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Identification of climatic and environmental factors associated with incidence of cutaneous leishmaniasis in Central Iran using satellite imagery

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Asian Pacific Journal of Tropical Biomedicine 2021年第1期11卷 40-46页

作者： Mohammad Javanbakht Abedin Saghafipour Keyvan Ezimand Amir Hamta Leyli Zanjirani Farahani Nazanin Soltani Department of Remote Sensing and GIS Faculty of GeographyTehran UniversityTehranIran Department of Public Health Faculty of HealthQom University of Medical SciencesQomIran Department of Remote Sensing and GIS Faculty of Earth ScienceShahid Beheshti UniversityTehranIran Department of Social Medicine Faculty of Medical SciencesQom University of medical sciencesQomIran Department of Medical Parasitology and Mycology School of Public HealthTehran University of Medical SciencesTehranIran Student Research Committee Qom University of Medical SciencesQomIran

Objective:To determine the effect of climatic and environmental factors on the incidence of cutaneous leishmaniasis in Qom province in ***:In this cross-sectional study,the data on cutaneous leishmaniasis incidence were collected from the Disease Control and Prevention Center in Qom *** and environmental data including Normalized Difference Vegetation Index(NDVI),Land Surface Temperature(LST),and soil moisture were extracted using satellite *** of altitude and sunny hours were provided based on shuttle radar topography mission digital elevation model and hemispherical viewshed algorithm,*** associations of climatic and environmental variables with the incidence of the disease were analyzed by Pearson correlation *** Arc GIS 10.3 software was used to determine the geographical distribution of these ***:There were positive correlations between cutaneous leishmaniasis incidence and the two climatic factors:LST and sunny hours per day(P=0.041,P=0.016),and it had weak negative correlations with the digital elevation model(P=0.27),soil moisture(P=0.54),and NDVI(P=0.62).The time delay analysis showed that in one-,two-,and three month periods,the correlations increased with a 95%confidence ***,the correlation with the three-month time delay was positive and relatively strong between the cutaneous leishmaniasis incidence and LST and sunny hours(P=0.027,P=0.02);nevertheless,there were negative correlations between the cutaneous leishmaniasis incidence and the soil moisture(P=0.27)and NDVI(P=0.62).Conclusions:As Qom is located in one of the semi-arid climate zones,topography and solar energy are important factors affecting the incidence of cutaneous leishmaniasis in ***,appropriate disease control programs are recommended.

关键词： Environmental factors Incidence satellite imagery Cutaneous leishmaniasis Iran

Spatio-Temporal Analysis of Landuse/Landcover Change of District Pishin Using satellite imagery and GIS

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Journal of Geographic Information System 2016年第3期8卷 361-368页

作者： Sanaullah Khan Said Qasim Romana Ambreen Zia-Ul-Haq Syed Department of Geography University of Balochistan Quetta Pakistan

Detecting change on the face of the globe using GIS (Geographic Information System) aided by remotely sensed imagery is now becoming an indispensable tool in managing the resources of our planet. The present study with the help of GIS and remote sensing (RS) is also a similar attempt in recording and quantifying change in land use and land cover in district Pishin both in spatial and temporal extents. satellite imagery was acquired from the USGS official website from three LANDSAT satellites. Theses satellites are LANDSAT 5, LANDSAT7 and LANDSAT 8. The data were acquired for the years 1992, 2003 and 2013. satellite imagery was processed in ArcMap 10.1 and maximum likelihood supervised image classification was applied in reaching the goal of detecting change. The result of the analysis revealed that built-up area was increased by 5.84%;vegetation was increased by 3.89%;water bodies were increased by 0.05% and bare surfaces were decreased by 9.78%. The decrease in the barren surfaces was attributed to the increase in vegetation and built-up area which replaced the barren land in the study area. This paper also shows the significance and potential of digital change detection methods in managing the resources of our environment and keeping an eye on the land use and land cover of our Earth.

关键词： Spatial-Temporal Land-Cover Change District Pishin GIS satellite imagery

Change Detection of Lake Chad Water Surface Area Using Remote Sensing and satellite imagery

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Journal of Geographic Information System 2021年第5期13卷 561-577页

作者： Abdel-Aziz Adam Mahamat Adeeba Al-Hurban Nehaya Saied Integrated International for Environmental Services (IIES) Kuwait City Kuwait Earth and Environmental Sciences Department Faculty of Science Kuwait University Kuwait City Kuwait

The Lake Chad located in the west-central Africa in the Sahel region at the edge of the Sahara experienced severe drought during 1970s and 1980s and overexploitation (unintegrated and unsustainable use), which is a result of variant land uses and water management practices during the last 50 years. This resulted in a decline of the water level in the Lake and surrounding rivers. The present study analyzed satellite images of Lake Chad from Landsat-MSS, Landsat-OLI to investigate the change of the open water surface area during the years of 1973, 1987, 2001, 2013, and 2017. Supervised classifications were performed for the land cover analysis. The open water area in 1973 was covering 16,157.34 km2 approximately, and that was 64.6% of the total lake area in the 1960s. As an ultimate result of the extreme drought that the study area witnessed through 1970s-1980s, the open water area has decreased to 1831.44 km2, i.e. around 11.33%, compared to that in 1973. The dilemma that the study area is suffering from is believed to be a catastrophic complication of the aforementioned drought crisis, which arose as an ultimate result the climate change, global warming, and the unintegrated and unsustainable use of water challenges the study area is still encountering.

关键词： satellite imagery Landsat Remote Sensing GIS Drought Overexploitation

Absolute pose estimation of UAV based on large-scale satellite image

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Chinese Journal of Aeronautics 2024年第6期37卷 219-231页

作者： Hanyu WANG Qiang SHEN Zilong DENG Xinyi CAO Xiaokang Wang School of Mechatronical Engineering Beijing Institute of TechnologyBeijing 100081China Beijing Institute of Technology Chongqing Innovation Center Chongqing 401120China

Obtaining absolute pose based on pre-loaded satellite images is one of the important means of autonomous navigation for small Unmanned Aerial Vehicles(UAVs)in Global Navigation satellite System(GNSS)denied *** of the previous works have tended to build Convolutional Neural Networks(CNNs)to extract features and then directly regress the pose,which will fail when solving the challenges caused by the huge viewpoint and size differences between“UAV-satellite”image pairs in real-world ***,this paper proposes a probability distribution/regression integrated deep model with the attention-guided triple fusion mechanism,which estimates discrete distributions in pose space and three-dimensional vectors in translation *** order to overcome the shortage of the relevant dataset,this paper simulates image datasets captured by UAVs with forward-facing cameras during target searching and autonomous *** effectiveness,superiority,and robustness of the proposed method are verified by simulated datasets and flight tests.

关键词： satellite imagery Unmanned Aerial Vehicle(UAV) Deep neural networks Vision navigation von Mises-Fisher distribution

Light at night and lung cancer risk:A worldwide interdisciplinary and time-series study

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Chinese Medical Journal Pulmonary and Critical Care Medicine 2024年第1期2卷 56-62页

作者： Runchen Wang Qixia Wang Jianfu Li Jianrong Zhang Shixuan Lyu Wenhao Chi Zhiming Ye Xuanzhuang Lu Ying Shi Yubin Wang Xinjian Wu Ruiyu Hu Mónica Pérez-Ríos Jianxing He Wenhua Liang Department of Thoracic Surgery and Oncology The First Affiliated Hospital of Guangzhou Medical UniversityState Key Laboratory of Respiratory DiseaseNational Clinical Research Center for Respiratory DiseaseGuangzhou Institute of Respiratory HealthGuangzhouGuangdong 510120China Department of Respiratory Disease China State Key Laboratory of Respiratory Disease and National Clinical Research Center for Respiratory DiseaseThe First Affiliated Hospital of Guangzhou Medical UniversityGuangzhouGuangdong 510120China Centre for Cancer Research&Department of General Practice Faculty of MedicineDentistry and Health SciencesUniversity of MelbourneVictorian Comprehensive Cancer CentreMelbourneVictoria 3010Australia Department of Civil Engineering University of BristolBristolBS81TRUK Academy of Mathematics and Systems Science Chinese Academy of SciencesBeijing 100190China University of Chinese Academy of Sciences Beijing 100049China Nanshan School Guangzhou Medical UniversityGuangzhouGuangdong 511436China State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing Wuhan UniversityWuhanHubei 430079China GNSS Research Center Wuhan UniversityWuhanHubei 430079China First Clinical School Guangzhou Medical UniversityGuangzhouGuangdong 511436China Preventive Medicine and Public Health Department University of Santiago de CompostelaCIBER de Epidemiología y Salud Pública(CIBERESP)Health Research Institute of Santiago de Compostela(IDIS)Santiago de CompostelaGalicia 15782Spain Southern Medical University GuangzhouGuangdong 510515China

Background:Light at night(LAN)has become a concern in interdisciplinary research in recent *** global interdisciplinary study aimed to explore the exposure-lag-response association between LAN exposure and lung cancer ***:LAN data were obtained from the Defense Meteorological satellite Program’s Operational Linescan *** of lung cancer incidence,socio-demographic index,and smoking prevalence of populations in 201 countries/territories from 1992 to 2018 were collected from the Global Burden of Disease *** correlation tests and population-weighted linear regression analysis were used to evaluate the correlation between LAN exposure and lung cancer incidence.A distributed lag nonlinear model(DLNM)was used to assess the exposure-lag effects of LAN exposure on lung cancer ***:The Spearman correlation coefficients were 0.286-0.355 and the population-weighted linear regression correlation coefficients were *** adjustment for socio-demographic index and smoking preva-lence,the Spearman correlation coefficients were 0.264-0.357 and the population-weighted linear regression correlation coefficients were *** the DLNM,the maximum relative risk was 1.04(1.02-1.06)at LAN exposure of 8.6 with a 2.6-year lag *** adjustment for socio-demographic index and smoking prevalence,the maximum relative risk was 1.05(1.02-1.07)at LAN exposure of 8.6 with a 2.4-year lag ***:High LAN exposure was associated with increased lung cancer incidence,and this effect had a specific lag *** with traditional individual-level studies,this group-level study provides a novel paradigm of effective,efficient,and scalable screening for risk factors.

关键词： Light at night satellite imagery Lung cancer Distributed lag nonlinear model(DLNM) Melatonin

An improved approach for the production of satellite-based geospatialreference imagery

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International Journal of Digital Earth 2008年第2期1卷 221-239页

作者： J.R.Gibson S.Nedelcu Canada Centre for Remote Sensing 588 Booth Street OttawaOntarioCanada

An innovative and practical satellite image product is described that is ideal for applications in Northern Canada because of its wide area coverage and mappingquality *** product is generated from a new procedure developed at the Canada Centre for Remote Sensing(CCRS)for processing Landsat 7 imagery,and by extension,imagery from other Earth Observation *** working with multiple satellite passes,each containing the equivalent of multiple scenes,the new procedure could dramatically reduce the turn-around time for generating georeferenced image products,and also increase their geometric and radiometric accuracy compared to those produced by the current *** objective of the process has been to generate satellite image mosaics covering large areas(e.g.>500000 km^(2))with uniformly distributed errors at sub-pixel *** paper discusses the theoretical basis of a photogrammetric adjustment for satellite imagery and the results obtained from several *** process is generic,involving a sensor model,a satellite orbit model and ground control information;thus it may be easily adapted to any satellite that allows for repeat coverage with overlapping *** performing an adjustment to correct the satellite position and attitude data prior to the production of orthoimage products,it is possible to create a mosaic with a single resampling process which minimises both the radiometric and geometric resampling *** results from three separate tests are presented,along with a discussion of the procedures that were followed in each *** three tests have successfully demonstrated that sub-pixel sample size errors may be consistently obtained over large areas.A by-product process developed to support the measurement of ground control point coordinates for the satellite adjustment was the automatic matching of geographic features such as lakes and islands in vector data *** has been a significant development in that it has e

关键词： satellite imagery photogrammetric geometric accuracy radiometric accuracy large area mosaics automatic registration

Mapping Air Quality Using Remote Sensing Technology: A Case Study of Nairobi County

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Open Journal of Air Pollution 2024年第1期13卷 1-22页

作者： Quinto Juma Meltus Faith Njoki Karanja Geospatial Engineering Department The University of Nairobi (UoN) Nairobi Kenya Data Management Modeling and Geoinformation Unit (DMMG) International Centre of Insect Physiology and Ecology (ICIPE) Nairobi Kenya

Nairobi County experiences rapid industrialization and urbanization that contributes to the deteriorating state of air quality, posing a potential health risk to its growing population. Currently, in Nairobi County, most air quality monitoring stations use low-cost, inaccurate monitors prone to defects. The study’s objective was to map Nairobi County’s air quality using freely available remotely sensed imagery. The Air Pollution Index (API) formula was used to characterize the air quality from cloud-free Landsat satellite images i.e., Landsat 5 TM, Landsat 7 ETM+, and Landsat 8 OLI from Google Earth Engine. The API values were computed based on vegetation indices namely NDVI, TVI, DVI, and the SWIR1 and NIR bands on the QGIS platform. Qualitative accuracy assessment was done using sample points drawn from residential, industrial, green spaces, and traffic hotspot categories, based on a passive-random sampling technique. In this study, Landsat 5 API imagery for 2010 provided a reliable representation of local conditions but indicated significant pollution in green spaces, with recorded values ranging from -143 to 334. The study found that Landsat 7 API imagery in 2002 showed expected results with the range of values being -55 to 287, while Landsat 8 indicated high pollution levels in Nairobi. The results emphasized the importance of air quality factors in API calibration and the unmatched spatial coverage of satellite observations over ground-based monitoring techniques. The study recommends the recalibration of the API formula for characteristic regions, exploring newer satellite sensors like those onboard Landsat 9 and Sentinel 2, and involving key stakeholders in a discourse to develop a suitable Kenyan air quality index.

关键词： Air Quality Air Pollution Index (API) satellite imagery Vegetation Indices Nairobi County

Overcast sky condition prevails on and influences the biometeorology of the tropical Andean Páramos

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Journal of Mountain Science 2023年第1期20卷 78-86页

作者： Paola MONTENEGRO-DÍAZ Rolando CELLERIALVEAR Galo CARRILLO-ROJAS Departamento de Recursos Hídricos y Ciencias Ambientales Universidad de CuencaCuenca010207Ecuador Facultad de Ingeniería Universidad de CuencaCuenca010207Ecuador Facultad de Ciencias Químicas Universidad de CuencaCuenca010207Ecuador

Clouds play a major role in modulating the biometeorological processes. We studied the influence of cloudiness on four biometeorological variables:daily air temperature(Tair), relative humidity(RH),reference evapotranspiration(ETr),and photosynthetic active radiation(PAR), recorded at four sites of Andean Páramos in southern Ecuador during 2.5 to 5.5 years. First, we quantified both the cloud cover percentage(Cloud%) creating cloud masks over the visible bands of Landsat 7 images and the sky condition(K_(T)) using the records of solar and extraterrestrial radiation. Second, we estimated KTfrom Cloud%. Finally, we quantified T_(air), RH, ET_(r), and PAR under clear, cloudy, and overcast K_(T) and their dependence on KT. The average Cloud% ranged between 65%–76%, and KTcorroborated the prevailing overcast sky(between 55% and 72.5% of the days) over the páramos. The proposed model performed well in the sites of calibration(R^(2)= 0.80;MBE = 0.00;RMSE = 0.05) and validation(R^(2)= 0.74;MBE =-0.07;RMSE = 0.11). The overcast sky diminished T_(air)(≤ 10℃), ET_(r)(≤ 1.6 mm day-1), and PAR(4 MJ m^(-2)day^(-1)) and increased RH(≥ 88%),while the variables showed the opposite behavior during the uncommon clear sky(≤ 5.5% of the days).Thus, mostly the dynamic of RH(R^(2)≥ 0.62), ETr(R^(2)≥ 0.85), and PAR(R2≥ 0.77) depended on K_(T). Hence,the prevailing overcast sky influenced the biometeorology of the páramos.

关键词： Cloudiness indicator Clearness index satellite imagery Tropical Andes

Deep Neural Network Based Detection and Segmentation of Ships for Maritime Surveillance

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Computer Systems Science & Engineering 2023年第1期44卷 647-662页

作者： Kyamelia Roy Sheli Sinha Chaudhuri Sayan Pramanik Soumen Banerjee Department of Electronics and Tele-Communication Engineering Jadavpur UniversityKolkata700032India Department of Electronics and Communication Engineering University of Engineering and ManagementKolkata700160India

In recent years,computer visionfinds wide applications in maritime surveillance with its sophisticated algorithms and advanced ***-matic ship detection with computer vision techniques provide an efficient means to monitor as well as track ships in water *** being an important medium of transport require continuous monitoring for protection of national *** remote sensing satellite images of ships in harbours and water bodies are the image data that aid the neural network models to localize ships and to facilitate early identification of possible threats at *** paper proposes a deep learning based model capable enough to classify between ships and no-ships as well as to localize ships in the original images using bounding box ***,classified ships are again segmented with deep learning based auto-encoder *** proposed model,in terms of classification,provides suc-cessful results generating 99.5%and 99.2%validation and training accuracy *** auto-encoder model also produces 85.1%and 84.2%validation and training *** the IoU metric of the segmented images is found to be of 0.77 *** experimental results reveal that the model is accu-rate and can be implemented for automatic ship detection in water bodies consid-ering remote sensing satellite images as input to the computer vision system.

关键词： Auto-encoder computer vision deep convolution neural network satellite imagery semantic segmentation ship detection