scholarly journals The use of Landsat 8 remote sensing data for assessing the temperature conditions of the Larus ridibundus L. habitat

2020 ◽  
Vol 9 (4) ◽  
pp. 184-191
Author(s):  
Sergey Arkadyevich Shurakov ◽  
Aleksey Nikolaevich Chashchin
Keyword(s):  
Remote Sensing ◽  
Surface Temperature ◽  
Land Surface ◽  
Satellite Image ◽  
Remote Sensing Data ◽  
Close Correlation ◽  
Primary Data ◽  
Landsat 8 ◽  
Sensing Data ◽  
Temperature Conditions

This paper discusses the possibilities of using Landsat 8 remote sensing data for assessing the temperature conditions of aquatic landscapes when studying the abundance and density of gulls. The study of the ornithological situation was carried out on the territory of the Perm international airport of the Perm Region, where the black-headed gull is an unfavorable factor in the safety of passenger aircraft flights. Within the boundaries of the region, 5 reservoirs were identified. A method for calculating the surface temperature from a multispectral satellite image of the Landsat 8 series is described in detail with the presentation of primary data sources, atmospheric parameters and obtaining raster coverage with a resolution of 30 meters per pixel. The tool used for the calculation is the Land Surface Temperature module of the QGIS software. The paper presents maps of temperature within the area of conducted ornithological surveys and the density of gulls. The densities of birds for individual bodies of water are calculated using the Spatial Analyst module of the ArcGIS program with the kernel density tool. According to the research results, a close correlation was established between the attractiveness of reservoirs for gulls and water temperature. The correlation coefficients were 0,83 and 0,71, respectively, with the abundance and density of gulls.

Study on the Application and Comparative Analysis of Land Surface Temperature Retrieval Method Based on Multi-Sensor Remote Sensing Data

2014 ◽  
Vol 1010-1012 ◽  
pp. 1276-1279 ◽  
Author(s):  
Yin Tai Na
Keyword(s):  
Remote Sensing ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Remote Sensing Data ◽  
Sensing Data ◽  
Advantages And Disadvantages ◽  
Urban Heat ◽  
Split Window Algorithm ◽  
Temperature Retrieval

The three commonly used remote sensing land surface temperature retrieval methods are described, namely single-window algorithm, split window algorithm and multi-channel algorithm, which have their advantages and disadvantages. The land surface temperature (LST) of study area was retrieved with multi-source remote sensing data. LST of study area was retrieved with the split window algorithm on January 10, 2003 and November 19, 2003 which is comparatively analyzed with the LST result of ETM+data with the single-window algorithm and the LST result of ASTER data with multi channel algorithm in the same period. The results show that land surface temperature of different land features are significantly different, where the surface temperature of urban land is the highest, and that of rivers and lakes is the lowest, followed by woodland. It is concluded that the expansion of urban green space and protection of urban water can prevent or diminish the urban heat island.

scholarly journals Pemetaan Wilayah Lahan Basah Berdasarkan Data Penginderaan Jauh Optik Dan Radar

2020 ◽  
Vol 4 (2) ◽  
pp. 48-61
Author(s):  
Rian Nurtyawan ◽  
Ervan Muktamar Hendarna
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Satellite Image ◽  
Soil Surface ◽  
Landsat 8 ◽  
Optical Remote Sensing ◽  
Radar Sensing

ABSTRAKPada umumnya lahan basah dikelola menjadi area pertanian ataupun perkebunan. Fungsi lahan basah memiliki fungsi ekologis seperti pengendali banjir, pencegah intrusi air laut, erosi, pencemaran, dan pengendali iklim global. Data pengindraan jauh yang digunakan pengelolaan lahan basah yaitu pengindraan jauh optik dan radar. Tujuan dari penelitian ini adalah mengeksplorasi korelasi potensial dari data optik dan radar untuk mengamati dinamika pada kawasan lahan basah tersebut dan melakukan pemetaan. Metode yang digunakan pada pengindraan jauh optik yaitu LST (Land Surface Temperature) berdasarkan Citra Satelit Landsat-8 dan metode yang digunakan pada pengindraan jauh radar yaitu estimasi kelembaban tanah berdasarkan Citra Satelit Sentinel-1A. Hasil pengamatan dinamika dan pemetaan pada wilayah Kabupaten Bandung Raya memiliki nilai kelembaban tanah tertinggi pada Bulan Mei dengan nilai kelembapan tanah tanah rata-rata sebesar 20,9 % pada polarisasi VH. Suhu permukaan tanah terendah terjadi pada bulan Mei dengan nilai suhu rata-rata sebesar 19.5 °C. Kolerasi antara nilai kelembapan tanah tanah dan suhu permukaan tanah pada wilayah Kabupaten Bandung Raya berdasarkan metode koefisien determinasi sebesar R2=0.705 didapatkan bahwa semakin tinggi nilai kelembapan tanah tanah maka nilai suhu permukaan tanah akan semakin rendah.Kata kunci: Kawasan lahan basah, Pengindraan Jauh Optik, Pengindraan Jauh Radar, Pengamatan Dinamika, Pemetaan. ABSTRACTIn general wetlands managed become an area of agriculture or plantations. The extent of wetland that has been used can be damaged if it is not managed properly and integrated.. The purpose of this research is to explore the potential correlations between several parameters of optical and radar data to observe the dynamics of wetlands area and mapping the wetlands area. The methodology that was used in optical remote sensing is LST (Land Surface Temperature) based on Landsat-8 Satellite Image and the method used in remote radar sensing is estimation of soil moisture based on Sentinel-1A Satellite Image. The result of the observation in the area and mapping the dynamics in Bandung Raya District had the highest soil moisture values in May with 27% of soil water level in VH polarization and 78.1% in VV polarization and the lowest value in each month is 11.8% and the highest soil surface temperature in August with a value 37.9 ° C and the minimum value 19 ° C..Keywords: Wetland Area, Optical Remote Sensing, Remote Radar Sensing, Dynamics Observation, Mapping.

scholarly journals Aplikasi Penghitungan Gross Primary Production dari Data Penginderaan Jauh

2016 ◽  
pp. 31
Author(s):  
Komang Gede Kurniadi ◽  
I Putu Agung Bayupati ◽  
I Dewa Nyoman Nurweda Putra
Keyword(s):  
Remote Sensing ◽  
Primary Production ◽  
Gross Primary Production ◽  
Satellite Image ◽  
Remote Sensing Data ◽  
Landsat 8 ◽  
Automatic Data ◽  
Sensing Data ◽  
Metadata File ◽  
Production Calculation

Calculation of Gross Primary Production that utilize remote sensing data is can be done on commercial remote sensing software by manual method. The commercial remote sensing software does not provides a specific feature that allow the user to do the Gross Primary Production calculation. This research is aimed to to build a remote sensing software that can be specifically used to do the Gross Primary Production calculation for Denpasar area. This software accepts remote sensing data as an input, such as satellite image from Landsat 8 OLI and TIRS and metadata file. The formulas and supporting data that required on the Gross Primary Production calculation are implemented on software in order to make an automatic image processing software. There also some additional feature on this software such as automatic data parsing from metadata file, cropping, masking and zoom that could help user to do the Gross Primary Production calculation. The developed software is able to produce information such as Gross Primary Production  value that depicted by a figure with color segmentation, area of the segments and mean, minimum and maximum value of the Gross Primary Production.  

Sign in / Sign up

Export Citation Format

Share Document