A5005891605- Landslides and related hazards
- Fire effects on ecosystems
- Tropical and Extratropical Cyclones Research
- Climate variability and models
- Soil Moisture and Remote Sensing
- Precipitation Measurement and Analysis
- Flood Risk Assessment and Management
- Computational Physics and Python Applications
- Geological and Geophysical Studies
- Coastal Management and Development
- Data Mining and Machine Learning Applications
- Agricultural and Environmental Management
- Ocean Waves and Remote Sensing
- Tree Root and Stability Studies
- Geotechnical and construction materials studies
- Soil Geostatistics and Mapping
- Fire Detection and Safety Systems
- Remote Sensing and LiDAR Applications
- Climate Change and Health Impacts
- Geophysics and Gravity Measurements
- Bayesian Modeling and Causal Inference
- Air Quality Monitoring and Forecasting
- Water and Land Management
- Climate change and permafrost
- Meteorological Phenomena and Simulations
Meteorological, Climatological, And Geophysical Agency
2019-2024
Universitat Politècnica de Catalunya
2023-2024
Understanding the key variables that characterise fire propagation is important for a better estimation of events and their impacts. This study uses machine learning combined with satellite remote sensing atmospheric modelled data to enhance estimations burned areas. It focuses on intense early summer weather patterns in South Asia during April May 2022 explores relationship between environmental factors spread. The employs various algorithms, including random forest, extra trees, extreme...
Rainfall is an identified trigger of landslides, and researchers have long attempted to ensure the total precipitation that can slope failures under different local climate condition, a problem scientific interest. In this study, we propose new empirical rainfall thresholds combining with antecedent soil moisture indexes for analysing initiation landslides in Banjarmangu districts, located Central Java. Daily landslide information were obtained from Banjarnegara Geophysical Station Regional...
A Random Forest (RF) regression-tree method to derive high-resolution (60 m) surface soil moisture maps is proposed in this study. The developed methodology integrates multi-source synergies by incorporating information from the visible, near-infrared until short-wave infrared spectrum (Sentinel-2), reanalysis data (ERA5-Land) and terrain (SRTM), using exclusively open access data. analysis focuses on central part of Iberian Peninsula covers a four-year period (2018-2021). resulting exhibit...
In the work a random forest model has been implemented as an interpretable machine learning tool in effort to estimate burned areas caused by fire outbreaks India, Pakistan, and Myanmar April May 2022. The proposed combines environmental atmospheric (including upper tropospheric) factors suggested drive patterns of areas, determines weight each factor on propagation fires. Results demonstrate that mimics actual area considering combination vegetation, atmosphere, human-related variables...
Most studies of the impact sea surface temperature (SST) have explored rainfall in a part Indonesia. This paper takes different approach and explores air-sea coupling interaction between Madden-Julian Oscillation (MJO) SST on variability East Nusa Tenggara (NTT). study uses daily observation from some NTT seasonal zone (ZOM) 1991to 2016. Meanwhile, gridded data around was obtained Japan Meteorological Agency (JMA). For amplitude MJO, downloaded Bureau Meteorology (BOM)’s website. used...
Understanding soil moisture (SM) at high spatiotemporal resolution provides crucial insights across various societal disciplines due to its direct impact on environmental and natural disaster monitoring, weather forecasting, agricultural productivity, water resource management.In recent decades, a variety of algorithms have been developed improve the spatial SM maps from passive sensors (∼40 km); however, resulting maps, often with resolutions around 1 km or even hundreds meters, still lack...
Keberadaan hutan sebagai paru-paru dunia berperan penting dalam menghasilkan gas oksigen. Pulau Kalimantan merupakan salah satu karena luas hutannya yang mencapai 40,8 juta hektar. Namun, pada saat ini kualitas dan kuantitas di mengalami penurunan drastis akibat adanya deforestasi kebakaran hutan. Kebakaran menjadi sorotan persebaran asapnya menyebabkan polusi udara berbagai wilayah Indonesia. Dampak dari asap dipengaruhi oleh kecepatan angin vertikal daerah tersebut. Penelitian bertujuan...
Abstract Most studies of the tropical cyclone (TC) forecasting are focused on track and wind radius forecasting, even though a formation alerts also developed. This paper takes different approach explores forecast TC occurrences. study presents development fuzzy logic (FL) models for predicting occurrence from five primary genesis parameters. These parameters low-level relative vorticity (θ), horizontal upper troposphere (u), sea surface temperature (SST), equivalent potential (θe), specific...
Abstract This research discusses the effect of climate change on extreme rainfall in West Java using RCP 4.5 and 8.5 scenarios by comparing daily data with model ACCESS-1, CSIROMK3.6 model, MIROC-5 from NASA Earth Exchange Global Daily Downscaled Projection (NEX-GDDP) ensemble three models each season Extreme Dependency Score (EDS) method. study projects an index 30 years (2011-2040). The indices issued Expert Detection Team Climate Change Index (ETCCDI) consisted Rx1day, R50mm, R95p used...
Jet streams' persistent tropospheric ridging plays a crucial role in temperature extremes, heatwaves, and consequent wildfires subtropical polar regions. To address this, the research presented this study incorporates jet stream variables into atmospheric data to enhance forecast of burned areas using machine learning (ML). Focusing on anomalous early intense summer weather South Asia during April May 2022, employed ML algorithms such as Random Forest, Support Vector Regression (SVR),...
El Niño yang terjadi pada periode 1991-2016 menyebabkan dampak kekeringan di berbagai wilayah, termasuk wilayah Nusa Tenggara Barat (NTB). Pemahaman mengenai pengaruh terhadap awal musim NTB diharapkan dapat mengurangi negatif dari berbeda setiap NTB. Dalam penelitian ini digunakan Oceanic Nino Index (ONI) untuk mendeteksi kejadian dan data curah hujan dasarian tahun 10 Zona Awal Musim (ZOM) menganalisis pergeseran musim. Analisis dilakukan dengan cara membandingkan pola kondisi rata-rata...