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 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.
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
3D
Real-time data + IoT (Internet of Things)
Story Maps
ArcGIS Pro
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.”
3D
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.
In ArcGIS Pro, users can compare a 2D view to its 3D and perform 3D spatial analysis. This image, from Esri, is showing analysis of airflow between buildings.
Real-time Data
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
Story Maps
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
Esri created this Story Map for the National Park Service to demonstrate its Cascade style.
ArcGIS Pro
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.
ArcGIS Pro has a highly customizable interface that adapts to the task at-hand.
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.
Part of the Toolkit, the Climate Explorer visualizes a variable (in this example, Mean Daily Maximum Temperature) from past, present to future.
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.
Humboldt produced this cross-section of Chimborazo (in Ecuador). It shows the plants he found at each altitude. The side tables show corresponding measured values of gravity, humidity, temperature and other properties.
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/
The GsAL is traveling back to Bangkok, Thailand to help the SERVIR-Mekong team, in partnership with the U.S. Forest Service-Remote Sensing Applications Center (USFS-RSAC), SilvaCarbon, and the Asian Development Bank GMS Core Environment Program (ADB-CEP), organize a workshop entitled Typology for a Regional Land Cover Monitoring System, in Bangkok, Thailand.
The main objectives of the workshop are to maximize consensus for a consistent regional land cover typology and establish working groups for developing a system to produce periodic regional land cover products.
Participants will be asked to review a technical document and prepare a brief presentation outlining their institution’s land cover monitoring-related work.
Background
In 2015, SERVIR-Mekong conducted a geospatial needs assessment for the Lower Mekong countries which included individual country consultations. The team found 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 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 transboundary needs, for example including consistent forest definitions in transboundary 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 country needs.
Based on this need and demand, SERVIR-Mekong is leveraging the recent development of remote sensing science and technology, such as Google Earth Engine (GEE), and working together with production partners to develop a system that will use a common set of input data sources to generate high-quality regional land cover maps on a regular basis (i.e. annual or every two years). The system is being designed to facilitate improved policy, planning, and decision making by a wide range of users (such as government agencies, local community groups, non-profit organizations, and the private sector). An important component of this system’s design is the ability to leverage the recent developments in remote sensing science and technology that can contribute significantly to more timely land cover inventories. The system’s design will also enable more effective and efficient mapping efforts. For example, GEE allows cloud-based storage and computation of large quantities of remotely sensed data that can be organized in many ways to meet specific needs.
The development of a consistent regional land cover typology for categorizing land cover data using regional [i.e., regionally agreed] definitions that is reasonably compatible with existing national classification systems, is the first step needed for such a Mekong specific monitoring system. In this context, a 3- day exchange will be organized to train, discuss, consult and agree on a consistent typology/classification system that will be used for the regional land cover monitoring system for Lower Mekong countries.
– See more at: http://servir.adpc.net/news-events/typology-regional-land-cover-monitoring-system-workshop#sthash.Zp5X4Rei.dpuf
