Estimation of Aboveground Stand Carbon using Landsat 8 OLI Satellite Image: A Case Study from Turkey

2020 ◽  
pp. 385-403
Author(s):  
Alkan Günlü ◽  
Sedat Keleş ◽  
İlker Ercanli ◽  
Muammer Şenyurt
Keyword(s):  
Satellite Image ◽  
Landsat 8 ◽  
Landsat 8 Oli

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

Making Of Classification Land Cover Through Result Of Visual Data Satellite Image Analysis Landsat 8 OLI : Case Study in Tapaktuan District, South Aceh District

2021 ◽  
Vol 6 (1) ◽  
pp. 59-65
Author(s):  
Safridatul Audah ◽  
Muharratul Mina Rizky ◽  
Lindawati
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Image Classification ◽  
Satellite Image ◽  
Landsat 8 ◽  
Landsat 8 Oli ◽  
Sensing Technology ◽  
Open Land ◽  
Cover Class ◽  
Satellite Image Analysis

Tapaktuan is the capital and administrative center of South Aceh Regency, which is a sub-district level city area known as Naga City. Tapaktuan is designated as a sub-district to be used for the expansion of the capital's land. Consideration of land suitability is needed so that the development of settlements in Tapaktuan District is directed. The purpose of this study is to determine the level of land use change from 2014 to 2018 by using remote sensing technology in the form of Landsat-8 OLI satellite data through image classification methods by determining the training area of the image which then automatically categorizes all pixels in the image into land cover class. The results obtained are the results of the two image classification tests stating the accuracy of the interpretation of more than 80% and the results of the classification of land cover divided into seven forms of land use, namely plantations, forests, settlements, open land, and clouds. From these classes, the area of land cover change in Tapaktuan is increasing in size from year to year.

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 Estimation of PM10 Distribution using Landsat5 and Landsat8 Remote Sensing

Proceedings ◽  
2018 ◽  
Vol 2 (23) ◽  
pp. 1430
Author(s):  
V. M. Fernández-Pacheco ◽  
C. A. López-Sánchez ◽  
E. Álvarez-Álvarez ◽  
M. J. Suárez López ◽  
L. García-Expósito ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Air Pollutants ◽  
Satellite Images ◽  
Satellite Image ◽  
Remote Sensing Image ◽  
Regional Studies ◽  
Landsat 8 ◽  
Landsat 8 Oli ◽  
Landsat 5 Tm ◽  
Source Of Information

Air pollution is one of the major environmental problems, especially in industrial and highly populated areas. Remote sensing image is a rich source of information with many uses. This paper is focused on estimation of air pollutants using Landsat-5 TM and Landsat-8 OLI satellite images. Particulate Matter with particle size less than 10 microns (PM10) is estimated for the study area of Principado de Asturias (Spain). When a satellite records the radiance of the surface received at sensor, does not represent the true radiance of the surface. A noise caused by Aerosol and Particulate Matters attenuate that radiance. In many applications of remote sensing, that noise called path radiance is removed during pre-processing. Instead, path radiance was used to estimate the PM10 concentration in the air. A relationship between the path radiance and PM10 measurements from ground stations has been established using Random Forest (RF) algorithm and a PM10 map was generated for the study area. The results show that PM10 estimation through satellite image is an efficient technique and it is suitable for local and regional studies.

scholarly journals NDVI Based Assessment of Land Cover Changes Using Remote Sensing and GIS (A case study of Srinagar district, Kashmir)

2020 ◽  
Author(s):  
Perminder Singh ◽  
Ovais Javeed
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Urban Areas ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Satellite Image ◽  
Spectral Signature ◽  
Landsat 8 ◽  
Thematic Mapping

Normalized Difference Vegetation Index (NDVI) is an index of greenness or photosynthetic activity in a plant. It is a technique of obtaining  various features based upon their spectral signature  such as vegetation index, land cover classification, urban areas and remaining areas presented in the image. The NDVI differencing method using Landsat thematic mapping images and Landsat oli  was implemented to assess the chane in vegetation cover from 2001to 2017. In the present study, Landsat TM images of 2001 and landsat 8 of 2017 were used to extract NDVI values. The NDVI values calculated from the satellite image of the year 2001 ranges from 0.62 to -0.41 and that of the year 2017 shows a significant change across the whole region and its value ranges from 0.53 to -0.10 based upon their spectral signature .This technique is also  used for the mapping of changes in land use  and land cover.  NDVI method is applied according to its characteristic like vegetation at different NDVI threshold values such as -0.1, -0.09, 0.14, 0.06, 0.28, 0.35, and 0.5. The NDVI values were initially computed using the Natural Breaks (Jenks) method to classify NDVI map. Results confirmed that the area without vegetation, such as water bodies, as well as built up areas and barren lands, increased from 35 % in 2001 to 39.67 % in 2017.Key words: Normalized Difference Vegetation Index,land use/landcover, spectral signature 

scholarly journals Possibility for Identifying/Extracting Rock Outcrop Using Landsat 8 OLI/TIRS - Case Study of Thua Thien Hue Province

2020 ◽  
Vol 36 (3) ◽  
Author(s):  
Nguyen Quang Tuan ◽  
Do Thi Viet Huong ◽  
Doan Ngoc Nguyen Phong ◽  
Nguyen Dinh Van
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Satellite Image ◽  
Object Orientation ◽  
Image Method ◽  
Landsat 8 ◽  
Landsat 8 Oli ◽  
Kappa Index ◽  
Exposed Rock ◽  
Ratio Image

This paper approaches the ratio image method to extract the exposed rock information from the Landsat 8 OLI/TIRS satellite image (2019) according to the object orientation classification. Combining automatic interpretation and interpretation through threshold of image index values according to interpretation key the object orientation classification to separate soil object containing exposed rock and no exposed rock in Thua Thien Hue province. Using the Topsoil Grain Size Index (TGSI), the Normalized Difference Vegetation Index (NDVI), the Normalized Difference Built-up Index (NDBI) and other related analytical problems have identified 40 exposed rock storage areas in the study area. The results have been verified in the field and the Kappa index is 85.10%.

scholarly journals Preliminary Study of Total Suspended Solid Distribution in Coastal Ujung Pangkah Gresik Based Reflectance Value of Landsat Satellite Imagery

2019 ◽  
Vol 51 (1) ◽  
pp. 42
Author(s):  
Hendrata Wibisana ◽  
Bangun Muljo Soekotjo ◽  
Umboro Lasminto
Keyword(s):  
Satellite Image ◽  
Image Data ◽  
Total Suspended Solid ◽  
Suspended Solid ◽  
Landsat 8 ◽  
Time Period ◽  
Satellite Image Data ◽  
Landsat Satellite ◽  
Solid Distribution

Total suspended solid (TSS) is one of the parameters that uses for detecting health in aquatic environments. The distribution of the TSS value in the water body will affect the aquatic ecosystem. In this research will be analyzed the distribution value of TSS during 5 year period by utilizing Landsat 8 satellite image data, where the developed method is extraction of reflectance value from Landsat 8 satellite image for 5 years using SEADASS and then compiled the TSS algorithm with reflectance value that already obtained on the existing conditions, the algorithm obtained is estimated over 5 years back to get a picture of change and distribution of TSS value. As a case study , the coast of Ujung Pangkah Gresik was taken which has the mouth of the river Bengawan Solo. The results obtained from this study illustrate the decrease of TSS value during that time period, so that with this decrease can be concluded that at the point of field coordinate, TSS value was decreasing and causing the erosion in the environment.

scholarly journals Determining PM10 Model in Hanoi Using Landsat 8 Oli and Ground-measured Dust Data

2018 ◽  
Vol 34 (1) ◽  
Author(s):  
Nguyen Nhu Hung ◽  
Tran Van Anh ◽  
Pham Quang Vinh ◽  
Nguyen Thanh Binh ◽  
Vu Van Hoang
Keyword(s):  
Air Pollutants ◽  
Satellite Image ◽  
Calculated Data ◽  
Regression Function ◽  
Measured Data ◽  
Landsat 8 ◽  
Mean Square ◽  
Correlation Model ◽  
Landsat 8 Oli

PM10 (Particulate matter 10 is a dust with aerodynamic diameters of 0.001 ÷ 10μm) is one of the air pollutants affecting human health. In this study, we conducted a modeling study to identify PM10 dust in the air by using Landsat 8 OLI satellite image, along with PM10 ground-measured data using the machine DustTrak II . Conduct regression analysis to determine the correlation model. Here, we used 16 in-situ measurement points. In that, 10 points were used to determine the regression function and 6 other points were used to test the regression model. Results were evaluated based on correlation coefficient (R) and Root Mean Square Error (RMSE) between measured and calculated data.

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