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Record W4404800978 · doi:10.1016/j.bamboo.2024.100118

Inventory of timber and non-timber forest products through remote sensing and mapping: The example of bamboo resources in chad

2024· article· en· W4404800978 on OpenAlexaff
Tchoutezou Guy Herman Zanguim, Tanougong Nkondjoua Armand Delanot, René Kaam, Henry Ouya Bondoro, Ngoh-Allah Odjimbaye, Nyong Princely Awazi, Martin Tchamba

Bibliographic record

VenueAdvances in Bamboo Science · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAfrican Botany and Ecology Studies
Canadian institutionsOttawa Public Health
Fundersnot available
KeywordsBambooForest inventoryForestryAgroforestryGeographyRemote sensingEnvironmental resource managementEnvironmental scienceForest managementEcology

Abstract

fetched live from OpenAlex

This study was initiated to explore the potential of the bamboo resource in Chad, a vital component for socio-economic development, environmental protection and biodiversity conservation. Inspired by proven methodologies in Ethiopia, Kenya, Uganda and Madagascar, our research mapped and inventoried Chad's bamboo resources using advanced remote sensing techniques. A series of multi-temporal Landsat images with a spatial resolution of 30 m were used. Almost 90 Landsat 8 OLI image sheets were assembled into a mosaic using Envi 5.3 software. Careful processing, including pre- and post-classification, was applied to refine the mapping. Validation of the presence of bamboo was carried out using GPS coordinates and very high spatial resolution images, such as those provided by Google Earth. The overall accuracy of the study was evaluated at 87.85 %, with a Kappa coefficient of 0.83, attesting to the reliability of the results obtained. Bamboos are present in three distinct climatic zones of the country: the Guinean, Sudanian and Sahelian zones. They cover a total area of around 35,600 ha, with a distribution of 21 % in the Sahelian zone and 79 % in the Sudanian zone, implying no traces of bamboo were found in the Guinean zone. Oxythenanthera abyssinica (A.Rich.) Munro was the only bamboo species identified on the territory, underlining its predominant ecological role and its adaptation to Chad's diverse environments. Although bamboo is not abundant in Chad, its importance cannot be overemphasized. Bamboo makes a significant contribution to the fight against climate change, thanks to its capacity to sequester carbon and its role in soil stabilization. These characteristics make bamboo a strategic resource in efforts to combat desertification. The results of our study provide a sound basis for the sustainable management of bamboo resources in Chad. Our findings call for the development of policies aimed at reducing rural poverty and integrating bamboo management into systems for combating desertification. We recommend that bamboo research and development programs be pursued in order to maximize its economic potential while preserving its ecological integrity. We therefore highlight the crucial role of bamboo in Chadian ecosystems and its untapped potential as a resource for sustainable development. Implementing the recommendations arising from our research will significantly transform Chad's socio-economic and environmental landscape, making bamboo a pillar of green growth and climate resilience. • The study explores bamboo's potential in Chad for socio-economic development, environmental protection, and biodiversity. • Bamboos are found in three climatic zones of Chad: Guinean, Sudanian, and Sahelo-Sudanian. • Oxytenanthera abyssinica is the only bamboo species in Chad, highlighting its ecological role and adaptability. • The study supports sustainable bamboo management, urging for policies to reduce rural poverty and fight desertification.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.236
Threshold uncertainty score0.714

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.034
GPT teacher head0.250
Teacher spread0.216 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2024
Admission routes1
Has abstractyes

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