Geosfera Indonesia最新文献

{"title":"Spatial Pattern of Multi-dimensional Regional Disparities in the Level of Socio-economic Development in West Bengal: A Geographical Analysis","authors":"Suranjan Majumder","doi":"10.19184/geosi.v6i3.25728","DOIUrl":"https://doi.org/10.19184/geosi.v6i3.25728","url":null,"abstract":"Micro-level spatial analysis of the different phenomenon duly associated with human development and also with the wellbeing of a nation. The study is a heart-core attempt to examine the inter-block regional disparity and development by constructing a multi-dimensional approach-based index. The study used thirty-four sub-dimensional variables under the five dimensions, including health, education, economy, socio-demography, and transport. The article used the data of the district statistical handbook of 2013 and census data of 2011. The empirical results of the study confirm the existence of huge inter-regional disparity on multi-dimensional developmental aspects, which drastically hampers the all-round growth and socio-economic development of Jalpaiguri Administrative Dvision (JAD) of West Bengal. The blocks of Khairabari, Darjeeling-Pulbazar, Rngli-rangit, Mirik, Kurseong, Kalimpong I & II are found to be high regional imbalances in the development of education, health, employment, and economy.  The study also helps to identify the most backward blocks. It confirms the huge inter-block/district disparities in West Bengal. The study argued that the low developed and high disparities blocks require special attention from policymakers in order to the improvement of overall socio-economic development of the study area.  \u0000Keywords: Jalpaiguri Administrative Dvision; Multi-dimensonal approach; regional disparity; regional imbalances; socio-economic development \u0000Copyright (c) 2021 Geosfera Indonesia and Department of Geography Education, University of Jember \u0000  \u0000 This work is licensed under a Creative Commons Attribution-Share A like 4.0 International License","PeriodicalId":33276,"journal":{"name":"Geosfera Indonesia","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41849202","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analysis of Mapping Forest, Settlement, and Rice Field Areas in Konawe Selatan District, Indonesia","authors":"A. Sejati, I. Saputra","doi":"10.19184/geosi.v6i3.27484","DOIUrl":"https://doi.org/10.19184/geosi.v6i3.27484","url":null,"abstract":"The rampant land-use change in Konawe Selatan District and the uncontrolled use leads to disaster and environmental stability effect, consequently, mapping the area function is important for controlling land-use activities to reduce the risk of disaster. Therefore, this study aims to determine the direction, distribution, and effective area of the function of forests, settlements, and rice fields. This study used a regional survey with a quantitative approach. Base map data of administrative, slope class, soil type, rainfall, and land-use obtained from the regional planning agency and SAS Planet were used and analyzed with quantitative descriptive analysis overlayed with scoring. The result showed that the direction of area functions was dominated by limited production forests by 50.05% while the distribution of protected forest function was spread across 14 sub-districts with limited production forests in all sub-districts, production forests in 17 sub-districts, settlements in 21 sub-districts, and rice fields in 9 sub-districts. Furthermore, the effective area shows that all area functions are accordance with the directions, except for rice fields which took over the function of forest while the effective area controlled by the regional planning shows that all area functions need correction following the regulation of the Minister of Agriculture of Indonesia. Areas which do not accordance with the function need to be evaluated, hence, regional planning is required to be revised by the people's representative in Konawe Selatan. \u0000Keywords: Analysis; Forest; Rice field; Settlement; Mapping \u0000Copyright (c) 2021 Geosfera Indonesia and Department of Geography Education, University of Jember \u0000  \u0000 This work is licensed under a Creative Commons Attribution-Share A like 4.0 International License","PeriodicalId":33276,"journal":{"name":"Geosfera Indonesia","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44037109","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Seasonal Variability of Waterlogging in Rangpur City Corporation Using GIS and Remote Sensing Techniques","authors":"Md. Naimur Rahman, Sajjad Hossain Shozib","doi":"10.19184/geosi.v6i2.21006","DOIUrl":"https://doi.org/10.19184/geosi.v6i2.21006","url":null,"abstract":"Waterlogging hazard is a significant environmental issue closely linked to land use for sustainable urbanization. NDWI is widely and effectively used in identifying and visualizing surface water distribution based on satellite imagery. Landsat 7 ETM+ and Landsat 8 OLI TIRS images of pre and post-monsoon (2002, 2019) have been used. The main objective of this study is to detect the seasonal variation of waterlogging in Rangpur City Corporation (RPCC) in 2002 and 2019. In the present study, we used an integrated procedure by using ArcGIS raster analysis. For pre and post-monsoon, almost 93% accuracy was obtained from image analysis. Results show that in 2002 during the pre and post-monsoon period, waterlogged areas were about 159.58 km2 and 32.32 km2, respectively, wherein in 2019, the changes in waterlogged areas are reversed than 2002. In 2019, during pre-monsoon, waterlogged area areas were 122.79 km2, and during post-monsoon, it increased to 127.05 km2. The research also depicts that the trend of the waterlogging situation largely depends on seasonal rainfall and a flawed drainage system. \u0000Keywords : Seasonal variation; Waterlogging; Remote sensing; GIS; Rangpur City Corporation \u0000  \u0000Copyright (c) 2021 Geosfera Indonesia and Department of Geography Education, University of Jember \u0000 This work is licensed under a Creative Commons Attribution-Share A like 4.0 International License","PeriodicalId":33276,"journal":{"name":"Geosfera Indonesia","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48793194","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessing The Impacts of Climate Variability on Rural Households in Agricultural Land Through The Application of Livelihood Vulnerability Index","authors":"Ginjo Gitima, Abiyot Legesse, Dereje Biru","doi":"10.19184/GEOSI.V6I1.20718","DOIUrl":"https://doi.org/10.19184/GEOSI.V6I1.20718","url":null,"abstract":"Climate variability adversely affects rural households in Ethiopia as they depend on rain-fed agriculture, which is highly vulnerable to climate fluctuations and severe events such as drought and pests. In view of this, we have assessed the impacts of climate variability on rural household’s livelihoods in agricultural land in Tarchazuria district of Dawuro Zone. A total of 270 samples of household heads were selected using a multistage sampling technique with sample size allocation procedures of the simple random sampling method. Simple linear regression, the standard precipitation index, the coefficient of variance, and descriptive statistics were used to analyze climatic data such as rainfall and temperature. Two livelihood vulnerability analysis approaches, such as composite index and Livelihood Vulnerability Index-Intergovernmental Panel on Climate Change (LVI-IPCC) approaches, were used to analyze indices for socioeconomic and biophysical indicators. The study revealed that the variability patterns of rainfall and increasing temperatures had been detrimental effects on rural households' livelihoods. The result showed households of overall standardized, average scores of Wara Gesa (0.60) had high livelihood vulnerability with dominant major components of natural, physical, social capital, and livelihood strategies to climate-induced natural hazards than Mela Gelda (0.56). The LVI-IPCC analysis results also revealed that the rural households in Mela Gelda were more exposed to climate variability than Wara Gesa and slightly sensitive to climate variability, considering the health and knowledge and skills, natural capitals, and financial capitals of the households. Therefore, interventions including road infrastructure construction, integrated with watershed management, early warning information system, providing training, livelihood diversification, and SWC measures' practices should be a better response to climate variability-induced natural hazards. \u0000Keywords: Households;  Livelihood Vulnerability Index; climate variability; Tarchazuria District \u0000  \u0000Copyright (c) 2021 Geosfera Indonesia and Department of Geography Education, University of Jember \u0000 This work is licensed under a Creative Commons Attribution-Share A like 4.0 International License","PeriodicalId":33276,"journal":{"name":"Geosfera Indonesia","volume":"6 1","pages":"96"},"PeriodicalIF":0.0,"publicationDate":"2021-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42265685","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Rethinking Urbanization: A Transit-Information-Communication –Technology-Oriented Development Path for the Developing Countries and Post-Industrial Towns","authors":"S. Lam, Heng Li, A. Yu","doi":"10.19184/GEOSI.V6I1.20810","DOIUrl":"https://doi.org/10.19184/GEOSI.V6I1.20810","url":null,"abstract":"This study explores a new path of urbanization to enhance the conventional economy-led urban development practice by conducting an urban quality of life (Uqol) survey.  It analyzes the Uqol evaluation gap caused by demographic attributes between developing countries, developed countries, and post-industrial town. We adopted a mixed-methods research design, including a literature review and an Uqol survey, to suggest the transit-oriented-development (TOD) and information-communication-technology (ICT) based urban-rural development concept. The finding indicates a disparity of Uqol mean score rankings among the developing countries, developed countries, and the marginalized post-industrial town. It highlights the health, transportation, socio-economic, and technological development in the developing countries strongly desired. Furthermore, Kruskal-Wallis H-test and Mann-Whitney U-test results show significant differences in economy, technology-ICT, smart living, and lifestyle within education, profession, age, and country groups.  It clarifies that the well-being gap is shaped by demography and exhibited geographically, which implies TOD-ICT advancement can break down geographical barriers for achieving sustainable growth in remote areas.  Supported by the planetary urbanization theory, the human-technology-driven urban development process would facilitate the maturity and implementation of the proposed TOD-ICT-based urban-ruralism (UxR) concept for enhancing the future global urbanization process. \u0000Keywords : Human and Social Geography; Information-Communication-Technology; Urban  Policymaking; Transit-Oriented-Development; Urban Quality of Life \u0000Copyright (c) 2021 Geosfera Indonesia and Department of Geography Education, University of Jember \u0000 This work is licensed under a Creative Commons Attribution-Share A like 4.0 International License","PeriodicalId":33276,"journal":{"name":"Geosfera Indonesia","volume":"6 1","pages":"1"},"PeriodicalIF":0.0,"publicationDate":"2021-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42942058","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Quantifying The Significance of Distance to Temporal Dynamics of Covid-19 Cases in Nigeria Using a Geographic Information System","authors":"I. Obuekwe, U. S. Anka, S. Ibrahim, Usman Ahmad Adam","doi":"10.19184/geosi.v6i1.21405","DOIUrl":"https://doi.org/10.19184/geosi.v6i1.21405","url":null,"abstract":"The coronavirus disease 2019 (COVID-19) is caused by a new strain of coronavirus that spreads primarily by close contact. Although Nigeria adopted lockdown measures, no defined strategies were used in setting the distance threshold for these lockdowns. Hence, understanding the drivers of COVID-19 is pivotal to an informed decision for containment measures in the absence of vaccines. Spatial and temporal analyses are crucial drivers to apprehending the pattern of diseases over space and time. Thus, this study aimed to quantify the significance of distance to the temporal dynamics of COVID-19 cases in Nigeria using the Geographic Information System. Incremental spatial autocorrelation was used to analyze datasets of each month in ArcGIS. March, April, May, and June exhibited patterns with no significant peaks, while July and August exhibited patterns with two statistically significant peaks. The first and second peaks of July were 301,338.39 and 365,947.83 meters, respectively, while August was 301,338.39 and 336,128.09 meters, respectively. Therefore, a significant difference in the clustering of COVID-19 over distances between July and August was established. This indicated that progression in the spread of the virus increased the virus's spatial coverage while the distance of risk of exposure decreased. This study's findings could be utilized to establish maximum movement restriction areas to contain the spread of COVID-19. \u0000Keywords: Distance; Incremental spatial autocorrelation; Covid-19; Disease; Nigeria \u0000Copyright (c) 2021 Geosfera Indonesia and Department of Geography Education, University of Jember \u0000 This work is licensed under a Creative Commons Attribution-Share A like 4.0 International License","PeriodicalId":33276,"journal":{"name":"Geosfera Indonesia","volume":"6 1","pages":"40"},"PeriodicalIF":0.0,"publicationDate":"2021-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48427145","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessment of Water Balance at Mayang Watershed, East Java","authors":"A. M. C. Sihombing, I. Indarto, S. Wahyuningsih","doi":"10.19184/GEOSI.V6I1.23111","DOIUrl":"https://doi.org/10.19184/GEOSI.V6I1.23111","url":null,"abstract":"Mayang Watersheds frequently hit by floods during the rainy season and drought during the dry season. This study aims to assess the water balance by calculating water resource availability and water demand in the Mayang watershed. The Water Evaluation and Planning (WEAP) model was used as the primary tool for the analysis. The supply of water comes only from precipitation. Demand was calculated based on the water demand for irrigation, domestic, urban, industrial, and livestock uses. The unit of time to calculate the water balance is ten days. It means that each month is divided into three-time steps. Analysis of the WEAP is based on the water demand from 2002 to 2019. The results showed that from 3rd December to 1st May, the Mayang river and its tributaries could supply all demand sites up to 100%. However, unmet demand occurs from 2nd May to 2nd December. The highest first unmet demand occurred in October, with 0.67 million m3. The management of water resources, especially in terms of distribution during the rainy season and dry season, must be considered. \u0000Keywords: Water balance; Water supply; Water demand; Mayang; Watershed; WEAP \u0000Copyright (c) 2021 Geosfera Indonesia and Department of Geography Education, University of Jember \u0000 This work is licensed under a Creative Commons Attribution-Share A like 4.0 International License","PeriodicalId":33276,"journal":{"name":"Geosfera Indonesia","volume":"6 1","pages":"55"},"PeriodicalIF":0.0,"publicationDate":"2021-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48274603","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development of Web-Based GIS Alert System for Informing Environmental Risk of Dengue Infections in Major Cities of Pakistan","authors":"Naureen Zainab, A. Tariq, S. Siddiqui","doi":"10.19184/GEOSI.V6I1.20792","DOIUrl":"https://doi.org/10.19184/GEOSI.V6I1.20792","url":null,"abstract":"Dengue is one of the emerging major public health problems, and its incidence varies with climate conditions. It affects millions of people's lives owing to unusual socioeconomic conditions and epidemiological factors. This study was designed to build a web-based GIS alert system for dengue data management and analysis which would centralize information and make it accessible to all relevant stakeholders before, during, and after crises. Three geographical regions were selected in this study. The user interface of the dengue alert system was developed based upon MapGuide. Results indicate that risk level was mainly associated with Breteau Index. Karachi and Lahore were at their highest risk, i.e., level 4. Islamabad and Chakwal were also at the highest risk, i.e., level 4. Attock had high risk, i.e., level 3 followed by Haripur with minimal level 1. The high Breteau Index showed a direct relationship to high potential transmission of dengue outbreaks, a more significant peak of dengue was the result of monsoons, while smaller peaks were observed due to domestic water storage. Hence, it was concluded that monsoon is the best suitable season for the development of dengue. Web-Based GIS Alert System for dengue data management and analysis was developed, centralizing information and making it accessible to all relevant stakeholders before, during & after a crisis. This program creation will provide a more analytical forum for advising multiple levels of risk and an experimental method for measuring the effect of different factors on risk level distribution by adjusting the component's weighting. \u0000Keywords : Dengue; GIS analysis; GUI; Alert system; Breteau index; Weighted overlay \u0000  \u0000Copyright (c) 2021 Geosfera Indonesia and Department of Geography Education, University of Jember \u0000 This work is licensed under a Creative Commons Attribution-Share A like 4.0 International License","PeriodicalId":33276,"journal":{"name":"Geosfera Indonesia","volume":"6 1","pages":"77"},"PeriodicalIF":0.0,"publicationDate":"2021-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43842322","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Landslide Hazard Analysis Using a Multilayered Approach Based on Various Input Data Configurations","authors":"I. Huqqani, T. Tien, J. Mohamad-Saleh","doi":"10.19184/GEOSI.V6I1.23347","DOIUrl":"https://doi.org/10.19184/GEOSI.V6I1.23347","url":null,"abstract":"Landslide is a natural disaster that occurs mostly in hill areas. Landslide hazard mapping is used to classify the prone areas to mitigate the risk of landslide hazards. This paper aims to compare spatial landslide prediction performance using an artificial neural network (ANN) model based on different data input configurations, different numbers of hidden neurons, and two types of normalization techniques on the data set of Penang Island, Malaysia. The data set involves twelve landslide influencing factors in which five factors are in continuous values, while the remaining seven are in categorical/discrete values. These factors are considered in three different configurations, i.e., original (OR), frequency ratio (FR), and mixed-type (MT) data, which act as an input to train the ANN model separately. A significant effect on the final output is the number of hidden neurons in the hidden layer. In addition, three data configurations are processed using two different normalization methods, i.e., mean-standard deviation (Mean-SD) and Min-Max. The landslide causative data often consist of correlated information caused by overlapping of input instances. Therefore, the principal component analysis (PCA) technique is used to eliminate the correlated information. The area under the receiver of characteristics (ROC) curve, i.e., AUC is also applied to verify the produced landslide hazard maps. The best result of AUC for both Mean-SD and Min-Max with PCA schemes are 96.72% and 96.38%, respectively. The results show that Mean-SD with PCA of MT data configuration yields the best validation accuracy, AUC, and lowest AIC at 100 number of hidden neurons. MT data configuration with the Mean-SD normalization and PCA scheme is more robust and stable in the MLP model's training for landslide prediction.  \u0000Keywords: Landslide; ANN; Hidden Neurons; Normalization; PCA; ROC; Hazard map \u0000  \u0000Copyright (c) 2021 Geosfera Indonesia and Department of Geography Education, University of Jember \u0000 This work is licensed under a Creative Commons Attribution-Share A like 4.0 International License","PeriodicalId":33276,"journal":{"name":"Geosfera Indonesia","volume":"6 1","pages":"20"},"PeriodicalIF":0.0,"publicationDate":"2021-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43214766","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Influence of Soil Conditioning on Soil Infiltration Rate in Urban Facilities","authors":"Searphin Nugroho, Wahyono Hadi","doi":"10.19184/geosi.v6i2.24646","DOIUrl":"https://doi.org/10.19184/geosi.v6i2.24646","url":null,"abstract":"Several attempts have been made to increase the permeable area in the cities, which include the building of green facilities such as parks and urban forests. Since these areas were built with soil compaction, the potential for infiltrating water differs compared with the natural green area. Therefore, this research aims to analyze the influence of soil conditioning on the constant infiltration rate using variables such as soil compaction, texture, and the presence of vegetation cover in urban facilities. The data used were obtained through field infiltration measurement using a single ring infiltrometer. In this research, the analysis carried out includes soil texture, Horton equation, the difference between conditioned soils and control plots, and USDA hydrologic soil classifications. The results showed that all variables (soil compaction, the presence of vegetation cover, and soil texture) have a significant effect on the constant infiltration rate. Based on the soil conditioning, the infiltration rate is increased on the vegetated plots and decreased on the plots with the combination of vegetation and compaction, as well as the compacted plots. Furthermore, the effect of vegetation cover is more significant in silt loam textured soil, while the influence of compaction is more on clay textured soil. The potential constant infiltration rate on the plots of similar characteristics with green urban areas are on K2 and L2 with 2.698 mm/h and 1.525 mm/h, respectively. Therefore, these plots have a moderate runoff potential based on USDA hydrologic soil classification. Keywords: Compaction; Infiltration; Soil conditioning; Urban facilities   Copyright (c) 2021 Geosfera Indonesia and Department of Geography Education, University of Jember This work is licensed under a Creative Commons Attribution-Share A like 4.0 International License","PeriodicalId":33276,"journal":{"name":"Geosfera Indonesia","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67985374","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}