scholarly journals Remote Sensing-Based Aerosol Optical Thickness for Monitoring Particular Matter over the City

Proceedings ◽  
2018 ◽  
Vol 2 (7) ◽  
pp. 362 ◽  
Author(s):  
Tran Thi Van ◽  
Nguyen Hang Hai ◽  
Vo Quoc Bao ◽  
Ha Duong Xuan Bao
Keyword(s):  
Urban Development ◽  
Optical Thickness ◽  
Satellite Image ◽  
Regression Function ◽  
Aerosol Optical Thickness ◽  
General Distribution ◽  
Space Technology ◽  
Observation Methods ◽  
Landsat Satellite ◽  
Industrial Zones

Urban development contributing to air pollution is one of the factors seriously affecting public health. Besides the traditional ground observation methods, the current space technology has been added to the monitoring and managing environment. This research used Landsat satellite image to detect PM10 from by the Aerosol Optical Thickness (AOT) method for Ho Chi Minh City area. The regression analysis was used for establishing the relationship between the PM10 data obtained at ground stations and AOT values from processed images in 2003. The analysis showed a good correlation coefficient (R = 0.95) for the case of AOT calculated from spectral reflective green band. The relative radiation normalization was carried out for satellite imaging in 2015 in order to simulate the spatial distribution of PM10 with the same regression function. The distribution for PM10 aerosol pollution is focused on the urban area, traffic booth and industrial zones. The results of this study provided a picture of general distribution for current pollution status and also supported the determining of specified polluted areas. This has provided helpful and good support for zoning and urban environmental management in accordance with urban development.

scholarly journals Apply Remote Sensing to Monitoring Dynamics of Built Environmental in The Core Area and The Border of Sokok City

2020 ◽  
Author(s):  
Silvia Evandi
Keyword(s):  
Environmental Changes ◽  
Confusion Matrix ◽  
Satellite Image ◽  
Early Period ◽  
Land Development ◽  
Image Data ◽  
Space Technology ◽  
Image Transformation ◽  
Test Technique ◽  
Landsat Satellite

The development of unmanned satellite space technology is increasingly willing, the emergence of medium resolution satellites with sensitivity and spectral variants such as Landsat is very effective in observing environmental changes, while the purpose of this study is to monitor the development of built-in land using image transformation techniques, estimating built-in land changes. The research method uses the NDVI image transformation technique, NDBI and Built Up Index, with Landsat satellite image data obtained from USGS. Accuracy sampling is done by purposive sampling with confusion matrix accuracy test technique. The research results were found. developed land for the period 2004 - 2010 with a percentage of 19.25%, for stages 2010 - 2018 with a percentage of 30.25%. The land development was built based on the area of ​​the highest sub-district in the Kubung area in the early period with a percentage of 7.20% then in the second period with a percentage of 32.23%. The quality of the accuracy of the results of image analysis using confusion matrix technique with an image accuracy level in a field sample of 185 with an image accuracy of 86.04%.

scholarly journals VEGETATION MONITORING OF MASHHAD USING AN OBJECT-ORIENTED POST CLASSIFICATION COMPARISON METHOD

2017 ◽  
Vol XLII-4/W4 ◽  
pp. 123-131
Author(s):  
N. Khalili Moghadam ◽  
M. R. Delavar ◽  
A. Forati
Keyword(s):  
Urban Development ◽  
Change Detection ◽  
Satellite Image ◽  
Object Oriented ◽  
Comparison Method ◽  
Vegetation Monitoring ◽  
Detection Techniques ◽  
Close Relationship ◽  
Multi Temporal ◽  
Landsat Satellite

By and large, todays mega cities are confronting considerable urban development in which many new buildings are being constructed in fringe areas of these cities. This remarkable urban development will probably end in vegetation reduction even though each mega city requires adequate areas of vegetation, which is considered to be crucial and helpful for these cities from a wide variety of perspectives such as air pollution reduction, soil erosion prevention, and eco system as well as environmental protection. One of the optimum methods for monitoring this vital component of each city is multi-temporal satellite images acquisition and using change detection techniques. In this research, the vegetation and urban changes of Mashhad, Iran, were monitored using an object-oriented (marker-based watershed algorithm) post classification comparison (PCC) method. A Bi-temporal multi-spectral Landsat satellite image was used from the study area to detect the changes of urban and vegetation areas and to find a relation between these changes. The results of this research demonstrate that during 1987-2017, Mashhad urban area has increased about 22525 hectares and the vegetation area has decreased approximately 4903 hectares. These statistics substantiate the close relationship between urban development and vegetation reduction. Moreover, the overall accuracies of 85.5% and 91.2% were achieved for the first and the second image classification, respectively. In addition, the overall accuracy and kappa coefficient of change detection were assessed 84.1% and 70.3%, respectively.

scholarly journals European primary forest database v2.0

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Francesco Maria Sabatini ◽  
Hendrik Bluhm ◽  
Zoltan Kun ◽  
Dmitry Aksenov ◽  
José A. Atauri ◽  
...  
Keyword(s):  
Conservation Planning ◽  
Human Impacts ◽  
Satellite Image ◽  
Primary Forest ◽  
Potential Natural Vegetation ◽  
Ecological Studies ◽  
Biogeographical Regions ◽  
Surrounding Landscape ◽  
Landsat Satellite ◽  
Primary Forests

AbstractPrimary forests, defined here as forests where the signs of human impacts, if any, are strongly blurred due to decades without forest management, are scarce in Europe and continue to disappear. Despite these losses, we know little about where these forests occur. Here, we present a comprehensive geodatabase and map of Europe’s known primary forests. Our geodatabase harmonizes 48 different, mostly field-based datasets of primary forests, and contains 18,411 individual patches (41.1 Mha) spread across 33 countries. When available, we provide information on each patch (name, location, naturalness, extent and dominant tree species) and the surrounding landscape (biogeographical regions, protection status, potential natural vegetation, current forest extent). Using Landsat satellite-image time series (1985–2018) we checked each patch for possible disturbance events since primary forests were identified, resulting in 94% of patches free of significant disturbances in the last 30 years. Although knowledge gaps remain, ours is the most comprehensive dataset on primary forests in Europe, and will be useful for ecological studies, and conservation planning to safeguard these unique forests.

Satellite-based PM2.5 estimation using fine-mode aerosol optical thickness over China

2017 ◽  
Vol 170 ◽  
pp. 290-302 ◽  
Author(s):  
Xing Yan ◽  
Wenzhong Shi ◽  
Zhanqing Li ◽  
Zhengqiang Li ◽  
Nana Luo ◽  
...  
Keyword(s):  
Optical Thickness ◽  
Aerosol Optical Thickness ◽  
Fine Mode ◽  
Fine Mode Aerosol
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