Fire is a natural disaster that usually occurs during dry season in both developed and developing countries. Best visualization of fire information is a map, because map is easy to use, and has a strong visual impression. Maps can also be used as a medium to deliver fire mitigation instruction. Fire data can be seen from hotspots data recorded using S-NPP VIIRS satellite imagery. Hotspot data from satellite imagery processed in Arc GIS to compose Fire Level Maps which is then used as fire disaster management reference. Based on this, it is necessary to conduct a study which purposively can map a fire level from S-NPP VIIRS satellite imagery hotspot data so it can used as disaster management reference. So this study entitled as Mapping of Fire Levels using S-NPP VIIRS as a Disaster Management Reference. This research is classified as quantitative descriptive research. Population and samples of the research are all hotspots recorded by S-NPP VIIRS satellite imagery in Banjarbaru City covering Banjarbaru Utara, Landasan Ulin, Cempaka, Banjarbaru Selatan and Lianganggang Subdistrict from 2012-2022. Monthly hotspot data is used in this research and are based on high, medium and low confidence levels. Hotspot data recorded from satellite imagery is processed using geographic information systems and remote sensing technology. The results show the number of hotspots recorded from S-NPP VIIRS Satellite Imagery from 2012-2022 in Banjarbaru City was 2.900 hotspot. The highest number of hotspots was in Linganggang (1429 hotspot) followed by Landasan Ulin (1.165 hotspot) and the least in Banjarbaru Selatan (14 hotspot). Most hotspots are found in dry months; August (307 hotspot), September (1.370 hotspot), October (1.053 hotspot) and November (128 hotspot). The number of hotspots based on the medium level of confidence is mostly found in Banjarbaru City (2.560 hotspot). High number of high and medium confidence hotspots data resulting into higher fire risk. Result from hotspot data processing is a Fire Level Map which can be used as a basis for disaster management so that the negative impact of fires can be minimized.
<p><span lang="EN-US">Fire is a disaster and its frequency is increasing every year. Seeing this, it is very important to know the spatial distribution of hotspots to determine the potential for fires in each area. Based on this, it is necessary to conduct research with the title "Spatial Distribution of Hotspots Using S-NPP VIIRS for Early Detection of Potential Fires". This research includes the type of descriptive research. The population in the study were all hotspots in Banjar Regency, South Kalimantan Province. Hotspots were taken from the results of the S-NPP VIIRS satellite imagery recording from 2012-2021. The number of samples is equal to the number of populations. The data analysis technique uses nearest neighbor analysis and descriptive analysis which is processed using Arc GIS software. The research results show that fires occur during the dry season, namely in July, August, September and October. Spatial distribution of hotspots from the results of S-NPP VIIRS satellite imagery based on the accuracy of the most confidence level in July, August, September and October. If the spatial distribution of hotspots is known, it can be used as an early detection effort. Early detection is carried out as an effort to prevent and control fires with a greater negative impact. In addition, with the existence of an early warning system, the community is better prepared to deal with fires so that the negative impacts that may arise due to fires can be minimized, including loss of life and property. </span></p>
This study aims to describe theEffectiveness of Using Village Funds on VillageDevelopment in Salat BaruVillage and Babai Village in Karau Kuala District from 2017 budget year. This research method uses a qualitative research approach with a qualitative descriptive research type. Data collection techniques used were observation, interviews, and documentation studies. Data analysis techniques are through the stages of data reduction, data presentation, and drawing conclusions/verification. The results founded that using of the Village Fund by the Salat Baru village governments or Babai village governments was still quite effective for village society when viewed from the implementation and needs of the village society because all the development programs implemented are opinions or idea from the village society. But , its can said still less effective when viewed from the implementation of the Village Minister's Regulation on the priority of using the Village Fund because in determining the goals and objectives of the use of the Village Fund only focused on physical development or village infrastructure development.
Regional tax is one of the main in state revenues. With the existence of regional autonomy, members of the government are strong for autonomous regions, namely being able to organize and manage their own households. Local governments need to maximize the potential of local taxes. This research use qualitative method with qualitative descriptive type. Indicator Based From Tax implementation such as SISMIOP Maintenance data base, Mass print simulation, bulk print, Submission of SPPT and DHKP PBB, billing, payment and evaluation meeting, So the Results at BP2RD departure point can be concluded Good Enough Against Admissions PAD. Supported by the local government, sufficient budget and facilities. And the State Civil Apparatus, lack of socialization and public awareness as an inhibiting factor. This research recommends the BP2RD office of Barito Kuala District to be more active in registering and socializing the Land and Building Tax to the public so that the public is aware of paying land and building taxes.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.