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This paper presents the development of an image-based integrated method for determining and mapping aerosol optical thickness (AOT). Using the radiative transfer (RT) equation, a methodology was developed to create a Geographical Information System (GIS) model that can visually display the AOT distribution over urban areas. In this paper, the model...
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... 11 Landsat satellite images were used due to their availability within the study area. The Landsat 5 TM images were acquired for 24 June 2010, 10 July 2010, 27 August 2010 Tables 1 and 2. During the satellite overpass, AOT measurements were taken using the Microtops II sunphotometer at five different locations in the greater Limassol area and the stationery Cimel sunphotom- eter located in the center of study area, which is part of the AERONET network, in order to assess the AOT values derived from the algorithm using the satellite images. Concurrently, the SVC HR-1024 spectroradiometer, with a spectral range of 350- 2500 nm, was used to measure the reflectance value of a large as- phalt surface located near the center of the satellite image, in order to acquire and assess the reflectance values used for the atmo- spheric correction. ...
Context 2
... 11 Landsat satellite images were used due to their availability within the study area. The Landsat 5 TM images were acquired for 24 June 2010, 10 July 2010, 27 August 2010 Tables 1 and 2. During the satellite overpass, AOT measurements were taken using the Microtops II sunphotometer at five different locations in the greater Limassol area and the stationery Cimel sunphotom- eter located in the center of study area, which is part of the AERONET network, in order to assess the AOT values derived from the algorithm using the satellite images. Concurrently, the SVC HR-1024 spectroradiometer, with a spectral range of 350- 2500 nm, was used to measure the reflectance value of a large as- phalt surface located near the center of the satellite image, in order to acquire and assess the reflectance values used for the atmo- spheric correction. ...
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Citations
... Four satellite images for the West Bank were used to accomplish this study (Table 1) (Themistocleous et al. 2013;Pettinari et al., 2016). Free Landsat-TM (Landsat 5) and Landsat-OLI (Landsat 8) images were acquired from the United States Geological Survey (USGS) website for the years 2001 and 2021. ...
... Characteristics of the satellite data used in the study (Themistocleous & Hadjimitsis, 2013;Pettinari, et al. 2016 ...
The West Bank is characterized by the diversity of its climate despite its small area. It includes four climatic regions:- a humid, semi-humid, arid and semi-arid climate. This in turn affected the geographical distribution of vegetation cover seasonally and over the years. This study investigated changes in vegetation cover of the West Bank, Palestine, using multitemporal Landsat data. Four images were selected for this purpose – two corresponding to the year 2001 and the other two corresponding to the year 2021. Seasonal change of the Normalized Difference Vegetation Index (NDVI) was investigated for the acquired images. ArcGIS 10.8 software was used for image processing and analysis. Results showed that the negative change of the NDVI of autumn for both dates is much higher than the positive change. About 98.89 percent of the West Bank area scored a negative change in 2001, while about 80.79 percent of the West Bank scored negative change in 2021. The negative change in autumn is due to the dryness of summer season, which in turn led to the drying of the green grasses and herbs that grow among the trees and on the eastern slopes of the highlands. Concerning the NDVI change between 2001 and 2021, results showed a considerable positive change of the NDVI. Around 90.91% of the surface area of the West Bank (5132.304 km²) has positive change, while only 9.09% (513.405 km²) which mainly represent urban centers has negative change. The main reason that the NDVI in 2021 was higher than the NDVI in 2001outside the urban centers is that the amount of rain in that year was greater, especially in the northern areas. Thematic maps of NDVI for the two dates were produced, and changes in vegetation cover were extracted from the four maps. Based on the results of the study, it is recommended that decision-makers in the Ministry of Agriculture and Environmental organizations to develop plans to increase permanent green spaces, especially in arid and semi-arid areas of the West Bank.
تتميز الضفة الغربية بالتنوع المناخي على الرغم من صغر مساحتها، فهي تشتمل على اربعة اقاليم مناخية: الاقليم الرطب، الاقليم شبه الرطب، الاقليم الجاف، والاقليم شبه الجاف. هذا التنوع المناخي اثر على التوزيع الجغرافي للغطاء النباتي فصليا وعلى مدى سنوات طويلة. تناولت هذه الدراسة التغيرات في كثافة الغطاء النباتي للضفة الغربية ، فلسطين ، باستخدام بيانات القمر الصناعي لاندسات بأوقات مختلفة. تم اختيار أربع مرئيات فضائية لهذا الغرض - اثنتان في عام 2001 والصورتان الأخريان في عام 2021. تم فحص التغيير الموسمي لمؤشر الفروق الطبيعية للغطاء النباتي (NDVI) من تلك المرئيات. كما تم استخدام برنامج ArcGIS 10.8 لمعالجة الصور وتحليلها. أظهرت النتائج أن التغير السلبي لمؤشر NDVI للخريف لكلا التاريخين أعلى بكثير من التغير الإيجابي. سجل حوالي 98.89 في المائة من مساحة الضفة الغربية تغيراً سلبياً في عام 2001 ، بينما سجل حوالي 80.79 في المائة من الضفة الغربية تغيراً سلبياً في عام 2021. ان التغير السلبي لمؤشر النبات يعود الى جفاف فصل الصيف والذي بدوره ادى الى جفاف النباتات الخضراء والحشائش التي تنمو بين الاشجار وعلى المنحدرات الشرقية للمرتفعات. وفيما يتعلق بتغير مؤشر NDVI بين عامي 2001 و 2021 ، أظهرت النتائج تغيراً إيجابياً ملحوظاً في مؤشر NDVI حوالي 90.91٪ من مساحة الضفة الغربية (5132.304 كيلومتر مربع)، بينما 9.09٪ فقط (513.405 كيلومتر مربع) والتي تمثل بشكل رئيسي المراكز العمرانية، لديها تغير سلبي. السبب الرئيسي في كون مؤشر النبات في عام 2021 كان اعلى من عام 2001 خارج حدود المناطق العمرانية هو ان كمية الامطار كانت اعلى في ذلك العام، وخاصة في المناطق الشمالية. تم إنتاج الخرائط الموضوعية NDVI للتاريخين، وتم استخلاص التغييرات في الغطاء النباتي من الخرائط الأربع. بناء على النتائج، فان الدراسة توصي اصحاب القرار في وزارة الزراعة والمؤسسات البيئية بتطوير خطط لزيادة المساحات الخضراء في الضفة الغربية، خاصة في المناطق الجافة وشبه الجافة.
... Given the monitoring mission at an hourly scale, geostationary satellites do us a favor. For instance, the new generation geostationary meteorological satellite of Japan, Himawari-8 [15], was launched on July 2, 2015, and the satellite-derived hourly aerosol optical depth (AOD) product has been routinely released, which can be used as a major predictor to estimate PM2.5 concentrations [16,17,13]. The relationship between AOD and PM2.5 has been extensively investigated, and a number of models were developed, including simulation-based models [18], semi-physical models [19,20], and statisticalbased models [21][22][23][24]. ...
Hourly monitoring of ground-level fine particulate matter (PM2.5) concentrations forms the basis to assess the short-term PM2.5 exposure and make rapid responses to pollution events. Satellite remote sensing and ground monitoring stations are able to measure hourly PM2.5 concentrations, but both of them have strengths and weaknesses: the former features wide spatial coverage, whereas displaying a discontinuous timeline as the retrievals have numerous gaps; conversely, the latter allows for temporally continuous monitoring, but with a limited spatial range around stations being reflected. Thus, efforts are required to map ground-level PM2.5 at an hourly scale with spatiotemporal continuity. In this study, we developed a framework to generate hourly seamless PM2.5 estimates by integrating the aforementioned two data sources with complementary spatiotemporal traits. The satellite-derived aerosol optical depth (AOD) acquisitions are converted along with auxiliary predictors to retrieve ground-level PM2.5, and then the missing gaps in the retrievals are filled by fusing the satellite-based retrievals and station-based measurements. Meanwhile, we proposed a promising approach to fill the gaps by combining an adapted spatiotemporal fusion model and an error correction method. The validity of the proposed method is confirmed by mapping hourly PM2.5 distributions for 2016 in the Wuhan urban agglomeration (WUA), China. The proposed reconstruction method achieved R2 (RMSE) of 0.87 (6.50 g/m3) and 0.82 (15.01 g/m3) in the area-based and point-based evaluation, respectively, indicating an excellent model performance. The presented framework maps hourly ground-level PM2.5 with spatiotemporal continuity and satisfactory accuracy, and represents an important step towards near real-time monitoring.
... ICTs are also used for the collection of rainfall data from stations installed at various points, equipped with sensors connected to the internet by routers, which send reports of precipitation levels (Rettig et al., 2014). In another work, RS relates black pixels to volumes of aerosol (gases harmful to the environment) through satellite images (Themistocleous;Hadjimitsis, 2013). Also, it is remakable that the themes of land and environment use and occupation were frequently associated throughout the texts read, reinforcing the strong relationship between territoriality and the natural landscape. ...
... ICTs are also used for the collection of rainfall data from stations installed at various points, equipped with sensors connected to the internet by routers, which send reports of precipitation levels (Rettig et al., 2014). In another work, RS relates black pixels to volumes of aerosol (gases harmful to the environment) through satellite images (Themistocleous;Hadjimitsis, 2013). Also, it is remakable that the themes of land and environment use and occupation were frequently associated throughout the texts read, reinforcing the strong relationship between territoriality and the natural landscape. ...
This research aims ats the analysis of the academic-scientific framework of the studies related to the new technological and innovative solutions applied in the process of planning for the improvement of the quality of urban landscape. From this perspective, its specific objectives are: to broaden the mapping of the debate on technologies and innovations that are essential to the correct interpretation of the central subject, and to develop subsidies for management, planning and design for appropriate urban landscape treatment within the framework of municipal master plans (MMPs) and the democratic administration of urbanized spaces. The research was developed in three main phases, including exploratory, descriptive and analytical methods. The first one - extension of the mapping, linked to the first specific objective - promoted the examination of theoretical and methodological references for understanding the theme. Thus, it was concentrated in the bibliographic consultation and in the bibliometric inference of papers available in the Journal Portal of the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES - Coordination of Improvement of Personnel of Higher Level) of 2001 - year of edition of the City Statute - until 2016 - first cicle of MMPs. The search of the articles was performed by inserting pairs of keywords in three languages (English, Portuguese and Spanish), and after that, submiting them to different selection criteria, therefore forming a set with a direct approach to the subjects of interest. Next, the most relevant were interpreted, cataloging them according to typologies of technology and innovation, secondary themes associated to the main ones, and geographic determination of the cases, thus allowing realization of the final stage of subsidy development. The main results point, in the first place, at deficiencies in scientific scenario of Brazil, regarding both the quoted portal, as well as the quantitative representativeness of Brazilian studies. On the other hand, it is possible to verify that geographic information system (GIS) is already consolidated in urban planning as the most widely used alternative, while information and communication technologies (ICTs) constitute the future trend in terms of public management and integration of the population. Furthermore, innovative processes are associated with analysis of regions’ economic improvement, whilist debates on technological options address themes such as urbanistic growth models, urban expansion forecasting and integrated development. It is also diagnosed the association of these subjects with both ‘smart cities’ - aiming at the digitization of citizens' experiences, as well as ‘geodesign’ - evidencing the propensity for territorial plans. Therefore, it is concluded that there is a need for greater investments in scientific research in Brazil, considering its lag with respect to other countries and the imperative of integrating technological typologies, with a broader digitalization of procedures related to city management, thus, producing important reflections on the context of the project and planning of cities landscape.
... The existing ERC has an extensive capacity related to the development of atmospheric correction algorithms for remote sensing data as well in the calibration of remote sensing data using test fields [4][5][6]. Indeed, this is a beneficial tool for the EMMENA region for the accuracy assessment of all the space-based applications. In the technical report released by Copernicus/ESA 'Copernicus data Quality Control -Technical Note Atmospheric Corrections' [7], four publications on atmospheric corrections by members of ERC [i.e., [8][9][10][11] are listed as key references for guidelines. ...
This paper presents the pathway towards the establishment of the ERATOSTHENES Centre of Excellence (ECoE), through the upgrade of the existing Remote Sensing & Geo-Environment Group - ERATOSTHENES Research Centre (ERC), within the Cyprus University of Technology (CUT). The ECoE aspires to become a sustainable, viable and autonomous Centre of Excellence for Earth Surveillance and Space-Based Monitoring of the Environment. The ECoE will provide the highest quality of related services in the National, European, Eastern Mediterranean and Middle East and Northern Africa areas (EMMENA). Therefore, drawing on the capitalization of experience and knowledge from previous projects and the research areas and international networks of the ERC, this papers highlights the importance of the establishment of the ECoE in the EMMENA area.
... The integrated use of remote sensing techniques with other auxiliary methods, such as field spectroscopy and geospatial tools is an additional research activity of ERC. Lastly, the Centre has a great experience in the pre-processing of satellite imagery, with emphasis on the development of novel atmospheric correction methods [26][27][28][29][30][31][32] as well as expertise on calibration using test fields. Indeed, in the technical report released by Copernicus /ESA 'Copernicus data Quality Control -Technical Note Atmospheric Corrections' (see [33]), four publications on atmospheric corrections by members of ERC [i.e., [30][31][32] are listed as key references for guidelines. ...
... Research indicates that the determined AOT from satellite image data can be used as a tool to assess air pollution as well as identify the sources of local emissions [2,7,[11][12][13][14][15][16][17][18][19][20][21][22][23][24]. AOT values can be used as a way of measuring air quality; determining AOT in large-scale pollution areas provides a synoptic, cost-effective means to further assess the air quality in such areas [16,[18][19][20][21][22][23][24]. ...
... The image-based integrated method presented in this chapter can accurately calculate AOT values retrieved from satellite imagery by using radiative transfer (RT) equations and GIS. The method can be used to visually display AOT levels using thematic maps in order to identify concentrations of AOT over an urban area [11]. The image-based method can also be used with archived satellite images, thereby providing detailed information regarding spatial aerosol concentration overtime [11]. ...
... The method can be used to visually display AOT levels using thematic maps in order to identify concentrations of AOT over an urban area [11]. The image-based method can also be used with archived satellite images, thereby providing detailed information regarding spatial aerosol concentration overtime [11]. ...
In this chapter, the image-based integrated method is developed to retrieve AOT values from satellite images and display these values in an urban area, using the example of Limassol, Cyprus. The findings show that the proposed integrated image-based method is able to accurately obtain AOT measurements from satellite images. The accuracy assessment shows strong agreement between the in-situ AOT values and the AOT values retrieved through the method described in the chapter. The proposed methodology is able to retrieve AOT using satellite images and visually display AOT over urban areas by using GIS to produce thematic maps. Also, the significance of the image-based integrated method is that the environmental data is not needed, as compared with other methods. This methodology is therefore an alternative to more sophisticated and complex methods of deriving AOT values from satellite images, especially where atmospheric or meteorological data are not accessible. Also, the methodology can be used with archived satellite images where environmental data are not available, thereby providing detailed information regarding spatial aerosol concentration overtime. Also, thematic maps can be generated to illustrate the distribution of AOT overtime in a specific area of interest and enabling trends to be identified.
The emerging threat for eco-sustainability has led to a breakthrough in satellite image analyses and such instantaneous monitoring of hazards could replenish the rejuvenation of natural ecosystem. Generally, the satellite images are huge dimensional data with numerous bands of specific details about the observed region. To apply immediate precautionary measures for environmental hazards and natural devastations, deploying a cloud-based intelligent web service for handling real time satellite image processing is inevitable. Therefore, the cloud implementation could afford integrated huge storage and parallel data processing tasks, the outcome of instantaneous satellite image processing relies with the effective data processing methods of less complexity. In this regard to address a major hazard of today which is drought monitoring, this paper focuses on developing an effective water segmentation method for such geospatial cloud web services. The Landsat 8 images of Sambhar lake region has been chosen for exploiting the water segmentation results. Most prevalent approaches from Spectral indices and unsupervised clustering such as normalized difference water index (NDWI), modified normalized difference water index, fuzzy C means, K-Means, Adaptive Regularized kernel fuzzy C means (ARKFCM) and simple linear iterative clustering-based superpixel segmentation (SLIC-SUPER) are compared, respectively. On comparative assessment using standard image quality assessment metrics, NDWI and ARKFCM outstands the rest with more accurate water body delineation. However, based on reduced computational complexity and instant localization, NDWI of spectral indexing approach clearly portray the significance of spectral influence in water body segmentation from satellite images. And it can be adapted as a persistent choice for instantaneous water body segmentation in a cloud-centered geospatial module.
The integration of satellite-derived aerosol optical depth (AOD) and station-measured PM2.5 (particulate matter with an aerodynamic diameter of less than 2.5 μm) provides a promising approach for the monitoring of PM2.5. Previous models have generally only considered either the spatiotemporal heterogeneities of the AOD-PM2.5 relationship or the nonlinear relationship between AOD and PM2.5. In this paper, to simultaneously allow for the nonlinearity and spatiotemporal heterogeneities of the AOD-PM2.5 relationship, the geographically and temporally weighted neural network (GTWNN) model is proposed for the satellite-based estimation of ground-level PM2.5. The GTWNN model represents the nonlinear AOD-PM2.5 relationship via a generalized regression neural network, and is separately established for individual locations and times, to address the spatiotemporal heterogeneities of the AOD-PM2.5 relationship. Meanwhile, a spatiotemporal weighting scheme is incorporated in the GTWNN model to capture the local relations of samples for the training of the AOD-PM2.5 relationship. By the use of the Moderate Resolution Imaging Spectroradiometer (MODIS) AOD product, meteorological data, and MODIS normalized difference vegetation index (NDVI) data as input, the GTWNN model was verified using ground station PM2.5 measurements from China in 2015. The GTWNN model achieved sample-based cross-validation (CV) and site-based CV R² values of 0.80 and 0.79, respectively, and it outperformed the geographically and temporally weighted regression model (CV R²: 0.75 and 0.73) and the daily geographically weighted regression model (CV R²: 0.72 and 0.72). The proposed model implements the combination of geographical law and a neural network, and will be of great use for remote sensing retrieval of environmental variables.
This work addresses the problem of detecting and classifying materials and targets in hyperspectral images based on their reflectance spectrum. Accurate target detection in hyperspectral imagery requires a radiative transfer model that maps between the spectral reflectance domain and the measured radiance domain. Such a model can be employed in two ways for detection – using atmospheric compensation, where the measured hyperspectral radiance image is converted to a reflectance image, and using forward modeling, where the target reflectance spectrum is converted to an at-sensor target radiance spectrum. This work presents a forward modeling detection method that utilizes in-scene information to estimate the parameters in the radiative transfer model. Uncertainty in the radiative transfer model and variability of the target spectra are captured using a constrained subspace model for the target. Target detection using library spectra and target rediscovery are evaluated in hyperspectral images of a complex urban scene.
The Empirical Line Method (ELM) enables the calibration of multi- and hyper-airborne/satellite image converting DN or radiance to reflectance values performed by using at ground data. High quality outcome can be reached with the selection of appropriate Pseudo-Invariant Targets (PIT). In this paper, spectral variability of “usual” (asphalt and concrete) and “unusual” (calcareous gravel, basaltic paving, concrete bricks, tartan paving and artificial turf) PITs is retrieved for ELM application. Such PITs are used to calibrate the Multispectral Infrared and Visible Imaging Spectrometer (MIVIS) airborne sensor in 12 different Runs. Firstly, processing of field spectral data enables the evaluation of pseudo-invariance of targets by studying their spectral changes in space and in time. Finally, these surfaces are used as Ground Calibration (GCT) and Validation Targets (GVT) in ELM. High calibration accuracy values are observed in Visible (VIS) range (98.9%) while a general decrease of accuracy in Near-InfraRed (NIR) (96.6%) and Middle-InfraRed (SWIR) (88.1%) are reached. Outcomes show that “usual” surfaces as asphalt and concrete and “unusual” surfaces such as tartan can be successfully used for MIVIS image calibration.
