scholarly journals ANALYSIS OF VISIBLE INFRARED IMAGING RADIOMETER SUITE CAPABILITY FOR POPULATION ESTIMATION ON JAVA ISLAND

2022 ◽  
Vol XLVI-4/W3-2021 ◽  
pp. 267-272
Author(s):  
M. D. H. Nurhadi ◽  
A. Cahyono
Keyword(s):  
Total Population ◽  
Infrared Imaging ◽  
Regional Scale ◽  
Population Data ◽  
Population Estimation ◽  
Coefficient Of Determination ◽  
Average Error ◽  
Entire Study ◽  
Percent Error ◽  
Nighttime Light Imagery

Abstract. Population data, despite their significance, are often missing or difficult to access, especially in cities/regencies not belonging to the metropolitan areas or centers of various human activities. This hinders practices that are contingent on their availability. In this study, population estimation was carried out using nighttime light imagery generated by the Visible Infrared Imaging Radiometer Suite (VIIRS) instrument. The variable illuminated area was integrated with the population data using linear regression based on an allometric formula so as to produce a regression value, correlation coefficient (r), and coefficient of determination (r2). The average r2 between the illuminated area and the total population was 0.86, indicating a strong correlation between the two variables. Validation using samples of population estimates from three different years yielded an average error of 73% for each city and 7% for the entire study area. The estimation results for the number of residents per city/regency cannot be used as population data due to the high percent error, but for the population on a larger regional scale, in this case, the island of Java, they have a much smaller percent error and can be used as an initial picture of the total population.

Faktor yang Berhubungan dengan Penggunaan Partograf dalam Persalinan oleh Bidan Praktik Mandiri

2020 ◽  
Vol 2 (2) ◽  
pp. 72-80
Author(s):  
Niluh Nita Silfia
Keyword(s):  
Total Population ◽  
Sampling Technique ◽  
Population Data ◽  
Statistical Test ◽  
Influential Factor ◽  
Test Results ◽  
Cross Sectional ◽  
Factors Associated ◽  
Survey Results ◽  
Research Criteria

Partographs are guidelines for childbirth observations that will facilitate labor assistants in first identifying emergency cases and complications for mothers and fetuses. Preliminary survey at the Sigi Community Health Sub-Center (Pustu) of the 8 Pustu midwives found two midwives (25%) to complete a complete partograph, six midwives (75%) incomplete. The purpose of this study was to determine the determinant factors associated with the use of partographs in labor. The design of this study used observational analytic methods with a cross-sectional approach. 24 BPM survey results were obtained with 30 samples of midwives who met the research criteria and data completeness. The sampling technique was by the total population. Data analysis used logistic regression. The multivariate analysis results showed that APN training was the most influential factor in the use of partographs in labor by midwives. Statistical test results obtained a POR value of 37.7 (95% CI 12.1 - 60.2). This study suggests that midwives must have APN certificates to be valid in providing services.

scholarly journals Night-Time Light Remote Sensing Mapping: Construction and Analysis of Ethnic Minority Development Index

2021 ◽  
Vol 13 (11) ◽  
pp. 2129
Author(s):  
Fei Zhao ◽  
Lu Song ◽  
Zhiyan Peng ◽  
Jianqin Yang ◽  
Guize Luan ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Ethnic Group ◽  
Ethnic Groups ◽  
Ethnic Minorities ◽  
Population Data ◽  
Night Time ◽  
Entire Study ◽  
Development Index ◽  
Remote Sensing Mapping ◽  
Entire Study Area

Using toponym data, population data, and night-time light data, we visualized the development index of the Yi, Wa, Zhuang, Naxi, Hani, and Dai ethnic groups on ArcGIS as well as the distribution of 25 ethnic minorities in the study area. First, we extracted the toponym data of 25 ethnic minorities in the study area, combined with night-time light data and the population proportion data of each ethnic group, then we obtained the development index of each ethnic group in the study area. We compared the development indexes of the Yi, Wa, Zhuang, Naxi, Hani, and Dai ethnic groups with higher development indexes. The results show that the Yi nationality’s development index was the highest, reaching 28.86 (with two decimal places), and the Dai nationality’s development index was the lowest (15.22). The areas with the highest minority development index were concentrated in the core area of the minority development, and the size varied with the minority’s distance. According to the distribution of ethnic minorities, we found that the Yi ethnic group was distributed in almost the entire study area, while other ethnic minorities had obvious geographical distribution characteristics, and there were multiple ethnic minorities living together. This research is of great significance to the cultural protection of ethnic minorities, the development of ethnic minorities, and the remote sensing mapping of lights at night.

scholarly journals The implementation of a mobile application to support community-based health workers

2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
A C F Martins ◽  
P L Pereira ◽  
A C C N Mafra ◽  
J L Miraglia ◽  
C N Monteiro ◽  
...  
Keyword(s):  
Health Care ◽  
Mobile Application ◽  
Total Population ◽  
Health Workers ◽  
Data Entry ◽  
Population Data ◽  
Administrative Staff ◽  
Economic Data ◽  
Process Change ◽  
Community Based

Abstract Issue Real-time access to up-to-date population information is essential to the strategic planning of primary health care (PHC). In the Brazilian public health system community-based health workers (CHWs), working as part of PHC teams, collect health, demographic and socio-economic data from individuals mainly through paper-based forms that are later entered manually into electronic information systems. Mobile applications could help to improve the quality and speed of this process facilitating the CHWs day-to-day work while improving the access to the collected information. Description of the Problem During September of 2019, a mobile application installed in tablets for the collection of health, demographic and socio-economic data was deployed for 432 CHWs of 87 PHC teams in the southern region of São Paulo, Brazil, serving a total population of 283,324 individuals. During implementation, the acceptability and challenges faced by CHWs were evaluated and the time taken to complete data entry. Results Seventy-two hours of training were offered to CHWs and other 139 professionals including managers, nurses and administrative staff (AS). Some CHWs reported concerns about the process change and fear of not being able to operate the application, especially those unfamiliar to the technology. With training and team support, fear was transformed into satisfaction with the realization of the benefits of the system. The main infrastructure challenge was the need for installation of Wi-Fi routers in some health care units, in addition to the replacement 4.4% of damaged tablets. In four months 97.6% of the total population was registered in the application. Lessons A WhatsApp group was created to clarify AS doubts, receive suggestions and disseminate guidelines. AS remained as the reference point at healthcare units and data completeness still needs to be reinforced. Key messages A mobile application was well-accepted by CHWs and could facilitate the collection of population data. A tablet app proved to be a useful tool to generate information for the PHC teams.

scholarly journals Multiscale observations of NH<sub>3</sub> around Toronto, Canada

2021 ◽  
Vol 14 (2) ◽  
pp. 905-921
Author(s):  
Shoma Yamanouchi ◽  
Camille Viatte ◽  
Kimberly Strong ◽  
Erik Lutsch ◽  
Dylan B. A. Jones ◽  
...  
Keyword(s):  
Temporal Variability ◽  
Grid Point ◽  
Regional Scale ◽  
Model Performance ◽  
In Situ Measurements ◽  
Coefficient Of Determination ◽  
Spatial And Temporal Variability ◽  
Predictive Capacity ◽  
Total Column

Abstract. Ammonia (NH3) is a major source of nitrates in the atmosphere and a major source of fine particulate matter. As such, there have been increasing efforts to measure the atmospheric abundance of NH3 and its spatial and temporal variability. In this study, long-term measurements of NH3 derived from multiscale datasets are examined. These NH3 datasets include 16 years of total column measurements using Fourier transform infrared (FTIR) spectroscopy, 3 years of surface in situ measurements, and 10 years of total column measurements from the Infrared Atmospheric Sounding Interferometer (IASI). The datasets were used to quantify NH3 temporal variability over Toronto, Canada. The multiscale datasets were also compared to assess the representativeness of the FTIR measurements. All three time series showed positive trends in NH3 over Toronto: 3.34 ± 0.89 %/yr from 2002 to 2018 in the FTIR columns, 8.88 ± 5.08 %/yr from 2013 to 2017 in the surface in situ data, and 8.38 ± 1.54 %/yr from 2008 to 2018 in the IASI columns. To assess the representative scale of the FTIR NH3 columns, correlations between the datasets were examined. The best correlation between FTIR and IASI was obtained with coincidence criteria of ≤25 km and ≤20 min, with r=0.73 and a slope of 1.14 ± 0.06. Additionally, FTIR column and in situ measurements were standardized and correlated. Comparison of 24 d averages and monthly averages resulted in correlation coefficients of r=0.72 and r=0.75, respectively, although correlation without averaging to reduce high-frequency variability led to a poorer correlation, with r=0.39. The GEOS-Chem model, run at 2∘ × 2.5∘ resolution, was compared to FTIR and IASI to assess model performance and investigate the correlation of observational data and model output, both with local column measurements (FTIR) and measurements on a regional scale (IASI). Comparisons on a regional scale (a domain spanning 35 to 53∘ N and 93.75 to 63.75∘ W) resulted in r=0.57 and thus a coefficient of determination, which is indicative of the predictive capacity of the model, of r2=0.33, but comparing a single model grid point against the FTIR resulted in a poorer correlation, with r2=0.13, indicating that a finer spatial resolution is needed for modeling NH3.

Source apportionment of heavy metal pollution in farmland soils on a regional scale using geographically weighted PCA

2021 ◽  
Author(s):  
Liu Shuyi ◽  
Gao Bingbo
Keyword(s):  
Heavy Metals ◽  
Heavy Metal ◽  
Source Apportionment ◽  
Rapid Development ◽  
Regional Scale ◽  
Analytical Framework ◽  
Pollution Sources ◽  
Entire Study ◽  
Soil Heavy Metals ◽  
Farmland Soils

&lt;p&gt;Source apportionment of soil heavy metals is an challenge and urgent work as the result of the rapid development of industrialization and urbanization. The common approach is multivariate statistical analysis, such as PCA and APCS/MLR, which infers only a single pattern of sources of heavy metals in entire study area. Due to complicated pathways and processes, patterns of pollution sources in a whole region may include two or more. Hence, we developed an analytical framework based on GWPCA to explore multiple patterns of sources of soil heavy metals on a regional scale. Xiangtan county, an important grain-producing area in China, was taken as a case study, which suffers the problem of heavy metal pollutions. Our results revealed the pollution situations of five soil heavy metals(Pb, Cd, As, Cr and Hg) in farmland soils and suggested that there exists various pollution patterns of these heavy metals in Xiangtan county. In each pattern, the structure of contamination sources is different. Our study also indicates that the analytical framework considering the spatial heterogeneity of pollution sources can help take more precise practices to solve this vital problem.&lt;/p&gt; &lt;p&gt;&amp;#160;&lt;/p&gt;

Multi-scale influence of topography on shallow-marine successions associated with long-term transgressions

2021 ◽  
Author(s):  
Miquel Poyatos-Moré ◽  
Ernesto Schwarz ◽  
Salvador Boya ◽  
Luz Elena Gomis-Cartesio ◽  
Ivar Midtkandal
Keyword(s):  
Regional Scale ◽  
Coarse Grained ◽  
Continuous Exposure ◽  
Entire Study ◽  
Shallow Marine ◽  
Sedimentary Characteristics ◽  
Multi Scale ◽  
Depositional Processes ◽  
Mouth Bars

&lt;p&gt;Thick shallow-marine successions associated with long-term transgressions are less well known than their thin, well-sorted counterparts, widely studied due to their potential to form good reservoirs. In these successions, particularly in storm-dominated examples, bioturbation can obliterate primary sedimentary characteristics, making stacking patterns and sequences difficult to define, and challenging our understanding of the main controls in their resulting depositional architecture. This study presents an example from the Jurassic of the Neuqu&amp;#233;n Basin (Argentina), with the aim to: a) refine the depositional model of a thick, shallow-marine succession associated with a long-term, early post-rift transgression, b) constrain multi-scale controls on stratigraphic architecture and lateral facies variability, and c) discuss their preservation and response to post-depositional processes. To do this, a &lt;300 m-thick succession has been studied along a &gt;10 km continuous exposure, with mapping, sedimentary logging and correlation of stratigraphic units, integrated with subsurface, biostratigraphic and ichnological data. The succession shows an overall retrogradational-aggradational-retrogradational stacking pattern, with several higher frequency regressive units (parasequences and parasequence sets, PSS). The lower part (PSS I) comprises laterally-discontinuous (10's of m) mouth-bars and distributary channel fills, dominated by several m-thick coarsening- and fining-up sandstone packages and m-scale erosive conglomeratic lenses. Above these, the succession (PSS II-IV) is composed by laterally-continuous (&gt;100's of m) storm-dominated lower-shoreface to upper-offshore deposits, dominated by &lt;1m-thick fine-grained and highly bioturbated tabular muddy sandstones and sandy mudstones, with rarely-preserved HCS and bioclastic-rich limestones; their internal characteristics and bed boundaries are diffuse due to pervasive bioturbation, suggesting overall low sedimentation rates and recurrent periods of colonization. The coarse-grained nature and lithology of the mouth bars and channel fills in the lower succession (PSS I) are consistent with a proximal sediment source, associated with erosion of intra-basinal highs. Its variable thickness, lateral distribution and onlap against underlying syn-rift deposits demonstrates partial infill of localized higher-accommodation areas. The well-sorted and finer-grained nature of the shoreface-offshore strata the middle and upper succession (PSS II-IV) indicates a more mature, distal source, with sediment redistributed by longshore currents, and then intensely bioturbated. These deposits display well-defined parasequences internally composed of laterally-continuous bedsets (&lt;5 m-thick). They extend along the entire study area, but show a significant vertical thickness variability. The integration of outcrop and subsurface data mapping (well and seismic) reveals this variability records the stratigraphic response of transgression over a complex, regional-scale ramp-step and underfilled rift topography, which controlled the location of main thickness and facies changes, and promoted areas of favored biogenic reworking. This study offers new insights in how to interpret thick transgressive successions based on primary depositional mechanisms and postdepositional processes, and provides useful tools to understand and predict the nature and potential preservation of these deposits in limited subsurface datasets.&lt;/p&gt;

scholarly journals Estimation of Winter Wheat Residue Coverage Using Optical and SAR Remote Sensing Images

2019 ◽  
Vol 11 (10) ◽  
pp. 1163
Author(s):  
Wenting Cai ◽  
Shuhe Zhao ◽  
Yamei Wang ◽  
Fanchen Peng ◽  
Joon Heo ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Crop Residues ◽  
Regional Scale ◽  
Microwave Remote Sensing ◽  
Estimation Accuracy ◽  
Coefficient Of Determination ◽  
Accurate Estimation ◽  
Optical Remote Sensing ◽  
Optimal Subset ◽  
Subset Regression

As an important part of the farmland ecosystem, crop residues provide a barrier against water erosion, and improve soil quality. Timely and accurate estimation of crop residue coverage (CRC) on a regional scale is essential for understanding the condition of ecosystems and the interactions with the surrounding environment. Satellite remote sensing is an effective way of regional CRC estimation. Both optical remote sensing and microwave remote sensing are common means of CRC estimation. However, CRC estimation based on optical imagery has the shortcomings of signal saturation in high coverage areas and susceptibility to weather conditions, while CRC estimation using microwave imagery is easily influenced by soil moisture and crop types. Synergistic use of optical and microwave remote sensing information may have the potential to improve estimation accuracy. Therefore, the objectives of this study were to: (i) Analyze the correlation between field measured CRC and satellite derived variables based on Sentinel-1 and Sentinel-2, (ii) investigate the relationship of CRC with new indices (OCRI-RPs) which combine optical crop residues indices (OCRIs) and radar parameters (RPs), and (iii) to estimate CRC in Yucheng County based on OCRI-RPs by optimal subset regression. The correlations between field measured CRC and satellite derived variables were evaluated by coefficient of determination (R2) and root mean square error (RMSE). The results showed that the normalized difference tillage index (NDTI) and radar indices 2 (RI2) had relatively higher correlations with field measured CRC in OCRIs and RPs (R2 = 0.570, RMSE = 6.560% and R2 = 0.430, RMSE = 7.052%, respectively). Combining OCRIs with RPs by multiplying each OCRI with each RP could significantly improve the ability of indices to estimate CRC, as NDTI × RI2 had the highest R2 value of 0.738 and lowest RMSE value of 5.140%. The optimal model for CRC estimation by optimal subset regression was constructed by NDI71 × σ V V 0 and NDTI × σ V H 0 , with a R2 value of 0.770 and a RMSE value of 4.846%, which had a great improvement when compared with the best results in OCRIs and RPs. The results demonstrated that the combination of optical remote sensing information and microwave remote sensing information could improve the accuracy of CRC estimation.

scholarly journals Constructing a New Inter-Calibration Method for DMSP-OLS and NPP-VIIRS Nighttime Light

2020 ◽  
Vol 12 (6) ◽  
pp. 937 ◽  
Author(s):  
Jinji Ma ◽  
Jinyu Guo ◽  
Safura Ahmad ◽  
Zhengqiang Li ◽  
Jin Hong
Keyword(s):  
Infrared Imaging ◽  
Dynamic Range ◽  
Calibration Method ◽  
Logistic Function ◽  
Coefficient Of Determination ◽  
Nighttime Light ◽  
Development Assessment ◽  
China Region

The anthropogenic nighttime light (NTL) data that are acquired by satellites can characterize the intensity of human activities on the ground. It has been widely used in urban development assessment, socioeconomic estimate, and other applications. However, currently, the two main sensors, Defense Meteorological Satellite Program’s Operational Linescan System (DMSP-OLS) and Suomi National Polar-orbiting Partnership Satellite’s Visible Infrared Imaging Radiometer Suite (NPP-VIIRS), provide inconsistent data. Hence, the application of NTL for long-term analysis is hampered. This study constructed a new inter-calibration method for DMSP-OLS and NPP-VIIRS nighttime light to solve this problem. First, NTL data were processed to obtain vicarious site across China. By comparing different candidate models, it is discovered the Biphasic Dose Response (BiDoseResp) model, which is a weighted combination of sigmoid functions, can best perform the regression between DMSP-OLS and logarithmically transformed NPP-VIIRS. The coefficient of determination of BiDoseResp model reaches 0.967. It’s residual sum of squares is 6.136 × 10 5 , which is less than 6.199 × 10 5 of Logistic function. After obtaining the BiDoseResp-calibrated VIIRS (BDRVIIRS), we smoothed it by a filter with optimal parameters to maximize the consistency. The result shows that the consistency of NTL data is greatly enhanced after calibration. In 2013, the correlation coefficient between DMSP-OLS and original NPP-VIIRS data in the China region is only 0.621, while that reaches to 0.949 after calibration. Finally, a consistent NTL dataset of China from 1992 to 2018 was produced. When compared with the existing methods, our method is applicable to the full dynamic range of DMSP-OLS. Besides, it is more suitable for country or larger scale areas. It is expected that this method can greatly facilitate the development of research that is based on the historical NTL archive.

An approach for assessing suitability for forest management based on constraints of the physical environment at a regional scale

2015 ◽  
Vol 45 (5) ◽  
pp. 529-539 ◽  
Author(s):  
André Robitaille ◽  
Jean-Pierre Saucier ◽  
Michel Chabot ◽  
Damien Côté ◽  
Catherine Boudreault
Keyword(s):  
Forest Management ◽  
Physical Environment ◽  
A Priori ◽  
Regional Scale ◽  
Forest Growth ◽  
Sensitivity Analyses ◽  
Land Area ◽  
Forest Operations ◽  
Entire Study ◽  
Aeolian Deposits

Constraints of the physical environment affect forest growth and forest operations. At a local scale, these constraints are generally considered during forest operations. At regional or continental scales, they are often integrated to larger assessments of the potential for a given land unit to be managed. In this study, we propose an approach to analyze the integration of physical-environment constraints in forest management activities at the regional scale (482 000 km2). The land features that pose constraints to forest management (i.e., hydromorphic organic deposits, dead-ice moraines, washed till, glacial block fields, talus, and active aeolian deposits, slopes > 40%) were evaluated within 1114 land districts. To distinguish land districts that can be suitably managed from those where constraints are too important for sustainable timber production, we carried out a sensitivity analysis of physical constraints for the 1114 land districts. After analysis of two portions of the study area under management, a land district was considered suitable for management when more than 20% of its land area consists of features imposing few constraints or, for mountain-type relief districts, when more than 40% of the land area consists of features imposing few constraints. These cutoff values were defined by expert opinion, based on sensitivity analyses performed on the entire study area, on analyses of two different sectors with different types of constraints and on a strong understanding of the study area. Our results show that land districts where the physical environment posed significant constraints covered 7.5% of the study area (36 000 km2). This study shows that doing an a priori classification of land units based on permanent environmental features could facilitate the identification of areas that are not suitable for forest management activities.

Seismic Hazard and Loss Analysis for Spatially Distributed Infrastructure in Christchurch, New Zealand

2016 ◽  
Vol 32 (2) ◽  
pp. 697-712 ◽  
Author(s):  
Hasan Manzour ◽  
Rachel A. Davidson ◽  
Nick Horspool ◽  
Linda K. Nozick
Keyword(s):  
New Zealand ◽  
Seismic Hazard ◽  
Ground Motion ◽  
Regional Scale ◽  
Average Error ◽  
Loss Analysis ◽  
Spatially Distributed ◽  
Small Set ◽  
Computationally Intensive ◽  
Distributed Infrastructure

The new Extended Optimization-Based Probabilistic Scenario method produces a small set of probabilistic ground motion maps to represent the seismic hazard for analysis of spatially distributed infrastructure. We applied the method to Christchurch, New Zealand, including a sensitivity analysis of key user-specified parameters. A set of just 124 ground motion maps were able to match the hazard curves based on a million-year Monte Carlo simulation with no error at the four selected return periods, mean spatial correlation errors of 0.03, and average error in the residential loss exceedance curves of 2.1%. This enormous computational savings in the hazard has substantial implications for regional-scale, policy decisions affecting lifelines or building inventories since it can allow many more downstream analyses and/or doing them using more sophisticated, computationally intensive methods. The method is robust, offering many equally good solutions and it can be solved using free open source optimization solvers.

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