Abstracts Track 2021

Area 1 - Data Acquisition and Processing
Area 2 - Domain Applications

Area 1 - Data Acquisition and Processing

Nr: 11
Title:

Corporate Accommodation Opportunities using Location Intelligence and GIS: Property Investments in the San Antonio Qualified Opportunity Zones (QOZ)
Authors:

Gloria Ciccolini
Abstract: The purpose of this study is to show how a UK SME (small and medium-sized enterprises) expanding their corporate accommodation business in American soil, can use location intelligence and GIS to find and analyze conditions for property investments in the San Antonio Qualified Opportunity Zones (QOZ) and determine those industrial clusters with the potential for corporate clients. Encouraging public and private investments in an economically challenged QOZ provides employment opportunities within the local community – where the median family income is on average 37% below the state median - as well as obtaining eligible gains and tax incentive. Location is a recurring factor in a serviced apartment booking process both for corporates and travel agencies. Expected results: • Identify those companies/sectors that might provide potential long-term clients (number of employees, revenue, imports/exports, location) • Determine those QOZs which will most likely attract property investments from a UK SME (Proximity to business or corporate hub, travel distance) A selection of optimal opportunity zones with detailed charts and maps will be produced from location intelligence data for decision makers to include in their investment choices.

Area 2 - Domain Applications

Nr: 8
Title:

Gathering Urban Communities around Open Data Collection and Geographic Information for Improving Resilience to Climate Change
Authors:

Vincent Lecamus
Abstract: Major cities on the African continent are facing the intensifying effects of climate change and natural disasters. The vulnerability of the fast growing urban population facing natural disasters as floods and loss of habitat is increasing, causing high migratory movements and health risks. Being both located by the ocean, the cities of Saint-Louis and Pointe-Noire are naturally exposed to the risks of coastal erosion and flooding. At a local level, in districts like the “Saint-Louis island” and the “Langue de Barbarie” in Saint Louis and the “Mboukou” and “Tchiniambi1” in Pointe Noire, habitats have been gradually engulfed by the decline of the coastline for several decades. Socio-economic facilities are threatened by coastal erosion and numerous floods, thus constituting a high socio-health and economic risk. Through our expertise in the field of geographic information, and through our association with local experts, city councils and universities, we are conducting participatory mapping campaigns with the communities and institutions in Saint-Louis and Pointe Noire. Geographic information has an essential role in supporting the management of urban growth and the risk of natural disasters. The lack of detailed and up-to-date geographic data limits urban planning, informed decisions, and hinders the resilience of populations facing natural disasters. For example, an entire district of Saint-Louis was built on non-aedificandi lands with flats backfilled with garbage. That added to the stagnant rain water and the rise of the sub-surface water causes floods which negatively impact the living environment and considerably weaken the health of the populations (proliferation of mosquitoes carrying malaria, diarrheal and skin diseases, risks of cholera, etc). Through our presentation we will also showcase how engaging the local communities in the participatory mapping sessions has impacted their long-term vision of the city and has brought a deeper sense of belonging to the habitants. How data collection has improved decision making and how the participatory mapping was used to update and complete the geographical data related to disaster risk management in priority areas. In addition, we will present the open source web GIS platform that was developed to facilitate data sharing and improve their use.
Nr: 14
Title:

Nationwide Analysis of the Philippines’ Forest Canopy Heights Derived from ICESat
Authors:

Alex S. Olpenda
Abstract: The general growth and structure of a forest is dictated by the different environmental factors surrounding it. A handful of studies globally have been done on the correlation of these factors and forest structure but only few of these have been conducted in the Philippines with the use of remote sensing datasets. This paper is an initial undertaking to analyze how these factors affect the forest canopy heights at country-wide scale using space-based laser technology. Forest maximum canopy height (MCH) and Lorey’s mean height (LMH) defined as the crown-area-weighted canopy heights were extracted from the Geoscience Laser Altimeter System (GLAS) LiDAR (light detection and ranging) instrument onboard the Ice, Cloud, and land Elevation (ICESat) Satellite. From the 18,578 statistically-selected globally distributed forested sites acquired between 2004 and 2008, 144 point locations of MCH and LMH were extracted all over the Philippines. The identification of the forest class was based on the 2010 MODIS International Geosphere-Biosphere Programme (IGBP) global land cover. Meanwhile, nationwide geographical parameters used in the study were generated from ASTER Digital Elevation Model (DEM). MCH were later assessed based on the reclassified parameters and was found out that those above 1000m above sea level or beyond 50% slope are statistically different from other classes indicating a different forest formation. Meanwhile, there is no indication that MCH are different when they are grouped based on the aspect (p=.172). However, there seems to be a conspicuous pattern of the canopy heights where values are lower on the north, east and south facing slopes but generally higher on northeast, southeast and southwest. These findings could be useful for modeling forest type distribution and rehabilitation efforts. Further test will be conducted including a univariate general linear model for the LMH to incorporate the soil types and meteorological data.
Nr: 6
Title:

Using GIS to Implement Social Responsibility during the COVID-19 Pandemic
Authors:

Paulina Y. Wong
Abstract: Six days after the first reported case of COVID-19 in Hong Kong on 23 January 2020, a collaborative community-based research project with Hong Kong Public Opinion Research Institute, known as the “Community Health Project” was planned and launched. The Community Health Project solicits public views on various aspects of the pandemic: (i) their perceived chance of being infected by COVID-19, (ii) public health risk in local communities, (iii) citizens’ stress levels, and (iv) which type and where there were more urgent demands for anti-epidemic commodities. The project uses online questionnaires to record public voices for opinion sharing. The outcomes of online survey were mapped daily and visualized through a web-based GIS dashboard which provides near real-time COVID-19 information and public health risk assessments for respective local communities. The GIS dashboard also serves as an important resource for the NGOs, District Council members and social workers to target the high risk-areas and vulnerable population groups to offer immediate attention and solid support. By mid-March, the project extended the survey to volunteers to engage people with limited internet access and those without a mobile phone by means of manual solicitation and assistance in completing the online survey questions. These organizations have also collected a lot of donated items (i.e. face mask, health supplies) from donors. Daily updates of anti-epidemic items in need by communities as reported through the GIS dashboard and GIS spatial analysis have enabled volunteers to make informed decisions and immediately channel items in demand to those with real needs. In addition, the location-allocation analysis by GIS enabled a more efficient and strategic resource allocation. These on-going initiatives continue to generate positive social impact to local communities of Hong Kong.
Nr: 7
Title:

Rural Roads’ Data Collection, Asset Management and Its Impact on Improving the RAI (Rural Access Index) and Economic Growth for Communities
Authors:

Vincent Lecamus
Abstract: Effective asset management (From transportation to utilities and linear infrastructures) plays a key role from enhancing economic growth to improving the quality of life inside communities (reducing safety and poverty issues) but also in budget optimization, maintenance follow-up and implementation. Asset management through Geographical Information Systems (GIS) is one of the pathways to sustainable management and investment efficiency for maintaining communities safe while insuring mobility, sustainability and economic growth. As an international company specialized in the use of GIS data dedicated to linear infrastructure’s asset management (road, rail, utilities network, urban planning, etc.), we have had the opportunity to participate and be a part of different projects around the world specially in developing countries with high isolation levels and low RAI. Our team is currently in charge of 2 Low volume roads’ projects from the World Bank in Togo and Madagascar. These projects emphasize the importance of Road data collection and asset management data to improve RAI, quality of live for the populations and decreasing mortality and poverty rates. Through our presentation, we will showcase how to use GIS data to optimize asset management and investment regarding low volume roads asset management, urban planning, the improvement of RAI, etc. With figures and case studies we will highlight best practices and their impacts in resources and budgeting optimization. Benefits of the use of innovative methods, such as flexible mobile mapping systems, web GIS platforms and apps for linear infrastructure data management will be displayed.