Conference Agenda

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Session Overview
303R: Urban land-system synergies and governance using remote sensing, modelling and big data analysis
Thursday, 25/Apr/2019:
1:30pm - 3:00pm

Session Chair: Dengsheng Lu
Session Chair: Jinwei Dong
Session Chair: Qingxu Huang
Session Chair: Jian Peng
Session Chair: Rafiq Hamdi
Session Chair: Wenhui Kuang
Location: MB-114
Main Building, 1st floor, west wing, 78 seats
Session Topics:
How do we support transformation?

Session Abstract

Worldwide, the urban dwellers are facing unprecedented multi-aspect challenges related to urban land system transformation and governance in order to achieve sustainable targets under climate change conditions. With the advent of remote sensing, process-based models and big data analysis, spatially explicit and fine-scale information will provide an important knowledge for urban land system transformation and governance. How to combine different source of information from remote sensing, process-based modeling, big data, and how to find synergies among multiples factors (i.e., urban function zones, land use/land cover, heat island, and so on) are becoming cutting-edge issues in order to study fine-scale and multi-element detection and analysis of urban land system to be used for urban governance and management. With the development of remote sensing, modeling and big data technologies as well as the improvement of mapping algorithms, a set of products such as impervious surface area at national and global scales, surface radiation and heat fluxes, surface and canyon heat island, and surface runoff in urbanized areas with higher spatial and temporal resolutions have been developed to fill this gap.

This session expects to provide an opportunity for urban land-system synergies and governance with remote sensing, modelling and big data integration. We welcome any studies related to the application of remote sensing, modelling and big data in the urban field. This session will share the latest advances in how urban government and management are using remote sensing, modelling and big data analysis and products to respond to climate change, capturing perspectives from cities around the world.

The potential topics may include the following:

1. Data integration or fusion methods from remote sensing, process-based modeling, or big data

2. High-spatial resolution mapping of urban land cover/land use (i.e., impervious surface, green space) at global or nation scale

3. Spatial mapping and exploratory analysis on urban heat island, urban hydrological process, and other ecological factors.

4. Knowledge mining or discovery from available fine-scale spatially explicit information for urban governance

This session is supported by the GLP Beijing Nodal Office

Session Organizers: Dengsheng Lu, Wenhui Kuang, Rafiq Hamdi, Jian Peng, Qingxu Huang, Guoming Du, and Jinwei Dong

Full talk
ID: 306 / 303R: 2
303R Urban land-system synergies and governance using remote sensing, modeling and big data analysis
Keywords: Urban-rural linkages, urban food security, GIS, Remote Sensing, Spatial Modeling, Sub-Saharan Africa

Urban-rural linkages and urban food security in sub-saharan africa

Tom Evans1, Zack Guido1, Andrew Zimmer1, Megan Konar2, Kurt Waldman3, Jordan Blekking3, Kelly Caylor4, Kathy Baylis2, Lyndon Estes5

1University of Arizona, United States of America; 2University of Illinois; 3Indiana University; 4University of California Santa Barbara; 5Clark University

Urban population growth in Sub-Saharan Africa is projected result in a transition whereby the urban population exceeds the rural population by 2050. And Africa is projected to be the fastest urbanizing continent between the present and 2050. This trend has important implications for urban-rural linkages and how the distribution of rural food production can meet the needs of urban households. While megacities will impose critical demands on food supplies, more than 60% or urban population in Africa live in cities with fewer than 1M residents. This suggests the importance of a dynamic spatial analysis to understand how the variable growth rate of cities regionally will affect food transfers and food prices. We present data from Sub-Saharan Africa investigating the impact of urban population growth on proximal and distal food production. This work draws on the concept of city-region food systems in acknowledging the spatial relationships inherent in food flows and the impacts of rural dynamics on urban food security. Cities of different sizes have different types of urban-rural linkages and we present implications for the resilience of urban food security to social and environmental shocks in rural areas drawing on remote sensing data, market prices and demographic data.

Full talk
ID: 594 / 303R: 3
303R Urban land-system synergies and governance using remote sensing, modeling and big data analysis
Keywords: GHG emissions, population modeling, CO2 model, Nightlights, SE Asia

High resolution mapping of gridded CO2 emissions to population distribution for Vietnam, Cambodia and Laos

Andrea Gaughan1, Alessandro Sorichetta2, Forrest Stevens1, Laura Krauser1, Tomohiro Oda4, Greg Yetman3, Rostyslav Bun5, Son Nghiem6

1University of Louisville, United States of America; 2WorldPop, University of Southampton; 3CIESIN, Columbia University, USA; 4NASA, Goddard Space Flight Center, USA; 5Lviv Polytechnic National University, Lviv, Ukraine; 6Jet Propulsion Laboratory, California Institute of Technology

With projected increases in greenhouse gases emissions (GHG) from countries in South and Southeast Asia, tracking temporal and spatial changes in GHG emissions is key to successful implementation of UNFCCC. Emission inventories provide a primary, robust tool to track emission trends over time at the country level; however, subnational emissions are subject to errors, bias, and uncertainty dependent on the spatial modeling approaches used to disaggregate them. Assessing these errors and uncertainties pose challenges due to the lack of physical measurements at subnational scales. To address potential discontinuities in emissions models this study spatially compares gridded CO2, modeled with nighttime lights (NTL) data to a gridded population map at a 1 km spatial resolution for the years 2000, 2005, and 2010. We do so for Vietnam, Cambodia, and Laos, using Odiac, a fossil fuels CO2 emissions dataset, along with a gridded population model parameterized using a set of harmonized geospatial covariates. With these modeled data sets, we characterize the spatial distribution and association of subnational CO2 emissions to population densities. We find that spatial correlations between the population and CO2 emission relationship over the three countries improved over time. Our approach provides the basis to assess how residential population may or may not reflect CO2 emissions, potentially varying with development and urbanization. We discuss implications and provide explanation for relationships based on shifts in demographic and socioeconomic patterns for the three Southeast Asian countries.

Full talk
ID: 378 / 303R: 4
303R Urban land-system synergies and governance using remote sensing, modeling and big data analysis
Keywords: Urban sprawl, social segregation, urban planning, Addis Ababa, Ethiopia

Detection of the urban sprawl and social segregation, in Africa's diplomatic capital, Addis Ababa, Ethiopia

Amanuel Tadesse Weldegebriel1,2, Engdawork Assefa Tilahun2, Anton Van Rompaey1

1KU Leuven university, Belgium; 2Addis Ababa University, Ethiopia

In the 21st century, urbanization, which is an overriding factor for land use change is growing at an unprecedented rate in the Global South. Currently, circa 30% of the population in the Global South resides in cities, and this figure is expected to double in 2040. In Ethiopia, Addis Ababa (the seat of African union and world diplomatic community), the rapid urbanization results in both positive and negative societal impacts. On the one hand the growth of Addis Ababa is driving the economic growth of the country and offering a better livelihood for many, but on the other hand it is the cause of mobility problems, population displacements, social segregation, city pollution and loss of biodiversity. Urban planning is therefore, the major challenge for a sustainable development of Ethiopia in the coming decades. However, at present, there is no reliable information on the extent of urban sprawl, its socioeconomic and biophysical drivers, and its consequences on the settlement pattern and social segregation. This study aims to contribute to this information gap, by (1) mapping the extent of the urban expansion, (2) identifying the major socioeconomic and biophysical controlling factors and (3), detection of the level of social segregation. Land use change over the past 4 decades in the study area was detected using the LANDSAT-archives. Backward analysis of these time-series was carried out to detect the controlling factors of the sprawl pattern. In a next stage the driving factors of urbanization and social segregation will be identified by means of semi-structured household interviews in contrasting neighborhoods in the rapidly changing urban landscape. Finally, a model-based spatial decision support tool will be developed to support planners and policy makers with the evaluation of alternative planning scenarios. This papers discusses a few of the possible future development pathways.

Flash talk
ID: 372 / 303R: 5
303R Urban land-system synergies and governance using remote sensing, modeling and big data analysis
Keywords: impervious surface area; dynamic change; driving forces; nighttime light; Landsat; socioeconomic data; China

Examining spatial patterns and driving forces of impervious surface expansion in China with multi-sensor remotely sensed and ancillary data

Dengsheng Lu1,2, Guiying Li2, Longwei Li3, Wei Guo2, Wenhui Kuang4

1Michigan State Univeristy, United States of America; 2Fujian Normal University; 3Zhejiang A&F University; 4Institute of Geographic Sciences and Natural Resources Research

Many studies such as urban environmental modeling, hydrological modeling, climate change, and socioeconomic analysis require detailed impervious surface area (ISA) data at regional and global scales, but updating these datasets remains a challenge due to complex urban landscapes and limitation of remotely sensed data. This research aims to (1) develop ISA data in China in 2000, 2010 and 2015 through the combined use of multiple data sources - nighttime light (Defense Meteorological Satellite Program (DMSP) Operational Linescan System (OLS)), Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band), Moderate Resolution Imaging Spectroradiometer (MODIS), and Landsat data for examining spatial patterns and dynamic change; and (2) examine forces driving urban expansions at different scales. The integration of nighttime light and MODIS NDVI data at 250 m spatial resolution were used to extract initial ISA data using the thresholding approach. The Landsat-derived normalized difference vegetation index (NDVI) and Modified Normalized Difference Water Index (MNDWI) images were used to mask vegetation and water areas from the initial ISA data. The spectral signatures of these ISA data were further extracted and used to modify the ISA data using cluster analysis. The relationship between ISA data with population and GDP at different scales were examined. The results indicate that ISA is largely distributed in the metropolitans and cities along the coastal regions. ISA expansion in the cities and rural areas are obvious, but vary considerably, depending on the geolocations. Population and GDP are importance factors in influencing spatial patterns and rates of ISA expansion, in particular, GDP plays much more important roles than population in ISA amount and expansion rates.

Full talk
ID: 270 / 303R: 6
203R Land use change processes and interactions along the urban-rural gradient
Keywords: Landuse change, land surface temperature, tropical cities, urban-rural gradient

Landuse change implications on land surface temperature in the tropical cities: An Assessment of urban-rural gradient

Sina Ayanlade

Obafemi Awolowo University, Ile-Ife, Nigeria, Nigeria

This study aims to estimate land use change effects on land surface temperature and heat fluxes over three cities in Niger Delta region, using satellite data. The study was carried out in three major urban areas in the Niger Delta of Nigeria: Benin City, Port Harcourt and Warri. Both in situ and satellite climatological data were used in this study to estimate the variations in heat fluxes over different land use/ land cover in three major urban areas around the Niger Delta region in Nigeria. The results showed that urban expansion in the Delta has resulted in variation in boundary currents and higher temperatures in the city areas compared to the immediate rural areas. It is clear from the results that different land uses exhibit different degree of LST during both wet and dry seasons, with temperaturs nearly 20C higher in dry season compared to the wet seasons. There appears to be a general increase in the mean LST, with an average of 1.43ÂșC increase between the years 2004 and 2015 with different urban land use. The estimated heat flux ranges from 30.55 to 102.05 W/m2 in the year 2004, but increases flux ranging from 33.25 to 120.06 W/m2 were estimated in the year 2015. The average heat flux was nearly 30.12W/m2 during wet season, but much higher during the dry season with average heat flux nearly 215.75W/m2. The results showed that urban expansion in the Delta has resulted to variation in boundary currents and higher temperatures in the cities area compared to its immediate rural areas. The study concluded that urban weather and climate, urban heat redistribution and other hydrosphere processes are determined by the energy processes and fluxes. The study concluded that urban climate, urban heat redistribution and other hydrosphere processes are greatly affected by the change in land use.