Written by Oz Brown
Google Earth Engine India Workshop
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.
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.
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