Skip to main content

NASA's Applied Remote Sensing Training Program (ARSET) has opened registration for Three New Open, Online NASA ARSET Remote Sensing Training (June-July 2020)

NASA's Applied Remote Sensing Training Program (ARSET) has opened registration for Three New Open, Online NASA ARSET Remote Sensing Training (June-July 2020)




Groundwater Monitoring using Observations from NASA's Gravity Recovery and Climate Experiment (GRACE) Missions (June 25, 2020)  Bilingual (English and Spanish)    
The webinar will provide an overview of the GRACE missions, groundwater data availability, and their applications in the monitoring and management of water resources. 

Understanding Phenology with Remote Sensing (June 30, July 7, 14, 2020)
This training series will focus on the use of remote sensing to understand vegetation phenology: the study of life-cycle events.
 
Advanced Webinar: Using Earth Observations to Monitor Water Budgets for River Basin Management II (July 21, 28,August 4, 2020)
This 3-part series will include lectures and hands-on exercises for participants to estimate water budgets for a given river basin. 

Please see below for more details for each training.  

NASA's Applied Remote Sensing Training Program (ARSET) program offers satellite remote sensing training that builds the skills to integrate NASA Earth Science data into an agency's and organization's decision-making activities. As all NASA data is open and free, so are ARSET trainings. 

All the best, 

Brock Blevins

Training Coordinator
Science Systems and Applications, Inc. (SSAI)
NASA Applied Remote Sensing Training Program (ARSET)
402-578-7313


Groundwater Monitoring using Observations from NASA's Gravity Recovery and Climate Experiment (GRACE) Missions (June 25, 2020)
Bilingual (English and Spanish)

Groundwater makes up roughly 30% of global freshwater. It also provides drinking water for the world's population, and irrigation for close to 1/3rd of global agricultural land. Because of this level of reliance, monitoring groundwater is crucial for water resources and land management. The Gravity Recovery and Climate Experiment (GRACE) and GRACE-Follow On (GRACE-FO) missions from NASA and the German Research Centre for Geosciences (GFZ) provide large-scale terrestrial water storage estimation from mid-2000 to present. The mission uses twin satellites to accurately map variations in the Earth's gravity field and surface mass distribution.

GRACE observations have been used for detecting groundwater depletion and for drought and flood predictions. This lightning-style training is designed to answer the demand and interest from the applications community in technologies that can be used to support water resources management. The webinar will provide an overview of the GRACE missions, groundwater data availability, and their applications in the monitoring and management of water resources. This lightning webinar will also serve as the foundation for the upcoming advanced webinar: Using Earth Observations to Monitor Water Budgets for River Basin Management II.

Course Date and Times: June 25, 2020
Register Here: English (11:00-12:30 ET)
Register Here: Spanish (14:00-15:30 ET)
Learning Objectives: By the end of this training, attendees will be able to access GRACE data and analyze regional groundwater changes

Course Format: A single, 1.5-hour webinar that includes a lecture and a question & answer session; One session offered in English (11:00-12:30 ET) and one in Spanish (14:00-15:30 ET)

Audience: The content of this training was developed for local, regional, state, federal, and international organizations engaged in the management of water resources, irrigation, and agricultural management.

Relevant UN Sustainable Development Goals: 
Target 6.4: By 2030, substantially increase water-use efficiency across all sectors and ensure sustainable withdrawals and supply of freshwater to address water scarcity and substantially reduce the number of people suffering from water scarcity




Understanding Phenology with Remote Sensing (June 30, July 7, 14, 2020)

This training will focus on the use of remote sensing to understand phenology: the study of life-cycle events. Phenological patterns and processes can vary greatly across a range of spatial and temporal scales, and can provide insights about ecological processes like invasive species encroachment, drought, wildlife habitat, and wildfire potential. This training will highlight NASA-funded tools to observe and study phenology across a range of scales. Attendees will be exposed to the latest in phenological observatory networks and science, and how these observations relate to ecosystem services, the carbon cycle, biodiversity, and conservation.

Course Dates: June 30, 2020. July 7,14, 2020

Time: 11:00 AM - 12:00 PM EDT (UTC-4)

Register Here

Learning Objectives: By the end of this training series, attendees will be able to:
Summarize NASA satellites and sensors that can be used for monitoring global phenology patterns
Outline the benefits and limitations of NASA data for phenology
Describe the multi-scalar approach to vegetation life cycle analyses
Compare and contrast data from multiple phenology networks
Evaluate various projects and case-study examples of phenological data
Course Format: Three, one-hour sessions

Audience: This training is designed for individuals and organizations interested in using satellite imagery for mapping vegetation health and seasonal patterns. 

Relevant UN Sustainable Development Goals:
Goal 13: Take urgent action to combat climate change and its impacts 
Goal 15: Protect, restore and promote sustainable use of terrestrial ecosystems, sustainably manage forests, combat desertification, and halt and reverse land degradation and halt biodiversity loss




Advanced Webinar: Using Earth Observations to Monitor Water Budgets for River Basin Management II (July 21, 28,August 4, 2020)

Rivers are a major source of freshwater. They support aquatic and terrestrial ecosystems, provide transportation, generate hydropower, and when treated, provide drinking and agricultural water. Estimating and monitoring water budgets within a river basin is required for sustainable management of water resources and flooding within watersheds. This advanced-level webinar series will focus on the use of NASA Earth observations and Earth system-modeled data for estimating water budgets in river basins.

Past ARSET trainings on monitoring water budgets for river basins focused on data sources relevant for river basin monitoring and management, and provided case studies for estimating the water budget of a watershed using remote sensing products. This advanced webinar will include lectures and hands-on exercises for participants to estimate water budgets for a given river basin.

Course Dates: July 21, 28, and August 4, 2020.

Times: 10:00-12:00 & 16:00-18:00 EDT (UTC-4); There will be identical sessions at two different times of the day

Register Here

Learning Objectives: By the end of this training, attendees will be able to:
Identify and access remote sensing and Earth system-modeled data for estimating water budgets in a river basin
Explain the uncertainties involved in estimating water budgets for river basins
Replicate the steps for estimating water budgets for a river basin and sub-watersheds using remote sensing products and GIS
Course Format: Three, two-hour parts that include lectures and demonstrations, exercises, and question and answer sessions. Each webinar will be broadcast in English with training materials available in Spanish.

Audience: The content of this training was developed for local, regional, state, federal, and international organizations engaged in the management of water resources, river basins, floods, droughts, land development, river transportation, hydroelectric power, and reservoirs.

Relevant UN Sustainable Development Goals: 

Target 6.4: By 2030, substantially increase water-use efficiency across all sectors and ensure sustainable withdrawals and supply of freshwater to address water scarcity and substantially reduce the number of people suffering from water scarcity
Target 6.5: By 20Retweet Option:30, implement integrated water resources management at all levels, including through transboundary cooperation as appropriate

-- 
You received this message because you are subscribed to the Google Groups "Conservation Remote Sensing Network (CRSNet)" group.
To unsubscribe from this group and stop receiving emails from it, send an email to Conservation_RS+unsubscribe@googlegroups.com.


....


Vineesh V
Assistant Professor of Geography,
Directorate of Education,
Government of Kerala.
https://g.page/vineeshvc
🌏🌎
🌐🌍

Comments

Popular posts from this blog

Disaster Management

1. Disaster Risk Analysis → Disaster Risk Reduction → Disaster Management Cycle Disaster Risk Analysis is the first step in managing disasters. It involves assessing potential hazards, identifying vulnerable populations, and estimating possible impacts. Once risks are identified, Disaster Risk Reduction (DRR) strategies come into play. DRR aims to reduce risk and enhance resilience through planning, infrastructure development, and policy enforcement. The Disaster Management Cycle then ensures a structured approach by dividing actions into pre-disaster, during-disaster, and post-disaster phases . Example Connection: Imagine a coastal city prone to cyclones: Risk Analysis identifies low-lying areas and weak infrastructure. Risk Reduction includes building seawalls, enforcing strict building codes, and training residents for emergency situations. The Disaster Management Cycle ensures ongoing preparedness, immediate response during a cyclone, and long-term recovery afterw...

Logical Data Model in GIS

In GIS, a logical data model defines how data is structured and interrelated—independent of how it is physically stored or implemented. It serves as a blueprint for designing databases, focusing on the organization of entities, their attributes, and relationships, without tying them to a specific database technology. Key Features Abstraction : The logical model operates at an abstract level, emphasizing the conceptual structure of data rather than the technical details of storage or implementation. Entity-Attribute Relationships : It identifies key entities (objects or concepts) and their attributes (properties), as well as the logical relationships between them. Business Rules : Business logic is embedded in the model to enforce rules, constraints, and conditions that ensure data consistency and accuracy. Technology Independence : The logical model is platform-agnostic—it is not tied to any specific database system or storage format. Visual Representat...

Approaches of Surface Water Management: Watershed-Based Approaches

Surface water management refers to the strategies used to regulate and optimize the availability, distribution, and quality of surface water resources such as rivers, lakes, and reservoirs. One of the most effective strategies is the watershed-based approach , which considers the entire watershed or drainage basin as a unit for water resource management, ensuring sustainability and minimizing conflicts between upstream and downstream users. 1. Watershed-Based Approaches Watershed A watershed (or drainage basin) is a geographical area where all precipitation and surface runoff flow into a common outlet such as a river, lake, or ocean. Example : The Ganga River Basin is a watershed that drains into the Bay of Bengal. Hydrological Cycle and Watershed Management Watershed-based approaches work by managing the hydrological cycle , which involves precipitation, infiltration, runoff, evapotranspiration, and groundwater recharge. Precipitation : Rainfall or snowfall within a...

Raster Data Structure

Raster Data Raster data is like a digital photo made up of small squares called cells or pixels . Each cell shows something about that spot — like how high it is (elevation), how hot it is (temperature), or what kind of land it is (forest, water, etc.). Think of it like a graph paper where each box is colored to show what's there. Key Points What's in the cell? Each cell stores information — for example, "water" or "forest." Where is the cell? The cell's location comes from its place in the grid (like row 3, column 5). We don't need to store its exact coordinates. How Do We Decide a Cell's Value? Sometimes, one cell covers more than one thing (like part forest and part water). To choose one value , we can: Center Point: Use whatever feature is in the middle. Most Area: Use the feature that takes up the most space in the cell. Most Important: Use the most important feature (like a road or well), even if it...

Disaster Management international framework

The international landscape for disaster management relies on frameworks that emphasize reducing risk, improving preparedness, and fostering resilience to protect lives, economies, and ecosystems from the impacts of natural and human-made hazards. Here's a more detailed examination of key international frameworks, with a focus on terminologies, facts, and concepts, as well as the role of the United Nations Office for Disaster Risk Reduction (UNDRR): 1. Sendai Framework for Disaster Risk Reduction 2015-2030 Adopted at the Third UN World Conference on Disaster Risk Reduction in Sendai, Japan, and endorsed by the UN General Assembly in 2015, the Sendai Framework represents a paradigm shift from disaster response to proactive disaster risk management. It applies across natural, technological, and biological hazards. Core Priorities: Understanding Disaster Risk: This includes awareness of disaster risk factors and strengthening risk assessments based on geographic, social, and econo...