The role of earth observation in an integrated deprived area mapping “system” for low-to-middle income countries

Urbanization in the global South has been accompanied by the proliferation of vast informal and marginalized urban areas that lack access to essential services and infrastructure. UN-Habitat estimates that close to a billion people currently live in these deprived and informal urban settlements, generally grouped under the term of urban slums. Two major knowledge gaps undermine the efforts to monitor progress towards the corresponding sustainable development goal (i.e., SDG 11—Sustainable Cities and Communities). First, the data available for cities worldwide is patchy and insufficient to differentiate between the diversity of urban areas with respect to their access to essential services and their specific infrastructure needs. Second, existing approaches used to map deprived areas (i.e., aggregated household data, Earth observation (EO), and community-driven data collection) are mostly siloed, and, individually, they often lack transferability and scalability and fail to include the opinions of different interest groups. In particular, EO-based-deprived area mapping approaches are mostly top-down, with very little attention given to ground information and interaction with urban communities and stakeholders. Existing top-down methods should be complemented with bottom-up approaches to produce routinely updated, accurate, and timely deprived area maps. In this review, we first assess the strengths and limitations of existing deprived area mapping methods. We then propose an Integrated Deprived Area Mapping System (IDeAMapS) framework that leverages the strengths of EO- and community-based approaches. The proposed framework offers a way forward to map deprived areas globally, routinely, and with maximum accuracy to support SDG 11 monitoring and the needs of different interest groups

Assessing heat exposure to extreme temperatures in urban areas using the Local Climate Zone classification

Trends of extreme-temperature episodes in cities are increasing (in frequency, magnitude and duration) due to regional climate change in interaction with urban effects. Urban morphologies and thermal properties of the materials used to build them are factors that influence spatial and temporal climate variability and are one of the main reasons for the climatic singularity of cities. This paper presents a methodology to evaluate the urban and peri-urban effect on extreme-temperature exposure in Barcelona (Spain), using the Local Climate Zone (LCZ) classification as a basis, which allows a comparison with other cities of the world characterised using this criterion. LCZs were introduced as input of the high-resolution UrbClim model (100 m spatial resolution) to create daily temperature (median and maximum) series for summer (JJA) during the period 1987 to 2016, pixel by pixel, in order to create a cartography of extremes. Using the relationship between mortality due to high temperatures and temperature distribution, the heat exposure of each LCZ was obtained. Methodological results of the paper show the improvement obtained when LCZs were mapped through a combination of two techniques (land cover-land use maps and the World Urban Database and Access Portal Tools - WUDAPT - method), and the paper proposes a methodology to obtain the exposure to high temperatures of different LCZs in urban and peri-urban areas. In the case of Barcelona, the distribution of temperatures for the 90th percentile (about 3-4 ∘C above the average conditions) leads to an increase in the relative risk of mortality of 80 %

Contributing to WUDAPT: A Local Climate Zone Classification of Two Cities in Ukraine

Local climate zones (LCZs) divide the urban landscape into homogeneous types based on urban structure (i.e.,morphology of streets and buildings), urban cover (i.e., permeability of surfaces), construction materials, and human activities (i.e., anthropogenic heat). This classification scheme represents a standardized way of capturing the basic urban form of cities and is currently being applied globally as part of the world urban database and portal tools (WUDAPT) initiative. This paper assesses the transferability of the LCZ concept to two Ukrainian cities, i.e., Kyiv and Lviv, which differ in urban form and topography, and considers three ways to validate and verify this classification scheme. An accuracy of 64% was achieved for Kyiv using an independent validation dataset while a comparison of the LCZ maps with the GlobeLand30 land cover map resulted in a match that was greater than 75% for both cities. There was also good correspondence between the urban classes in the LCZ maps and the urban points of interest in OpenStreetMap (OSM). However, further research is still required to produce a standardized validation protocol that could be used on a regular basis by contributors to WUDAPT to help produce more accurate LCZ maps in the future

Perspectives on the structural health monitoring of bridges by synthetic aperture radar

Large infrastructures need continuous maintenance because of materials degradation due to atmospheric agents and their persistent use. This problem makes it imperative to carry out persistent monitoring of infrastructure health conditions in order to guarantee maximum safety at all times. The main issue of early warning infrastructure fault detection is that expensive in-situ distributed monitoring sensor networks have to be installed. On the contrary, the use of satellite data has made it possible to use immediate and low-cost techniques in recent years. In this regard, the potential of spaceborne Synthetic Aperture Radar for the monitoring of critical infrastructures is demonstrated in geographically extended areas, even in the presence of clouds, and in really tough weather. A complete procedure for damage early-warning detection is designed, by using micro-motion (m-m) estimation of critical sites, based on modal proprieties analysis. Particularly, m-m is processed to extract modal features such as natural frequencies and mode shapes generated by vibrations of large infrastructures. Several study cases are here considered and the “Morandi” Bridge (Polcevera Viaduct) in Genoa (Italy) is analyzed in depth highlighting abnormal vibration modes during the period before the bridge collapsed

Geography Newsletter

Contents:Head’s Column [Page] 2 Dr. Lin Visits China [Page] 3 Field Research in Portugal [Page] 3 Return to Romania [Page] 4 Excursion to Cuba [Page] 4 Students Visit Jerry Wilson’s Eco-Friendly Solar House [Page] 5 GIS at St. Francis Indian School [Page] 5 Great Plains- Rocky Mountain Division Meeting [Page] 6 Kearney Field Excursion [Page] 6 Gamma Theta Upsilon (GTU): Delta Zeta (DZ) [Page] 6 Geography Awareness Week (GAW) Speaker [Page] 7 SDGA Promotes GAW [Page] 7 Cole Krehbiel Wins Prestigious Award [Page] 8 Delora Bennett: Employee of the Month [Page] 8 Graduate Student and Alumnae Add Depth to Class [Page] 8 Alumni Spotlight [Page] 9 What Inspires Donors [Page] 9 111th Annual Meeting of the AAG in Chicago [Page] 10 46th Annual South Dakota State Geography Convention 2015 [Page] 11-13 Alumni Awards [Page] 14 Friend of Geography & Young Professional [Page] 15 SDSU Geographers at EROS [Page] 16-17EROS Scholarship [Page] 17 Activities of the Graduate Teaching Assistants (GTAs) [Page] 18-20 Virtual Colleagues [Page] 20-21 Geography Faculty [Page] 22-23 Geography Club in the Hobo Day Parade [Page] 24https://openprairie.sdstate.edu/geo_news/1003/thumbnail.jp

Applications of econometrics and machine learning to development and international economics

In the first chapter, I explore whether features derived from high resolution satellite images of Sri Lanka are able to predict poverty or income at local areas. I extract from satellite imagery area specific indicators of economic well-being including the number of cars, type and extent of crops, length and type of roads, roof extent and roof type, building height and number of buildings. Estimated models are able to explain between 60 to 65 percent of the village-specific variation in poverty and average level of log income. The second chapter investigates the effects of preferential trade programs such as the U.S. African Growth and Opportunity Act (AGOA) on the direction of African countries’ exports. While these programs intend to promote African exports, textbook models of trade suggest that such asymmetric tariff reductions could divert African exports from other destinations to the tariff reducing economy. I examine the import patterns of 177 countries and estimate the diversion effect using a triple-difference estimation strategy, which exploits time variation in the product and country coverage of AGOA. I find no evidence of systematic trade diversion within Africa, but do find evidence of diversion from other industrialized destinations, particularly for apparel products. In the third chapter I apply three model selection methods – Lasso regularized regression, Bayesian Model Averaging, and Extreme Bound Analysis -- to candidate variables in a gravity models of trade. I use a panel dataset of of 198 countries covering the years 1970 to 2000, and find model selection methods suggest many fewer variables are robust that those suggested by the null hypothesis rejection methodology from ordinary least squares

Monitoring the impact of groundwater pumping on infrastructure using Geographic Information System (GIS) and Persistent Scatterer Interferometry (PSI)

Transportation infrastructure is critical for the advancement of society. Bridges are vital for an efficient transportation network. Bridges across the world undergo variable deformation/displacement due to the Earth’s dynamic processes. This displacement is caused by ground motion, which occurs from many natural and anthropogenic events. Events causing deformation include temperature fluctuation, subsidence, landslides, earthquakes, water/sea level variation, subsurface resource extraction, etc. Continual deformation may cause bridge failure, putting civilians at risk, if not managed properly. Monitoring bridge displacement, large and small, provides evidence of the state and health of the bridge. Traditionally, bridge monitoring has been executed through on-site surveys. Although this method of bridge monitoring is systematic and successful, it is not the most efficient and cost-effective. Through technological advances, satellite-based Persistent Scatterer Interferometry (PSI) and Geographic Information Systems (GIS) have provided a system for analyzing ground deformation over time. This method is applied to distinguish bridges that are more at risk than others by generating models that display the displacement at various locations along each bridge. A bridge’s health and its potential risk can be estimated upon analysis of measured displacement rates. In return, this process of monitoring bridges can be done at much faster rates; saving time, money and resources. PSI data covering Oxnard, California, revealed both bridge displacement and regional ground displacement. Although each bridge maintained different patterns of displacement, many of the bridges within the Oxnard area displayed an overall downward movement matching regional subsidence trends observed in the area. Patterns in displacement-time series plots provide evidence for two types of deformation mechanisms. Long-term downward movements correlate with the relatively large regional subsidence observed using PSI in Oxnard. Thermal dilation from seasonal temperature changes may cause short-term variabilities unique to each bridge. Overall, it may be said that linking geologic, weather, and groundwater patterns with bridge displacement has shown promise for monitoring transportation infrastructure and more importantly differentiating between regional subsidence and site-specific displacements

Evaluation and Analysis of the Effectiveness of the Main Mitigation Measures against Surface Urban Heat Islands in Different Local Climate Zones through Remote Sensing

The significant transformation of land use as a consequence of current population growth, together with global warming (atmospheric emissions and extreme weather events), is generating increases in ambient temperatures. This circumstance is affecting people’s quality of life, especially those considered more vulnerable or with fewer economic resources. Currently, 30% of the world’s population suffers climatic conditions of extreme heat, and forecasts indicate that in the next 20 years, this number will reach 74%. The present study analyzes the effectiveness of the main mitigation strategies for the surface urban heat island (SUHI) effect between the years 2002 and 2022 in the different local climate zones of the city of Granada (Spain). Using Landsat 5 and 8 images, the evolution experienced by the land surface temperature and the surface urban heat island was determined and connected to the following variables: normalized difference vegetation index, vegetal proportion, normalized difference building index, and albedo. Our results indicate that compact and industrial areas have higher temperatures and lower vegetation and albedo in contrast to open areas, which have lower temperatures and higher vegetation and albedo. The mitigation measures analyzed presented similar efficiencies, but a greater minimization of the SUHI was reported when vegetation was increased in open areas as opposed to in closed areas, where the increase in albedo was more effective. Our study will allow the implementation of more efficient measures based on the types of LCZs in cities