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Fulltext Some explicit conditions for a stationary representation of the unilateral second-order spatial ARMA model

Saidatulnisa Abdullah, Shitan, Mahendran

Pertanika Journal of Science & Technology, 2009;17(1):-.
MyJurnal

The analysis of the spatial data has been carried out in many disciplines such as demography, meteorology, geology and remote sensing. The spatial data modelling is important because it recognizes the phenomenon of spatial correlation in field experiments. Three main categories of the spatial models, namely, the simultaneous autoregressive (SAR) models (Whittle, 1954), the conditional autoregressive (CAR) models (Bartlett, 1971), and the moving average (MA) models (Haining, 1978) have been studied. Whittle (1954) presented a form of bilateral autoregressive (AR) models, whereas Basu and Reinsel (1993) considered the first-order autoregressive moving average (ARMA) model of the quadrant type. Awang, N. and Mahendran Shitan (2003) presented the second-order ARMA model, and established some explicit stationary conditions for the model. When fitting the spatial models and making prediction, it is assumed that, the properties of the process would not change with sites. Properties like stationarities have to be assumed, and for this reason, it was therefore imperative that the researchers had made certain that the process was stationary. This could be achieved by providing the explicit stationarity conditions for the model. The explicit conditions, for a stationary representation of the second-order spatial unilateral ARMA model denoted as ARMA(2,1;2,1), have been established (Awang, N. and Mahendran Shitan, 2003) and in this paper, some explicit conditions are established for a stationary representation of the second-order spatial unilateral ARMA model, denoted as ARMA(2,2;2,2).

Matched MeSH terms: Remote Sensing Technology
Fulltext Measuring and mapping urban growth patterns using remote sensing and GIS techniques

Aburas, Maher Milad, Sabrina Ho Abdullah, Mohammad Firuz Ramli, Zulfa Hanan Ash'aari

The Pertanika Journal of Scholarly Research Reviews, 2017;3(1):55-69.
MyJurnal

Remote sensing and geographic information system techniques are significant and popular approaches that have been used in recent years to measure and map urban growth patterns. This paper primarily aims to provide a basis for a literature review of urban growth measurement and mapping by using different methods. For this purpose, the general characteristics of measuring and mapping urban growth patterns are described and classified. The strengths and weaknesses of the various methods have been identified from an analysis and discussion of the characteristics of the techniques. Results of reviews confirm that combining quantitative and qualitative techniques, such as Shannon approach and change detection, to measure and map urban growth patterns will improve understanding of the phenomenon of urban growth. Moreover, using social and economic data such as population and income data will improve understanding of the relationships between causes and effects. The integration of social and economic factors with quantitative and qualitative techniques will contribute to a perfect evaluation of urban growth patterns and land use changes, taking technical, social, economic, spatial, and temporal factors into account.

Matched MeSH terms: Remote Sensing Technology
Image signal-to-noise ratio and noise variance estimation using autoregressive model

Kamel NS, Sim KS

Scanning, 2004 12 23;26(6):277-81.
PMID: 15612204

During the last three decades, several techniques have been proposed for signal-to-noise ratio (SNR) and noise variance estimation in images, with different degrees of success. Recently, a novel technique based on the statistical autoregressive model (AR) was developed and proposed as a solution to SNR estimation in scanning electron microscope (SEM) image. In this paper, the efficiency of the developed technique with different imaging systems is proven and presented as an optimum solution to image noise variance and SNR estimation problems. Simulation results are carried out with images like Lena, remote sensing, and SEM. The two image parameters, SNR and noise variance, are estimated using different techniques and are compared with the AR-based estimator.

Matched MeSH terms: Remote Sensing Technology
Fulltext Ionizing Radiation Monitoring Technology at the Verge of Internet of Things

Ahmad MI, Ab Rahim MH, Nordin R, Mohamed F, Abu-Samah A, Abdullah NF

Sensors (Basel), 2021 Nov 17;21(22).
PMID: 34833705 DOI: 10.3390/s21227629

As nuclear technology evolves, and continues to be used in various fields since its discovery less than a century ago, radiation safety has become a major concern to humans and the environment. Radiation monitoring plays a significant role in preventive radiological nuclear detection in nuclear facilities, hospitals, or in any activities associated with radioactive materials by acting as a tool to measure the risk of being exposed to radiation while reaping its benefit. Apart from in occupational settings, radiation monitoring is required in emergency responses to radiation incidents as well as outdoor radiation zones. Several radiation sensors have been developed, ranging from as simple as a Geiger-Muller counter to bulkier radiation systems such as the High Purity Germanium detector, with different functionality for use in different settings, but the inability to provide real-time data makes radiation monitoring activities less effective. The deployment of manned vehicles equipped with these radiation sensors reduces the scope of radiation monitoring operations significantly, but the safety of radiation monitoring operators is still compromised. Recently, the Internet of Things (IoT) technology has been introduced to the world and offered solutions to these limitations. This review elucidates a systematic understanding of the fundamental usage of the Internet of Drones for radiation monitoring purposes. The extension of essential functional blocks in IoT can be expanded across radiation monitoring industries, presenting several emerging research opportunities and challenges. This article offers a comprehensive review of the evolutionary application of IoT technology in nuclear and radiation monitoring. Finally, the security of the nuclear industry is discussed.

Matched MeSH terms: Remote Sensing Technology
Assessment of spatiotemporal variability of ultraviolet index (UVI) over Kerala, India, using satellite remote sensing (OMI/AURA) data

Valappil NKM, Mammen PC, de Oliveira-Júnior JF, Cardoso KRA, Hamza V

Environ Monit Assess, 2024 Jan 03;196(2):106.
PMID: 38168710 DOI: 10.1007/s10661-023-12239-w

The spatial and temporal dynamics of daily ultraviolet index (UVI) for a period of 18 years (2004-2022) over the Indian state of Kerala were statistically characterised in the study. The UVI measurements used for the study were derived from the ultraviolet-B (UVB) irradiance measured by the Ozone Monitoring Instrument (OMI) of the AURA satellite and classified into different severity levels for analysis. Basic statistics of daily, monthly and seasonal UVI as well as Mann-Kendall (MK) statistical trend characteristics and the rate of change of daily UVI using Theil-Sen's slope test were also evaluated. A higher variability of UVI characteristics was observed in the Kerala region, and more than 79% of the measurements fell into the categories of very high and extreme UVI values, which suggests the need of implementation of appropriate measures to reduce health risks. Although the UVI measured during the study period shows a slight decrease, most of the data show a seasonal variation with undulating low and peak values. Higher UVI are observed during the months of March, April and September. The region also has higher UVI during the southwest monsoon (SWM) and summer seasons. Although Kerala region as a single whole unit, UVI show a non-significant decreasing trend (-0.83), the MK test revealed the increasing and decreasing trends of UVI ranging from -1.96 to 0.41 facilitated the delineation of areas (domains) where UVI are increasing or decreasing. The domain of UVI increase occupies the central and southern (S) parts, and the domains of decrease cover the northern (N) and S parts of the Kerala region. The rate of change of daily UVI in domain of increase and decrease shows an average rate of 0.34 × 10-5 day-1 and -2 × 10-5 day-1, respectively. The parameters (rainfall, air temperature, cloud optical depth (COD) and solar zenith angle (SZA)) that affect the strength of UV rays reaching the surface indicate that a cloud-free atmosphere or low thickness clouds prevails in the Kerala region. Overall, the study results indicate the need for regular monitoring of UVI in the study area and also suggest appropriate campaigns to disseminate information and precautions for prolonged UVI exposure to reduce the adverse health effects, since the study area has a high population density.

Matched MeSH terms: Remote Sensing Technology
Spatio-temporal remotely sensed data for analysis of the shrinkage and shifting in the Al Hawizeh wetland

Ghobadi Y, Pradhan B, Shafri HZ, bin Ahmad N, Kabiri K

Environ Monit Assess, 2015 Jan;187(1):4156.
PMID: 25421858 DOI: 10.1007/s10661-014-4156-0

Wetlands are regarded as one of the most important ecosystems on Earth due to various ecosystem services provided by them such as habitats for biodiversity, water purification, sequestration, and flood attenuation. The Al Hawizeh wetland in the Iran-Iraq border was selected as a study area to evaluate the changes. Maximum likelihood classification was used on the remote sensing data acquired during the period of 1985 to 2013. In this paper, five types of land use/land cover (LULC) were identified and mapped and accuracy assessment was performed. The overall accuracy and kappa coefficient for years 1985, 1998, 2002, and 2013 were 93% and 0.9, 92% and 0.89, 91% and 0.9, and 92% and 0.9, respectively. The classified images were examined with post-classification comparison (PCC) algorithm, and the LULC alterations were assessed. The results of the PCC analysis revealed that there is a drastic change in the area and size of the studied region during the period of investigation. The wetland lost ~73% of its surface area from 1985 to 2002. Meanwhile, post-2002, the wetland underwent a restoration, as a result of which, the area increased slightly and experienced an ~29% growth. Moreover, a large change was noticed at the same period in the wetland that altered ~62% into bare soil in 2002. The areal coverage of wetland of 3386 km(2) in 1985 was reduced to 925 km(2) by 2002 and restored to 1906 km(2) by the year 2013. Human activities particularly engineering projects were identified as the main reason behind the wetland degradation and LULC alterations. And, lastly, in this study, some mitigation measures and recommendations regarding the reclamation of the wetland are discussed. Based on these mitigate measures, the discharge to the wetland must be kept according to the water requirement of the wetland. Moreover, some anthropogenic activities have to be stopped in and around the wetland to protect the ecology of the wetland.

Matched MeSH terms: Remote Sensing Technology*
A comparison of radiometric correction techniques in the evaluation of the relationship between LST and NDVI in Landsat imagery

Tan KC, Lim HS, Matjafri MZ, Abdullah K

Environ Monit Assess, 2012 Jun;184(6):3813-29.
PMID: 21755424 DOI: 10.1007/s10661-011-2226-0

Atmospheric corrections for multi-temporal optical satellite images are necessary, especially in change detection analyses, such as normalized difference vegetation index (NDVI) rationing. Abrupt change detection analysis using remote-sensing techniques requires radiometric congruity and atmospheric correction to monitor terrestrial surfaces over time. Two atmospheric correction methods were used for this study: relative radiometric normalization and the simplified method for atmospheric correction (SMAC) in the solar spectrum. A multi-temporal data set consisting of two sets of Landsat images from the period between 1991 and 2002 of Penang Island, Malaysia, was used to compare NDVI maps, which were generated using the proposed atmospheric correction methods. Land surface temperature (LST) was retrieved using ATCOR3_T in PCI Geomatica 10.1 image processing software. Linear regression analysis was utilized to analyze the relationship between NDVI and LST. This study reveals that both of the proposed atmospheric correction methods yielded high accuracy through examination of the linear correlation coefficients. To check for the accuracy of the equation obtained through linear regression analysis for every single satellite image, 20 points were randomly chosen. The results showed that the SMAC method yielded a constant value (in terms of error) to predict the NDVI value from linear regression analysis-derived equation. The errors (average) from both proposed atmospheric correction methods were less than 10%.

Matched MeSH terms: Remote Sensing Technology/methods*
Application of a GIS-/remote sensing-based approach for predicting groundwater potential zones using a multi-criteria data mining methodology

Mogaji KA, Lim HS

Environ Monit Assess, 2017 Jul;189(7):321.
PMID: 28593561 DOI: 10.1007/s10661-017-5990-7

This study integrates the application of Dempster-Shafer-driven evidential belief function (DS-EBF) methodology with remote sensing and geographic information system techniques to analyze surface and subsurface data sets for the spatial prediction of groundwater potential in Perak Province, Malaysia. The study used additional data obtained from the records of the groundwater yield rate of approximately 28 bore well locations. The processed surface and subsurface data produced sets of groundwater potential conditioning factors (GPCFs) from which multiple surface hydrologic and subsurface hydrogeologic parameter thematic maps were generated. The bore well location inventories were partitioned randomly into a ratio of 70% (19 wells) for model training to 30% (9 wells) for model testing. Application results of the DS-EBF relationship model algorithms of the surface- and subsurface-based GPCF thematic maps and the bore well locations produced two groundwater potential prediction (GPP) maps based on surface hydrologic and subsurface hydrogeologic characteristics which established that more than 60% of the study area falling within the moderate-high groundwater potential zones and less than 35% falling within the low potential zones. The estimated uncertainty values within the range of 0 to 17% for the predicted potential zones were quantified using the uncertainty algorithm of the model. The validation results of the GPP maps using relative operating characteristic curve method yielded 80 and 68% success rates and 89 and 53% prediction rates for the subsurface hydrogeologic factor (SUHF)- and surface hydrologic factor (SHF)-based GPP maps, respectively. The study results revealed that the SUHF-based GPP map accurately delineated groundwater potential zones better than the SHF-based GPP map. However, significant information on the low degree of uncertainty of the predicted potential zones established the suitability of the two GPP maps for future development of groundwater resources in the area. The overall results proved the efficacy of the data mining model and the geospatial technology in groundwater potential mapping.

Matched MeSH terms: Remote Sensing Technology*
Fulltext Projecting range-wide sun bear population trends using tree cover and camera-trap bycatch data

Scotson L, Fredriksson G, Ngoprasert D, Wong WM, Fieberg J

PLoS One, 2017;12(9):e0185336.
PMID: 28961243 DOI: 10.1371/journal.pone.0185336

Monitoring population trends of threatened species requires standardized techniques that can be applied over broad areas and repeated through time. Sun bears Helarctos malayanus are a forest dependent tropical bear found throughout most of Southeast Asia. Previous estimates of global population trends have relied on expert opinion and cannot be systematically replicated. We combined data from 1,463 camera traps within 31 field sites across sun bear range to model the relationship between photo catch rates of sun bears and tree cover. Sun bears were detected in all levels of tree cover above 20%, and the probability of presence was positively associated with the amount of tree cover within a 6-km2 buffer of the camera traps. We used the relationship between catch rates and tree cover across space to infer temporal trends in sun bear abundance in response to tree cover loss at country and global-scales. Our model-based projections based on this "space for time" substitution suggested that sun bear population declines associated with tree cover loss between 2000-2014 in mainland southeast Asia were ~9%, with declines highest in Cambodia and lowest in Myanmar. During the same period, sun bear populations in insular southeast Asia (Malaysia, Indonesia and Brunei) were projected to have declined at a much higher rate (22%). Cast forward over 30-years, from the year 2000, by assuming a constant rate of change in tree cover, we projected population declines in the insular region that surpassed 50%, meeting the IUCN criteria for endangered if sun bears were listed on the population level. Although this approach requires several assumptions, most notably that trends in abundance across space can be used to infer temporal trends, population projections using remotely sensed tree cover data may serve as a useful alternative (or supplement) to expert opinion. The advantages of this approach is that it is objective, data-driven, repeatable, and it requires that all assumptions be clearly stated.

Matched MeSH terms: Remote Sensing Technology*
Functionalization of remote sensing and on-site data for simulating surface water dissolved oxygen: Development of hybrid tree-based artificial intelligence models

Tiyasha T, Tung TM, Bhagat SK, Tan ML, Jawad AH, Mohtar WHMW, et al.

Mar Pollut Bull, 2021 Sep;170:112639.
PMID: 34273614 DOI: 10.1016/j.marpolbul.2021.112639

Dissolved oxygen (DO) is an important indicator of river health for environmental engineers and ecological scientists to understand the state of river health. This study aims to evaluate the reliability of four feature selector algorithms i.e., Boruta, genetic algorithm (GA), multivariate adaptive regression splines (MARS), and extreme gradient boosting (XGBoost) to select the best suited predictor of the applied water quality (WQ) parameters; and compare four tree-based predictive models, namely, random forest (RF), conditional random forests (cForest), RANdom forest GEneRator (Ranger), and XGBoost to predict the changes of dissolved oxygen (DO) in the Klang River, Malaysia. The total features including 15 WQ parameters from monitoring site data and 7 hydrological components from remote sensing data. All predictive models performed well as per the features selected by the algorithms XGBoost and MARS in terms applied statistical evaluators. Besides, the best performance noted in case of XGBoost predictive model among all applied predictive models when the feature selected by MARS and XGBoost algorithms, with the coefficient of determination (R2) values of 0.84 and 0.85, respectively, nonetheless the marginal performance came up by Boruta-XGBoost model on in this scenario.

Matched MeSH terms: Remote Sensing Technology
Fulltext CropCam UAV for land use/land cover mapping over Penang Island, Malaysia

Faez M. Hassan, Lim, H.S., Mat Jafri, M.Z.

Pertanika Journal of Science & Technology, 2011;19(3):69-76.
MyJurnal

The problem of difficulty in obtaining cloud-free scene at the equatorial region from satellite platforms can be
overcome by using airborne imagery as an attempt for introducing an economical method of remote sensing
data; which only requires a digital camera to provide near time data. Forty three digital images were captured
using a high resolution digital camera model pentax optio A40 (12 megapixels)at a selected location in the same day in Penang Island from a low-altitude flying autopilot aircraft (CropCam) to generate land use/land cover (LULC) map of the test area. The CropCam was flown at an average altitude of 320 meters over the ground while capturing images which were taken during two flying missions for the duration of approximately 15 and 20 minutes respectively. The CropCam was equipped with a digital camera as a sensor to capture the GPS points based digital images according to the present time to ensure the mosaic of the digital images. Forty one images were used in providing a mosaic image of a bigger coverage of area (full panorama). Training samples were collected simultaneously when the CropCam captured the images by using hand held GPS. Supervised classification techniques, such as the maximum likelihood, minimum-to-distance, and parallelepiped were applied to the panoramic image to generate LULC map for the study area. It was found that the maximum likelihood classifier produce superior results and achieved a high degree of accuracy. The results indicated that the CropCam equipped with a high resolution digital camera can be useful and suitable tool for the tropical region, and this technique could reduce the cost and time of acquiring images for LULC mapping.

Matched MeSH terms: Remote Sensing Technology
Fulltext Land cover classification of ALOS PALSAR data using maximum likelihood and dual mode polarization

Sim, C.K., Abdullah, K., Mat Jafri, M.Z., Lim, H.S.

Pertanika Journal of Science & Technology, 2011;19(3):83-88.
MyJurnal

Microwave Remote sensing data have been widely used in land cover and land use classification. The objective of this research paper is to investigate the feasibility of the multi-polarized ALOS-PALSAR data for land cover mapping. This paper presents the methodology and preliminary result including data acquisitions, data processing and data analysis. Standard supervised classification techniques such as the maximum likelihood, minimum distance-to-mean, and parallelepiped were applied to the ALOS-PALSAR images in the land cover mapping analysis. The PALSAR data training areas were chosen based on the information obtained from
optical satellite imagery. The best supervise classifier was selected based on the highest overall accuracy and
kappa coefficient. This study indicated that the land cover of Butterworth, Malaysia can be mapped accurately
using ALOS PALSAR data.

Matched MeSH terms: Remote Sensing Technology
Fulltext A spatial decision support tool for oil palm plantation management

Loh, Kok Fook, Ponusamy, Ragu, Shattri Mansor, Jamil Ismail

Pertanika Journal of Science & Technology, 2009;17(1):-.
MyJurnal

Malaysia is in the process of modernizing its oil palm plantation management, by implementing geo-information technologies which include Remote Sensing (RS), Geographic Information System (GIS), and Spatial Decision Support System (DSS). Agencies with large oil palm plantations such as the Federal Land Development Authority (FELDA), Federal Land Consolidation and Rehabilitation Authority (FELCRA), Guthrie Sdn. Bhd., and Golden Hope Sdn. Bhd. have already incorporated GIS in their plantation management, with limited use of RS and DSS. In 2005, FELCRA, Universiti Putra Malaysia (UPM) and Espatial Resources Sdn. Bhd. (ESR) collaborated in a research project to explore the potentials of geo-informatics for oil palm plantation management. The research was conducted in FELCRA located in Seberang Perak Oil Palm Scheme. In that research, a tool integrating RS, GIS and Analytical Hierarchy Process (AHP) was developed to support decision making for replanting of the existing old palms. RS was used to extract productive stand per hectare; AHP was used to compute the criteria weights for the development of a suitable model; and GIS was used for spatial modelling so as to generate the decision support layer for replanting. This paper highlights the approach adopted in developing the tool with special emphasis on the AHP computation.

Matched MeSH terms: Remote Sensing Technology
Fulltext Evaluation of the spatial growth of Bauchi metropolis using remote sensing and geographic information systems (GIS) techniques

Mohammed Aliyu Modibbo, Mohammed Arif Shahidah, Isah Funtua Abdulkadir, Umar Wali

Journal of Advanced Research in Applied Sciences and Engineering Technology, 2017;6(1):28-36.
MyJurnal

This paper has evaluated the spatial growth of Bauchi Metropolis from 1976 to 2015
through the application of Remote Sensing and GIS techniques. Various satellite
imageries of the metropolis (Landsat MSS of 1976, TM of 1986, 1996 and ETM+ of 2006
and 2015) were integrated; processed and classified using ERDAS imagine 9.1. The
results showed an increase in area from 11.68km2
in 1976 to 12.51km2
in 1986 to
32.44km2 in 1996, to 49.66km2
in 2006 and finally to 89.23km2 in 2015. It is
recommended that government should provide the required capacities for the use of
Remote Sensing and GIS in planning for the growth of the town.

Matched MeSH terms: Remote Sensing Technology
Fulltext A Solar Panel-Integrated Modified Planner Inverted F Antenna for Low Earth Orbit Remote Sensing Nanosatellite Communication System

Alam T, Islam MT, Ullah MA, Cho M

Sensors (Basel), 2018 Jul 31;18(8).
PMID: 30065233 DOI: 10.3390/s18082480

One of the most efficient methods to observe the impact of geographical, environmental, and geological changes is remote sensing. Nowadays, nanosatellites are being used to observe climate change using remote sensing technology. Communication between a remote sensing nanosatellite and Earth significantly depends upon antenna systems. Body-mounted solar panels are the main source of satellite operating power unless deployable solar panels are used. Lower ultra-high frequency (UHF) nanosatellite antenna design is a crucial challenge due to the physical size constraint and the need for solar panel integration. Moreover, nanosatellite space missions are vulnerable because of antenna and solar panel deployment complexity. This paper proposes a solar panel-integrated modified planner inverted F antenna (PIFA) to mitigate these crucial limitations. The antenna consists of a slotted rectangular radiating patch with coaxial probe feeding and a rectangular ground plane. The proposed antenna has achieved a -10 dB impedance bandwidth of 6.0 MHz (447.5 MHz⁻453.5 MHz) with a small-sized (80 mm× 90 mm× 0.5 mm) radiating element. In addition, the antenna achieved a maximum realized gain of 0.6 dB and a total efficiency of 67.45% with the nanosatellite structure and a solar panel. The challenges addressed by the proposed antenna are to ensure solar panel placement between the radiating element and the ground plane, and provide approximately 55% open space to allow solar irradiance into the solar panel.

Matched MeSH terms: Remote Sensing Technology
Assessment of spatial and temporal ecological environment quality under land use change of urban agglomeration in the North Slope of Tianshan, China

Airiken M, Zhang F, Chan NW, Kung HT

Environ Sci Pollut Res Int, 2022 Feb;29(8):12282-12299.
PMID: 34564811 DOI: 10.1007/s11356-021-16579-3

In the current context of rapid development and urbanization, land use and land cover (LULC) types have undergone unprecedented changes, globally and nationally, leading to significant effects on the surrounding ecological environment quality (EEQ). The urban agglomeration in North Slope of Tianshan (UANST) is in the core area of the Silk Road Economic Belt of China. This area has experienced rapid development and urbanization with equally rapid LULC changes which affect the EEQ. Hence, this study quantified and assessed the spatial-temporal changes of LULC on the UANST from 2001 to 2018 based on remote sensing analysis. Combining five remote sensing ecological factors (WET, NDVI, IBI, TVDI, LST) that met the pressure-state-response(PSR) framework, the spatial-temporal distribution characteristics of EEQ were evaluated by synthesizing a new Remote Sensing Ecological Index (RSEI), with the interaction between land use change and EEQ subsequently analyzed. The results showed that LULC change dominated EEQ change on the UANST: (1) From 2001 to 2018, the temporal and spatial pattern of the landscape on the UANST has undergone tremendous changes. The main types of LULC in the UANST are Barren land and Grassland. (2) During the study period, RSEI values in the study area were all lower than 0.5 and were at the [good] levels, reaching 0.31, 0.213, 0.362, and 0346, respectively. In terms of time and space, the overall EEQ on the UANST experienced three stages of decline-rise-decrease. (3) The estimated changes in RSEI were highly related to the changes of LULC. During the period 2001 to 2018, the RSEI value of cropland showed a trend of gradual increase. However, the rest of the LULC type's RSEI values behave differently at different times. As the UANST is the core area of Xinjiang's urbanization and economic development, understanding and balancing the relationship between LULC and EEQ in the context of urbanization is of practical application in the planning and realization of sustainable ecological, environmental, urban, and social development in the UANST.

Matched MeSH terms: Remote Sensing Technology
Impacts of industrial production and air quality by remote sensing on nitrogen dioxide concentration and related effects: An econometric approach

Kurniawan R, Budi Alamsyah AR, Fudholi A, Purwanto A, Sumargo B, Gio PU, et al.

Environ Pollut, 2023 Oct 01;334:122212.
PMID: 37454714 DOI: 10.1016/j.envpol.2023.122212

The high concentration of nitrogen dioxide (NO2) is to blame for West Java's poor Air Quality Index (AQI). So, this study aims to determine the influence of industrial activity as reflected by the value of its imports and exports, wind speed, and ozone (O3) on the high concentration of tropospheric NO2. The method used is the econometric Vector Error Correction Model (VECM) approach to capture the existence of a short-term and long-term relationship between tropospheric NO2 and its predictor variables. The data used in this study is in the form of monthly time series data for the 2018-2022 period sourced from satellite images (Sentinel-5P and ECMWF Climate Reanalysis) and publications of the Central Bureau of Statistics (BPS-Statistics Indonesia). The results explained that, in the short-term, tropospheric NO2 and O3 influence each other as they would in a photochemical reaction. In the long-term, exports from the industrial sector and wind speed have a significant effect on the concentration of tropospheric NO2. The short-term effect occurs directly in the first month after the shock, while the long-term effect occurs in the second month after the shock. Wind gusts originating from industrial areas cause air conditions to be even more alarming because tropospheric NO2 pollutants spread throughout the region in West Java. Based on the coefficient correlation result, the high number of pneumonia cases is one of the impacts caused by air pollution.

Matched MeSH terms: Remote Sensing Technology
Remote sensing for chromophoric dissolved organic matter (CDOM) monitoring research 2003-2022: A bibliometric analysis based on the web of science core database

Li Z, Zhang F, Shi J, Chan NW, Tan ML, Kung HT, et al.

Mar Pollut Bull, 2023 Nov;196:115653.
PMID: 37879130 DOI: 10.1016/j.marpolbul.2023.115653

Chromophoric dissolved organic matter (CDOM) occupies a critical part in biogeochemistry and energy flux of aquatic ecosystems. CDOM research spans in many fields, including chemistry, marine environment, biomass cycling, physics, hydrology, and climate change. In recent years, a series of remarkable research milestone have been achieved. On the basis of reviewing the research process of CDOM, combined with a bibliometric analysis, this study aims to provide a comprehensive review of the development and applications of remote sensing in monitoring CDOM from 2003 to 2022. The findings show that remote sensing data plays an important role in CDOM research as proven with the increasing number of publications since 2003, particularly in China and the United States. Primary research areas have gradually changed from studying absorption and fluorescence properties to optimization of remote sensing inversion models in recent years. Since the composition of oceanic and freshwater bodies differs significantly, it is important to choose the appropriate inversion method for different types of water body. At present, the monitoring of CDOM mainly relies on a single sensor, but the fusion of images from different sensors can be considered a major research direction due to the complex characteristics of CDOM. Therefore, in the future, the characteristics of CDOM will be studied in depth inn combination with multi-source data and other application models, where inversion algorithms will be optimized, inversion algorithms with low dependence on measured data will be developed, and a transportable inversion model will be built to break the regional limitations of the model and to promote the development of CDOM research in a deeper and more comprehensive direction.

Matched MeSH terms: Remote Sensing Technology
Fulltext Remote Monitoring of Implantable Cardioverter-Defibrillators: A Systematic Review and Meta-Analysis of Clinical Outcomes

Parthiban N, Esterman A, Mahajan R, Twomey DJ, Pathak RK, Lau DH, et al.

J Am Coll Cardiol, 2015 Jun 23;65(24):2591-2600.
PMID: 25983009 DOI: 10.1016/j.jacc.2015.04.029

BACKGROUND: Remote monitoring (RM) of implantable cardioverter-defibrillators (ICD) is an established technology integrated into clinical practice. One recent randomized controlled trial (RCT) and several large device database studies have demonstrated a powerful survival advantage for ICD patients undergoing RM compared with those receiving conventional in-office (IO) follow-up.
OBJECTIVES: This study sought to conduct a systematic published data review and meta-analysis of RCTs comparing RM with IO follow-up.
METHODS: Electronic databases and reference lists were searched for RCTs reporting clinical outcomes in ICD patients who did or did not undergo RM. Data were extracted from 9 RCTs, including 6,469 patients, 3,496 of whom were randomized to RM and 2,973 to IO follow-up.
RESULTS: In the RCT setting, RM demonstrated clinical outcomes comparable with office follow-up in terms of all-cause mortality (odds ratio [OR]: 0.83; p = 0.285), cardiovascular mortality (OR: 0.66; p = 0.103), and hospitalization (OR: 0.83; p = 0.196). However, a reduction in all-cause mortality was noted in the 3 trials using home monitoring (OR: 0.65; p = 0.021) with daily verification of transmission. Although the odds of receiving any ICD shock were similar in RM and IO patients (OR: 1.05; p = 0.86), the odds of inappropriate shock were reduced in RM patients (OR: 0.55; p = 0.002).
CONCLUSIONS: Meta-analysis of RCTs demonstrates that RM and IO follow-up showed comparable overall outcomes related to patient safety and survival, with a potential survival benefit in RCTs using daily transmission verification. RM benefits include more rapid clinical event detection and a reduction in inappropriate shocks.

Matched MeSH terms: Remote Sensing Technology/methods*; Remote Sensing Technology/standards
Fulltext Drone for medical products transportation in maternal healthcare: A systematic review and framework for future research

Zailani MAH, Sabudin RZAR, Rahman RA, Saiboon IM, Ismail A, Mahdy ZA

Medicine (Baltimore), 2020 Sep 04;99(36):e21967.
PMID: 32899033 DOI: 10.1097/MD.0000000000021967

INTRODUCTION: Medical products transportation has become an important research topic requiring multidisciplinary collaboration among experts in medicine, engineering, and health economics. Current modes of transportation are unable to overcome the limited settings in maternal healthcare, particularly during the event of obstetric emergencies. The drone is a promising medical product aerial transportation (MedART) that holds an enormous potential for delivery of medical supplies in the healthcare system. We conducted a systematic review to examine scientific evidence of positive impact of drone transportation on maternal health.
METHODS: The following electronic databases were searched from inception to July 2019: ScienceDirect, PubMed, and EMBASE. The report was made in accordance with the principles of PRISMA guidelines. The search terms used were related to drones including unmanned aerial vehicle (UAV) and unmanned aerial system (UAS), and related to obstetric/maternal including obstetric emergencies and postpartum hemorrhage. Studies were selected if the intervention used were drones, and if any direct or indirect maternal health indicators were reported. Meta-analysis was not done throughout the study in view of the anticipated heterogeneity of each study.
RESULTS: Our initial search yielded a total of 244 relevant publications, from which 236 were carried forward for a title and abstract screening. After careful examination, only two were included for systematic synthesis. Among the reasons for exclusion were irrelevance to maternal health purpose, and irrelevance to drone applications in healthcare. An updated search yielded one additional study that was also included. Overall, two studies assessed drones for blood products delivery, and one study used drones to transport blood samples.
CONCLUSION: A significant deficiency was found in the number of reported studies analyzing mode of medical products transportation and adaptation of drones in maternal healthcare. Future drone research framework should focus on maternal healthcare-specific drone applications in order to reap benefits in this area.

Matched MeSH terms: Remote Sensing Technology/instrumentation*; Remote Sensing Technology/trends

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