries, (iii) to examine the relationship between LST and different Land Use/Land Cover (LU/LC) types for the years 2001 and 2014. The study is implemented in the central districts of Antalya. Initially, the brightness temperatures are retrieved and the LST values are calculated from Landsat thermal images. Then, the LU/LC maps are created from Landsat pan-sharpened images using Random Forest (RF) classifier. Normalized Difference Vegetation Index (NDVI) image, ASTER Global Digital Elevation Model (GDEM) and DMSP_OLS nighttime lights data are used as auxiliary data during the classification procedure. Finally, UHI effect is determined and the LST values are compared with LU/LC classes. The overall accuracies of RF classification results were computed higher than 88&thinsp;% for both Landsat images. During 13-year time interval, it was observed that the urban and industrial areas were increased significantly. Maximum LST values were detected for dry agriculture, urban, and bareland classes, while minimum LST values were detected for vegetation and irrigated agriculture classes. The UHI effect was computed as 5.6&thinsp;&deg;C for 2001 and 6.8&thinsp;&deg;C for 2014. The validity of the study results were assessed using MODIS/Terra LST and Emissivity data and it was found that there are high correlation between Landsat LST and MODIS LST data (r<sup>2</sup>&thinsp;=&thinsp;0.7 and r<sup>2</sup>&thinsp;=&thinsp;0.9 for 2001 and 2014, respectively).

scholarly journals Spatial Monitoring of Urban Development Direction using Landsat 7 ETM+ and Landsat 8 OLI/TIRS in Balikpapan City, Indonesia

2020 ◽  
Vol 9 (4) ◽  
pp. 2703-2711
Keyword(s):  
Urban Development ◽  
Urban Areas ◽  
Control Function ◽  
Temporal Analysis ◽  
Bare Soil ◽  
Landsat 8 ◽  
Vegetation Density ◽  
Landsat 8 Oli ◽  
Density Class ◽  
Landsat 7

The development of urban areas in the city of Balikpapan increases over time and is characterized by increasing population. The growth and development of urban areas needs to be monitored so that the control function on area spatial can be implemented. This research aims to determine the direction of urban areas and measure the density of the built-up as a leading indicator of the development of urban areas in Balikpapan. The method used in this study is the multispasio-temporal analysis of remote sensing data of Landsat 7 ETM+ and Landsat 8 OLI/TIRS which contain a combination of spectral transformation, classification supervised Maximum Likelihood, accuracy assessment and statistical analysis. The results showed the trend of urban development from 2001 to 2019 towards east and northeast with the highest built-up density located in the sub-district of Balikpapan Tengah by 82.07% and followed by the sub-district of Balikpapan Kota by 76.94%. The largest land conversion took place on the bare soil with low vegetation density class to be vegetation with the converted area of 7095.91 ha or approximately 14.10% followed by the bare soil with low vegetation density class to be built-up with the converted area of 5826.86 ha or about 11.58% of the total area of Balikpapan city during the period from 2001 to 2019. The accuracy of urban development map in 2001 reaches 92.39 % and the year 2019 reaches 95.69 %, while the accuracy of land cover map in 2001 reaches 85.57% and the year 2019 reaches 87.28 %.

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