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Enregistrement W36315020 · doi:10.1093/eurjpc/zwac246

Spatial techniques for multi-source national planted forest assessment and reporting

2013· article· en· W36315020 sur OpenAlexaboutno aff
Barbara Höck, T. W. Payn

Notice bibliographique

RevueEuropean Journal of Preventive Cardiology · 2013
Typearticle
Langueen
DomaineEnvironmental Science
ThématiqueForest Management and Policy
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésRiparian zoneNational forestEnvironmental resource managementSpatial analysisSustainabilityNational parkGeographyRiparian forestEnvironmental scienceForestryRemote sensingEcology

Résumé

récupéré en direct d'OpenAlex

The national assessment of New Zealand’s planted forests is required for economic and environmental monitoring and for international reporting to organ isations such as FAO and the Montreal Process. Spat ial techniques can aid in determining national planted forest information; two approaches are described in this presentation. Firstly a number of national spatial datasets were investigated for their potential to c ontribute to the reporting on forest sustainability indicators. Seco ndly, spatial data was combined with non-spatial da ta to develop visual representations for enhanced reporting. For the investigation of national spatial datasets for reporting, one of the issues was to determine h ow well national datasets meet sustainability reporting req uirements. One method to determine this is to compare national data with data at a higher resolution; from this th e error margins in the reporting can be estimated. For example, one of the Montreal Process (MP) indicators (4.3.a) requires reporting on the proportion of forest man agement activities that meet best practice for protecting w ater resources. Riparian strips around waterways is one such practise; by overlaying GIS data of different resol utions for a number of case study areas and summing the differences in the riparian areas of each data set, it was determined that the resolution of the natio nal datasets would be inadequate for reporting on riparian pract ices. Using the same case study data, the effect of deducting the riparian areas from the national planted forest area (MP 2.a Area of forest land for wood producti on) indicated that the national datasets could over-est imate the land under productive forestry by up to 6 %. Monitoring based on sampling provides another avenue for generating reporting data; national datasets were used to guide the locations of national monitoring sites . A sampling approach developed by Environment Waikato for monitoring significant soil erosion, based on aeria l photography evaluations of sample points on a 2km grid, was applied to the whole country. The grid points were overlaid in GIS with land cover and erosion suscept ibility data, and the sampling intensity of particularly th e highly erodible forest lands was determined. This verified that the approach would be useful for national soil repo rting (MP 4.2.b Area of forest land with soil degra dation) though implementation of the approach on only areas of high risk could miss impacts elsewhere. Water quality monitoring is another field that reli es on a sampling approach; planted forest water qua lity reporting (MP 4.3.b water bodies in forest areas wi th significant changes) is based on those national water quality monitoring sites specifically for monitoring water flows from exotic forest catchments. The locations of these monitoring sites were assessed based on national GI S datasets. Land cover, river and catchment data we re combined to analyse whether the existing water monitoring sites are representative of exotic forest ca tchments, and to identify potential additional sites. The ana lysis determined that a number of the existing plan ted forest monitoring sites have other production land uses up -stream from their locations, such as grazed pastur e. In addition, different types of river environments are were found to be underrepresented in the national approach for monitoring water from planted forest. A number of new sites were recommended for this monitoring. Finally, a number of visual representations of the sustainability data were explored for the reporting of national forest data. The aim was to provide a quick overvie w of the state of sustainability indicators. The ap proach needed to cope with such issues as mixing quantitat ive and qualitative data, and variable numbers of i ndicators

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,014
score de la tête « metaresearch » (Gemma)0,059
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,015
Score d'incertitude au seuil0,076

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0140,059
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0010,002
Bibliométrie0,0110,018
Études des sciences et des technologies0,0010,001
Communication savante0,0030,005
Science ouverte0,0020,005
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0150,004

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,042
Tête enseignante GPT0,321
Écart entre enseignants0,278 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2013
Routes d'admission1
Résumé présentoui

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