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1.
Environ Sci Pollut Res Int ; 28(3): 3644-3659, 2021 Jan.
Artigo em Inglês | MEDLINE | ID: mdl-32929670

RESUMO

Drought is a major natural disaster that significantly impacts the susceptibility and flexibility of the ecosystem by changing vegetation phenology and productivity. This study aimed to investigate the impact of extreme climatic variation on vegetation phenology and productivity over the four sub-regions of China from 2000 to 2017. Daily rain gauge precipitation and air temperature datasets were used to estimate the trends, and to compute the standardized precipitation-evapotranspiration index (SPEI). Remote sensing-based Enhanced Vegetation Index (EVI) data from a moderate resolution imaging spectroradiometer (MODIS) was used to characterize vegetation phenology. The results revealed that (1) air temperature had significant increasing trends (P < 0.05) in all sub-regions. Precipitation showed a non-significant increasing trend in Northwest China (NWC) and insignificant decreasing trends in North China (NC), Qinghai Tibet area (QTA), and South China (SC). (2) Integrated enhanced vegetation index (iEVI) and SPEI variations depicted that 2011 and 2016 were the extremely driest and wettest years during 2000-2017. (3) Rapid changes were observed in the vegetation phenology and productivity between 2011 and 2016. In 2011, changes in the vegetation phenology with the length of the growing season (ΔLGS) = was - 14 ± 36 days. In 2016, the overall net effect changed at the onset and end of the growing season with ΔLGS of 34 ± 71 days. The change in iEVI per SPEI increased rapidly with a changing rate of 0.16 from arid (NWC, and QTA) to semi-arid (NWC, QTA and NC) and declined with a rate of - 0.04 from semi-humid (QTA, NC, and SC) to humid (SC) region. A higher association was observed between iEVI and SPEI as compared to iEVI and precipitation. Our finding exposed that north China is more sensitive to climatic variation.


Assuntos
Ecossistema , Tecnologia de Sensoriamento Remoto , China , Mudança Climática , Imagens de Satélites , Estações do Ano , Temperatura , Tibet
2.
Environ Monit Assess ; 192(12): 808, 2020 Dec 02.
Artigo em Inglês | MEDLINE | ID: mdl-33263783

RESUMO

Assessment of chlorophyll-a, an algal pigment, typically measured by field and laboratory in situ analyses, is used to estimate algal abundance and trophic status in lakes and reservoirs. In situ-based monitoring programs can be expensive, may not be spatially, and temporally comprehensive and results may not be available in the timeframe needed to make some management decisions, but can be more accurate, precise, and specific than remotely sensed measures. Satellite remotely sensed chlorophyll-a offers the potential for more geographically and temporally dense data collection to support estimates when used to augment or substitute for in situ measures. In this study, we compare available chlorophyll-a data from in situ and satellite imagery measures at the national scale and perform a cost analysis of these different monitoring approaches. The annual potential avoided costs associated with increasing the availability of remotely sensed chlorophyll-a values were estimated to range between $5.7 and $316 million depending upon the satellite program used and the timeframe considered. We also compared sociodemographic characteristics of the regions (both public and private lands) covered by both remote sensing and in situ data to check for any systematic differences across areas that have monitoring data. This analysis underscores the importance of continued support for both field-based in situ monitoring and satellite sensor programs that provide complementary information to water quality managers, given increased challenges associated with eutrophication, nuisance, and harmful algal bloom events.


Assuntos
Lagos , Tecnologia de Sensoriamento Remoto , Clorofila/análise , Clorofila A/análise , Monitoramento Ambiental
3.
Environ Pollut ; 267: 115456, 2020 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-33254715

RESUMO

On-road remote sensing (RS) is a rapid, non-intrusive and economical tool to monitor and control the emissions of in-use vehicles, and currently is gaining popularity globally. However, a majority of studies used a single RS technique, which may bias the measurements since RS only captures a snapshot of vehicle emissions. This study aimed to use a unique dual RS technique to assess the characteristics of on-road vehicle emissions. The results show that instantaneous vehicle emissions are highly dynamic under real-world driving conditions. The two emission factors measured by the dual RS technique show little correlation, even under the same driving condition. This indicates that using the single RS technique may be insufficient to accurately represent the emission level of a vehicle based on one measurement. To increase the accuracy of identifying high-emitting vehicles, using the dual RS technique is essential. Despite little correlation, the dual RS technique measures the same average emission factors as the single RS technique does when a large number of measurements are available. Statistical analysis shows that both RS systems demonstrate the same Gamma distribution with ≥200 measurements, leading to converged mean emission factors for a given vehicle group. These findings point to the need for a minimum sample size of 200 RS measurements in order to generate reliable emission factors for on-road vehicles. In summary, this study suggests that using the single or dual RS technique will depend on the purpose of applications. Both techniques have the same accuracy in calculating average emission factors when sufficient measurements are available, while the dual RS technique is more accurate in identifying high-emitters based on one measurement only.


Assuntos
Poluentes Atmosféricos , Condução de Veículo , Monitoramento Ambiental , Veículos Automotores , Tecnologia de Sensoriamento Remoto , Projetos de Pesquisa , Tamanho da Amostra , Emissões de Veículos
4.
Ying Yong Sheng Tai Xue Bao ; 31(11): 3795-3804, 2020 Nov.
Artigo em Chinês | MEDLINE | ID: mdl-33300730

RESUMO

The arid area is mainly composed of desert, with fragile eco-environment and being extremely vulnerable to the influence of natural and human perturbations. Based on the remote sen-sing ecological index (RSEI), the arid remote sensing ecological index (ARSEI) was formed to improve the remote sensing ecological index for arid area, which was coupled with the information of greenness, humidity, salinity, heat and land degradation to quantitatively evaluate the eco-environment quality. We used ARSEI and RSEI to dynamically monitor and evaluate the eco-environment quality of Ulan Buh Desert from 2000 to 2019, and analyzed their differences and their applicability in arid area. We further examined the characteristics and reasons of the temporal and spatial variations of the eco-environment quality of Ulan Buh Desert. The results showed that the ARSEI index had better applicability to the eco-environment quality in arid area than the RSEI, and it enhanced the role of land use changes in the ecological environment quality assessment. From 2000 to 2019, the overall eco-environmental quality of Ulan Buh Desert was worse. The parts under better, good, and medium grades were mainly distributed in the northern region, the parts with worse grades were mainly concentrated in the gobi and sandy land, and the poor ones were mainly located in area with low coverage vegetation. From 2000 to 2019, the overall quality of the eco-environment in the Ulan Buh Desert were becoming better. Meanwhile, the eco-environment quality of towns and farms in the northern part of the desert changed complexly, with deterioration and improvement alternately distributed. The main reason for the changes in the eco-environment of Ulan Buh Desert was the positive effects of ecological agriculture and sand industry.


Assuntos
Ecossistema , Tecnologia de Sensoriamento Remoto , Cidades , Clima Desértico , Monitoramento Ambiental , Humanos
5.
Environ Monit Assess ; 192(12): 798, 2020 Dec 01.
Artigo em Inglês | MEDLINE | ID: mdl-33263174

RESUMO

The existing drought monitoring mechanisms in the sub-Saharan Africa region mostly depend on the conventional methods of drought monitoring. These methods have limitations based on timeliness, objectivity, reliability, and adequacy. This study aims to identify the spread and frequency of drought in Nigeria using Remote Sensing/Geographic Information Systems techniques to determine the areas that are at risk of drought events within the country. The study further develops a web-GIS application platform that provides drought early warning signals. Monthly NOAA-AVHRR Pathfinder NDVI images of 1 km by 1 km spatial resolution and MODIS with a spatial resolution of 500 m by 500 m were used in this study together with rainfall data from 25 synoptic stations covering 32 years. The spatio-temporal variation of drought showed that drought occurred at different times of the year in all parts of the country with the highest drought risk in the north-eastern parts. The map view showed that the high drought risk covered 5.98% (55,312 km2) of the country's landmass, while low drought risk covered 42.4% (391,881 km2) and very low drought risk areas 51.5% (476,578 km2). Results revealed that a strong relationship exists between annual rainfall and season-integrated NDVI (r2 = 0.6). Based on the spatio-temporal distribution and frequency of droughts in Nigeria, drought monitoring using remote sensing techniques of VCI and NDVI could play an invaluable role in food security and drought preparedness. The map view from the web-based drought monitoring system, developed in this study, is accessible through localhost.


Assuntos
Secas , Tecnologia de Sensoriamento Remoto , Monitoramento Ambiental , Nigéria , Reprodutibilidade dos Testes
6.
PLoS One ; 15(11): e0242554, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-33232344

RESUMO

The negative air ion (NAI) concentration is an essential indicator of air quality and atmospheric pollution. The NAI concentration can be used to monitor air quality on a regional scale and is commonly determined using field measurements. However, obtaining these measurements is time-consuming. In this paper, the relationship between remotely sensed surface parameters (such as land surface temperature, normalized difference vegetation index (NDVI), and leaf area index) obtained from MODIS data products and the measured NAI concentration using a stepwise regression method was analyzed to estimate the spatial distribution of the NAI concentration and verify the precision. The results indicated that the NAI concentration had a negative correlation with temperature, leaf area index (LAI), and gross primary production while it exhibited a positive correlation with the NDVI. The relationship between land surface temperature and the NAI concentration in the Daxing'anling region is expressed by the regression equation of y = -35.51x1 + 11206.813 (R2 = 0.6123). Additionally, the NAI concentration in northwest regions with high forest coverage was higher than that in southeast regions with low forest coverage, suggesting that forests influence the air quality and reduce the impact of environmental pollution. The proposed inversion model is suitable for evaluating the air quality in Daxing'anling and provides a reference for air quality evaluation in other areas. In the future, we will expand the quantity and distribution range of sampling points, conduct continuous observations of NAI concentrations and environmental parameters in the research areas with different land-use types, and further improve the accuracy of inversion results to analyze the spatiotemporal dynamic changes in NAI concentration and explore the possibility of expanding the application areas of NAI monitoring.


Assuntos
Ionização do Ar , Poluição do Ar , Ânions/análise , Modelos Teóricos , Imagens de Satélites , Altitude , China , Florestas , Oxigênio/análise , Tecnologia de Sensoriamento Remoto , Amostragem
7.
PLoS One ; 15(11): e0241981, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-33166359

RESUMO

Mobile sensing data has become a popular data source for geo-spatial analysis, however, mapping it accurately to other sources of information such as statistical data remains a challenge. Popular mapping approaches such as point allocation or voronoi tessellation provide only crude approximations of the mobile network coverage as they do not consider holes, overlaps and within-cell heterogeneity. More elaborate mapping schemes often require additional proprietary data operators are highly reluctant to share. In this paper, I use human settlement information extracted from publicly available satellite imagery in combination with stochastic radio propagation modelling techniques to account for that. I show in a simulation study and a real-world application on unemployment estimates in Senegal that better coverage approximations do not necessarily lead to better outcome predictions.


Assuntos
Telefone Celular , Tecnologia de Sensoriamento Remoto/métodos , Sistemas de Informação Geográfica , Humanos , Armazenamento e Recuperação da Informação , Imagens de Satélites , Senegal
8.
PLoS One ; 15(11): e0241066, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-33175888

RESUMO

One of the most remarkable groups of deep-sea squids is the Magnapinnidae, known for their large fins and strikingly long arm and tentacle filaments. Little is known of their biology and ecology as most specimens are damaged and juvenile, and in-situ sightings are sparse, numbering around a dozen globally. As part of a recent large-scale research programme in the Great Australian Bight, Remotely Operated Vehicles and a towed camera system were deployed in depths of 946-3258 m resulting in five Magnapinna sp. sightings. These represent the first records of Bigfin Squid in Australian waters, and more than double the known records from the southern hemisphere, bolstering a hypothesis of cosmopolitan distribution. As most previous observations have been of single Magnapinna squid these multiple sightings have been quite revealing, being found in close spatial and temporal proximity of each other. Morphological differences indicate each sighting is of an individual rather than multiple sightings of the same squid. In terms of morphology, previous in-situ measurements have been roughly based on nearby objects of known size, but this study used paired lasers visible on the body of a Magnapinna squid, providing a more accurate scaling of size. Squid of a juvenile size were also recorded and are confirmed to possess the long distal filaments which have thus far been mostly missing from specimens due to damage. We have described fine-scale habitat, in-situ colouration, and behavioural components including a horizontal example of the 'elbow' pose, and coiling of distal filaments: a behaviour not previously seen in squid. These sightings add to our knowledge of this elusive and intriguing genus, and reinforce the value of imagery as a tool in deep-sea squid research.


Assuntos
Distribuição Animal , Comportamento Animal/fisiologia , Decapodiformes/fisiologia , Animais , Austrália , Técnicas de Observação do Comportamento/instrumentação , Técnicas de Observação do Comportamento/métodos , Decapodiformes/anatomia & histologia , Tecnologia de Sensoriamento Remoto/instrumentação , Tecnologia de Sensoriamento Remoto/métodos , Gravação em Vídeo
9.
Environ Monit Assess ; 192(12): 784, 2020 Nov 25.
Artigo em Inglês | MEDLINE | ID: mdl-33241472

RESUMO

Changes in vegetation land cover are influenced by, and therefore an indicator of, climatic conditions. The aim of this study is to investigate the relationship between vegetation cover changes and drought events in a small-scale area. Six Landsat images during 1987-2019 were used to extract information about the vegetation land cover changes using the normalized difference vegetation index (NDVI) and the fractional vegetation cover (FVC) in Balqarn Governorate in the northern mountains of Asir, Saudi Arabia. Two climatic parameters, temperature and precipitation, were used as time series for the same period and were decomposed to investigate the seasonal and trend changes for each parameter. The two parameters were also used to calculate the standardized precipitation evapotranspiration index (SPEI) to conduct an in-depth analysis of the drought events influencing vegetation cover. The results showed that the state of the vegetation coverage of the study area remained at a medium level with an average NDVI value, but the FVC values showed evidence of dynamic variability associated with drought and moisture events. The SPEI showed that the study area has been undergoing a long-duration drought event since 2004, ranging from light to severe drought, which was consistent with the time series decomposition results. This investigation has revealed that drought drives changes in vegetation cover and is expressed on small geographic scales as changes in the vegetation cover structure. The framework described here is simple and can be used to evaluate and manage drought risks.


Assuntos
Secas , Tecnologia de Sensoriamento Remoto , Monitoramento Ambiental , Arábia Saudita , Temperatura
10.
Nat Commun ; 11(1): 5995, 2020 11 25.
Artigo em Inglês | MEDLINE | ID: mdl-33239609

RESUMO

Infectious diseases are worldwide a major cause of morbidity and mortality. Fast and specific detection of pathogens such as bacteria is needed to combat these diseases. Optimal methods would be non-invasive and without extensive sample-taking/processing. Here, we developed a set of near infrared (NIR) fluorescent nanosensors and used them for remote fingerprinting of clinically important bacteria. The nanosensors are based on single-walled carbon nanotubes (SWCNTs) that fluoresce in the NIR optical tissue transparency window, which offers ultra-low background and high tissue penetration. They are chemically tailored to detect released metabolites as well as specific virulence factors (lipopolysaccharides, siderophores, DNases, proteases) and integrated into functional hydrogel arrays with 9 different sensors. These hydrogels are exposed to clinical isolates of 6 important bacteria (Staphylococcus aureus, Escherichia coli,…) and remote (≥25 cm) NIR imaging allows to identify and distinguish bacteria. Sensors are also spectrally encoded (900 nm, 1000 nm, 1250 nm) to differentiate the two major pathogens P. aeruginosa as well as S. aureus and penetrate tissue (>5 mm). This type of multiplexing with NIR fluorescent nanosensors enables remote detection and differentiation of important pathogens and the potential for smart surfaces.


Assuntos
Infecções Bacterianas/diagnóstico , Nanotubos de Carbono/química , Testes Imediatos , Tecnologia de Sensoriamento Remoto/instrumentação , Infecções Bacterianas/microbiologia , Diagnóstico Diferencial , Escherichia coli/isolamento & purificação , Fluorescência , Humanos , Hidrogéis/química , Pseudomonas aeruginosa/isolamento & purificação , Espectroscopia de Luz Próxima ao Infravermelho/instrumentação , Staphylococcus aureus/isolamento & purificação , Líquido Sinovial/microbiologia
11.
IEEE Pulse ; 11(5): 24-27, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-33064641

RESUMO

Citizens' dissatisfaction with the scope of the United States health care system has been a hot topic for many years. In a country where patient to nurse ratios remain 6:1, even universal health care coverage cannot guarantee adequate patient care. These issues were further highlighted by the COVID-19 pandemic, where inadequate hospital funding and lack of attention to patients led to challenging situations in hotspot areas. Although this pandemic will shape us for many years to come with far reaching impacts, social distancing norms have accelerated technologies that enable services to be delivered remotely, a capability even more necessary in our health care system. By providing care that can be delivered remotely, we can focus in-person care in our hospitals to only the ones who really need it. This allows us to scale our systems, protect lives, and safeguard economic activity.


Assuntos
Assistência à Saúde , Internet das Coisas , Betacoronavirus , Infecções por Coronavirus/epidemiologia , Infecções por Coronavirus/terapia , Redução de Custos , Assistência à Saúde/economia , Equipamentos e Provisões , Humanos , Monitorização Fisiológica/métodos , Monitorização Fisiológica/estatística & dados numéricos , Pandemias , Pneumonia Viral/epidemiologia , Pneumonia Viral/terapia , Tecnologia de Sensoriamento Remoto , Transportes , Estados Unidos/epidemiologia , Gerenciamento de Resíduos
12.
J Biomed Opt ; 25(10)2020 10.
Artigo em Inglês | MEDLINE | ID: mdl-33089674

RESUMO

SIGNIFICANCE: The COVID-19 pandemic is changing the landscape of healthcare delivery in many countries, with a new shift toward remote patient monitoring (RPM). AIM: The goal of this perspective is to highlight the existing and future role of wearable and RPM optical technologies in an increasingly at-home healthcare and research environment. APPROACH: First, the specific changes occurring during the COVID-19 pandemic in healthcare delivery, regulations, and technological innovations related to RPM technologies are reviewed. Then, a review of the current state and potential future impact of optical physiological monitoring in portable and wearable formats is outlined. RESULTS: New efforts from academia, industry, and regulatory agencies are advancing and encouraging at-home, portable, and wearable physiological monitors as a growing part of healthcare delivery. It is hoped that these shifts will assist with disease diagnosis, treatment, management, recovery, and rehabilitation with minimal in-person contact. Some of these trends are likely to persist for years to come. Optical technologies already account for a large portion of RPM platforms, with a good potential for future growth. CONCLUSIONS: The biomedical optics community has a potentially large role to play in developing, testing, and commercializing new wearable and RPM technologies to meet the changing healthcare and research landscape in the COVID-19 era and beyond.


Assuntos
Infecções por Coronavirus , Pandemias , Pneumonia Viral , Telemedicina , Dispositivos Eletrônicos Vestíveis , Betacoronavirus , Redes de Comunicação de Computadores , Humanos , Tecnologia de Sensoriamento Remoto
13.
Annu Int Conf IEEE Eng Med Biol Soc ; 2020: 4151-4155, 2020 07.
Artigo em Inglês | MEDLINE | ID: mdl-33018912

RESUMO

To build a system for monitoring elderly people living alone, an important step needs to be done: identifying the presence/absence of the person being monitored and his location. Such task has several applications that we discuss in this paper, and remains very important. Several techniques were proposed in the literature. However, most of them suffer from issues related to privacy, coverage or convenience. In the current paper, we propose an infrared array sensor-based approach to detect the presence/absence of a person in a room. We used a wide angle low resolution sensor (i.e., 32×24 pixels) to collect heat-related information from the area monitored, and used Deep Learning (DL) to identify the presence of up to 3 people with an accuracy reaching 97%. Our approach also detects of the presence or absence of a person with a 100% accuracy. Nevertheless, it allows identifying the location of the detected people within a room of dimensions 4×7.4 m with a margin of 0.3 m.


Assuntos
Aprendizado Profundo , Nível de Saúde , Tecnologia de Sensoriamento Remoto , Idoso , Temperatura Alta , Humanos , Monitorização Fisiológica , Características de Residência
14.
Mar Pollut Bull ; 161(Pt B): 111770, 2020 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-33120037

RESUMO

A dinoflagellate under the ambit of Harmful Algal Blooms (HAB), the bioluminescent Noctiluca scintillans (NS), has been infesting the northern Arabian Sea increasingly over the last few decades during late winter. Their occurrence is found to be due to seasonal oscillations in the coastal currents. The physical and biogeochemical parameters associated with the seasonal blooms are reasonably well known. But accurate quantitative estimation capability using remote sensing sensors over the extensive oceanic regime is still lacking. This is especially due to a lack of information on bio-optical properties associated with cell density measurements. We attempted to show that remote sensing reflectance and chl-a show significant relationship e.g., Rrs(531)/Rrs(510) = 0.8261 + 6.06 × 10-6NS + 0.02323chl-a (N = 19, R2adj = 0.99, p = 2.5 × 10-17, RMSE = 0.1083) which is applicable over diverse areas of the northeastern Arabian Sea e.g., coastal, shelf and offshore regions. The model is supported by a second dataset with an RMSE of 0.022893 (N = 8) for the Rrs(531)/Rrs(510) ratio. The NS cell densities were derived from the Rrs(510)/Rrs(531) band ratio within reasonable error and accuracy limits. Including sensor capability at 510 nm is suggested in future satellite launches.


Assuntos
Dinoflagelados , Fitoplâncton , Contagem de Células , Monitoramento Ambiental , Oceanos e Mares , Tecnologia de Sensoriamento Remoto
15.
Environ Monit Assess ; 192(11): 695, 2020 Oct 11.
Artigo em Inglês | MEDLINE | ID: mdl-33040184

RESUMO

In the present paper, land use/land cover (LULC) change was predicted in the Greater Isfahan area (GIA), central Iran. The GIA has been growing rapidly in recent years, and attempts to simulate its spatial expansion would be essential to make appropriate decisions in LULC management plans and achieve sustainable development. Several modeling tools were employed to outline sustainable scenarios for future dynamics of LULCs in the region. Specifically, we explored past LULC changes in the study area from 1996 to 2018 and predicted its future changes for 2030 and 2050. For this purpose, we performed object-oriented and decision tree techniques on Landsat and Sentinel-2 satellite images. The CA-Markov hybrid model was utilized to analyze past trends and predict future LULC changes. LULC changes were quantitatively measured using landscape metrics. According to the results, the majority of changes were related to increasing residential areas and decreasing irrigated lands. The results indicated that residential lands would grow from 27,886.87 ha to 67,093.62 ha over1996-2050 while irrigated lands decrease from 99,799.4 ha to 50,082.16 ha during the same period of time. The confusion matrix of the 2018 LULC map was built using a total of 525 ground truth points and yielded a Kappa coefficient and overall accuracy of 78% and 82%, respectively. Moreover, the confusion matrix constructed base on the Sentinel-2 map, as a reference, to judge the predicted 2018 LULC map with a Kappa coefficient of 88%. The results of this study provide useful insights for sustainable land management. The results of this research also proved the promising capability of remote sensing algorithms, CA-Markov model and landscape metrics future LULC planning in the study area.


Assuntos
Conservação dos Recursos Naturais , Tecnologia de Sensoriamento Remoto , Benchmarking , Monitoramento Ambiental , Irã (Geográfico)
16.
Environ Monit Assess ; 192(11): 734, 2020 Oct 29.
Artigo em Inglês | MEDLINE | ID: mdl-33123801

RESUMO

Forest age is an important stand description factor and plays an important role in the carbon cycle of forest ecosystems. However, forest age data are typically lacking or are difficult to acquire at large spatial scale. Thus, it is important to develop a method of spatial forest age mapping. In this study, a method of forest age estimation based on multiple-resource remote sensing data was developed. Forest age was estimated by using average tree height estimated from the ICESat/GLAS and MODIS BRDF products. The results showed that forest age was significantly related to average tree height with a correlation coefficient of 0.752. Then, the average tree height was inversed using a waveform parameter extracted from ICESat/GLAS and was extended to continuous space with the help of the MODIS BRDF product. Thus, forest age mapping was realized. Lastly, the structure of forest age in the study area was evaluated. The results indicated that this method can be used to estimate forest age at the local scale and at large scale and can facilitate understandings of the real forest age structure features of a research area.


Assuntos
Ecossistema , Tecnologia de Sensoriamento Remoto , Monitoramento Ambiental , Florestas , Árvores
17.
Huan Jing Ke Xue ; 41(11): 5060-5072, 2020 Nov 08.
Artigo em Chinês | MEDLINE | ID: mdl-33124249

RESUMO

Remote sensing monitoring of black-odor water is an important method for understanding the current status of urban water quality, and comprehensively evaluating the effect of urban water environment treatment. A total of 171 samples were collected in Nanjing, Changzhou, Wuxi, and Yangzhou cities and water quality parameters and optical parameters were measured simultaneously. Based on the analysis of the water color and optical characteristics of the black-odor water and non-black-odor water (denoted as general water), a decision tree was constructed to identify the severe, mild black-odor water, and general water as green and yellow water. The results found that:①According to the water color, the water bodies can be divided into six types. Among them, type 1 to 4 water bodies are black-odor water, which are gray black, dark gray, gray, and light gray water, respectively, and type 5 and 6 water bodies are general water, which are green and yellow water, respectively; ②Type 1 water body contains high contents of non-pigmented particulate matter and colored dissolved organic matter(CDOM), however, the absorption of pigmented particulate matter is not dominant. Type 2 and 5 water bodies are dominated by pigmented particulate matter. Type 3, 4, and 6 water bodies are dominated by non-pigmented particulate matter; ③After water color classification, and according to the differences of the reflection spectrums of the six types of water bodies, the difference of black-odorous water index (DBWI), green-red-nir area water index (G-R-NIR AWI), the green band reflectance and the normalized difference black-odorous water index (NDBWI) were used to construct a decision tree to identify the severe, mild black-odor water, and general water; ④The decision tree was applied to the PlanetScope satellite image of Yangzhou City on April 9, 2019, and 10 synchronous sampling points were used for verification. The overall recognition accuracy reached 80.00%, and the K value reached 0.67. The urban water classification model, after water color classification, can be applied to other similar water bodies, and provides a technical method for the supervision of black-odor water bodies.


Assuntos
Tecnologia de Sensoriamento Remoto , Água , Cidades , Árvores de Decisões , Monitoramento Ambiental , Odorantes
18.
Huan Jing Ke Xue ; 41(8): 3591-3600, 2020 Aug 08.
Artigo em Chinês | MEDLINE | ID: mdl-33124332

RESUMO

Unmanned aerial vehicle (UAV) multispectral remote sensing can be used to monitor multiple water quality parameters, such as suspended solids, turbidity, total phosphorus, and chlorophyll. Establishing a stable and accurate water quality parameter inversion model is a prerequisite for this work. The matching pixel-by-pixel (MPP) algorithm is an inversion algorithm for high resolution features of UAV images; however, it is associated with problems of excessive computation and over-fitting. To overcome these problems, the optimize-MPP (OPT-MPP) algorithm is proposed. In this study, Qingshan Lake in Hangzhou City, Zhejiang Province, was used as the research area. Forty-five samples were collected to construct the OPT-MPP algorithm inversion model for two water quality parameters:the suspended sediments concentration (SS) and turbidity (TU). The results showed that the optimal suspended sediment concentration inversion model had a determination coefficient (R2) of 0.7870 and a comprehensive error of 0.1308. The optimal turbidity inversion model had a R2 of 0.8043 and a comprehensive error of 0.1503. Hence, the inversion of the spatial distribution information for water quality parameters in each experimental area of QingShan Lake was realized by using the optimal models of the two established parameters.


Assuntos
Tecnologia de Sensoriamento Remoto , Qualidade da Água , Algoritmos , Clorofila , Lagos
19.
PLoS One ; 15(10): e0239591, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-33017406

RESUMO

Traditional methods to measure spatio-temporal variations in biomass rely on a labor-intensive destructive sampling of the crop. In this paper, we present a high-throughput phenotyping approach for the estimation of Above-Ground Biomass Dynamics (AGBD) using an unmanned aerial system. Multispectral imagery was acquired and processed by using the proposed segmentation method called GFKuts, that optimally labels the plot canopy based on a Gaussian mixture model, a Montecarlo based K-means, and a guided image filtering. Accurate plot segmentation results enabled the extraction of several canopy features associated with biomass yield. Machine learning algorithms were trained to estimate the AGBD according to the growth stages of the crop and the physiological response of two rice genotypes under lowland and upland production systems. Results report AGBD estimation correlations with an average of r = 0.95 and R2 = 0.91 according to the experimental data. We compared our segmentation method against a traditional technique based on clustering. A comprehensive improvement of 13% in the biomass correlation was obtained thanks to the segmentation method proposed herein.


Assuntos
Oryza/crescimento & desenvolvimento , Tecnologia de Sensoriamento Remoto/métodos , Algoritmos , Biomassa , Colômbia , Produtos Agrícolas/crescimento & desenvolvimento , Sistemas de Informação Geográfica/instrumentação , Sistemas de Informação Geográfica/estatística & dados numéricos , Processamento de Imagem Assistida por Computador/métodos , Processamento de Imagem Assistida por Computador/estatística & dados numéricos , Raios Infravermelhos , Aprendizado de Máquina , Tecnologia de Sensoriamento Remoto/instrumentação , Tecnologia de Sensoriamento Remoto/estatística & dados numéricos , Análise Espaço-Temporal
20.
J Cardiovasc Electrophysiol ; 31(11): 2814-2823, 2020 11.
Artigo em Inglês | MEDLINE | ID: mdl-32954600

RESUMO

INTRODUCTION: Remote monitoring (RM) has significantly transformed the standard of care for patients with cardiac electronic implantable devices. It provides easy access to valuable information, such as arrhythmic events, acute decompensation manifestations and device-related issues, without the need of in-person visits. METHODS: Starting March 1st, 332 patients were introduced to an RM program during the Italian lockdown to limit the risk of in-hospital exposure to severe acute respiratory syndrome-coronavirus-2. Patients were categorized into two groups based on the modality of RM delivery (home [n = 229] vs. office [n = 103] delivered). The study aimed at assessing the efficacy of the new follow-up protocol, assessed as mean RM activation time (AT), and the need for technical support. In addition, patients' acceptance and anxiety status were quantified via the Home Monitoring Acceptance and Satisfaction Questionnaire and the Generalized Anxiety Disorder 7-item scale. RESULTS: AT time was less than 48 h in 93% of patients and 7% of them required further technical support. Despite a higher number of trans-telephonic technical support in the home-delivered RM group, mean AT was similar between groups (1.33 ± 0.83 days in home-delivered vs 1.28 ± 0.81 days in office-delivered patients; p = .60). A total of 28 (2.5%) urgent/emergent in-person examinations were required. A high degree of patient satisfaction was reached in both groups whereas anxiety status was higher in the office-delivered group. CONCLUSIONS: The adoption of RM resulted in high patient satisfaction, regardless of the modality of modem delivery; nonetheless, in-office modem delivery was associated with a higher prevalence of anxiety symptoms.


Assuntos
/prevenção & controle , Estimulação Cardíaca Artificial , Cardioversão Elétrica/instrumentação , Cardiopatias/terapia , Marca-Passo Artificial , Tecnologia de Sensoriamento Remoto , Telemedicina , Idoso , Idoso de 80 Anos ou mais , Desfibriladores Implantáveis , Cardioversão Elétrica/efeitos adversos , Estudos de Viabilidade , Feminino , Cardiopatias/diagnóstico , Cardiopatias/fisiopatologia , Humanos , Itália , Masculino , Pessoa de Meia-Idade , Aceitação pelo Paciente de Cuidados de Saúde , Satisfação do Paciente , Valor Preditivo dos Testes , Estudos Prospectivos , Desenho de Prótese , Falha de Prótese
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