Urbanization, economic development, and environmental changes in transitional economies in the global south: a case of Yangon.

Background: Transitional economies in Southeast Asia-a distinct group of developing countries-have experienced rapid urbanization in the past several decades due to the economic transition that fundamentally changed the function of their economies, societies and the environment. Myanmar, one of the least developed transitional economies in Southeast Asia, increased urbanization substantially from 25% in 1990 to 31% in 2019. However, major knowledge gaps exist in understanding the changes in urban land use and land cover and environment and their drivers in its cities. Methods: We studied Yangon, the largest city in Myanmar, for the urbanization, environmental changes, and the underlying driving forces in a radically transitioned economy in the developing world. Based on satellite imagery and historic land use maps, we quantified the expansion of urban built-up land and constructed the land conversion matrix from 1990 through 2020. We also used three air pollutants to illustrate the changes in environmental conditions. We analyzed the coupled dynamics among urbanization, economic development, and environmental changes. Through conducting a workshop with 20 local experts, we further analyzed the influence of human systems and natural systems on Yangon's urbanization and sustainability. Results: The city of Yangon expanded urban built-up land rapidly from 1990 to 2000, slowed down from 2000 to 2010, but gained momentum again from 2010 to 2020, with most newly added urban built-up land appearing to be converted from farmland and green land in both 1990-2000 and 2010-2020. Furthermore, the air pollutant concentration of CO decreased, but that of NO2 and PM2.5 increased in recent years. A positive correlation exists between population and economic development and the concentration of PM2.5 is highly associated with population, the economy, and the number of vehicles. Finally, the expert panel also identified other potential drivers for urbanization, including the extreme climate event of Cyclone Nargis, capital relocation, and globalization. Conclusions: Our research highlights the dramatic expansion of urban land and degradation of urban environment measured by air pollutants and interdependent changes between urbanization, economic development, and environmental changes.

Examining ground and surface water changes in response to environmental variables, land use dynamics, and socioeconomic changes in Canada.

Canada's abundant and high-quality water resources support a growing human population, as well as thriving industrial and agricultural economies. However, recent intense drought conditions have raised concerns for current water resource availability. Patterns of long-term ground and surface water (GSW) changes, and their response to environmental conditions, land-use dynamics, and socioeconomic changes are not well-understood across this large and diverse country. To address this crucial gap, we identified regions of ground and surface water (GSW) changes in all the Provinces of Canada between 2002 and 2016 from the Gravity Recovery and Climate Experiment (GRACE) and Global Land Data Assimilation System (GLDAS) datasets. We explored the relationships between GSW changes and environmental, socioeconomic, and land-use dynamics over time. We found that all the Provinces of Canada gained a net 4.46 mm Liquid Water Equivalent (LWE) per year, equivalent to a total increase of 66.9 mm LWE. GSW increases were significantly associated with the normalized difference vegetation index and evapotranspiration rates. In contrast, GSW declines were significantly related to deforestation rate, urban expansion, and economic development (median household income). Despite apparent widespread post-drought recovery detected from 2002 to 2016, the rapid GSW declines were also observed in almost all of Western Canada and part of Ontario, amounting to a net loss of 66.13 mm. This indicates that a pronounced drought had emerged. It is anticipated that Canada will be experiencing more frequent and severe droughts under ongoing climate change and increasing demand for water resources.

Spatiotemporal land use change and environmental degradation surrounding CAFOs in Michigan and North Carolina.

Concentrated Animal Feeding Operations (CAFOs) have arisen and expanded in the U.S. and globally to address efficiencies in livestock production. CAFOs tend to cluster in space for logistical purposes. Efficient distribution of concentrated manures produced by these operations is often not economically feasible, which may lead to accumulation on land near CAFOs, potentially resulting in local environmental changes. Moreover, as CAFOs are established or expand, they may need more lands to apply their manures, likely driving land use changes even after their establishment. Studies have yet to investigate these spatiotemporal impacts of CAFOs. We investigated whether the presence of regulated liquid waste CAFOs is associated with land use change over time and space as well as degraded environmental conditions surrounding those facilities. We used MODIS (Moderate Resolution Imaging Spectrometer) images from 2000 to 2018 to examine these questions in Michigan and North Carolina- states with varied CAFO establishment histories. We found that cropland extent increased while savanna and forest decreased near CAFOs. Similar observations did not occur outside of areas influenced by CAFOs. We also found evidence of environmental degradation, including decreased evapotranspiration and increased day and nighttime land surface temperatures in North Carolina. This study advances our understanding of environmental impacts surrounding CAFOs. Our findings can support policy changes and highlight the need to better understand these globally increasing entities.

Fine resolution air quality dynamics related to socioeconomic and land use factors in the most polluted desert metropolitan in the American Southwest.

Air pollution kills approximately 4.2 million people every year. As air pollution varies significantly in different urban areas, the assessment of urban emissions is key to taking appropriate actions and formulating policies for sustainable built environments and to promote the wellbeing of people. The overarching goal of this study was to generate fine resolution aerosol optical depth (AOD) using Landsat imagery and examine both the socioeconomic inequalities of air pollution exposure and the air quality variation related to different land-use categories. This study has focused on a period of unusual population growth, 2000-2010, in the Phoenix Metropolitan Area. It was found that socioeconomic factors, vegetation indexes, and land use land cover types are all strong predictors of AOD, and the negative coefficients of socioeconomic values reveal insight into the social inequality of air pollution exposure. Results suggest that the government regulation on air pollution during the study period helped to improve air quality. Meanwhile, planting vegetation to mitigate air pollution should be carefully examined in order to find the right vegetation species and spatial configuration of vegetation cover in urban settings.

Optimization of residential green space for environmental sustainability and property appreciation in metropolitan Phoenix, Arizona.

Cities in arid and semi-arid regions have been exploring urban sustainability policies, such as lowering the vegetation coverage to reduce residential outdoor water use. Meanwhile, urban residents express concerns that such policies could potentially impact home prices regardless of the reduced water costs because studies have shown that there is a positive correlation between vegetation coverage and home values. On the other hand, lower vegetation coverage in arid and semi-arid desert regions could increase surface temperatures, and consequently increases energy costs. The question is therefore where the point in which residential outdoor water use can be minimized without overly increasing surface temperatures and negatively impacting home values. This study examines the impacts of spatial composition of different vegetation types on land surface temperature (LST), outdoor water use (OWU), and property sales value (PSV) in 302 local residential communities in the Phoenix metropolitan area, Arizona using remotely sensed data and regression analysis. In addition, the spatial composition of vegetation cover was optimized to achieve a relatively lower LST and OWU and maintain a relatively higher PSV at the same time. We found that drought-tolerant landscaping that is composed of mostly shrubs and trees adapted to the desert environment is the most water efficient way to reduce LST, but grass contributes to a higher PSV. Research findings suggest that different residential landscaping strategies may be better suited for different neighborhoods and goal sets can be used by urban planners and city managers to better design urban residential landscaping for more efficient water conservation and urban heat mitigation for desert cities.

Repeated Hurricanes Reveal Risks and Opportunities for Social-Ecological Resilience to Flooding and Water Quality Problems.

Hurricanes that damage lives and property can also impact pollutant sources and trigger poor water quality. Yet, these water quality impacts that affect both human and natural communities are difficult to quantify. We developed an operational remote sensing-based hurricane flood extent mapping method, examined potential water quality implications of two "500-year" hurricanes in 2016 and 2018, and identified options to increase social-ecological resilience in North Carolina. Flooding detected with synthetic aperture radar (>91% accuracy) extended beyond state-mapped hazard zones. Furthermore, the legal floodplain underestimated impacts for communities with higher proportions of older adults, disabilities, unemployment, and mobile homes, as well as for headwater streams with restricted elevation gradients. Pollution sources were repeatedly affected, including ∼55% of wastewater treatment plant capacity and swine operations that generate ∼500 M tons/y manure. We identified ∼4.8 million km2 for possible forest and wetland conservation and ∼1.7 million km2 for restoration or altered management opportunities. The results suggest that current hazard mapping is inadequate for resilience planning; increased storm frequency and intensity necessitate modification of design standards, land-use policies, and infrastructure operation. Implementation of interventions can be guided by a greater understanding of social-ecological vulnerabilities within hazard and exposure areas.

Examining spatiotemporal salinity dynamics in the Mekong River Delta using Landsat time series imagery and a spatial regression approach.

Most coastal areas globally face water shortages in the dry season due to salinization and drought. The Mekong River Delta (MRD) is recognized as the "Rice Bowl" in Vietnam but the negative effects of salinization and drought have damaged rice production in recent decades. However, regional assessment of the perturbation has been lacking. A Landsat-based satellite salinity index, the Enhanced Salinity Index (ESI), was developed in this study to explore patterns of annual salinity variations in agricultural land and their relationship to drought in the MRD from 1989 to 2018. The performance of the index was superior to that of other previously published remotely sensed indices, based on correlations with field measurements of electrical conductivity (i.e. groundwater and soil EC), which can be used as a proxy for salinity. The time-series ESI was then utilized to explore the spatiotemporal dynamics of salinity in the study area using the Theil-Send median trend (TS) and Mann-Kendall significance tests (MK). In addition, temporal relationships with the Normalized Difference Water Index (NDWI) were used to investigate the relationship between drought and saline intrusion. Our results showed that freshwater and brackish areas increased inland, whereas those developed for shrimp farming may increase soil and groundwater salinity. A negative correlation between drought and salinity was also observed in surface water where fish and shrimp farming activities took place, while a positive relationship was discovered in rice and annual cropland areas. This study highlights the use of ESI as an effective parameter for modelling vegetation salinity and its relationship with cropland change. We also demonstrate the feasibility of integrating satellite imagery with spatiotemporal analyses to monitor and assess regional salinization dynamics.

Assessing environmental impacts and change in Myanmar's mangrove ecosystem service value due to deforestation (2000-2014).

Myanmar is one of the mangrove-richest countries in the world, providing valuable ecosystem services to people. However, due to deforestation driven primarily by agricultural expansion, Myanmar's mangrove forest cover has declined dramatically over the past few decades, while what remains is still under pressure. To support management planning, accurate quantification of mangrove forest cover changes on a national scale is needed. In this study, we quantified Myanmar's mangrove forest cover changes between 2000 and 2014 using remotely sensed data, examined the environmental impacts of such changes, and estimated the changes in the economic values of mangrove ecosystem services in the country. Results indicate that Myanmar had a net mangrove loss of 191,122 ha over the study period. Since 2000, Myanmar has been losing mangrove forest cover at an alarming rate of 14,619 ha/year (2.2%/year). The loss was predominant in Rakhine and Ayeyarwady. The observed mangrove forest cover loss has resulted in decreased evapotranspiration, carbon stock, and tree cover percentage. Due to deforestation, Myanmar also suffered a net loss of 2,397 million US$/year in its mangrove ecosystem service value (i.e. 28.7% decrease from 2000), in which maintenance of fisheries nursery populations and habitat and coastal protection were among those services that were greatly affected. We suggest that intensive reforestation and mangrove protection programs be implemented immediately. Agroforestry and community forestry programs are encouraged in areas that are under immense pressure from paddy field expansion, fuelwood extraction, charcoal production, and fish and shrimp farming activities. Potential alternative sustainable solutions should include intensive government-led private forest plantations or community-owned forest plantations to be developed with care by local farmers, nongovernmental organizations, and business owners.

Patterns of land change and their potential impacts on land surface temperature change in Yangon, Myanmar.

This study used remote sensing imagery to characterize land use/cover patterns and to derive land surface temperature (LST) of Greater Yangon, the largest urban agglomeration in Myanmar, to provide insights into the association between land use/cover and seasonal, daytime, and nighttime LST change. Analysis of Landsat images from 1987 to 2015 showed urban expansion radiating from the city center and along prominent rivers, with major increases in built-up land (6.4%) and grassland (10.1%) and consequent decline in agricultural land (17%). Examination of MODIS LST showed that agricultural land was warmer than the city core during daytime in hot seasons, while in cold seasons, the city core was warmer than its rural surroundings during both daytime and nighttime. Correlation analysis revealed stronger association between built-up land and nighttime LST from 2000 to 2015, suggesting an increased surface urban heat island effect. Furthermore, this study highlighted two main differences from prior work on the influences of land use/cover on LST. First, the predominant land use/cover type that had great overall impact on LST was agricultural land, marked by its statistically significant correlation coefficients across all time periods of analysis. Such finding emphasized the influence of agriculture and related practices on the atmosphere and climate system. Second, the temporal analysis of LST highlighted a stronger and more complicated role water played because of its negative correlations with daytime LST and positive correlations with nighttime LST. The findings of this study underscored more complex effects of land use/cover on the spatial and temporal variations of LST in Yangon, compared to prior work that generally reported high LST in the urban areas. These insights improve the understanding of the land change consequences on the temporal dynamics of LST and can support sustainable land use planning for the better well-being of the inhabitants in Greater Yangon.

Landscape determinants of spatio-temporal patterns of aerosol optical depth in the two most polluted metropolitans in the United States.

Elevated concentration of atmospheric aerosols during severe urban air pollution episodes necessitates a deep understanding of the underlying determinants for a sustainable urban environment. The 15-year (2001-2015) Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical depth (AOD) data for the Phoenix and Los Angeles Metropolitan Areas were applied to examine the spatio-temporal patterns and dynamics of urban aerosols. The strongly correlated temporal trends of AOD were observed due to the similar seasonal pattern of aerosol emissions and potential synoptic connections between two areas. Relatively higher mean value and lower decreasing trend of AOD were found in the PMA. Correlations reveal that topography is the predominant factor affecting the spatial pattern of AOD, as compared to the urban land use and vegetation. The effect of urbanization on air pollution varies with preexisting landscape, which apparently alleviates aerosol concentration in the PMA. Vegetation mitigates air pollution despite its emission of fine mode aerosols. As a cross-validation, the ground-measured concentrations of particulate matters (PM2.5 and PM10) were compared against AOD. The abnormal weak positive or strong negative AOD-PM2.5 associations result from the relatively small portion of anthropogenic aerosols and the changing atmospheric boundary layer height.

Effects of landscape composition and pattern on land surface temperature: An urban heat island study in the megacities of Southeast Asia.

Due to its adverse impacts on urban ecological environment and the overall livability of cities, the urban heat island (UHI) phenomenon has become a major research focus in various interrelated fields, including urban climatology, urban ecology, urban planning, and urban geography. This study sought to examine the relationship between land surface temperature (LST) and the abundance and spatial pattern of impervious surface and green space in the metropolitan areas of Bangkok (Thailand), Jakarta (Indonesia), and Manila (Philippines). Landsat-8 OLI/TIRS data and various geospatial approaches, including urban-rural gradient, multiresolution grid-based, and spatial metrics-based techniques, were used to facilitate the analysis. We found a significant strong correlation between mean LST and the density of impervious surface (positive) and green space (negative) along the urban-rural gradients of the three cities, depicting a typical UHI profile. The correlation of impervious surface density with mean LST tends to increase in larger grids, whereas the correlation of green space density with mean LST tends to increase in smaller grids, indicating a stronger influence of impervious surface and green space on the variability of LST in larger and smaller areas, respectively. The size, shape complexity, and aggregation of the patches of impervious surface and green space also had significant relationships with mean LST, though aggregation had the most consistent strong correlation. On average, the mean LST of impervious surface is about 3°C higher than that of green space, highlighting the important role of green spaces in mitigating UHI effects, an important urban ecosystem service. We recommend that the density and spatial pattern of urban impervious surfaces and green spaces be considered in landscape and urban planning so that urban areas and cities can have healthier and more comfortable living urban environments.

Size Matters: What Are the Characteristic Source Areas for Urban Planning Strategies?

Urban environmental measurements and observational statistics should reflect the properties generated over an adjacent area of adequate length where homogeneity is usually assumed. The determination of this characteristic source area that gives sufficient representation of the horizontal coverage of a sensing instrument or the fetch of transported quantities is of critical importance to guide the design and implementation of urban landscape planning strategies. In this study, we aim to unify two different methods for estimating source areas, viz. the statistical correlation method commonly used by geographers for landscape fragmentation and the mechanistic footprint model by meteorologists for atmospheric measurements. Good agreement was found in the intercomparison of the estimate of source areas by the two methods, based on 2-m air temperature measurement collected using a network of weather stations. The results can be extended to shed new lights on urban planning strategies, such as the use of urban vegetation for heat mitigation. In general, a sizable patch of landscape is required in order to play an effective role in regulating the local environment, proportional to the height at which stakeholders' interest is mainly concerned.

Examining the ecosystem health and sustainability of the world's largest mangrove forest using multi-temporal MODIS products.

Sweeping across Bangladesh and India, the Sundarbans forest is the world's largest contiguous mangrove forest. Although the human population density is high at the edge, Sundarbans has not encountered significant areal transformation in the last four decades. However, we argue that forest degradation can occur discontinuously within the forest without alteration of the entire forest area. In this paper, we used MODIS land products to compare the spatiotemporal ecological dynamics of the Bangladesh and Indian part of this mangrove forest between 2000 and 2010. We used the following 5 ecological parameters for our analysis: the Percent Tree Cover (PTC), Enhanced Vegetation Index (EVI), Net Primary Productivity (NPP), Leaf Area Index (LAI), and Evapotranspiration (ET). Our pixel-based time-series trend analysis for each MODIS image stack, using an ordinary least square (OLS) regression method, showed that forest degradation is happening in fragmented parcels within the forest. The degradation rate is comparatively higher in the Bangladesh part than in the Indian part of Sundarbans. Compartments 8, 10, 12, and 15 in the Bangladesh part, in particular, show high degradation, while compartment 48 and the southern edge of 45 show slight increases in PTC or EVI. Forest degradation in the Indian part of the forest is evident in the National Park and Reserve Forest blocks; however, no substantial degradation is evident in the western section. We have identified certain anthropogenic stressors (i.e., oil pollution, shrimp farming) and natural stressors (i.e., increased salinity, cyclones, forest fire) which might be responsible for the observed degradation. We have provided sustainable planning options and policy transformation alternatives for those areas under pressure from these stressors. We anticipate that our analysis of forest degradation will help management agencies, conservators, and policy makers achieve better management of this world's largest mangrove forest for a sustainable future.

Quantifying outdoor water consumption of urban land use/land cover: sensitivity to drought.

Outdoor water use is a key component in arid city water systems for achieving sustainable water use and ensuring water security. Using evapotranspiration (ET) calculations as a proxy for outdoor water consumption, the objectives of this research are to quantify outdoor water consumption of different land use and land cover types, and compare the spatio-temporal variation in water consumption between drought and wet years. An energy balance model was applied to Landsat 5 TM time series images to estimate daily and seasonal ET for the Central Arizona Phoenix Long-Term Ecological Research region (CAP-LTER). Modeled ET estimations were correlated with water use data in 49 parks within CAP-LTER and showed good agreement (r² = 0.77), indicating model effectiveness to capture the variations across park water consumption. Seasonally, active agriculture shows high ET (>500 mm) for both wet and dry conditions, while the desert and urban land cover types experienced lower ET during drought (<300 mm). Within urban locales of CAP-LTER, xeric neighborhoods show significant differences from year to year, while mesic neighborhoods retain their ET values (400-500 mm) during drought, implying considerable use of irrigation to sustain their greenness. Considering the potentially limiting water availability of this region in the future due to large population increases and the threat of a warming and drying climate, maintaining large water-consuming, irrigated landscapes challenges sustainable practices of water conservation and the need to provide amenities of this desert area for enhancing quality of life.

Comparison of Remote Sensing Image Processing Techniques to Identify Tornado Damage Areas from Landsat TM Data.

Remote sensing techniques have been shown effective for large-scale damagesurveys after a hazardous event in both near real-time or post-event analyses. The paperaims to compare accuracy of common imaging processing techniques to detect tornadodamage tracks from Landsat TM data. We employed the direct change detection approachusing two sets of images acquired before and after the tornado event to produce a principalcomponent composite images and a set of image difference bands. Techniques in thecomparison include supervised classification, unsupervised classification, and object-oriented classification approach with a nearest neighbor classifier. Accuracy assessment isbased on Kappa coefficient calculated from error matrices which cross tabulate correctlyidentified cells on the TM image and commission and omission errors in the result. Overall,the Object-oriented Approach exhibits the highest degree of accuracy in tornado damagedetection. PCA and Image Differencing methods show comparable outcomes. Whileselected PCs can improve detection accuracy 5 to 10%, the Object-oriented Approachperforms significantly better with 15-20% higher accuracy than the other two techniques.