Related items
Showing items related by metadata.
-
PresentationAsia and Pacific Commission on Agricultural Statistics - 29th Session. Land cover mapping through remote sensing and machine learning for Indonesian Census of Agriculture 2023
APCAS_21_7.4
2022Also available in:
No results found. -
Journal articleCoupling machine learning and forest simulations to promote the applicability of long-term forest projections under climate change perspectives
XV World Forestry Congress, 2-6 May 2022
2022Also available in:
No results found.Projecting forest dynamics is the foundation for sound decision support in adaptive forest management. However, due to their complexity, many forest modeling techniques addressing global changes in terrestrial ecosystems are limited to scientific applications. Integrating conventional research and artificial intelligence technologies has the potential to bridge research and practical use. In this study, we propose a Machine Learning (ML) framework that facilitates the implementation of long-term forest projections under climate change scenarios. Our approach combines ML and forest simulations based on process-based models to project forest dynamics. The goal is to leverage the complementary strength of process-based and state-of-the-art ML models to improve predictions at a reduced computational cost. We use environmental data and periodic field measurements at a national scale to train ML models to predict forest growth. By integrating process-based simulations we investigate how the additional variables can improve the prediction accuracy. The proposed hybrid ML framework identifies forest dynamics processes and drivers across spatial and temporal scales, contributing at many levels to the climate change adaptation: from increasing awareness of the climate-induced hazards to enhancing education and assisting in sustainable natural resource management and planning. Keywords: adaptive forest management, climate change, forest growth modelling, machine learning ID: 3623078 -
Manual / guideExperiences With Manually Operated Net-Braiding Machine In Bangladesh - BOBP/WP/50 1986
Also available in:
No results found.This paper documents the BOBP’s experience with intermediate technology for net manufacture in Chittagong, Bangladesh. The intermediate technology tool was a manually operated net machine, originally of Japanese design but modified by a Bombay firm. It was hoped that the net machine could be operated by fisherwomen to supplement family incomes and also increase the supply of gillnets. The Bombay suppliers of the machine assisted in installing the manually operated machine in Bangladesh and in training fisherwomen to operate it. The machine was tried out at the CAR ITAS-supported Kalidaha Fishing Project near Chittagong from May 1982 to March 1 984 and by a private entrepreneur from February 1985 to April 1986. A comparative study was carried out between the manually operated machine, hand-braiding of nets and industrial net-making. On behalf of the Directorate of Fisheries, Bangladesh, Mr. A Bashiruddin, Assistant Inspector of Fisheries, Chittagong supervised the trials. From the BOBP, Mr. G. Pajot, Senior Fishing Technologist, and Mr. A Kashem, Project Officer in Bangladesh, provided monitoring and coordination.
Users also downloaded
Showing related downloaded files
No results found.
Version History
You are currently viewing version 2 of the item.