Monitoring the state of waste disposal facilities using remote sensing data

2018 ◽  
Vol 941 (11) ◽  
pp. 47-53
Author(s):  
U.D. Niyazgulov ◽  
A.A. Gebgart ◽  
V.G. Krestinkov ◽  
F.K. Niyazgulov
Keyword(s):  
Remote Sensing ◽  
Spatial Resolution ◽  
Imaging System ◽  
Remote Sensing Data ◽  
Aerial Survey ◽  
The State ◽  
Household Waste ◽  
Ecological State ◽  
Solid Waste Landfills ◽  
The Impact

The technology of monitoring objects of solid household waste in the Moscow region using the data of space and aerial survey is considered. In order to solve the problem, we used space survey materials obtained from the Worldview-2 satellite (spatial resolution of 1,5 m per pixel) and special aerial filming performed with the help of an Azimuth-2M photo-imaging system based on a hang glider (spatial resolution not coarser than 0,1 m per pixel). On the basis of those materials, digital models of accommodation facilities for solid household wastes and orthophotoplans were obtained, using which a comparative analysis of the state of landfills was performed. The analysis was carried out according to several indicators, including the impact of polygons on the ecological state of the surrounding territories and the cluttering the surrounding territory with waste was determined. It is shown that the use of remote sensing materials enables obtaining the necessary information to monitor the state of solid waste landfills, while performing the minimum amount of field geodetic works.

scholarly journals The impact of aeration on ecological state of lake Telbyn in Kyiv

2021 ◽  
Vol 30 (1) ◽  
pp. 179-189
Author(s):  
Viktor I. Vyshnevskyi ◽  
Vladislav A. Zhezherya ◽  
Inna M. Nezbrytska ◽  
Olena P. Bilous
Keyword(s):  
Remote Sensing ◽  
Water Surface ◽  
Negative Impact ◽  
Remote Sensing Data ◽  
Bottom Layer ◽  
Small Cells ◽  
Ecological State ◽  
Sensing Data ◽  
Artificial Aeration ◽  
The Impact

Lake Telbyn is considered to be one of the largest lakes located in the eastern part of Kyiv. The artificial aeration of this lake was started at the end of 2016 by using of 8 aerators, which has been continuing so far. The main perpose of this measure is improving the ecological state of the lake mostly for recreational use. There were carried out a field study of the lake and the analysis of remote sensing data. Physical and chemical characteristics of water, phytoplankton biomass, chlo- rophyll a concentration and some other parameters at the different depths were studied. It was found out that artificial aeration has a positive effect on the ecological state of the lake. The water aeration causes the blur of thermocline whereas the impact on its depth is not essential. Under impact of aeration the concentration of dissolved oxygen become larger, mostly in the bottom layer. The highest concentration of ammonium nitrogen in a warm period is observed in the bottom layer of the lake. The deep location of aerators causes the increasing of concentration in bottom layer. At the same time there is not visible impact on concentration near the surface. The similar result was obtained for the concentration of inorganic phosphorus. The impact of aeration on algal bloom is not such essential as on hydrochemical characteristics. The artificial aeration causes negative impact on the phytoplankton abundance and less effect on their biomass. It means the larger effect on the algae with small cells. In other words the aeration has larger impact on green algae than on blue-green ones. The use of remote sensing data showed that ecological state of Lake Telbyn during the aeration period improved comparably with other lakes of Kyiv. As a result of aeration, the view of water surface of the lake became more similar to water surface of the Dnipro River, which flows through the city.

scholarly journals The estimation of the impact of anthropogenic and natural factors on state of the forests using remote sensing data in Staritsky forestry of Tver region

2021 ◽  
pp. 127-137
Author(s):  
Александра Федоровна Мейсурова ◽  
Наталья Юрьевна Сметанина
Keyword(s):  
Remote Sensing ◽  
Satellite Images ◽  
Remote Sensing Data ◽  
Timber Harvesting ◽  
The State ◽  
Common Variants ◽  
Sensing Data ◽  
Natural Factors ◽  
Tver Region ◽  
The Impact

Проведена оценка влияния антропогенных и природных факторов на состояние лесов Старицкого лесничества Тверской области на основе серий спутниковых изображений Santinel-2 за период с 2019 по 2021 гг. Использованы распространенные варианты комбинаций каналов для интерпретация основных видов лесоизменений: рубки - комбинация 4,3,2 «естественные цвета»; подтопление - комбинация 5,6,2 - «здоровая растительность» с преобладанием фиолетовых оттенков; ветровалы и буреломы - комбинация 5,4,3 - «искусственные цвета» с преобладанием красного цвета. Выяснено, что общая площадь лесоизменений в лесничестве составила 2246,9 га. Наибольшее воздействие на состояние лесов изученной территории оказывает вырубка лесных насаждений с целью заготовки древесины. Общая площадь вырубленных лесов составила 92% от общей площади всех лесоизменений. An assessment of the influence of anthropogenic and natural factors on the state of the forests of the Staritsa Forestry of the Tver Region was carried out in a series of Santinel-2 satellite images for the period from 2019 to 2021. Common variants of canal combinations were used to interpret the main types of forest changes: felling - a combination of 4,3,2 "natural colors"; flooding - a combination of 5,6,2 - "healthy vegetation" with a predominance of purple tints; windblows and windbreaks - a combination of 5,4,3 - "artificial colors" with a predominance of red. The total area of forest changes in the forestry was 2246.9 hectares. The greatest impact on the state of forests in the studied area are done by the timber-harvesting activities. The total area of deforestation was 92% of the total area of all forest changes.

scholarly journals Analysing the Impact of Climate Change on Hydrological Ecosystem Services in Laguna del Sauce (Uruguay) Using the SWAT Model and Remote Sensing Data

2021 ◽  
Vol 13 (10) ◽  
pp. 2014
Author(s):  
Celina Aznarez ◽  
Patricia Jimeno-Sáez ◽  
Adrián López-Ballesteros ◽  
Juan Pablo Pacheco ◽  
Javier Senent-Aparicio
Keyword(s):  
Climate Change ◽  
Remote Sensing ◽  
Ecosystem Services ◽  
Water Resources ◽  
Swat Model ◽  
Remote Sensing Data ◽  
Erosion Control ◽  
Sensing Data ◽  
Extreme Precipitation Events ◽  
The Impact

Assessing how climate change will affect hydrological ecosystem services (HES) provision is necessary for long-term planning and requires local comprehensive climate information. In this study, we used SWAT to evaluate the impacts on four HES, natural hazard protection, erosion control regulation and water supply and flow regulation for the Laguna del Sauce catchment in Uruguay. We used downscaled CMIP-5 global climate models for Representative Concentration Pathways (RCP) 2.6, 4.5 and 8.5 projections. We calibrated and validated our SWAT model for the periods 2005–2009 and 2010–2013 based on remote sensed ET data. Monthly NSE and R2 values for calibration and validation were 0.74, 0.64 and 0.79, 0.84, respectively. Our results suggest that climate change will likely negatively affect the water resources of the Laguna del Sauce catchment, especially in the RCP 8.5 scenario. In all RCP scenarios, the catchment is likely to experience a wetting trend, higher temperatures, seasonality shifts and an increase in extreme precipitation events, particularly in frequency and magnitude. This will likely affect water quality provision through runoff and sediment yield inputs, reducing the erosion control HES and likely aggravating eutrophication. Although the amount of water will increase, changes to the hydrological cycle might jeopardize the stability of freshwater supplies and HES on which many people in the south-eastern region of Uruguay depend. Despite streamflow monitoring capacities need to be enhanced to reduce the uncertainty of model results, our findings provide valuable insights for water resources planning in the study area. Hence, water management and monitoring capacities need to be enhanced to reduce the potential negative climate change impacts on HES. The methodological approach presented here, based on satellite ET data can be replicated and adapted to any other place in the world since we employed open-access software and remote sensing data for all the phases of hydrological modelling and HES provision assessment.

LAI Retrieval Based on PROSPECT-SAILH Model from Multi-Angular Data of WiDAS Imaging System

2012 ◽  
Vol 518-523 ◽  
pp. 5697-5703
Author(s):  
Zhao Yan Liu ◽  
Ling Ling Ma ◽  
Ling Li Tang ◽  
Yong Gang Qian
Keyword(s):  
Remote Sensing ◽  
Imaging System ◽  
Remote Sensing Data ◽  
Canopy Reflectance ◽  
Area Index ◽  
Sensing Data ◽  
Spectral Bands ◽  
Sensing Technology ◽  
Leaf Optical Properties ◽  
Angular Data

The aim of this study is to assess the capability of estimating Leaf Area Index (LAI) from high spatial resolution multi-angular Vis-NIR remote sensing data of WiDAS (Wide-Angle Infrared Dual-mode Line/Area Array Scanner) imaging system by inverting the coupled radiative transfer models PROSPECT-SAILH. Based on simulations from SAILH canopy reflectance model and PROSPECT leaf optical properties model, a Look-up Table (LUT) which describes the relationship between multi-angular canopy reflectance and LAI has been produced. Then the LAI can be retrieved from LUT by directly matching canopy reflectance of six view directions and four spectral bands with LAI. The inversion results are validated by field data, and by comparing the retrieval results of single-angular remote sensing data with multi-angular remote sensing data, we can found that the view angle takes the obvious impact on the LAI retrieval of single-angular data and that high accurate LAI can be obtained from the high resolution multi-angular remote sensing technology.

scholarly journals Capacity Development for Use of Remote Sensing for REDD+ MRV Using Online and Offline Activities: Impacts and Lessons Learned

2021 ◽  
Vol 13 (11) ◽  
pp. 2172
Author(s):  
Sarah Carter ◽  
Martin Herold ◽  
Inge Jonckheere ◽  
Andres Espejo ◽  
Carly Green ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Forest Cover ◽  
Hybrid Approach ◽  
Remote Sensing Data ◽  
Lessons Learned ◽  
Multiple Partners ◽  
Large Audience ◽  
Forest Cover Changes ◽  
The Impact ◽  
And Training

Four workshops and a webinar series were organized, with the aim of building capacity in countries to use Earth Observation Remote Sensing data to monitor forest cover changes and measure emissions reductions for REDD+ results-based payments. Webinars and workshops covered a variety of relevant tools and methods. The initiative was collaboratively organised by a number of Global Forest Observations Initiative (GFOI) partner institutions with funding from the World Bank’s Forest Carbon Partnership Facility (FCPF). The collaborative approach with multiple partners proved to be efficient and was able to reach a large audience, particularly in the case of the webinars. However, the impact in terms of use of tools and training of others after the events was higher for the workshops. In addition, engagement with experts was higher from workshop participants. In terms of efficiency, webinars are significantly cheaper to organize. A hybrid approach might be considered for future initiatives; and, this study of the effectiveness of both in-person and online capacity building can guide the development of future initiatives, something that is particularly pertinent in a COVID-19 era.

Mapping and verification of the snow cover timing in the Baikal region by remote sensing data MODIS “snow cover”

2021 ◽  
Vol 973 (7) ◽  
pp. 21-31
Author(s):  
Е.А. Rasputina ◽  
A.S. Korepova
Keyword(s):  
Remote Sensing ◽  
Snow Cover ◽  
Spatial Resolution ◽  
Baikal Region ◽  
Remote Sensing Data ◽  
Meteorological Station ◽  
Sensing Data ◽  
Modis Data ◽  
Weather Stations ◽  
The Difference

The mapping and analysis of the dates of onset and melting the snow cover in the Baikal region for 2000–2010 based on eight-day MODIS “snow cover” composites with a spatial resolution of 500 m, as well as their verification based on the data of 17 meteorological stations was carried out. For each year of the decennary under study, for each meteorological station, the difference in dates determined from the MODIS data and that of weather stations was calculated. Modulus of deviations vary from 0 to 36 days for onset dates and from 0 to 47 days – for those of stable snow cover melting, the average of the deviation modules for all meteorological stations and years is 9–10 days. It is assumed that 83 % of the cases for the onset dates can be considered admissible (with deviations up to 16 days), and 79 % of them for the end dates. Possible causes of deviations are analyzed. It was revealed that the largest deviations correspond to coastal meteorological stations and are associated with the inhomogeneity of the characteristics of the snow cover inside the pixels containing water and land. The dates of onset and melting of a stable snow cover from the images turned out to be later than those of weather stations for about 10 days. First of all (from the end of August to the middle of September), the snow is established on the tops of the ranges Barguzinsky, Baikalsky, Khamar-Daban, and later (in late November–December) a stable cover appears in the Barguzin valley, in the Selenga lowland, and in Priolkhonye. The predominant part of the Baikal region territory is covered with snow in October, and is released from it in the end of April till the middle of May.

scholarly journals Assessment of the Impacts of Image Signal-to-Noise Ratios in Impervious Surface Mapping

2019 ◽  
Vol 11 (22) ◽  
pp. 2603
Author(s):  
George Xian ◽  
Hua Shi ◽  
Cody Anderson ◽  
Zhuoting Wu
Keyword(s):  
Spatial Resolution ◽  
Signal To Noise Ratio ◽  
Spatial Scales ◽  
Regression Tree ◽  
Remote Sensing Data ◽  
Impervious Surface ◽  
Landsat 8 ◽  
Signal To Noise ◽  
Study Results ◽  
The Impact

Medium spatial resolution satellite images are frequently used to characterize thematic land cover and a continuous field at both regional and global scales. However, high spatial resolution remote sensing data can provide details in landscape structures, especially in the urban environment. With upgrades to spatial resolution and spectral coverage for many satellite sensors, the impact of the signal-to-noise ratio (SNR) in characterizing a landscape with highly heterogeneous features at the sub-pixel level is still uncertain. This study used WorldView-3 (WV3) images as a basis to evaluate the impacts of SNR on mapping a fractional developed impervious surface area (ISA). The point spread function (PSF) from the Landsat 8 Operational Land Imager (OLI) was used to resample the WV3 images to three different resolutions: 10 m, 20 m, and 30 m. Noise was then added to the resampled WV3 images to simulate different fractional levels of OLI SNRs. Furthermore, regression tree algorithms were incorporated into these images to estimate the ISA at different spatial scales. The study results showed that the total areal estimate could be improved by about 1% and 0.4% at 10-m spatial resolutions in our two study areas when the SNR changes from half to twice that of the Landsat OLI SNR level. Such improvement is more obvious in the high imperviousness ranges. The root-mean-square-error of ISA estimates using images that have twice and two-thirds the SNRs of OLI varied consistently from high to low when spatial resolutions changed from 10 m to 20 m. The increase of SNR, however, did not improve the overall performance of ISA estimates at 30 m.

scholarly journals Efficient land use based on remote sensing data

2021 ◽  
Vol 3 ◽  
pp. 180-185
Author(s):  
Y. M. Kenzhegaliyev ◽  
◽  
◽  
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Remote Sensing Data ◽  
Crop Productivity ◽  
The State ◽  
Agricultural Crops ◽  
Earth Remote Sensing ◽  
Spectral Reflectivity ◽  
Sensing Data ◽  
Current Location

The goal -is to explore ways of using Earth remote sensing data for efficient land use. Methods - detailed information on current location of certain types of agricultural crops in the study areas has been summarized, which opens up opportunities for the effective use of cultivated areas. It was revealed that the basis of the principle of the method under consideration is the relationship between the state and structure of vegetation types with its reflective ability. It has been determined that information on the spectral reflective property of the vegetation cover in the future can help replace more laborious methods of laboratory analysis. For classification of farmland, satellite images of medium spatial resolution with a combination of channels in natural colors were selected. Results - a method for identifying agricultural plants by classification according to the maximum likelihood algorithm was considered. The commonly used complexes of geoinformation software products with modules for special image processing allow displaying indicators in the form of raster images. It is shown that the use of Earth remote sensing data is the most relevant solution in the field of crop recognition and makes it possible to simplify the implementation of such types of work as the analysis of the intensity of land use, the assessment of the degree of pollution with weeds and determination of crop productivity. Conclusions - the research results given in the article indicate that timely information on the current location of certain types of agricultural crops in the studied territories significantly simplifies the implementation of the tasks and increases the resource potential of agricultural lands. In turn, the timing of the survey and the state of environment affect the spectral reflectivity of vegetation.

scholarly journals LIGHT POLLUTION IN SLOVENIA IN 2019 WITH SPECIAL REGARD TO NATURA 2000 AREAS

2020 ◽  
Vol 42 ◽  
pp. 69-81
Keyword(s):  
Remote Sensing ◽  
Protected Areas ◽  
Remote Sensing Data ◽  
Natura 2000 ◽  
The State ◽  
Light Pollution ◽  
Sensing Data ◽  
Special Regard ◽  
Ljubljansko Barje

Light pollution in Slovenia in 2019 with special regard to Natura 2000 areas The article shows the state of light pollution in Slovenia. Remote sensing data from the Suomi satellite were analysed. Light pollution is shown by radiance expressed in nW/(sr cm2 ). In Slovenia, there are large differences in state of light polution. The most polluted areas are located in the area of larger settlements and in areas with higher levels of infrastructure. The spread of light does not stop at the borders of protected areas, so we also analyzed the state of light pollution in Natura 2000 sites in Slovenia. It turns out that the most lightpolluted areas are those that lie around larger settlements or suburbanised regions (Ljubljansko Barje, Šmarna gora, Drava).

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