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FIDWaC - Fast inverse distance weighting and compressionDatasets

SoftwareX
FIDWaC (Fast Inverse Distance Weighting and Compression) is a Python-based toolkit designed for efficient processing and storage of compressed geospatial data.
Andrzej Łysko, Wojciech Maleika, Witold Maćków, Malwina Bondarewicz, Jakub Śledziowski, Paweł Terefenko   +5 more
doaj   +3 more sources

Weather Data Mixing Models for Day-Ahead PV Forecasting in Small-Scale PV Plants

Energies, 2021
As a large number of small-scale PV plants have been deployed in distribution systems, generation forecasting of such plants has recently been gaining interest.
Shree Krishna Acharya, Young-Min Wi, Jaehee Lee   +2 more
doaj   +1 more source

Analysis of Machine Learning Performance in Spatial Interpolation of Rainfall Data

IEEE Access
The spatialization of precipitation data is crucial for studies on climatology, agriculture, and climate change, as well as for urban and environmental planning. Established spatial interpolation methods such as Inverse Distance Weighting are widely used
Alexandre E. L. Nobrega, Itamir M. Barroca Filho   +1 more
doaj   +1 more source

POLA SEBARAN KERUSAKAN BANGUNAN AKIBAT GEMPA BUMI BERBASIS METODE INVERSE DISTANCE WEIGHTING (STUDI KASUS KOTA PALU, PROVINSI SULAWESI TENGAH)

Jurnal Pendidikan Ilmu Sosial, 2019
Kota Palu merupakan salah satu kawasan seismik aktif di Indonesia. Tingginya tingkat aktivitas kegempaan di kawasan ini tidak lepas dari lokasinya yang berada pada zona benturan tiga lempeng tektonik utama dunia, yaitu Indo-Australia, Eurasia dan Pasifik.
Andi Dibya Widadi Nasrullah, Sherly Hanifarianty, Ihwan Fauzi   +2 more
doaj   +1 more source

Merging Satellite Products and Rain-Gauge Observations to Improve Hydrological Simulation: A Review

Earth, 2022
Improving the quality of atmospheric precipitation measurements is crucial in the view of minimizing the uncertainty in weather forecasting, climate change impact assessment, water resource assessment and management, and drought and flood prediction ...
Haile Belay, Assefa M. Melesse, Getachew Tegegne   +2 more
doaj   +1 more source

Inverse distance weighting interpolated soil properties and their related landslide occurrences

MATEC Web of Conferences, 2018
The causes of landslides can be categorized into three factors: climate, topographic, and soil properties. In many cases, thematic maps of landslide hazards do not involve slope stability analyses to predict the region of potential landslide risks. Slope
B. Santoso Purwanto, Yanto, Apriyono Arwan, Suryani Rani   +3 more
doaj   +1 more source

Centrality measure and visualization technique for multiple-parent nodes of earthquakes based on correlation-metric

Applied Network Science, 2023
In this paper, we address the problem of earthquake declustering, and propose a k-nearest neighbors approach based on the selection of multiple-parent nodes with respect to each of the given earthquakes, which can be regarded as a natural extension of ...
Yuki Yamagishi, Kazumi Saito, Kazuro Hirahara, Naonori Ueda   +3 more
doaj   +1 more source

Random Forest Spatial Interpolation

Remote Sensing, 2020
For many decades, kriging and deterministic interpolation techniques, such as inverse distance weighting and nearest neighbour interpolation, have been the most popular spatial interpolation techniques.
Aleksandar Sekulić, Milan Kilibarda, Gerard B.M. Heuvelink, Mladen Nikolić, Branislav Bajat   +4 more
doaj   +1 more source

Geospatial Modeling of Soil Plasticity Index and Water Content Distribution in Coastal Bengkulu: A Basis for Resilient Infrastructure Planning

Journal Innovation of Civil Engineering
Bengkulu Province, located along the western coast of Sumatra, is one of Indonesia’s most seismically vulnerable regions due to its proximity to major tectonic boundaries.
Melly Zuhadjar Putri, Lindung Zalbuin Mase, Khairul Amri, Rena Misliniyati, Hardiansyah Hardiansyah, Refrizon Refrizon   +5 more
doaj   +1 more source

Distance in spatial interpolation of daily rain gauge data [PDF]

Hydrology and Earth System Sciences, 2006
Spatial interpolation of rain gauge data is important in forcing of hydrological simulations or evaluation of weather predictions, for example. This paper investigates the application of statistical distance, like one minus common variance of observation
B. Ahrens, B. Ahrens
doaj