Logo Lanfrica
  • Home
  • Atlas
  • Insights
  • Docs
  • Sign in

© 2026 Lanfrica. All rights reserved. All copyrights of the resources shown on the Lanfrica website belong to the original copyright holders, unless explicitly stated otherwise.

Near-real time forecasting and change detection for an open ecosystem

Domain:

environment and energygeospatialclimate

Record type:

software
Creator:
Slingsby, JasperWilson, AdamMoncrieff, Glenn
Publisher:
fig
Host:avatar
Presentation given for the GEO BON Open Science Meeting, July 2020 conf2020.geobon.org - complete with narration!
We present a hierarchical Bayesian modelling framework that allows us to forecast remotely sensed vegetation indices in a fire-dependent and seasonally fluctuating ecosystem, the Fynbos of South Africa. This framework allows several applications including: 1) detecting near real-time changes in the state of the ecosystem by comparing observed vegetation signal with the model forecasts; 2) determining the influence of plant traits on vegetation productivity and seasonality; 3) forecasting changes in vegetation productivity and seasonality under altered climate or community composition; and 4) estimating ecosystem properties like leaf area index (LAI) or above ground biomass. As such, it provides the means to draw linkages across and/or monitor several EBV classes.

Visit

doi.orgfigshare.com

Tags

Botany60299 Ecology not elsewhere classifiedFOS: Biological sciencesFOS: Biological sciences69902 Global Change Biology60208 Terrestrial Ecology

Licenses

Creative Commons Attribution 4.0 Internationalhttps://creativecommons.org/licenses/by/4.0/legalcode

Similar

Pyeo: A Python package for near-real-time forest cover change detection from Earth observation using machine learningAn Open Source Approach for Near-Real Time Mapping of Oil Spills along the Mediterranean Coast of Egyptpyaj0/near-real-time-drought-exposureNear--Real-Time Conflict-Related Fire Detection in Sudan Using Unsupervised Deep LearningA Google Earth Engine and Machine Learning Model for Near-Real Time Spatiotemporal Change Detection: Enhancing Vegetation Cover Assessment in Nech Sar National Park, EthiopiaNear-Real Time SIM-box Fraud Detection Using Machine Learning in the case of ethio telecom

Pyeo: A Python package for near-real-time forest cover change detection from Earth observation using machine learning

Monitoring forest cover change from Earth observation data streams in near-real-time presents a c

An Open Source Approach for Near-Real Time Mapping of Oil Spills along the Mediterranean Coast of Egypt

Oil pollution is one of the major critical risks to the Egypt’s marine environment due to the heavy

pyaj0/near-real-time-drought-exposure

Near Real-Time Drought Exposure: Case Study of the Central Region, Ghana # near-real-time-drought-e

Near--Real-Time Conflict-Related Fire Detection in Sudan Using Unsupervised Deep Learning

Ongoing armed conflict in Sudan highlights the need for rapid monitoring of conflict-related fire-af

A Google Earth Engine and Machine Learning Model for Near-Real Time Spatiotemporal Change Detection: Enhancing Vegetation Cover Assessment in Nech Sar National Park, Ethiopia

Nech Sar National Park (NSNP), a vital biodiversity sanctuary in Ethiopia, is experiencing increasin

Near-Real Time SIM-box Fraud Detection Using Machine Learning in the case of ethio telecom

The advancement of telecommunication era is rapidly growing, however, telecom fraudsters encouraged