Pemanfaatan Data CHIRPS untuk Pemetaan Curah Hujan Per Kabupaten di Wilayah Jambi dengan Menggunakan ArcGIS Utilization of CHIRPS Data for Rainfall Mapping by District in Jambi Region Using ArcGIS

Crossmark

Main Article Content


Abstract

It was recorded that several areas in jambi region in the last 5 years from 2020 to 2024 have the potential to be affected by flooding, especially in densely populated urban areas and around the lowland, at least once a year there was flood with quite large water discharges that occurred during the rainy season.therefore, this research was carried out, where this research aims to explore information related to average rainfall which includes information on the distribution of rain, mapping rainfall part of district by utilizing rain datas that coincides in jambi area.another aim of this research is to learn more about how to map raw data using the ArcGIS application.this research uses monthly data sourced from CHIRPS (climate hazards center infra red precipitation with station data).this data is used as a solution for areas where rainfall data is rarely available and USGS: lansat 8 then the data will be processing using ArcGIS software.and then the data was summarized using Microsoft excel and from the result it can be seen that the distribution of rainfall in jambi is fairly even and is in the range of 1501-3000 mm at each district.

Downloads

Download data is not yet available.

Citation Metrics & Similar Scopus Articles

Data source Crossref
0
citations
Citation counts are source-specific and may differ because database coverage, reference matching, and update schedules are different. Counts are not added together. Crossref values represent citation links registered and matched by Crossref.
Check Secondary Documents in Scopus
Open this article in Scopus, then check the Secondary documents tab. Use Manual Citation Fallback only for counts you have verified manually.
Open in Scopus
Similar Scopus Articles
Scopus
  1. Naemi Z. (2027)
    The Relationship between Second Language Learning Strategies, Learning Engagement, and Writing Skill in the Arabic Writing Curriculum
    Language Related Research, 17(4), 331-360
  2. Davoodi A. (2027)
    A Reflection on The Moral Virtues And Vices Described in Nahj al-Balāghah in The Light of Image Schemas
    Language Related Research, 17(4), 103-137
  3. Sadati Nooshabadi S.M. (2027)
    Object Agreement: A Syntactic Phenomenon in Middle Persian Zoroastrian Texts
    Language Related Research, 17(4), 71-101

Article Details

How to Cite
Umairoh, P. S., & Gusmira, E. (2024). Pemanfaatan Data CHIRPS untuk Pemetaan Curah Hujan Per Kabupaten di Wilayah Jambi dengan Menggunakan ArcGIS. Al-DYAS, 4(1), 212-221. https://doi.org/10.58578/aldyas.v4i1.4408

References

Anjarwati, S., Ery Suhartanto, & Linda Prasetyorini. (2024). Aplikasi Sistem Informasi Geografis (SIG) Untuk Pemetaan Daerah Rawan Banjir Sebagai Upaya Mitigasi Di DAS Laweyan. Jurnal Teknologi Dan Rekayasa Sumber Daya Air, 4(02), 1386–1399. https://doi.org/10.21776/ub.jtresda.2024.004.02.140

Girsang, R. G. (2024). Pemetaan Wilayah Potensi Longsor Desa Cukilan Kecamatan Suruh Kabupaten Semarang Menggunakan Sistem Informasi Geografi. Jurnal Biocelebes, 18(1), 44–56. https://doi.org/10.22487/bioceb.v18i1.16563

Maneno, R., Lestari, A. K. D., & Fallo, K. (2023). Pemetaan Curah Hujan Tahunan Dan Keadaan Hidrogeologi di Kabupaten Timor Tengah Utara Untuk Identifikasi Potensi Kekeringan. Journal of Physics and It’s Application, 3(2), 271–276. https://doi.org/10.59632/magnetic.v3i2.375

Nurhijriah, L., Ruhiyat, Y., Saefullah, A., & Rostikawati, D. A. (2022). Pemetaan Distribusi Curah Hujan Rata-Rata Menggunakan Metode Isohyet Di Wilayah Kabupaten Tangerang. Journal of Physics, 3(2), 46–55. https://doi.org/10.33369/nmj.v3i2.23100

Pratama, D., Sutikno, S., & Yusa, M. (2024). Pemetaan Daerah Rawan Ancaman Banjir di Area Kabupaten Kampar Dengan Menggunakan GEE (Google Earth Engine). Jurnal Saintis, 24(01), 21–28. https://doi.org/10.25299/saintis.2024.vol24(01).15487

Ramadhani, M. A., Amin, M., & Tusi, A. (2023). Analisis Tingkat Kerawanan Bencana Banjir di Kota Bandar Lampung Berbasis GIS ( Geographic Information System ) dan Citra Landsat 8 Oli. Jurnal Agricultural Biosystem Engineering, 2(4), 510–514. https://jurnal.fp.unila.ac.id/index.php/ABE/article/view/8392

Risamasu, R. G., Laimeheriwa, S., Madubun, E. L., & Luhukay, M. (2023). Analisis Perubahan Curah Hujan Dan Pemetaan Zona Agroklimat Oldeman Pulau Seram Provinsi Maluku. Journal Of Social Science Research, 3(3), 1010–1024.

SAIDAH, H., WIRADHARMA, L. W., SUPRIYADI, A., & KAMTIKA, M. J. (2024). Pemanfaatan Data Hujan Berbasis Satelit Chirps Untuk Pemetaan Hujan Rancangan Di Kabupaten Lombok Utara. Jurnal Ganec Swara, 18(3), 1667. https://doi.org/10.35327/gara.v18i3.1032

Seprianto, M., Anggo, M., Harudu, L., & Aldiansyah, S. (2024). Pemetaan Daerah Potensi Rawan Banjir Menggunakan Metode Overlay. Jurnal Penelitian Penelitian Geografi, 9(October), 214–226. https://doi.org/10.36709/jppg.v9i4.260

Susanto, S. (2023). Analisis Kajian Bibliometrika Dalam Pemetaan Arcgis Curah Hujan Di Kabupaten Kediri. Jurnal Engineering, 14(1), 67–76. https://doi.org/10.24905/jureng.v14i1.36

Susanto, S., Pratikto, H., Winarto, S., & Siswanto, E. (2024). Pemetaan Curah Hujan dengan Metode Interpolasi Invers Distance Weighting (IDW) Kabupaten Kediri. Jurnal Engineering, 15(1), 44–55. https://doi.org/10.24905/jureng.v15i1.7