A hugely productive summer for USF’s Geospatial Analysis Lab (GsAL) began with one of our graduate research assistants, Radhika Bhargava, attending the 2017 Information and Communications Technologies for Development conference in India, in May. The focus of the conference was improving the use of data and technology to help the drive toward development in less developed countries and meet the UN’s sustainable development goals and was well attended by representatives from around the world.
Radhika’s key assignment for the week was to collaborate with Google to deliver training in the use of Google Earth Engine (GEE) at Google Hyderabad to around 60 participants from technical and non-technical backgrounds. This kind of training and collaboration is greatly valued by participants as it allows for groups working within and across nations to connect with each other, share ideas and improve common understanding of the contexts surrounding local, national and global development issues. GEE combines colossal geospatial data-sets and petabytes of satellite imagery with formidable planetary-scale analytical capabilities to provide researchers with the ability to identify, quantify and study the effects of changes to the Earth’s surface – and by harnessing the power of their Cloud technology, this is all possible on a standard home computer. The sense of purpose, learning and new ideas for applications at the conference were all outstanding, and extremely encouraging for the future of progress towards meeting the UN sustainability goals.
Summer Internship on Coastal Management
In July our graduate research assistant at GsAL, Radhika Bhargava, worked with the Suganthi Devadason Marine Research Institute (SDMRI) in Tuticorin, in the state of Tamil Nadu in India. After convincing the director of SDMRI, Dr J. K. Patterson Edward, to offer her a short research placement there, she spent two weeks learning about the issue of bycatch in the Gulf of Mannar, by Tuticorin’s coastal village fishing industry. Bycatch is the unavoidable process of catching fish or other marine life that are not of target species, age, sex or weight. In the case of Tuticorin, a key concern is the bycatch of soft and hard coral species, and sponges, which could easily be seen in the early morning in the fishermen’s nets. The fishermen assert that they do not target coral-rich areas as coral can destroy fishing nets, but there is approximately 10 kilograms of benthic substrate – essentially, the material that makes up the floor of a given body of water, in this case coral – being pulled up per boat, per day. The types of nets are consistent among the villages and each village operates from 100-300 boats, so it is clear that there is a need for the excellent work that SDMRI and other environmental research organizations are doing to learn about the effects of destructive fishing practices and work with communities towards more sustainable economic activity.
How do you link gender inequality and disaster risk management? Climate change and social vulnerability? Where do you start? Those are the questions that have been needling at me for the past few months. As part of the gender cluster this summer at SEI, I have been tasked with investigating how we can use GIS tools to better understand the relationships between climate change and gender inequalities in the Mekong region. The journey to understanding the complexity of this problem has taken me to Cambodia and Vietnam, and down many rabbit holes of the internet in search of peer-reviewed literature and archived datasets.
Initially, the breadth and interconnectedness of the social causes of vulnerability were overwhelming. Every avenue that I explored lead to the realization that it is misleading to assess the impact of any one aspect of social vulnerability in isolation. For example, I began my research by investigating the impacts of extreme flooding events on school dropout rates of women and girls in Cambodia. I discovered that flooding had a high impact on dropout rates of women and girls in affected areas, but through further study it became clear that this was not the whole picture. In reality, while flooding certainly exacerbates dropout rates, it is only a possible final step in the long and difficult road that women and girls in these regions face in pursuing an education. As I dove more deeply into my research, I found the real causes were a myriad of social constructs surrounding traditional gendered attitudes towards women in the region. In rural areas, for example, very little importance is placed on female education because women are expected to take on the burden of domestic work around the home. This is especially prevalent among low-income families who will prioritize the education of sons over daughters, who can be kept home to assist with domestic chores. Other factors that contribute to the low levels of education of women in Cambodia include low parental literacy levels and lack of physical access to schools. As such, we can begin to see that when flooding events occur, the attitudes and social obstacles that women and girls face make it that much harder for them to maintain their education.
Furthermore, this web of attitudes and ideas continues to haunt females later in life because the impact of the lack of education can greatly inhibit women’s understanding of their rights to equality and protection under the law. This can make them vulnerable to repeated cycles of domestic violence and abuse. It can also make it very hard for rural women to break out of the poverty cycle by finding off-farm employment in non-exploitative trades. It can also impact an individual’s own perception of education and these attitudes may be passed on to the next generation, continuing the cycle of devaluing education for women and keeping them in positions that do not allow them to be any more influential or economically productive than the preceding generation.
This is not only the case with education but these same cycles of inequality can be identified through various social institutions such as health, income, access to resources, representation in political roles, etc. All of these indicators are often viewed as singular topics but they are undeniably interrelated and must be examined within a framework of vulnerability. The concept of social vulnerability as a collective measure of several indices is not new. The Gender Inequality Index (GII) created by the UNDP in 2010 is an index for measurement of the gender disparity in the areas of reproductive health, empowerment and labor market participation. Although the GII can give us a better understanding of gender inequality across and within nations, it does not explain the variation in inequality that exists at a sub-national or sub-regional level. As such it is of limited use in understanding where women are most vulnerable and cannot be used to target specific resources to alleviate the root causes of inequality. It is because of this gap in regional specificity that the end of my time at SEI has culminated in the proposal to create a provincial-level gender inequality index for Cambodia and Vietnam. The development of such a tool will be created in collaboration with two regional technical groups on gender and GIS – SERVIR-Mekong and SEI – alongside regional women’s organizations in the respective countries, such as the National Women’s Machinaries and the Ministry of Women’s Affairs (MoWA) in Cambodia, and the Vietnam Women’s Union (VWU) in Vietnam. Development of a regionally specific gender-inequality index can be used as a complementary tool in the analysis of gender gaps and vulnerabilities in a region. For instance, the index could be used in tandem with climate change forecasting data, such as drought or flood, in order to assess the gendered dimensions of climate change risk. Additionally, the publication of the index has the potential to draw attention to gender inequalities that exist across social institutions and can be used as a catalyst for action. Lastly, the hope is that this index will put pressure on agencies to collect more gender disaggregated data and with greater frequency.
How do you sustainably manage urban growth in a way that allows you to make the most efficient use of your land and water resources? How do you account for rapid declines in forest cover and the resulting physical, ecological and human problems this can cause? Further – how do you account for declines in forest cover in a neighbouring country, for which you may not have access to accurate, up-to-date mapping data? And how do you reduce the risk of losing hard earned development gains in areas that are prone to natural disasters such as landslides or flooding? These are some of the problems that current land-use planners and decision makers face in a world of rapid change and shifting climates; problems in the Lower Mekong Region that are being tackled in a wide collaboration to produce a dynamic new mapping tool that provides greater detail and accuracy of data.
From the 1st to the 3rd of August 2017, SERVIR Mekong in collaboration the University of San Francisco’s Geospatial Analysis Lab (GsAL), the US Forest Service and SilvaCarbon held the fourth in a series of conferences to launch their Regional Land Cover Monitoring System (RLCMS). This is an innovative tool designed to produce high-quality land cover maps that will allow decision makers in the Lower Mekong region – from national governments to local community groups, non-profits and the private sector – to make informed policy and planning decisions about resource allocation, disaster preparedness, climate change resilience, ecological conservation, carbon accounting and a whole host of other critical issues affecting these societies. The conference was led by David Saah, the director of GsAL, who has been working closely with the GsAL lab manager, Megan Danielson, on developing the RLCMS since its conception.
Over the last two years the SERVIR-Mekong and GsAL teams have been working closely with stakeholders across the Lower Mekong region (Thailand, Vietnam, Myanmar, Laos and Cambodia) and Indonesia to identify local, regional and national needs, to develop a consistent regional classification scheme, to collect and employ on-the-ground reference data, develop algorithms for identification of land-cover classes and implement plans for how the RLCMS will be used. One of the most encouraging and affirming aspects of the process is that representatives from groups in all of these countries (e.g. government reps, non-profits and local interests) have come together to develop and learn to use a tool that crosses political boundaries and provides better opportunities for the citizens, environments and industries of the Lower Mekong region to interact and prosper in more sustainable ways.
Since the late 90s there has been a drive in the environmental sciences community to produce global land cover mapping data and a number of detailed and invaluable maps have been created, such as the European Space Agency’s GlobCover Land Cover V2, the UN Food and Agriculture Organization’s Global Land Cover-SHARE and the Natinoal Geomatics Center of China’s GlobeLand30. Traditionally, regional actors have used such efforts to extract what information they can for their own varied uses, but this method has its limitations. Existing maps are infrequently updated, the classification systems they use can be inconsistent, the actual classes they identify can be inadequate (i.e. they do not provide accurate representation of the range of biophysical layers present in a given area), they may not meet accuracy assessment requirements and some need significant data storage and processing power to run. The RLCMS, on the other hand, harnesses the processing power of Google Earth Engine (GEE) to enable the this kind of analysis to be performed on a standard computer and combines its staggering quantity of satellite imagery and data with local field research by stakeholders to provide functionality, speed and accuracy. Biophysical layers are mapped by training statistical models and machine learning algorithms on reference data obtained from said field research or existing legacy data-sets. Thanks to the input of regional stakeholders since the beginning of the process the tool uses a consistent classification scheme to describe a broad range of layers appropriate to the diverse ecology of the Lower Mekong region which can be customized and expanded as required by the user, creating high quality land cover maps that are regularly updated.
Many of the national priorities for the countries comprising the Lower Mekong region with regards to the RLCMS are similar – to simply improve the quality of their own nation’s land cover maps, to help meet targets for carbon capture and emissions and to build capacity to meet their development needs. However, many other uses for the RLCMS have been identified which reflect the different needs of these countries and organisations working within them. Laos requires improved forest mapping data and accuracy; the Mekong River Commission, an inter-governmental organisation representing the water needs of Laos, Thailand, Vietnam and Cambodia, will use it as an additional input into their flood monitoring systems; Indonesia has suffered from peat fires for decades and famously had an extreme crisis event in the 2015 fire season when 2.6 million hectares of land were burned, tripling their annual carbon emissions – so there is a significant need to be able to accurately define the areas affected, complete analysis of land cover changes over time and incorporate the new data they retrieve into existing methodology to prepare for and reduce the negative effects of those fires.
A tremendous amount of work has been poured into the collaboration to develop the RLCMS over the last three years and there are significant steps still to take – chiefly, using reference data to input land cover classes in the stakeholders’ respective areas of interest. However, many key obstacles have been already overcome and it is clear that this tool will afford users greatly improved prospects for informed decision making and positive change. In producing and developing the RLCMS, SERVIR-Mekong, GsAL, the US Forest Service, SilvaCarbon and the regional stakeholders involved are setting the groundwork for a comprehensive and reliable data mapping tool that has dizzying application potential.
On Monday April 24th, 2017 the Graduate Student Senate (GSS) at USF hosted Graduate Student Academic Showcase to highlight graduate students’ research and other work. This is a unique graduate student event that aims to highlight and showcase the diverse array of academic and scholarly works for graduate students from all of the academic schools and colleges at USF.
During this event, GsAL research assistant, Radhika Bhargava, received the Excellence in Academic Research award for her involvement in a project designed to build the capacity to monitor land use and land cover changes in the Lower Mekong region. The project is based on a geospatial needs assessment conducted by SERVIR-Mekong in 2015 for the Lower Mekong countries which included individual country consultations. The assessment revealed that many countries were dependent on land cover and land use maps for land resource planning, quantifying ecosystem services including resilience to climate change, biodiversity conservation, and other critical social issues. Many of the Lower Mekong countries have developed national-scale land cover maps derived in part from remote sensing products and geospatial technologies. However, updates are infrequent and classification systems and accuracy assessment do not always meet the needs of key user groups. In addition, data products stop at political boundaries and are often not accessible. Many of the Lower Mekong countries rely on global land cover products to fill the gaps of their national efforts, compromising consistency between data and policies. These gaps in national efforts can be filled by a flexible regional land cover monitoring system that is co-developed by regional partners with the specific intention of meeting national trans-boundary needs, for example including consistent forest definitions in trans-boundary watersheds. During this assessment, regional stakeholders identified a need for a land cover monitoring system that will produce frequent, high quality land cover maps using a consistent regional classification scheme that is compatible with national requirements.
This system is dependent on a sustainable source of field data that insures data quality and improves potential impact. Based on this need, collaborative workshops were held to create a robust regional reference data system that integrates results from field data, national inventories and high resolution imagery to meet the end user needs. The results presented here highlight the value of collaboratively developed systems that use data convergence to improve land cover mapping results for multiple end users.
The mission of the National Oceanic and Atmospheric Administration’s Office of National Marine Sanctuaries is to serve as the trustee for the nation’s system of marine protected areas, to conserve, protect, and enhance their biodiversity, ecological integrity and cultural legacy. The Greater Farallones National Marine Sanctuary (GFNMS) protects the wildlife, habitats, and cultural resources of one of the most diverse and bountiful marine environments in the world, an area of 3,295 square miles off the California coast from Point Arena to Año Nuevo. The waters within the sanctuary are part of a nationally significant marine ecosystem that supports an abundance of life, including many threatened or endangered species, and a rich cultural landscape.
GFNMS requires the technical and professional services of a Marine GIS Analyst to develop high-quality cartographic products, online maps, and analytic products to support sanctuary management, education, science, operations, and resource protection. The maps and information generated by the GIS Analyst will inform management decisions for the sanctuary and its partners, as well as contribute to an improved understanding of the region. Products range from highly technical to public exhibits.
Work with sanctuary staff and partners to identify their spatial data needs and develop GIS and cartographic products accordingly.
Analyze spatial information to create products that convey complex topics to sanctuary stakeholders, partners and the public.
Obtain, organize, update, archive and manage the spatial data required to implement sanctuary priorities.
Create and update all metadata in compliance with Federal Geographic Data Committee (FGDC) standards.
Coordinate and manage existing seafloor map data, and identify priority areas for future mapping.
Integrate new data into the existing GIS databases of biological, oceanographic, geologic, socioeconomic, cultural, water quality and other thematic data.
Communicate with local, regional, state and national GIS and sanctuary staff to ensure effective data exchange and to keep spatial information up to date.
Present geospatial information at meetings and discussions with sanctuary partners, stakeholders and the public.
Respond to spatial information requests from other NOAA components, Federal agencies, state and local governmental bodies, private organizations, academic and research institutions, and the public.
Incorporate still photographs and video into geospatial products.
Evaluate and implement new GIS technology.
Perform other duties as assigned by supervisor.
The applicant should have:
Advanced understanding of spatial data concepts, including projections, relational databases, and cartographic production.
Advanced knowledge of GIS database administration and management principles, methods and techniques, including quality control methods and practices.
Expertise in data analysis and visualization.
Expertise in ArcGIS platforms (ArcGIS for Desktop, Spatial Analyst, 3D Analyst, ArcGIS Online, ArcGIS Story Maps and Journals), SeaSketch, Microsoft Excel, Word and PowerPoint, and Adobe desktop publishing products.
Experience with Python and Model Builder for ArcGIS.
Excellent verbal and written skills in communicating complex, technical GIS information to professional and lay audiences.
Good understanding of statistical analysis.
Ability to interact and work effectively with sanctuary staff, partners, and the public to disseminate GIS data and cartographic products.
Ability to work independently or as part of a team. Self motivated.
Minimum of 3-5 years GIS experience. Master’s Degree with concentration in geography, GIS, marine science, or equivalent is preferred.
Experience with management of marine biology, ecology, habitat, and/or oceanography data sets is preferred.
Experience with coastal issues in the central and northern California coast is a plus.
The employee will be based at the sanctuary office in the Presidio of San Francisco, CA and will be provided with desk space, computer and GIS software, access to phone, internet, fax, copy machine, etc. The employee is expected to be available during normal business hours, Monday through Friday. Employment and health benefits are included with the position. Periodic travel will be required. Salary is commensurate with experience.
The GIS Analyst will be employed by Sanctuary Supporters, LLC and detailed to the GFNMS Program Operations team. They will be supervised by the Coordinator of that team. The Coordinator will provide oversight, feedback, and set priorities through regular meetings and communication.
Applications should be submitted via email by Nov 4, 2016. Interviews will be conducted in November 2016. Target start date is ASAP after the candidate is selected. Qualified individuals should provide a statement of interest, resume with salary history, 2-3 work samples, and short list of professional references to:
Greater Farallones National Marine Sanctuary
This article was provided by SERVIR-Mekong/ADPC, and is also available on the ADPC website.
Take a look at this land cover photo. What do you see? Is it a forest, agriculture, water or something else?
Photo Credit: Google
It may seem like an irrelevant question, but it is not. Understanding land cover and land use change is important for land resource planning and for ecosystem services. This includes biodiversity conservation, water provision and purification, and resilience to climate change, among others. However, updates to land cover maps are infrequent, and classification systems can be inconsistent across years and countries.
Wildlife Conservation Society (WCS) and ADPC participants from the Regional Land
Cover Monitoring System workshop discuss a consistent path forward in classifying
different plots. Photo Credit: Watcharaporn Usomchat
Returning to the question in the beginning, how do we classify different land types? Working with key partners in the region is necessary to promote a coordinated approach in mapping and land classification. In March 2016, the Asian Disaster Preparedness Center (ADPC), along with SilvaCarbon, the US Forest Service and the Spatial Informatics Groups (SIG), brought partners from the region to begin the process of agreeing to common land classifications that could address the needs of several groups. This was part of a larger process of building a Regional Land Cover Monitoring System in the Lower Mekong Region, one of the flagship systems being created under the SERVIR-Mekong initiative funded by the United States Agency for International Development (USAID) with NASA and implemented by ADPC.
This work continued from 7-14 July 2016 as SERVIR-Mekong, along with SilvaCarbon, the US Forest Service and SIG, hosted a Google Earth Engine Training and a second workshop for the Regional Land Cover Monitoring System. Stakeholders worked particularly on algorithm development and reference data collection approaches. During the workshop, partners in the region convened to determine a consistent path forward in classifying different plots (or land types). This is a key step in the development of the Regional Land Cover Monitoring System, which will promote in-depth and reliable analysis on land cover issues in the Lower Mekong and provide reliable and consistent maps for the region.
Workshop facilitator, David Saah (Associate Professor & Director of Geospatial
Analysis Lab, Department of Environmental Science, University of San Francisco)
works with some ADPC, WCS and University Partnership Network participants in
using Google Earth Engine. Photo Credit: Watcharaporn Usomchat
As development of the Regional Land Cover Monitoring System continues, SERVIR-Mekong will be launching MAPCHA, a custom built and innovative tool that will allow for crowd sourced visual interpretation of satellite images. Along with other reference data sets from ministries and departments, image interpretations from participants throughout the Lower Mekong region will constitute a large training and validation dataset.
With the Regional Land Cover Monitoring System, decision makers, partners, and the general public will have access to reliable information on land cover, providing evidence based data to inform land use planning for climate resilience.
SERVIR-Mekong is a unique partnership with USAID and NASA, to promote the use of publicly available space technology for resilient development in the Lower Mekong. SERVIR-Mekong is implemented by Asian Disaster Preparedness Center with Spatial Informatics Group, Stockholm Environment Institute and Deltares.
There is a new position opening on at the Nature Conservancy Global Lands Carbon Science Team. They are looking for a qualified Geospatial Analyst to analyze and map climate mitigation opportunities as part of their growing Natural Climate Solutions work.
To view apply, click here (internal Conservancy applicants here).
For more information about the job posting click the link below!
By Jacquie Moss – MSEM Candidate at the University of San Francisco
I attended the Esri User Conference in San Diego from June 27-July 1, 2016 as a representative of the University of San Francisco. I also attended the Esri Imaging and Mapping Forum the weekend prior (June 25-26).
I was unprepared for the scale of this conference. Every minute of the conference offered a dozen or more options for participating. There were an estimated 16,000 people from a wide range of industries — government, architecture, real estate, conservation, agriculture, technology, criminal justice, defense/intelligence, health and human services, transportation, telecommunications, public utilities, and more.
Over this week of hands-on learning, technical workshops, real-world examples, and product demonstrations, I noticed a handful of pervasive topics:
UAVs (unmanned aerial vehicles), e.g. drones
Real-time data + IoT (Internet of Things)
This summary is written for the benefit of my colleagues in the MSEM program at USF, especially those seeking GIS certification.
UAVs (unmanned aerial vehicles ), e.g. drones
The Imaging & Mapping Forum could have more appropriately been called the “Drone Forum.” Most sessions covered some form of aerial capture — mostly lidar or drones (and sonar used for deep waters). Featured wasDrone2Map, a software tool created by Esri to make it simpler to create maps and perform analysis in ArcGIS from drone-captured still imagery.
Point cloud data that is captured by aerial vehicles provides new possibilities for 3D analysis and imagery. Real-world examples included forest management, monitoring coastal erosion, vegetation management, and monitoring species habitat.
One interesting tidbit is that Alaska was captured using airborne IFSAR, rather than lidar for a few reasons. Given that Alaska spans more than 1.7 KM2, it was going to be too costly to use lidar. Also, cloud coverage is a big issue with capture in Alaska and IFSAR works better in this situation.
Drones were discussed as a disruption to GIS — exposing more people to geospatial data. To clarify, the real disruption is the data (people don’t even know that they need GIS… they just want to fiddle with drones). Kass Green (“remote sensing rock star”) espoused, “out of chaos comes opportunity.”
With the improved supply of high resolution optical imagery from drones and satellites, 3D imagery is expected to become much more ubiquitous. ArcGIS has native lidar support and integrated 3D display and analysis, which makes it easier than ever to import and manipulate 3D assets.
Of particular interest is a massive project led by USGS. “The National Map” — 3D Elevation Program (3DEP) — is collecting point cloud data for all of the nation’s natural and constructed features. Combined with NOAA’s coastal mapping project, much of the nation has been captured. Coastal mapping project is freely available online.
The significance of 3D is beyond the cool factor. Certainly, it opens the door for more intriguing and accurate representations of a scene, including VR (virtual reality). More importantly, 3D creates opportunity for deeper analysis. With the inclusion of elevation data, other factors become relevant, such as: depth, volume, massing, slope, sun exposure, etc… One example that was shared was that of using 3D analysis to investigate the effects of sea-level rise on a built environment to the scale of which floors in which buildings will be affected.
Certainly there was talk about big data (volume, variety, velocity). But the buzz was about real-time data. Technological advances have made it possible to collect data from numerous sources at instantaneous rates. This persistent surveillance system is made possible by the Internet of Things (IoT), comprised of:
Smart sensors on electric meters, weather, streams, natural resources, heavy equipment, high-value assets
Imagery from satellites, frame cameras, and drones
Human activity from social media streams, smartphone activity, web logs, and GPS telemetry
Analysts who are interested in being most agile with this extremely valuable data need skill with Python. It is the glue language of data analysis. One expert recommends the following tools:
Pandas: Python library for data manipulation and data analysis
Geopandas: Power of Pandas applied to spatial data
Esri now offers web-based tools that allow users to create an interactive experience that combines text, video, live maps, imagery, and 3D scenes. This set of tools are called Story Maps, and they can be authored in several different formats — as stand-alone website, embedded within an existing website, or as an app. The layout templates are elegant and designed to make content shine. Super easy to use, Story Maps are being used by map makers to prototype, collaborate, and communicate with audiences.
Features of Story Maps that I found most compelling:
Web maps used in Esri Story Maps and the data they present are hosted in the ArcGIS Online cloud
Responsive design (works across devices, i.e. desktop, tablet, and smartphone)
Tools are all web-based and do not require user to download any software; access using ArcGIS online credentials
There are different types of story maps that users can create. With each the layout and set of features vary. The types are: Journal, Tour, Series, Swipe and Spyglass. In addition, Esri has a couple of new types in beta: Cascade and Crowdsource.
If someone didn’t want to use one of the templates, Story Maps can also be created from scratch using the developer APIs and tools
And ultimately, the star of the week was the fully redesigned product by Esri, ArcGIS Pro. ArcGIS Pro combines Esri’s suite of tools into one integrated product, and it is the future of the company. The interface is a big improvement over ArcMap, and it’s highly customizable to the project and set of tasks that the user is performing. ArcGIS Pro is a fully 64-bit, multithreaded application that runs on Windows — that means it’s faster and can perform more than one task at a time.
Below is an overview of just some of the features of ArcPro.
Create and publish both 2D and 3D maps.
Share what you create in ArcGIS Pro with others using ArcGIS Online or Portal for ArcGIS.
Application knows when you’re in edit mode and gives you real-time feedback as you make edits (eliminated the need to start and stop edits).
It has a whole new drawing engine that includes true transparency and anti-aliasing. As a designer, I am very excited about this improvement.
It supports many layouts, rather than having to create a new file for each layout.
In addition to these five themes that I noticed at the conference, I also want to share three of my favorite slices of the conference.
U.S. Climate Resilience Toolkit
Developed by the National Oceanic and Atmospheric Administration (NOAA) and other Federal agencies, theClimate Resilience Toolkit is designed to enable municipalities to evaluate their vulnerabilities and inform action planning. It provides county-scale climate projections, aggregates state and municipal climate-vulnerability assessments, and allows users to visualize different variables from past to future.
It is useful to reference the climate change indicators that the U.S. Global Change Research Program has developed. Described as a preliminary set, the indicators include Greenhouse Gas Index, Arctic Sea Ice Extent, Forest Cover, Ocean Chlorophyll Concentrations, and Vibrio Infections.
Living Atlas of the World
The Living Atlas of the World is Esri’s endeavor to bring content together to make the GIS of the world. GIS specialists can submit their maps, apps, scenes, story maps, and even data to be included. This community also provides a place to retrieve helpful basemaps, historical maps, data layers, tools, services for your own work.
Alexander von Humboldt
And now, the most enjoyable for last… in her Keynote, Andrea Wulf shared glorious maps and engaging stories about German naturalist, explorer, and cartographer Alexander von Humboldt (1769-1859). Wulf has just written a non-fiction book about his accomplishments, called “The Invention of Nature.” In his time, Humboldt inspired Charles Darwin and Thomas Jefferson, among others.
In addition, he produced some of the most complex, detailed, and gorgeous information graphics and maps that I have ever seen, such as the one below. If you have 45-minutes to watch this highly entertaining and informative video, Esri has made Wulf’s keynote publicly available.
GIS Boot Camp for Faculty will be a hands on experience that actively guides faculty through a standard GIS overlay assessment. Faculty members will be exposed to a variety of GIS formats. In addition, they will learn how to import files into ESRI products and they will learn how to do the most common geospatial processes. At the end of the class, attendees will have produced a map and have been exposed to the tools, buttons and datasets common to most GIS projects. This course is open to faculty members of all levels of experience. There is no previous experience necessary to attend this class. Lastly, there will be time at the end of the class to discuss any academic projects as they relate to GIS.
This event is hosted by the GsAL and sponsored by CRASE http://craseusf.org/