PREDICTIVE MODEL FOR EARLY WARNING SYSTEM FOR HOTSPOT OCCURRENCE UTILIZING SPATIO-TEMPORAL AND PROBIT REGRESSION MODEL BASED ON PEATLAND CHARACTERISTICS AND PRECIPITATION
Spatial mapping in hotspot modeling typically does not account for temporal effects. This limitation becomes significant when time information is a crucial factor, such as in early warning systems. The formulation of a probit regression model with covariates following a space-time process, such a...
Saved in:
Main Author: | Caesar Suherlan, Bagas |
---|---|
Format: | Theses |
Language: | Indonesia |
Online Access: | https://digilib.itb.ac.id/gdl/view/84181 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Institut Teknologi Bandung |
Language: | Indonesia |
Similar Items
-
RISK MAPPING OF GROUNDWATER LEVEL CHANGES IN PEATLAND AREA UTILIZING A SPATIO-TEMPORAL MODEL WITH WEIGHT CONSTRUCTED BASED ON MINIMUM SPANNING TREE
by: Caesar Suherlan, Bagas -
Spatio-temporal diffusion pattern and hotspot detection of dengue in Chachoengsao province, Thailand
by: Phaisarn Jeefoo, et al.
Published: (2018) -
VP-Hotspot: Tool for visualising and predicting hotspot occurrences
by: Sunsika Chaikul, et al.
Published: (2019) -
Geospatial and Spatio-Temporal Models
by: Benito, Daniel Joseph, et al.
Published: (2023) -
SPATIO-TEMPORAL GAUSSIAN PROCESS REGRESSION (STGPR) FOR RELATIVE RISK OF COVID-19 MODELING
by: Widyawati, Erni