scholarly journals SPATIAL PATTERN OF RICE FIELD PRODUCTIVITY BASED ON PHYSICAL CHARACTERISTICS OF LANDSCAPE IN CITARUM WATERSHED, WEST JAVA, INDONESIA

2018 ◽  
Vol 5 (2) ◽  
pp. 237
Author(s):  
Nugroho Purwono ◽  
Arif Aprianto
Keyword(s):  
Spatial Pattern ◽  
Spatial Autocorrelation ◽  
Rice Field ◽  
Close Relation ◽  
Physical Characteristics ◽  
P Value ◽  
West Java ◽  
Index Measurement ◽  
Middle Stream ◽  
Downstream Area

This research analyse the pattern of rice field productivity. It was identified from the characteristics of the land component based on physiographic condition through landscape perspective. Identification of productivity pattern has been done partially based on each typology of land components into several segment of the Citarum watershed, West Java Province, Indonesia. Spatial autocorrelation through GIS tool was used as the method in this research. By using moran’s I (index) measurement, degree of dependency of these variables are generated to find the spatial pattern. The result of this study is separated the value of productivity based on segments of watershed, the values of the average of productivity are upstream (6.39 ton/Ha), middle stream (6.52 ton/Ha), and downstream (7.17 ton/Ha), sequentially. The highest productivity is in the downstream area (9.83 ton/Ha) and the lowest is in the upstream area (4.55 ton/Ha). In accordance with physiographic typology showed the rice field in the middle stream has more variation than the upstream or teh downstream area. The highest of average rice field productivity is on alluvial plain. Overall, the rice field productivity on the hills is higher rather that other types of landform the stuctural formation is more dominant, in addition. The spatial pattern shows the distribution of rice field  productivity most likely to clustered based on the similarity of physiographic type. Statistically, it has p-value <0.01 and z-score >2.58 (239.26) correspond to Spatial Autocorrelation (Moron’s I). This positive value means a less than 1% likelihood that this clustered pattern could be result of random choice, which the rice field productivity value has similar pattern to others. Thus, it can be generated that the pattern of rice field productivity has a very close relation with the physical characteristics which associated of each typology of land components.

scholarly journals Spatial Pattern of Rice Field Productivity based on Physical Characteristics of Landscape in Citarum Watershed, West Java

2018 ◽  
Vol 5 (2) ◽  
pp. 237
Author(s):  
Nugroho Purwono ◽  
Arif Aprianto
Keyword(s):  
Spatial Pattern ◽  
Spatial Autocorrelation ◽  
Rice Field ◽  
Close Relation ◽  
Physical Characteristics ◽  
P Value ◽  
West Java ◽  
Index Measurement ◽  
Middle Stream ◽  
Downstream Area

This research to analyse the pattern of rice field productivity that is identified through landscape perspective. Identification of productivity pattern has been done partially based on each typology of land components into several segment of the Citarum watershed, West Java Province, Indonesia. Spatial autocorrelation through GIS tool is used as the method in this research. By using moran’s I (index) measurement, degree of dependency of these variables are generated to find the spatial pattern. The result of this study is separated the value of productivity based on segments of watershed, the values of the average of productivity are upstream (6,39 ton/Ha), middle stream (6,52 ton/Ha), and downstream (7,17 ton/Ha), sequentially. The highest productivity is in the downstream area (9,83 ton/Ha) and the lowest is in the upstream area (4,55 ton/Ha). In accordance with physiographic typology showed the rice field in the middle stream has more variation than the upstream or teh downstream area. The highest of average rice field productivity is on alluvial plain. Overall, the rice field productivity on the hills is higher rather that other types of landform the stuctural formation is more dominant, in addition. The spatial pattern shows the distribution of rice field  productivity most likely to clustered based on the similarity of physiographic type. Statistically, it has p-value <0,01 and z-score >2,58 (239,26) correspond to Spatial Autocorrelation (Moron’s I). This positive value means a less than 1% likelihood that this clustered pattern could be result of random choice, which the rice field productivity value has similar pattern to others. Thus, it can be generated that the pattern of rice field productivity has a very close relation with the physical characteristics which associated of each typology of land components.

scholarly journals Hot-spots Clusters of HIV Infection in Cameroon: Space-time Analysis from the Demographic and Health Surveys

2021 ◽  
Author(s):  
Arsène Brunelle Sandie ◽  
Jules Brice Tchatchueng ◽  
Anne Esther Njom Nlend
Keyword(s):  
Hiv Infection ◽  
Spatial Pattern ◽  
Spatial Autocorrelation ◽  
Health Survey ◽  
Hot Spots ◽  
Space Time ◽  
Demographic And Health Survey ◽  
Effective Control ◽  
P Value ◽  
Time Analysis

Abstract Background : The Human Immunodeficiency Virus(HIV) infection prevalence in Cameroon has consecutively decreased from 5.28% in 2004 to 2.8% in 2018. However , this total decrease in prevalence may hide some disparities especially in terms of spatial or geographical pattern. Efficient control and fighting against HIV infection requires to target hotspot areas . This study was aimed to investigate whether there is a spatial pattern of HIV in Cameroon and to determine the hot-spots clusters .Methods : HIV biomarkers data with Global Positioning System (GPS) location data were leveraged from the Cameroon 2004, 2011, and 2018 Demographic and Health Survey ( DHS ) after an approved request from the MEASURES Demographic and Health Survey Program . The spatial autocorrelation test was performed with the Moran I test through the R package " DCluster ". The discrete Poisson model was fitted to scan and detect hot-spots clusters based on the Kulldorff test with the SaTScan software version 9.4, with purely spatial and space -time analysis respectively . Finally , the data and detected clusters were imported to QGIS software version 3.20.2 for maps manipulations.Results : For the three considered periods of 2004, 2011, and 2018 respectively , there was a spatial autocorrelation of HIV infection in Cameroon . A total of 3, 5, and 2 significant hot-spots clusters were detected for the periods of 2004, 2011, and 2018 respectively . In the prospective space -time analysis , 2 significant clusters have been detected from 2004 to 2018. The relative- risk in the significant detected clusters were 2.72 (p-value =0.001 ) and 3.37 (p-value= 0.026) respectively . Cluster 1 included the following subdivisions : Mefou et Afamba , Nyong et So'o , Nyong et Mfoumou , Haute Sanaga , Mvila , Dja et lobo , Haut- Nyong , Boumba et Ngoko ; Kadey , Lom et Djerem , and Mbere . The other cluster included : Nkam , Sanaga -Maritime, and Nyong - Ekele .Conclusion : Despite the decrease of HIV epidemiology in Cameroon , the study revealed that there is a spatial pattern of HIV in Cameroon and the hot-spots clusters were detected . In its effort to eliminate HIV infection by 2030 in Cameroon , the public health policies should target more of the detected HIV hot-spots clusters in this study while maintaining effective control in other parts of the country which are cold -spots.

scholarly journals Hot-Spots Clusters of HIV Infection in Cameroon : Space-Time Analysis from the Demographic and Health Surveys

2021 ◽  
Author(s):  
Arsène Brunelle Sandie ◽  
Jules Brice Tchatchueng Mbougua ◽  
Anne Esther Njom Nlend
Keyword(s):  
Hiv Infection ◽  
Spatial Pattern ◽  
Spatial Autocorrelation ◽  
Health Survey ◽  
Hot Spots ◽  
Space Time ◽  
Demographic And Health Survey ◽  
Effective Control ◽  
P Value ◽  
Time Analysis

Abstract Background: The Human Immunodeficiency Virus(HIV) infection prevalence in Cameroon has consecutively decreased from 5.28% in 2004 to 2.8% in 2018. However, this total decrease in prevalence may hide some disparities especially in terms of spatial or geographical pattern. Efficient control and fighting against HIV infection requires to target hotspot areas. This study was aimed to investigate whether there is a spatial pattern of HIV in Cameroon and to determine the hot-spots clusters.Methods: HIV biomarkers data with Global Positioning System (GPS) location data were leveraged from the Cameroon 2004, 2011, and 2018 Demographic and Health Survey (DHS) after an approved request from the MEASURES Demographic and Health Survey Program. The spatial autocorrelation test was performed with the Moran I test through the R package ”DCluster”. The discrete Poisson model was fitted to scan and detect hot-spots clusters based on the Kulldorff test with the SaTScan software version 9.4, with purely spatial and space-time analysis respectively. Finally, the data and detected clusters were imported to QGIS software version 3.20.2 for maps manipulations.Results: For the three considered periods of 2004, 2011, and 2018 respectively, there was a spatial autocorrelation of HIV infection in Cameroon. A total of 3, 5, and 2 significant hot-spots clusters were detected for the periods of 2004, 2011, and 2018 respectively. In the prospective space-time analysis, 2 significant clusters have been detected from 2004 to 2018. The relative-risk in the significant detected clusters were 2.72(p-value= 0.001) and 3.37(p-value=0.026) respectively. Cluster 1 included the following subdivisions : Mefou et Afamba, Nyong et So’o, Nyong et Mfoumou, Haute Sanaga, Mvila, Dja et lobo, Haut-Nyong, Boumba et Ngoko; Kadey, Lom et Djerem, and Mbere. The other cluster included : Nkam, Sanaga-Maritime, and Nyong-Ekele.Conclusion: Despite the decrease of HIV epidemiology in Cameroon, the study revealed that there is a spatial pattern of HIV in Cameroon and the hot-spots clusters were detected. In its effort to eliminate HIV infection by 2030 in Cameroon, the public health policies should target more of the detected HIV hot-spots clusters in this study while maintaining effective control in other parts of the country which are cold-spots.

Accuracy Analysis of DEM Based on Coons Surface

2011 ◽  
Vol 65 ◽  
pp. 214-217
Author(s):  
Yao Ge Wang ◽  
Peng Yuan Wang
Keyword(s):  
Spatial Pattern ◽  
Spatial Autocorrelation ◽  
Boundary Curve ◽  
Digital Elevation ◽  
Grid Points ◽  
Elevation Model ◽  
Global Spatial Autocorrelation ◽  
Core Problem ◽  
Dem Model ◽  
Better Than

Interpolation is the core problem of Digital Elevation Model (DEM). The Coons DEM model is better than bilinear interpolation and moving surface fitting. It is constructed by grid boundary curve, the curve interpolates by some adjoining grid points. Its spatial pattern of error is random in global area, there is no significant global spatial autocorrelation, but it is an increasing trend along with the terrain average gradient increases.There is significant local spatial autocorrelation, the spatial pattern of error converges strongly in local areas.

FISH DIVERSITY IN THE DOWNSTREAM REGION OF CIPANAS RIVER INDRAMAYU, WEST JAVA INDONESIA

Zoo Indonesia ◽  
2020 ◽  
Vol 29 (1) ◽  
Author(s):  
Titin Herawati ◽  
Gema Wahyudewantoro ◽  
Yuli Andriani ◽  
Heti Herawati ◽  
Naomi Masnida Yunisia Siregar
Keyword(s):  
Water Quality ◽  
Census Data ◽  
Fish Assemblages ◽  
Survey Methods ◽  
Upstream Region ◽  
Fish Diversity ◽  
West Java ◽  
Fish Collection ◽  
Java Sea ◽  
Downstream Area

Cipanas River is one river in West Java where its upstream region in Tampomas Mountain, Sumedang and it is emptied into the Java Sea, Indramayu. The study was aimed to investigate fish diversity in the downstream area of Cipanas River. The study was conducted by survey methods with census data collection techniques, taken place at 3 stations of Santing, Tempalong, and Cemara of Indramayu Regency. The parameters measured consisted water quality and fish assemblages. Water quality was measured referring to standard laboratory protocol, and fish collection was made by case net with different mesh sizes. The results showed that water quality conditions of the Cipanas River downstream was suitable for inhabiting fishes. There were as many as 548 individual fishes caught belonging to 21 species, 16 genera, and 14 families. Fish diversity was categorized as medium with 1.6 ≤ H ’≤ 2.2 indicating fairly good community structure, and the Evenness index was 0.81 ≤ E ≤ 0.86 to show highly evenly distributed.

scholarly journals Kesesuaian dan Arahan Penggunaan Lahan Berdasarkan Rencana Pola Ruang Wilayah di Hulu Daerah Aliran Sungai Kelara

2017 ◽  
Vol 9 (2) ◽  
pp. 75
Author(s):  
Usman Arsyad ◽  
Andang Suryana Soma ◽  
Wahyuni Wahyuni ◽  
Tita Rahayu Arief
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Spatial Pattern ◽  
Rice Field ◽  
Landsat Imagery ◽  
Agroforestry Systems ◽  
Community Forest ◽  
Dryland Agriculture ◽  
Dry Land ◽  
Land Cover Maps

This study aimed to analyze the compatibility between the land cover spatial pattern plan and determine the direction of land use in the event of a discrepancy. This research was conducted on the Kelara Upstream Watershed located in gowa and jeneponto using land cover maps generated from landsat imagery interpretation 8. Then overlay to map the spatial pattern plan. Then determined the order of land use is done when there is a discrepancy between the results of the overlay with maps of land cover spatial pattern plan. The result showed that 41,05% of the total area of the Kelara Upstream Watershed of 28.185,68 ha a land use form of a orchards. After overlay discovered discrepancy land cover maps with maps of spatial pattern plan. Based on a map spatial pattern plan that should in reality the field is man made forest, orchards, dryland agriculture and rice field. According to these condition the specified order of land use that is Hkm (Community Forest) with agroforestry and Agroforestry Systems. Rice field In the Protected and Production forest order to intensification land use and plantations forest, orchards and dry land agriculture order to Community Forest with agroforestry systems . In the area of cultivation the land use rice field, orchards and dryland agriculture order to agroforestry systems.

scholarly journals Beban Keluarga Berhubungan dengan Kemampuan Keluarga dalam Merawat Pasien Halusinasi

2020 ◽  
Vol 8 (1) ◽  
pp. 97
Author(s):  
Cucu Rokayah ◽  
Fahmi Dwi Novian ◽  
Supriyadi Supriyadi
Keyword(s):  
Univariate Analysis ◽  
Psychiatric Hospitals ◽  
Sampling Technique ◽  
P Value ◽  
West Java ◽  
Chi Square ◽  
Hospital Outpatient ◽  
The Family ◽  
Chi Square Test ◽  
Heavy Burden

Skizofrenia merupakan suatu gangguan mental yang menyebabkan timbulnya pikiran, persepsi, emosi, gerakan, perilaku yang aneh dan terganggu.Penderita skizofrenia 70% diantaranya mengalami halusinasi.Dampak terberat yang dirasakan oleh keluarga dalam merawat pasien dengan halusinasi adalah dampak pada psikologis, terutama stress atau beban yang dirasakan oleh keluarga. Tujuan penelitian ini adalah untuk mengetahui Hubungan Beban Keluarga dengan Kemampuan Keluarga Dalam Merawat Pasien Halusinasi di InstalasI Rawat Jalan Rumah Sakit Jiwa Provinsi Jawa Barat. Metode penelitian ini menggunakan deskriptif korelasional dengan tehnik purposive samplingterhadap 69 responden dari populasi 996 responden di Instalasi Rawat Jalan Rumah Sakit Jiwa Provinsi Jawa Barat. instrumen yang digunakan dalam penelitian ini adalah kuesioner beban keluarga dan kemampuan keluarga yang terdiri dari kognitif dan psikomotor. Analisa univariat dalam penelitian ini menggunakan distribusi frekuensi dan analisa bivariat pada penelitian ini menggunakan uji chi square  hasil penelitian menunjukan beban berat yaitu 35 responden (50,7 %), sedangkan untuk kemampuan keluarga baik 46 responden (42 %). kesimpulannya bahwa ada hubungan antara beban keluarga dengan kemampuan keluarga dalam merawat pasien halusinasi di Instalasi Rawat Jalan Rumah Sakit Jiwa Provinsi Jawa Barat dengan nilai p value (0,001) < (0,005). Kata kunci: halusinasi, beban keluarga, kemampuan keluarga FAMILY BURDEN CONNECTED WITH FAMILY ABILITY TO TREAT HALLUCINATORY PATIENTS ABSTRACTSchizophrenia is a mental disorder that causes the onset of thought, perception, emotion, movement, strange and disturbing behavior. Schizophrenia 70% of them have hallucinations.The toughest impact the family feels in treating patients with hallucinations is its impact on the psychological, especially the stress or burden felt by the family.The purpose of this research is to know the family's burden relationship with the ability of the family to treat hallucinative patients in the installation of hospital outpatient in West Java province.This method of study uses descriptive correlation with purposive sampling technique against 69 respondents from the population of 996 respondents in an outpatient installation of psychiatric hospitals in West Java province. The instruments used in this reseacrh used family load questionnaires and family skills questionnaires comprising cognitive and psychomotor. Univariate analysis in this research using frequency distribution and bivariat analysis of this study using chi square test. the results showed a heavy burden of 35 respondents (50.7%), while for family ability of either 46 respondents (42%).in conclusion that there is a connection between the burden of the family with the ability of families to treat hallucinatory patients in the hospital outpatient installation in the psychiatric province of West Java with a value of P (0.001) < (0.005). Keywords: hallucinations, family load, abillity family

scholarly journals Spatial pattern and Factors associated with khat chewing among adult males 15-59 years in Ethiopia, EDHS 2016. Generalized Estimating Equation Approach

2020 ◽  
Author(s):  
Zemenu Tessema Tadesse ◽  
Tadele Amare Zeleke
Keyword(s):  
Spatial Pattern ◽  
Estimating Equation ◽  
Scan Statistics ◽  
Outcome Variable ◽  
P Value ◽  
Age Group ◽  
Adult Males ◽  
Factors Associated ◽  
Khat Chewing ◽  
Generalized Estimating

Abstract Background Khat chewing has become prevalent in the world due to the improvement of road and air transportation. In Ethiopia, khat chewing is more prevalent and wildly practiced by men. Khat has a negative effect on social, economic and mental health. Therefore, this study aims to show spatial patterns and factors associated with khat chewing among male adults 15-59 years in Ethiopia. Methods A total of 12,594 men who chew khat in their were included in this study. ArcGIS version 10.7 software was used to visualize spatial pattern chewing khat among adult men in Ethiopia. The Bernoulli model was applied using Kilduff SaTScan version 9.6 software to identify significant purely spatial clusters for chewing khat in Ethiopia. The robust standard error method of generalized estimating equations was used for the binary outcome variable from the clustered data and adjusted odds ratios with 95% confidence interval were reported. Results A total of 12,594 participants were included in the analysis. The prevalence of ever khat chewing in this study was 3418 (27.14%) with 95% CI 26.37% to 27.92%. From EDHS 2016 survey the high proportion of chewing khat was located in Diredawa, Harari, Southern Oromia, Somai and Benishangu Gumuz Regions. In spatial scan statistics analysis, a total of 126 clusters (RR= 4.02, P-value < 0.001) was identified. Age group 30-44 (AOR=1.44, 95% CI: 1.27, 1.62), being single (AOR=1.86, 95% CI: 1.64, 2.12), Muslim religion (AOR=4.91, 95% CI: 3.69, 8.19), media exposure (AOR=0.77, 95% CI: 0.68, 0.86), working status(AOR=0.45, 95% CI: 0.39, 0.53), alcohol drinking (AOR=2.91, 95% CI: 2.43, 3.39) and region were statistically significant factors affecting chewing Khat in Ethiopia. Conclusions The prevalence of chewing chat in Ethiopia was high and located in Diredawa, Harari, Southern Oromia, Somai and Benishangu Gumuz Regions. Older age group, single, drinker, media unexposed, had no work and Muslim religion follower should be given spatial attention in reducing the prevalence of chewing khat. Therefore, it is good to teach the health impact of khat chewing through media.

Spatial analysis of rural drinking water supply in China

Water Policy ◽  
2014 ◽  
Vol 17 (3) ◽  
pp. 441-453 ◽  
Author(s):  
Hongxing Li ◽  
Qi Zhang ◽  
Weiwei Li ◽  
Qing Luo ◽  
Kaitai Liu ◽  
...  
Keyword(s):  
Drinking Water ◽  
Water Supply ◽  
Spatial Pattern ◽  
Spatial Autocorrelation ◽  
Drinking Water Supply ◽  
Spatial Autocorrelation Analysis ◽  
Autocorrelation Analysis ◽  
Rural Water Supply ◽  
Rural Water ◽  
Rural Drinking Water Supply

A spatial autocorrelation analysis method was employed to process the spatial change of rural water supply over the past 19 years in the People's Republic of China. Statistical analyses indicate great achievements in rural water supply construction. Two main indices describing rural drinking water supply status, the Rural Popularization Rate of Tap Water and the Rural Popularization Rate of Water Improvement Beneficiaries, were found to be spatially auto-correlated. The Global Moran's I of the latter decreased generally, and local spatial autocorrelation analysis showed that the regional gap of rural water supply infrastructure is declining. The main factors affecting the spatial pattern of rural water supply were analyzed through the mean centre method. Our research shows that the spatial pattern of economic development and government investment has had a decisive role in the formation and evolution of rural water supply.

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