Environmental Restoration Planners

Life, Physical, and Social Science Occupations
O*NET-SOC-Code
19-2041.02

Collaborate with field and biology staff to oversee the implementation of restoration projects and to develop new products. Process and synthesize complex scientific data into practical strategies for restoration, monitoring or management.

Berufsbezeichnungen und Aufgabenbeschreibungen werden wie veröffentlicht auf Englisch angezeigt. Beschriftungen, einschließlich der Aufgabenarten, sind übersetzt.

KI-Exposition

  • Datenquelle: BLSVeröffentlicht: 2026-08

    Sehr hoch· relativ

    NiedrigVier relative BänderSehr hoch

    Wert auf Berufsgruppenebene

    Skala, Bezugsmenge und Quelle

    Vier relative Bänder (Niedrig / Mittel / Hoch / Sehr hoch)

    831 detaillierte Berufe in der BLS-Beschäftigungsprojektionstabelle. Der Wert wird je Code der National Employment Matrix (NEM) vergeben, daher erhalten Berufe mit demselben NEM-Code dasselbe Band

    Quelldatensatz (XLSX-Download)

  • Datenquelle: AnthropicVeröffentlicht: 2026-03

    0.055

    0.000Spannweite der hier geführten Werte0.745

    Wert auf Berufsgruppenebene

    Skala, Bezugsmenge und Quelle

    Index der beobachteten Exposition, 0–1 wie veröffentlicht

    Auf O*NET-Aufgaben abgebildet

    Veröffentlicht je SOC-2018-Beruf; jeder O*NET-Beruf mit demselben SOC-2018-Code erhält diesen Wert

    Quelldatensatz (CSV-Download)

  • Datenquelle: ILOVeröffentlicht: 2025

    0.38

    0.09Spannweite der hier geführten Werte0.70

    Wert auf Berufsgruppenebene

    Skala, Bezugsmenge und Quelle

    Index der Exposition gegenüber generativer KI, 0–1 wie veröffentlicht

    Veröffentlicht je ISCO-08-Berufsgattung. Mit diesem Beruf ganz oder teilweise verknüpft durch Anwendung der Umsteigeschlüssel des U.S. Bureau of Labor Statistics (ISCO-08 zu SOC 2010, SOC 2010 zu SOC 2018) in veröffentlichter Form

    Quelldatensatz (PDF-Download)

Welche Art von Wert diese Quelle veröffentlicht

Die Kategorie von BLS ist ein relativer Rang und kein absolutes Niveau, und sie ist keine eigene Messung: Sie fasst die Perzentilränge des Berufs aus mehreren veröffentlichten Studien in vier Bänder zusammen. Sie ist weder eine Beschäftigungs- oder Lohnprognose noch eine Einführungswahrscheinlichkeit und unterscheidet nicht zwischen Automatisierung und Augmentierung.

KI-Exposition (OpenAI-Rubrik)

23 bewertete Aufgaben · 22 Aufgaben mit β ≥ 0,5 (95.7%)

β = direkte Exposition (E1) + 0,5 × Exposition bei verfügbaren Werkzeugen (E2), gemäß der Definition des Quell-Repositorys.

  • Quelleinheit: Aufgaben aus O*NET 27.2 → Berufscode aus O*NET 31.0
  • Alle bewerteten Aufgaben stehen in der Aufgabenliste von O*NET 31.0.
Quelle
OpenAI "GPTs are GPTs" exposure rubric
Ausgabe
gh-main-0471612
Lizenz
MIT License, Copyright (c) 2024 OpenAI

Aufgaben

Aufgabenbeschreibungen aus der O*NET® 31.0 Database, Kernaufgaben zuerst.

AufgabeArtβ (OpenAI)
Notify regulatory or permitting agencies of deviations from implemented remediation plans.Kern1
Develop environmental restoration project schedules and budgets.Kern0,5
Develop and communicate recommendations for landowners to maintain or restore environmental conditions.Kern0,5
Create diagrams to communicate environmental remediation planning, using geographic information systems (GIS), computer-aided design (CAD), or other mapping or diagramming software.Kern0,5
Apply for permits required for the implementation of environmental remediation projects.Kern0,5
Review existing environmental remediation designs.Kern0,5
Supervise and provide technical guidance, training, or assistance to employees working in the field to restore habitats.Kern0
Provide technical direction on environmental planning to energy engineers, biologists, geologists, or other professionals working to develop restoration plans or strategies.Kern0,5
Plan or supervise environmental studies to achieve compliance with environmental regulations in construction, modification, operation, acquisition, or divestiture of facilities such as power plants.Kern0,5
Inspect active remediation sites to ensure compliance with environmental or safety policies, standards, or regulations.Kern0,5
Plan environmental restoration projects, using biological databases, environmental strategies, and planning software.Kern0,5
Identify short- and long-term impacts of environmental remediation activities.Kern0,5
Identify environmental mitigation alternatives, ensuring compliance with applicable standards, laws, or regulations.Kern0,5
Create environmental models or simulations, using geographic information system (GIS) data and knowledge of particular ecosystems or ecological regions.Kern0,5
Conduct feasibility and cost-benefit studies for environmental remediation projects.Kern0,5
Conduct environmental impact studies to examine the ecological effects of pollutants, disease, human activities, nature, and climate change.Kern0,5
Communicate findings of environmental studies or proposals for environmental remediation to other restoration professionals.Kern0,5
Collect and analyze data to determine environmental conditions and restoration needs.Kern0,5
Develop natural resource management plans, using knowledge of environmental planning or state and federal environmental regulatory requirements.Kern0,5
Develop environmental management or restoration plans for sites with power transmission lines, natural gas pipelines, fuel refineries, geothermal plants, wind farms, or solar farms.Kern0,5
Create habitat management or restoration plans, such as native tree restoration and weed control.Kern0,5
Conduct site assessments to certify a habitat or to ascertain environmental damage or restoration needs.Kern0,5
Write grants to obtain funding for restoration projects.Kern1

Berufsinformationen

Quellen und Namensnennung

This page includes information from the O*NET® 31.0 Database (https://www.onetcenter.org/database.html) by the U.S. Department of Labor, Employment and Training Administration (USDOL/ETA). Used under the CC BY 4.0 license (https://creativecommons.org/licenses/by/4.0/). O*NET® is a trademark of USDOL/ETA. AI Changing Work has modified all or some of this information: the O*NET-SOC code, title and task statements are reproduced in English without change; task-type labels are shown in the page's language and tasks are listed core first; any Korean occupation title shown on the Korean-language page is AI Changing Work's translation; any KSCO-8 unit groups linked to this occupation were paired with it by AI Changing Work's judgment, and the relation labels and statuses are AI Changing Work's additions. USDOL/ETA has not approved, endorsed, or tested these modifications.

Any AI exposure figures on this page are published by third parties, not by AI Changing Work, and none is part of the O*NET information. OpenAI publishes task-level scores (MIT License) for O*NET 27.2 task statements; each is shown next to the O*NET 31.0 task statement with the same task ID, whose wording can differ from the 27.2 statement that was scored. OpenAI also publishes occupation-level scores for O*NET-SOC codes in the same release, and any such score is shown on the O*NET occupation with the same code. Anthropic publishes an observed exposure index in the Anthropic Economic Index (CC-BY), and the U.S. Bureau of Labor Statistics publishes relative AI exposure categories (public domain); both are published per SOC code, and each value is shown on every O*NET occupation with that code. The International Labour Organization publishes a generative AI exposure index in ILO Working Paper 140 (CC BY 4.0) for ISCO-08 unit groups; AI Changing Work links those groups to O*NET occupations by applying the U.S. Bureau of Labor Statistics ISCO-08 to 2010 SOC and 2010 SOC to 2018 SOC crosswalks as published, without case-by-case selection, and these crosswalks match many groups only in part. Where several unit groups are linked, each group's published value is listed, and any summary shows only the lowest and highest of those values with the number of groups; no exposure figure is averaged or recalculated. Any employment figures are published by the U.S. Bureau of Labor Statistics for the SOC group containing this occupation. Each source is credited where its figures are shown.

O*NET OnLine: 19-2041.02 Environmental Restoration Planners

KSCO 코드·명칭: 한국표준직업분류(제8차 개정) — 통계청 고시 제2024-328호 (2024-07-01 고시, 2025-01-01 시행). 저작권법 제7조 제2호의 고시 항목이다. 명칭 표기(가운뎃점·띄어쓰기)는 해설서 2차 정오 반영판의 표기를 따랐으며, 고시 항목표와는 18개 명칭에서 가운뎃점 글리프나 띄어쓰기만 다르다. 통계청은 2025년 10월 국가데이터처로 개편되었다. 이 페이지의 KSCO 연결은 통계청·국가데이터처의 공식 연계표가 아니다.

Vollständige Namensnennung und Lizenzen