scholarly journals Forecast landslide activity in the zones of technogenic geochemical anomalies of urban areas based on remote sensing data

2018 ◽  
Vol 27 (1) ◽  
pp. 88-94 ◽  
Author(s):  
T. P. Mokritskaya ◽  
D. A. Dovganenko
Keyword(s):  
Remote Sensing ◽  
Urban Areas ◽  
Salt Content ◽  
Remote Sensing Data ◽  
Statistical Research ◽  
Aeration Zone ◽  
Landslide Activity ◽  
Geochemical Anomalies ◽  
Landslide Process ◽  
Remote Sensing Methods

The analysis and forecast of landslide activity on the territories of cities is an actual task. Remote sensing methods are successfully used to solve a whole range of tasks: from classification to modeling. The possibilities of interpreting data are expanding. The processing involves standard methods of statistical research, methods of theories of fuzzy sets, pattern recognition, and others. This paper describes the experience of involving the method of grouping arguments into a prediction model. Firstly, an irregular time series of values of reflection coefficient on areas of active development of the landslide process is investigated. According to the results of the prognosis, it is proved that in the nearest future changes in solar activity (11 - year cycle) will not lead to activation of the process. Secondly, the forecast of the activation of the landslide process under the influence of man-made factors was fulfilled. The connection between the content of readily soluble salts in the pores of forest soils of the aeration zone and the values of the coefficient of reflection and. The model extends the possibilities of using the method of group consideration of arguments for mapping zones of landslide activity in sections of man-made geochemical anomalies. The analysis of the model shows that the connection is. In the future it is possible to determine certain values of salt content and values of reflection coefficients, which will be indicators of the probability of activating the landslide process in other conditions.

scholarly journals Estimation of the temperature distribution in urban areas by using remote sensing data.

1994 ◽  
Vol 22 ◽  
pp. 267-273 ◽  
Author(s):  
Shinji KANEKO ◽  
Toshiie MAEDA ◽  
Takahito UENO ◽  
Hidefumi IMURA
Keyword(s):  
Remote Sensing ◽  
Temperature Distribution ◽  
Urban Areas ◽  
Remote Sensing Data ◽  
Sensing Data

scholarly journals Possibilities of milpa identification in Yucatan through remote sensing techniques and Sentinel-2 data

10.29007/hbs2 ◽  
2019 ◽  
Author(s):  
Juan Carlos Valdiviezo-Navarro ◽  
Adan Salazar-Garibay ◽  
Karla Juliana Rodríguez-Robayo ◽  
Lilián Juárez ◽  
María Elena Méndez-López ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Urban Areas ◽  
Food Sovereignty ◽  
Region Of Interest ◽  
Remote Sensing Data ◽  
Support Vector ◽  
Multispectral Images ◽  
Crop Fields ◽  
Remote Sensing Techniques ◽  
Sentinel 2

Maya milpa is one of the most important agrifood systems in Mesoamerica, not only because its ancient origin but also due to lead an increase in landscape diversity and to be a relevant source of families food security and food sovereignty. Nowadays, satellite remote sensing data, as the multispectral images of Sentinel-2 platforms, permit us the monitor- ing of different kinds of structures such as water bodies, urban areas, and particularly agricultural fields. Through its multispectral signatures, mono-crop fields or homogeneous vegetation zones like corn fields, barley fields, or other ones, have been successfully detected by using classification techniques with multispectral images. However, Maya milpa is a complex field which is conformed by different kinds of vegetables species and fragments of natural vegetation that in conjunction cannot be considered as a mono-crop field. In this work, we show some preliminary studies on the availability of monitoring this complex system in a region of interest in Yucatan, through a support vector machine (SVM) approach.

scholarly journals Forest areas remote monitoring within the limits of transport objects impact

2021 ◽  
pp. 109-118
Author(s):  
Dmytro Liashenko ◽  
◽  
Dmytro Pavliuk ◽  
Vadym Belenok ◽  
Vitalii Babii ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Spatial Data ◽  
Remote Monitoring ◽  
Forest Cover ◽  
Landsat Imagery ◽  
Remote Sensing Data ◽  
Transport Infrastructure ◽  
Nature Management ◽  
Collecting Methods ◽  
Remote Sensing Methods

The article studies the issues of using remote sensing data for the tasks of ensuring sustainable nature management in the territories within the influence of transport infrastructure objects. Peculiarities of remote monitoring for tasks of transport networks design and in the process of their operation are determined. The paper analyzes the development of modern remote sensing methods (satellite imagery, the use of mobile sensors installed on cars or aircraft). A brief overview of spatial data collecting methods for the tasks of managing the development of territories within the influence of transport infrastructure (roads, railways, etc.) has made. The article considers the experience of using remote sensing technologies to monitor changes in the parameters of forest cover in the Transcarpathian region (Ukraine) in areas near to highways, by use Landsat imagery.

Have vehicle emissions of primary NO2 peaked?

2016 ◽  
Vol 189 ◽  
pp. 439-454 ◽  
Author(s):  
David C. Carslaw ◽  
Tim P. Murrells ◽  
Jon Andersson ◽  
Matthew Keenan
Keyword(s):  
Remote Sensing ◽  
Urban Areas ◽  
Vehicle Emissions ◽  
Remote Sensing Data ◽  
Vehicle Emission ◽  
Oxides Of Nitrogen ◽  
Vehicle Exhaust ◽  
Road Vehicles ◽  
Limit Values ◽  
Sensing Data

Reducing ambient concentrations of nitrogen dioxide (NO2) remains a key challenge across many European urban areas, particularly close to roads. This challenge mostly relates to the lack of reduction in emissions of oxides of nitrogen (NOx) from diesel road vehicles relative to the reductions expected through increasingly stringent vehicle emissions legislation. However, a key component of near-road concentrations of NO2 derives from directly emitted (primary) NO2 from diesel vehicles. It is well-established that the proportion of NO2 (i.e. the NO2/NOx ratio) in vehicle exhaust has increased over the past decade as a result of vehicle after-treatment technologies that oxidise carbon monoxide and hydrocarbons and generate NO2 to aid the emissions control of diesel particulate. In this work we bring together an analysis of ambient NOx and NO2 measurements with comprehensive vehicle emission remote sensing data obtained in London to better understand recent trends in the NO2/NOx ratio from road vehicles. We show that there is evidence that NO2 concentrations have decreased since around 2010 despite less evidence of a reduction in total NOx. The decrease is shown to be driven by relatively large reductions in the amount of NO2 directly emitted by vehicles; from around 25 vol% in 2010 to 15 vol% in 2014 in inner London, for example. The analysis of NOx and NO2 vehicle emission remote sensing data shows that these reductions have been mostly driven by reduced NO2/NOx emission ratios from heavy duty vehicles and buses rather than light duty vehicles. However, there is also evidence from the analysis of Euro 4 and 5 diesel passenger cars that as vehicles age the NO2/NOx ratio decreases. For example the NO2/NOx ratio decreased from 29.5 ± 2.0% in Euro 5 diesel cars up to one year old to 22.7 ± 2.5% for four-year old vehicles. At some roadside locations the reductions in primary NO2 have had a large effect on reducing both the annual mean and number of hourly exceedances of the European Limit Values of NO2.

scholarly journals Direct estimation of Byram's fire intensity from infrared remote sensing imagery

2017 ◽  
Vol 26 (8) ◽  
pp. 668 ◽  
Author(s):  
Joshua M. Johnston ◽  
Martin J. Wooster ◽  
Ronan Paugam ◽  
Xianli Wang ◽  
Timothy J. Lynham ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Remote Sensing Data ◽  
Fire Intensity ◽  
Ancillary Data ◽  
Remote Sensing Imagery ◽  
Method Of Calculation ◽  
Rate Of Spread ◽  
Radiative Power ◽  
Thermal Infrared Imagery ◽  
Remote Sensing Methods

Byram’s fire intensity (IB,tot; kWm–1) is one the most important and widely accepted metrics for quantifying wildfire behaviour. Calculation of IB,tot requires measurement of fuel consumption, heat of combustion and rate of spread; existing methods for obtaining these measurements are either inexact or at times impossible to obtain in the field. This paper presents and evaluates a series of remote sensing methods for directly deriving radiative fire intensity (IB,rad; kWm–1) using the Fire Radiative Power (FRP) approach applied to thermal infrared imagery of spreading vegetation fires. Comparisons between the remote sensing data and ground-sampled measurements were used to evaluate the various estimates of IB,tot, and to determine the radiative fraction (radF) of a fire’s emitted energy. Results indicate that the IB,tot along an advancing flame front can be reasonably estimated (and agrees with traditional methods of estimation (R2=0.34–0.73)) from appropriately collected time-series of remote sensing imagery without the need for ground sampling or ancillary data. We further estimate that the radF of the fire’s emitted energy varies between 0.15 and 0.20 depending on the method of calculation, which is similar to previous estimates.

scholarly journals Urban Sprawl Assessment and Its Effect on Land Use Transformation in Varanasi City using Remote Sensing and GIS

2019 ◽  
Vol 9 (2) ◽  
pp. 1056-1061
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Urban Sprawl ◽  
Urban Areas ◽  
Urban Expansion ◽  
Remote Sensing Data ◽  
Gis And Remote Sensing ◽  
Land Use Transformation ◽  
Vegetation Water ◽  
Almost All

This paper seeks to examine the effect of urbanization on changes in land use in the peri-urban areas of Varanasi city in India. The area of study is divided into six different classes of land use: built-up area, agriculture, vegetation, water bodies, sand and other land use. Using the maximum likelihood technique, Landsat 5 TM satellite data were used to identify land use and land cover changes from 1996 to 2017. The findings indicate a substantial increase in the built-up area, associated with reduced water and other land use cover. The urban sprawl is observed in almost all directions from the city boundaries, and along highways. Shannon’s entropy analysis reveals dispersed distribution of built-up area. The approach based on GIS and remote sensing data, together with statistical analysis, has proved instrumental in the analysis of urban expansion. It also helps to identify priority areas that require adequate planning for sustainable development.

scholarly journals CREATION OF GIS-RESOURCES FOR PHYSIOGRAPHIC ZONING OF THE TRANSBOUNDARY RUSSIAN-MONGOLIAN TERRITORY

2021 ◽  
Vol 26 (2) ◽  
pp. 91-102
Author(s):  
Andrew N. Beshentsev ◽  
◽  
Alexander A. Ayurzhanaev ◽  
Bator V. Sodnomov ◽  
◽  
...  
Keyword(s):  
Remote Sensing ◽  
Remote Sensing Data ◽  
Landsat Images ◽  
Statistical Research ◽  
Active Biomass ◽  
Sensing Data ◽  
Digital Elevation ◽  
Geographical Regions ◽  
Elevation Model ◽  
Geographical Characteristics

The article is aimed at the development of methodological foundations for the creation of geoin-formation resources of transboundary territories based on cartographic materials and remote sensing data, as well as physical and geographical zoning of the transboundary Russian-Mongolian territory. The methodological basis of the study is cartographic and statistical research methods, geoinformation technology, as well as processing and analysis of remote sensing data. As a result, the study deter-mines the features of geoinformation resources, presents their characteristics, develops a classification and substantiates their integrating value in making interstate territorial decisions. The article gives the physical and geographical characteristics of the territory, determines the scale of mapping, establishes the basic units of geoinformation mapping and modeling, creates the coverage of the basin division, and proposes a scheme for creating basic geoinformation resources for the physical and geographical zoning of the territory. Based on the analysis of the digital elevation model, the territory was zoned according to the morphometric parameters of the relief. As a result of processing and analysis of Landsat images at different times, the territory was zoned in terms of the amount of photosynthetically active biomass (NDVI). As a result of zoning, 6 physical-geographical regions and 33 physical-geographical areas were identified.

scholarly journals Evaluation of Soil Degradation Based on High Resolution Remote Sensing Data

2005 ◽  
pp. 145-148
Author(s):  
Péter Burai ◽  
János Tamás
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Soil Salinity ◽  
Strong Correlation ◽  
Soil Degradation ◽  
Vegetation Index ◽  
Near Infrared ◽  
Salt Content ◽  
Remote Sensing Data ◽  
Test Site

Soil salinity is the main problem of soil degradation in the Grate Plain with cultivated area of 20% affected. Its influence is accelerated on the water managed and irrigated lands. Remote sensing can significantly contribute to detecting temporal changes of salt-related surface features. We have chosen a farm where intensive crop cultivation takes place as a test site as soil degradation can be intensive as a result of land use and irrigation. In order to evaluate soil salt content and biomass analysis, we gathered detailed data from an 100x250 m area. We analyzed the salinity property of the samples. In our research we used a TETRACAM ADC multispectral camera to take high resolution images (0,2-0,5 m) of low altitude (300-500 m). A Normalized Vegetation Index was computed from near infrared (750-950 nm) and red (620-750 nm) bands. This data was compared with the samples of investigated area. Analyzing the images, we evaluated image reliability, and the connection between the bands and the soil properties (pH, salt content). A strong correlation observed between NDVI and soil salinity (EC) makes the multispectral images suitable for construction of salinity map. A further strong correlation was determined between NDVI and yield.

scholarly journals Evaluation criteria and methods of environmental conditions in urban areas using remotely sensed data

2014 ◽  
pp. 39-47
Author(s):  
Liudmila Lischenko ◽  
Volodimir Filipovich ◽  
Anton Mychak ◽  
Natalia Pazynych ◽  
Alexander Teremenko
Keyword(s):  
Remote Sensing ◽  
Environmental Conditions ◽  
Urban Areas ◽  
Urban Landscape ◽  
Evaluation Criteria ◽  
Remote Sensing Data ◽  
Spectral Space ◽  
Integrated Analysis ◽  
Remotely Sensed Data ◽  
Space Images

Methodology of integral estimation of the ecological state of urban areas is examined with remote sensing data. The digitalstudy of spectral descriptions of landscape-functional zones of city onspaceimagesis used. A result of their integrated analysis is the districting of urban area relation to the level of prosperity and environmental conditions. It is proposed to distinguish six levels as follows: comfortable, optimal, satisfactory, inadequate, pre-crisis and emergency. Key words: remote sensing, multi spectral space images, urban landscape, municipal territory, environmental conditions.

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