Search Courses: 60 records shown

Filter by
Course Category Help with Select filter
Page: 1 2 3 ()
CategorySort by Category Ascending
Course NameSort by Course Name Ascending
Course SummarySort by Course Summary Ascending Ascending
Course restoration in progress 
Course restoration in progress copy 1 
BIA Travel eBook 
Strengthening Student Resiliency  
NPS Museum Fire Protection Series (self-paced) 
Integrated Charge Card Program Overview (170601) 
Purchase Business Line (170602) 
Travel Business Line (170603) 
Information Management and Technology (IMT) Awareness Training
Target Audience: New Employees

Description:  As a part of the mandatory initial and annual Information Management and Technology (IMT) training, this course fulfills legal requirements for:

  • Privacy Awareness
  • Paper Reduction Act
  • Records Management Awareness
  • Section 508 Awareness
  • Federal Information System Security Awareness (FISSA)
  • Annual acknowledgement of Rules of Behavior for Computer Network Users
Arid and Semi-Arid Lands Seed Technology and Restoration Course

Target Audience:  Anyone interested in implementing Arid and Semi-Arid restoration projects including: Emergency Stabilization & Rehabilitation (ES&R) Plan Developers; Rangeland Management Specialists; Wildlife Biologists; Riparian Specialists; Foresters; Threatened & Endangered Species Biologists; Fisheries Biologists; Realty Specialists; Mineral, Oil & Gas Personnel; Botanists; Natural Resource Specialists; Fuels Specialists; Restoration Practitioners.   

Course Description:  This self-paced on-line course is intended to serve as an introduction to seed technology and Arid and Semi-Arid lands restoration as a first step towards more in-depth in person restoration and revegetation courses.

Course Objectives:  By the end of the course, participants will have an understanding of:  Ecological Restoration principles, standards of practice, and concepts to increase the success of restoration efforts in Arid and Semi-Arid ecosystems and the challenges they pose to successful restoration, and how to apply ecological restoration best practices and concepts in restoration planning.


The course consists of the following modules/lessons. Each are accessed separately and must be taken in sequential order.


Module 1:  Introduction
Module 2:  The National Seed Strategy
Module 3:  Principles, Standards and Concepts

Lesson 3.1:  Principles and Standards for the Practice of Ecological Restoration
Lesson 3.2:  Principles, Standards and Concepts - Native Seed Standards

Module 4:  Arid and Semi-Arid Systems

Lesson 4.1:  Overview of Drylands
Lesson 4.2:  Restoration Challenges
Lesson 4.3:  Current Knowledge

Module 5:  Developing and Implementing a Restoration Plan 

Introduction
Lesson 5.1:  Project Context
Lesson 5.2:  Vision, Goals, and Objectives
Lesson 5.3:  Plant Materials Selection and Procurement
Lesson 5.4:  Site Preparation
Lesson 5.5:  Developing and Implementing Seeding and Planting Strategies
Lesson 5.6:  Monitoring and Management
Lesson 5.7:  Putting It All Together

Sampling-Based Estimation of Area and Map Accuracy

Audience:

Individuals who will benefit from this course include: 
  1. Remote sensing specialist in countries reporting to REDD+ 
  2. Officials working on uncertainty and data analysis for carbon accounting 
  3. Students of remote sensing in forestry applications 
Course Summary and Objectives:

Reducing emissions from deforestation and forest degradation and the role of conservation, sustainable management of forests and enhancement of forest carbon stocks in developing countries (REDD+) is a framework under the United Nations Framework Convention on Climate Change (UNFCCC) with the goal of building international cooperation to achieve climate mitigation from forests.    

A core element of REDD+ MRV is the monitoring and tracking of forest conversions to other lands due to human activities.  Satellite information is the data source with enough periodicity and coverage to provide information on land use, type and intensity of land changes, deforestation and forest degradation. In order to meet REDD+ reporting criteria of unbiasedness and uncertainty quantification, sampling-based approaches for the estimation of area and map accuracy are necessary. This e-learning course will introduce participants to the concept, rationale and how-to of sampling-based estimation. 

Please Note:  This course is available in different languages.  Please select the best one for you:
The online version of this course runs on the latest versions of Chrome and Safari. There is no downloadable version of the course currently. 

Duration:  Approximately 2 hours.  



FY 25 - Assessment, Inventory and Monitoring (AIM) Lotic Core Methods Training

Target Audience:  Anyone involved in lotic monitoring data collection, interpretation, or application, including monitoring field crews (BLM seasonal employees and career staff and current lotic AIM contractors/agreement holders), and BLM or other DOI resource specialists.  Any other interested parties must first obtain permission from the National Lotic AIM team to enroll in this course and an enrollment fee will apply. 

Objective: To ensure standard, consistent, and proficient implementation of:  

  • Spatially balanced random sample design (if applicable). 
  • All core, contingent, and covariate methods, which focus on: 
  • Biodiversity and riparian habitat quality (e.g., macroinvertebrate sampling, floodplain connectivity, bank stability and cover), 
  • Water quality (e.g., pH, connectivity, temperature), 
  • Watershed function and instream habitat quality (e.g., pool dimensions, streambed particle size, slope). 
  • Electronic data capture applications (Survey123, Field Maps). 
  • Data quality assurance and quality control procedures. 

 PREREQUISITES REQUIRED:  

  1. You must be a DOI employee, an active AIM contractor, or actively collecting AIM data through an agreement.  Please refer to the Lotic Data Management and QA & QC Protocol for more details on who should enroll and how often. 

  1. Once enrolled in the class, you must complete the mandatory pre-training material prior to attending the in-person, 6-day field training component. 

Special Requirements:  NTC must receive requests for interpreters, or other reasonable accommodations, no later than 45 days prior to the start of class. The special request form can be accessed at http://www.blm.gov/ntc/st/en/reasonable_accommodation.html. 

Continuous Degradation Detection (CODED) of Forests in Tropical Countries

USGS Logo

Introduction:

This e-learning course will introduce you to the idea of continuous degradation detection, or CODED, and how it can be used to monitor and forecast forest health. By taking this course you will learn about:

1. The challenges of forest degradation monitoring

2. The methodology and purpose of CODED algorithm

3. Spectral un-mixing and the Normalized Difference Fraction Index (NDFI)

4. How degradation and natural disturbances are distinguished from deforestation

Audience:

Who will benefit from this course include:

1. Remote sensing specialist in countries reporting to REDD+

2. Officials working on understanding the role of forest degradation on carbon emission

3. Students of remote sensing in forestry applications

4. Individuals interested in estimation of land cover change using earth observation

Duration:

Approximately 2 hours

Course No.:  USGS-GSP-21-135


Continuous Degradation Detection (CODED) of Forests in Tropical Countries - French Version

USGS Logo

Introduction:

This e-learning course will introduce you to the idea of continuous degradation detection, or CODED, and how it can be used to monitor and forecast forest health. By taking this course you will learn about:

1. The challenges of forest degradation monitoring

2. The methodology and purpose of CODED algorithm

3. Spectral un-mixing and the Normalized Difference Fraction Index (NDFI)

4. How degradation and natural disturbances are distinguished from deforestation

Audience:

Who will benefit from this course include:

1. Remote sensing specialist in countries reporting to REDD+

2. Officials working on understanding the role of forest degradation on carbon emission

3. Students of remote sensing in forestry applications

4. Individuals interested in estimation of land cover change using earth observation

Duration:

Approximately 2 hours


Continuous Degradation Detection (CODED) of Forests in Tropical Countries - Vietnamese version

USGS Logo

Introduction:

This e-learning course will introduce you to the idea of continuous degradation detection, or CODED, and how it can be used to monitor and forecast forest health. By taking this course you will learn about:

1. The challenges of forest degradation monitoring

2. The methodology and purpose of CODED algorithm

3. Spectral un-mixing and the Normalized Difference Fraction Index (NDFI)

4. How degradation and natural disturbances are distinguished from deforestation

Audience:

Who will benefit from this course include:

1. Remote sensing specialist in countries reporting to REDD+

2. Officials working on understanding the role of forest degradation on carbon emission

3. Students of remote sensing in forestry applications

4. Individuals interested in estimation of land cover change using earth observation

Duration:

Approximately 2 hours


Continuous Degradation Detection (CODED) of Forests in Tropical Countries - Spanish Version

USGS Logo

Introducción:

Este curso de aprendizaje electrónico le presentará la idea de la detección continua de la degradación, o codificación y cómo se puede utilizar para monitorear y pronosticar el estado de los bosques.

Al realizar este curso, aprenderá sobre:

1. Los desafíos del seguimiento de la degradación forestal

2. La metodología y el propósito del algoritmo CODED

3. Espectral sin mezclas y índice de fracción de diferencia normalizada (NDFI)

4. Cómo se distinguen la degradación y las perturbaciones naturales de la deforestación

Audiencia:

Quienes se beneficiarán de este curso:

1. Especialista en teledetección en países que reportan a REDD +

2. Funcionarios que trabajan para comprender el papel de la degradación forestal en las emisiones de carbono.

3. Estudiantes de teledetección en aplicaciones forestales

4. Personas interesadas en estimar el cambio de la cobertura terrestre mediante la observación de la tierra.

Recursos y lenguajes de codificación sugeridos antes de comenzar este e-learning - Descripción general de Earth Engine - Earth Engine 101 - JavaScript, imágenes, colecciones, mapa y reducción

Duración:

Aproximadamente 2 horas.


Sampling-based Estimation of Area and Map Accuracy--Vietnamese Version

Audience:

Individuals who will benefit from this course include: 

1.     Remote sensing specialist in countries reporting to REDD+ 

2.     Officials working on uncertainty and data analysis for carbon accounting 

3.     Students of remote sensing in forestry applications 

Course Summary and Objectives:

Reducing emissions from deforestation and forest degradation and the role of conservation, sustainable management of forests and enhancement of forest carbon stocks in developing countries (REDD+) is a framework under the United Nations Framework Convention on Climate Change (UNFCCC) with the goal of building international cooperation to achieve climate mitigation from forests.    

A core element of REDD+ MRV is the monitoring and tracking of forest conversions to other lands due to human activities.  Satellite information is the data source with enough periodicity and coverage to provide information on land use, type and intensity of land changes, deforestation and forest degradation. In order to meet REDD+ reporting criteria of unbiasedness and uncertainty quantification, sampling-based approaches for the estimation of area and map accuracy are necessary. This e-learning course will introduce participants to the concept, rationale and how-to of sampling-based estimation. 

Please Note:  This course is available in different languages.  Please select the best one for you:

System Requirements 

The online version of this course runs on the latest versions of Chrome and Safari. There is no downloadable version of the course currently. 

Duration:  Approximately 2 hours.  


Sampling-based Estimation of Area and Map Accuracy--French Version

Audience:

Individuals who will benefit from this course include: 

1.     Remote sensing specialist in countries reporting to REDD+ 

2.     Officials working on uncertainty and data analysis for carbon accounting 

3.     Students of remote sensing in forestry applications 

Course Summary and Objectives:

Reducing emissions from deforestation and forest degradation and the role of conservation, sustainable management of forests and enhancement of forest carbon stocks in developing countries (REDD+) is a framework under the United Nations Framework Convention on Climate Change (UNFCCC) with the goal of building international cooperation to achieve climate mitigation from forests.    

A core element of REDD+ MRV is the monitoring and tracking of forest conversions to other lands due to human activities.  Satellite information is the data source with enough periodicity and coverage to provide information on land use, type and intensity of land changes, deforestation and forest degradation. In order to meet REDD+ reporting criteria of unbiasedness and uncertainty quantification, sampling-based approaches for the estimation of area and map accuracy are necessary. This e-learning course will introduce participants to the concept, rationale and how-to of sampling-based estimation. 

Please Note:  This course is available in different languages.  Please select the best one for you:

System Requirements 

The online version of this course runs on the latest versions of Chrome and Safari. There is no downloadable version of the course currently. 

Duration:  Approximately 2 hours.  

NPS Climate Smart Recovery for Field Coordinators (Self-Paced; eDOIU)

Course Summary: 

This course guides you through key considerations for rebuilding after natural disasters with an eye on the climate's changing patterns. You'll explore how to protect our natural and cultural heritage, grasp the impacts of climate change, and develop strategies for a resilient future. It's about collaborating to create a smarter, stronger recovery plan.

Course Learning Objectives:

  1. Explain the relationship between climate change and natural disasters and why a climate-smart approach is critical for recovery efforts.
  2. Identify major factors influencing climate change and impacts on cultural and natural resources.
  3. Describe a range of possible climate-smart recovery strategies for cultural and natural resources.
  4. Connect Department of Interior guidance and other federal resources to climate-smart recovery efforts for cultural and natural resources.
  5. Identify elements of a climate-informed recovery plan incorporating effective communication principles and scientifically valid climate change data sources.


Target Audience:
Field Coordinators

2025 Bicycle Subsidy Benefit Program

Target Audience:  All DOI employees who wish to obtain the bicycle subsidy benefit.

Description:  This course will provide an overview of the Federal government's bicycle subsidy benefit.  It will discuss benefit requirements, internal controls and participant roles and responsibilities.  Successful completion of this course is required for DOI employees who wish to obtain the bicycle subsidy benefit in FY 2025.

Page: 1 2 3 ()
Export as