Future Urban Expansion Research Articles

A Comprehensive Review on Land Use/Land Cover (LULC) Change Modeling for Urban Development: Current Status and Future Prospects

Land use land cover (LULC) modeling is considered as the best tool to comprehend and unravel the dynamics of future urban expansion. The present paper provides a comprehensive review of existing LULC modeling techniques and novel approaches used by the research community. Moreover, the review also compares each technique’s applications, utility, drawbacks, and broader differences. The rationale behind such a comparison is to highlight the strengths/weakness of individual techniques. The review further highlights the utility of the hybridization of different techniques (e.g., machine learning model combined with statistical models) to LULC modeling to complement their strengths. Although significant progress has been made in LULC modeling, the review highlights the need to incorporate the policy framework into LULC modeling for better urban planning and management. The present review will help researchers and policymakers to achieve better land management practices and ultimately assist in achieving Sustainable Development Goal-15 (SDG-15) (i.e., life on land).

Impacts of global urban expansion on natural habitats undermine the 2050 vision for biodiversity

Urban expansion can impact natural habitats by changing land covers, and then threatening biodiversity. Assessing the impacts of future urban expansion on natural habitats is fundamental for achieving the 2050 Vision for Biodiversity of living in harmony with nature. Here, we simulated the global urban expansion from 2016 to 2050 and assessed its impacts on natural habitats at the global, biome and ecoregion scales. We projected that urban land will increase by 280 - 490 thousand km2 from 2016 to 2050, resulting in a loss of 110 - 190 thousand km2 of natural habitats globally. Such loss will affect the threatened species, resulting in nearly 40% of ecoregions (310/825) may fail to achieve the 2050 Biodiversity Conservation Goal in the future. We suggested that special attention should be paid to biodiversity conservation at the ecoregion scale instead of mainly at global or national scale.

Prediction of land use changes at a metropolitan city using integrated cellular automata: past and future

ABSTRACT In the cities of developing countries like India, rapid and uncontrolled urbanization has been taking place due to continuous population growth in last few decades. As a result, land use/land cover (LU/LC) is changing very fast in the cities of developing countries. Therefore, this study aims to examine the changes in LU/LC pattern in Delhi during 1991–2018 and simulate the future LU/LC pattern of Delhi for 2030. The LU/LC pattern mapping was done from Landsat datasets using k-means clustering technique. The cellular automata (CA) technique was integrated with artificial neural network (ANN) for simulating the future LU/LC patterns. The projected LU/LC pattern shows that Delhi’s built-up area will increase to nearly 60% of the total area of city, while cropland and open land will decrease to 19.86 and 0.15%, respectively. The highest increase in built-up area was observed in the northern, western, and south-western sub-districts of Delhi. Outcomes of the study may be used for future land use planning in Delhi and other cities. In addition, they can also provide valuable insights for the development of transportation network and other facilities and amenities in the areas of future urban expansion.

Evaluating the influences of urban expansion on multiple ecosystem services in drylands

ContextEffectively estimating the influences of urban expansion on multiple ecosystem services (ESs) is of great importance for improving urban planning in drylands. However, there are some shortcomings in the existing urban expansion models, which lead to great uncertainties in the assessment of the influences of urban expansion on multiple ESs.ObjectivesThis study sought to effectively estimate the influences of urban expansion on multiple ESs in drylands.MethodsWe combined the land use scenario dynamics-urban model and ES models to estimate the influences of urban expansion on habitat quality, food production, water retention, air quality regulation, sand fixation, and aesthetics.ResultsThe results showed that (1) our method can effectively evaluate the influences of urban expansion on multiple ESs in drylands, and the accuracy increased by more than 20% on average. (2) Under the impacts of future urban expansion, the annual average loss per unit area of habitat quality, food production, water retention, air quality regulation, sand fixation, and aesthetics will increase. (3) Future urban expansion will occupy more cropland and grassland, which will be the main reason for the intensified degradation of multiple ESs.ConclusionsWe suggest that the local government should focus on protecting key ecosystems, especially grasslands, from urban expansion to mitigate the potential influences on multiple ESs in drylands.

Simulation of urban land expansion in China at 30 m resolution through 2050 under shared socioeconomic pathways

ABSTRACT Rapid urbanization has profoundly impacted social and environmental systems. China is the world’s largest developing country. Projecting future urban expansion in China is critical to alleviate any adverse impacts and achieve sustainable development goals. However, the existing national-scale urban expansion simulations at low or medium resolutions produce significant distortions in urban spatial patterns, limiting the utility of future projections. High-resolution simulation of urban expansion is challenging on a large scale owing to high computational demands. In this study, we used a high-performance cellular automata model (Tensor-FLUS) to simulate the urban expansion of China from 2015 to 2050, at 30 m spatial resolution, under shared socioeconomic pathways. The high-resolution (30 m) urban expansion simulations preserve greater spatial details and avoid 34.07–37.60% underestimation of the urban area, compared with simulation at 1 km resolution. The environmental impact assessments revealed that future urban expansion mainly encroaches on cropland (88.00–88.29%), with a greater likelihood of occupying productive cropland, placing substantial pressure on food production. Although the proportion of occupied natural land is relatively small (11.32–11.60%), newly expanded urban areas will tend to consume woodland and grassland of high ecological value, leading to profound impacts on the ecosystem. In general, the produced high-resolution future simulations can reduce the uncertainty of environmental impact assessment at the national scale. Furthermore, it can provide consistent projection data for research at the provincial or metropolitan scales to support urban planning and local climate change mitigation.

An integrated modeling approach for ecological risks assessment under multiple scenarios in Guangzhou, China

High-intensity human activities have caused dramatic changes in land-use structure in Guangzhou. It is essential to understand the spatiotemporal dynamics of land use and the induced ecological risks. In this research, a framework was developed for landscape ecological risk (LER) prediction based on a patch-generating land use simulation (PLUS) model through incorporating analysis of land expansion strategies, CA model based on multi-type random patch seeds and LER assessment model. The results showed: 1) the urbanization process of Guangzhou was obvious in the past 20 years. Proximity to railways, highways, and secondary roads have the primary impact on the expansion of cultivated land, grassland and construction land, respectively, 2) Guangzhou's future urban expansion is inevitable based on the PLUS model prediction, 3) during 2000–2020, the overall LER in Guangzhou was at a relatively low level. The higher ecological risk area was mainly distributed in the southern sea area, and 4) from 2020 to 2040, Guangzhou's higher ecological risk areas are on an overall decreasing trend under three scenarios. This research can provide a reference for the planning of regional ecological environmental protection and sustainable development of land resources, as well as LER prediction.

Flood Susceptibility Assessment in Arid Areas: A Case Study of Qatar

Over the past decade, the adverse impacts of climate change and excessive urbanization have contributed to several unfamiliar and costly floods in the Gulf Cooperation Council (GCC), especially in Qatar. With limited historical rainfall records and unprecedented precipitation intensities impacting the efficiency of hydrological models, the multi-criteria decision analysis (MCDA) presents a suitable alternative approach to assess and identify flood-susceptible areas. In this study, we applied MCDA to several factors that contribute to flood susceptibility, namely: elevation, slope, groundwater depth, distance to a drainage system, and land use. These criteria were assigned different weights based on their contribution and previous literature and later underwent a sensitivity analysis. The study’s results correlate well with recent flooding events, proving the method’s efficiency in identifying hotspots. This study is expected to provide a rapid tool to support the decision-making process for future urban expansion, sustainable development, and resilience planning in Qatar.

The Impact of Urbanization Growth Patterns on Carbon Dioxide Emissions: Evidence from Guizhou, West of China

Little attention has been paid to the impact of future urban expansion patterns on carbon emissions based on the existing urban pattern of a region. This study used the Central Guizhou Urban Agglomeration as the study area, and the relationships between regional urbanization and CO2 emissions in the study area were analyzed based on historical data. Urban growth patterns were then simulated in four scenarios that focused on the next 15 years, and they were based on the cellular automaton model. In each different scenario, the CO2 emissions were predicted, and some implications regarding the impact of those emissions were provided. The results showed that as urban land-use intensity increases, CO2 emissions first increase then decrease; however, the rate of decline for CO2 emissions is much slower than the rate at which it rises. Moreover, in the next 15 years, urban expansion will lead to a significant increase in CO2 emissions. The CO2 emissions were found to be lowest in the spatial agglomeration scenario and highest in the spatial dispersion scenario. The spatial agglomeration scenario was conducive to understanding how CO2 emissions eventually peak; however, different cities in the study area should adopt different urban expansion patterns. These research results can provide a reference guide for the government with regard to urban planning.

Impact of climate change on catchment nutrient dynamics: insights from around the world

This study is a meta-analysis of global articles on hydrological nutrient dynamics to determine trends and consensus on: (1) the effects of climate change-induced hydrological and temperature drivers on nutrient dynamics and how these effects vary along the catchment continuum from land to river to lake; (2) the convergence of climate change impacts with other anthropogenic pressures (agriculture, urbanization) in nutrient dynamics; and (3) regional variability in the effects of climate change on nutrient dynamics and water-quality impairment across different climate zones. An innovative web crawler tool was employed to help critically synthesize the information in the literature. The literature suggests that climate change will impact nutrient dynamics around the globe and exacerbate contemporary water-quality challenges. Nutrient leaching and overland flow transport are projected to increase globally, promoted by extreme precipitation. Seasonal variations in streamflow are expected to emulate changing precipitation patterns, but the specific local impacts of climate change on hydrology and nutrient dynamics will vary both seasonally and regionally. Plant activity may reduce some of this load in nonagricultural soils if the expected increase in plant uptake of nutrients prompted by increased temperatures can compensate for greater nitrogen (N) and phosphorus (P) mineralization, N deposition, and leaching rates. High-temperature forest and grass fires may help reduce mineralization and microbial turnover by altering N speciation via the pyrolysis of organic matter. In agricultural areas that are at higher risk of erosion, extreme precipitation will exacerbate existing water-quality issues, and greater plant nutrient uptake may lead to an increase in fertilizer use. Future urban expansion will amplify these effects. Higher ambient temperatures will promote harmful cyanobacterial blooms by enhancing thermal stratification, increasing nutrient load into streams and lakes from extreme precipitation events, decreasing summer flow and thus baseflow dilution capacity, and increasing water and nutrient residence times during increasingly frequent droughts. Land management decisions must consider the nuanced regional and seasonal changes identified in this review (realized and predicted). Such knowledge is critical to increasing international cooperation and accelerating action toward the United Nations’s global sustainability goals and the specific objectives of the Conference of Parties (COP) 26.

Projections of urban built-up area expansion and urbanization sustainability in China's cities through 2030

In the context of socioeconomic initiatives to address world development sustainability such as the Sustainable Development Goals (SDGs), China's urbanization with increasing intensity and quickening pace has always been central to debates over the past few decades. Although the United Nations (UN) recommend to estimate and predict the local-scale urbanization sustainability by using the SDG indicator 11.3.1: “ratio of land consumption rate to population growth rate (LCRPGR)”, there remains a lack of reliable projections and applicable assessments at the city level, especially for the future urban expansion. Until now, limited knowledge of the urbanization sustainability dynamics in the next decade has been the primary challenge to inform the realization of urban sustainable development goal under the framework of SDGs. To evaluate the geographic region- and population size-specific urbanization sustainability at the city level in mainland China between 2020 and 2030, an integrated downscaling approach of trend extrapolation and regression analysis was developed based on historical statistics of urban built-up area and subnational scenarios of population and gross domestic product (GDP) under the Shared Socioeconomic Pathways (SSPs). The SSPs-consistent urban built-up area projections across different scales showed that the logistic regression had a better modeling performance than the panel data regression, while there was little difference between the linear and exponential extrapolation methods. Despite the geographical heterogeneity and size-related disparity, the scenario modeling results suggested that the average value of LCRPGR indicator in mainland China was expected to decline continuously, and would reach at the ideal state with a coordination between urban expansion and population growth through 2030. Specifically, the population growth stagnation of cities in Northeast China and the allometric urban expansion of cities in Western China should be the focus of strengthened regulations, and the urban growth of megacities would experience a steady and slower trend compared to their surrounding super-large cities and large cities. In summary, China's urbanization process might have headed toward a more sustainable and coordinated future under feasible SSPs scenarios. The local-scale forecasts will not only fill the data gap of SSPs-consistent urban land demand for all county- and prefecture-level cities in mainland China, but can also provide a reference for forecasting and assessment of urbanization sustainability to meet the SDGs in urban areas such as indicator 11.3.1.

Geospatial modelling of the future urban expansion map using AHP and GIS in Bordj Bou Arreridj, Algeria

The study aimed to determine the areas of future urban expansion in Bordj Bou Arreridj, Algeria, by using multi-criteria analysis for decision-making. First, the future population was estimated to calculate the area we would need for the horizon of 2041AD. Second, criteria that contribute to determining the best areas for future expansion were selected based on recent research literature. Six factors were adopted: (industrial areas, agricultural lands, urban areas, road network, slopes, and hydrographic network). Third, the analytic hierarchy process (AHP) was used to make a comparison of the previous standards and to extract the weights. Fourth, translating the results obtained in the (QGIS) program and extracting a digital map showing areas suitable for future urban expansion according to three classifications (high spatial suitability, acceptable, and low). The results showed that the areas with high spatial suitability it densely distributed in the northeastern and western directions with an area of 12.42 km² or 23%. It is considered an insufficient area to meet the future need of 2041 AD, which amounted to 14.20 km². Followed by areas with acceptable suitability distributed in four geographical directions, occupying an area of 15.67 km² or 35%, which is a sufficient area and can be placed as a balance to fill the deficit. While the areas with low suitability densely distributed in the east-west sides, with an area of 16.26 km² or 37%. The research proved that the integration between (AHP) and (GIS) technologies have an important role in helping decision-makers identify suitable areas for future expansion, reduce the problems of random urbanization and create a homogeneous sustainable environment. Urban development in the future.

Future land-use competition constrains natural climate solutions

Natural climate solutions (NCS) are an essential complement to climate mitigation and have been increasingly incorporated into international mitigation strategies. Yet, with the ongoing population growth, allocating natural areas for NCS may compete with other socioeconomic priorities, especially urban development and food security. Here, we projected the impacts of land-use competition incurred by cropland and urban expansion on the climate mitigation potential of NCS. We mapped the areas available for implementing 9 key NCS strategies and estimated their climate change mitigation potential. Then, we overlaid these areas with future cropland and urban expansion maps projected under three Shared Socioeconomic Pathway (SSP) scenarios (2020-2100) and calculated the resulting mitigation potential loss of each selected NCS strategy. Our results estimate a substantial reduction, 0.3–2.8 GtCO2 yr−1 or 4–39 %, in NCS mitigation potential, of which cropland expansion for fulfilling future food demand is the primary cause. This impact is particularly severe in the tropics where NCS hold the most abundant mitigation potential. Our findings highlight immediate actions prioritized to tropical areas are important to best realize NCS and are key to developing realistic and sustainable climate policies.

Delimiting China's Urban Growth Boundaries Under Localized Shared Socioeconomic Pathways and Various Urban Expansion Modes

AbstractDelimiting the urban growth boundary (UGB) is important for limiting urban sprawl and improving urban sustainability. However, the future UGB delimitation for the entire China is still lacking. Here, we delimited China's UGBs before 2100 under localized shared socioeconomic pathways and 11 urban expansion modes (i.e., spontaneous growth, organic growth, and nine modes integrating both) and evaluated the urban shrinkage pressure and the effects on other land use/cover types and ecosystem services. The results revealed that China's urban land demand was projected to increase first and then decrease under five scenarios before 2100. The extent of UGBs was projected to be 121,199–142,982 km2, 34.14–58.25% higher than the urban area in 2020. As a result of urban population decline, China's urban land demand in 2100 was projected to be 20.83–53.41% lower than the extent of UGBs, implying that China, especially the three provinces of Heilongjiang, Jilin, and Liaoning, will face remarkable urban shrinkage pressure. Future urban expansion in China will mainly occupy cropland, and lead to a simultaneous decline in habitat quality, food production and carbon sequestration. Spontaneous growth will cause greater losses of ecosystem services than organic growth at the national scale, while in some provinces, such a difference will be reversed. To address the urban shrinkage pressure, China needs to control urban area and optimize urban spatial patterns based on UGBs. In addition, the place‐based optimal urban expansion mode is also required to reduce the negative impacts of future urban expansion on ecosystem services and promote sustainable development.

Examining the Use of Urban Growth Boundary for Future Urban Expansion of Chattogram, Bangladesh

With the rapid and unregulated nature of urban expansion occurring in Chattogram, Bangladesh, the adoption of urban growth restriction mechanisms such as the urban growth boundary (UGB) can provide a robust framework necessary to direct the development of built-up areas in a way that curtails the growth in environmentally sensitive areas of the city. Using a support vector machine (SVM)-based urban growth simulation model, this paper examines the areas of future contiguous expansion of the city to aid in the delineation of the UGB. Utilizing landcover, topographic, and population density data from a variety of sources for the past twenty years, the SVM method with the radial basis function (RBF) kernel is used to develop a model based on fourteen predictor variables. A grid-search is used to tune the hyperparameters and determine the best performance combination of the hyperparameters for the RBF kernel function used in the SVM. The final SVM model using the best performance combination of the hyperparameters indicates a high percentage agreement of 91.79% and a substantial agreement for the Kappa coefficient of 0.7699. The developed SVM simulation model identifies potential areas that are more likely to undergo urban expansion in Chattogram in the next twenty years and provides aids for a stringent and strict delineation of UGB for this region.

Global impacts of future urban expansion on terrestrial vertebrate diversity

Rapid urban expansion has profound impacts on global biodiversity through habitat conversion, degradation, fragmentation, and species extinction. However, how future urban expansion will affect global biodiversity needs to be better understood. We contribute to filling this knowledge gap by combining spatially explicit projections of urban expansion under shared socioeconomic pathways (SSPs) with datasets on habitat and terrestrial biodiversity (amphibians, mammals, and birds). Overall, future urban expansion will lead to 11–33 million hectares of natural habitat loss by 2100 under the SSP scenarios and will disproportionately cause large natural habitat fragmentation. The urban expansion within the current key biodiversity priority areas is projected to be higher (e.g., 37–44% higher in the WWF’s Global 200) than the global average. Moreover, the urban land conversion will reduce local within-site species richness by 34% and species abundance by 52% per 1 km grid cell, and 7–9 species may be lost per 10 km cell. Our study suggests an urgent need to develop a sustainable urban development pathway to balance urban expansion and biodiversity conservation.

Three-Dimensional Simulation Model for Synergistically Simulating Urban Horizontal Expansion and Vertical Growth

Urban expansion studies have focused on two-dimensional planar dimensions, ignoring the impact of building height growth changes in the vertical direction on the urban three-dimensional (3D) spatial expansion. Past 3D simulation studies have tended to focus on simulating virtual cities, and a few studies have attempted to build 3D simulation models to achieve the synergistic simulation of real cities. This study proposes an urban 3D spatial expansion simulation model to achieve a synergistic simulation of urban horizontal expansion and vertical growth. The future land use simulation model was used to simulate urban land use changes in the horizontal direction. The random forest (RF) regression algorithm was used to predict building height growth in the vertical direction. Furthermore, the RF algorithm was used to mine the patterns of spatial factors affecting building heights. The 3D model was applied to simulate 3D spatial changes in Shenzhen City from 2014 to 2034. The model effectively simulates the horizontal expansion and vertical growth of a real city in 3D space. The crucial factors affecting building heights and the simulation results of future urban 3D expansion hotspot areas can provide scientific support for decisions in urban spatial planning.

China’s Socioeconomic and CO2 Status Concerning Future Land-Use Change under the Shared Socioeconomic Pathways

China has experienced a huge socioeconomic advancement over the past few decades, resulting in great change in land use and land cover. To date, negligible attention has been given to examining the socioeconomic changes in the context of land-use change, especially from a futuristic standpoint. However, motivated by China’s latest carbon neutrality target, this study analyzes the prospective changes in socioeconomic status, and carbon dioxide emission in the context of future land-use change, focusing on three future periods: 2026–2030 (carbon dioxide peak phase), 2056–2060 (carbon-neutral phase), and 2080–2099 (long-term period). In this regard, recently published land-use products under seven Shared Socioeconomic Pathways-based scenarios (SSP1-1.9, SSP1-2.6, SSP4-3.4, SSP2-4.5, SSP4-6.0, SSP3-7.0, and SSP5-8.5) as part of the CMIP6, as well as the projected GDP and population under five socioeconomic scenarios are used. To estimate socioeconomic change over prominent land-use types (urban), we combined five socioeconomic scenarios with seven corresponding SSPs-based land-use change scenarios (SSP1 with SSP1-1.9 and SSP1-2.6; SSP2 with SSP2-4.5; SSP3 with SSP3-7.0; SSP4 with SSP4-3.4 and SSP4-6.0; and SSP5 with SSP5-8.5 scenarios). Our results reveal that rapid urban land expansion in the future is the most dominant aspect in China. In the carbon neutrality phase (2056–2060), urban land is expected to expand ~80% more than that of the reference period (1995–2014). In the spatial aspect, the expansion of urban land is mainly prominent in the eastern and central parts of China. For socioeconomic changes, the most prominent increase in the urban population is estimated at 630.8% under SSP5-8.5 for the 2056–2060 period compared to the reference period. Regarding GDP for the urban area, industrial GDP will be higher than service GDP in the carbon emission peak phase (2026–2030), but it is projected to be overtaken by service GDP for the carbon-neutral target (2056–2060) and long-term periods (2080–2099). Further, the CO2 emission in China was found to increase with intensified urban land for the historical period (1995–2019). In the future, the largest increase in CO2 emission from the urban area is anticipated under SSP5-8.5 in the carbon-neutral target (2056–2060) phase, while CO2 emission will largely decline after (2056–2060) under SSP1-1.9, SSP1-2.6, and SSP4-3.4. Importantly, population change is expected to be the most predominant factor in future urban land expansion in China. These findings highlight the importance of well-governed urban-land development as a key measure to achieve China’s carbon neutrality goal.

Urban simulation incorporating coordination relationships of multiple ecosystem services

● A cellular automata model incorporating ecosystem service interactions is developed ● Future urban expansion under influence of ecosystem service interaction is simulated ● The improved model better captures ES relationship changes caused by urban expansion ● Multi-level ES protection mechanism is highly recommended in spatial planning Rapid urbanization evidently affected ecosystem service provisions. Although numerous models have incorporated ecosystem services into land use decisions, most of them typically ignored the interactions between multiple ecosystem services (MES), as well as their impact on future urban expansion. Here, we propose a novel urban simulation model based on the integration of the coupling coordination evaluation of MES and cellular automata. The Wuhan Metropolitan Area was selected to test the model. Six conservation scenarios at different ecological coupling coordination levels were designed to predict urban expansion in 2030 and examine how ES interactions impact urban expansion modes. The results showed that the proposed model has an accuracy of 84.01% and can better capture the changes in MES interactions caused by urban expansion. A significantly negative correlation exists between the coupling coordination degree of MES and urban expansion, with a decreased coefficient from -0.924 to -0.945 during the period of 2010-2015. Our results also suggest that single conservation scenario may be inadequate to coordinate MES and urban expansion, which necessitates a comprehensive ecological protection mechanism in spatial planning. The proposed model can provide better understanding of relationships between MES interactions and urban expansion, and help planners to generate sustainable urban development policies.

Modeling direct above-ground carbon loss due to urban expansion in Zanzibar City Region, Tanzania

Abstract Expansion of urban fabric on carbon storages is estimated to cause loss of 1.38 Pg of Above-Ground Carbon (AGC) in pan-tropics between 2000 and 2030. This would be approximately 5% of all emissions caused by tropical land use changes. Despite the significance of the phenomenon, these emissions are rarely measured, monitored, or addressed in climate change mitigation plans, especially in Sub-Saharan Africa. Therefore, we demonstrated a state-of-the-art approach predicting AGC loss of Zanzibar City Region under multiple alternative urban planning scenarios between 2013 and 2030. The AGC information was modeled based on field measured forest inventory sample plots and RapidEye satellite data from 2013, while the future urban expansion model was calibrated with data of happened expansion between 2004, 2009 and 2013, and geospatial independent variables influencing the expansion patterns. This model was then projected until 2030, while alternative urban planning scenarios were integrated to the model by modifying the geospatial variables. The combination of these two models indicates that 42,000 Mg or 15% of total AGC in Zanzibar City Region can be anticipated to be lost by 2030 due to urban expansion. Majority of the loss will take place in the agroforest and fruit tree plantations surrounding the city, while natural forest face limited impacts. None of the tested alternative urban planning scenarios significantly impact the loss of AGC compared to the business-as-usual scenario. Therefore, alternative policies and plans are seriously needed to address the issue in Zanzibar. These could include promoting urban densification, directing urban expansion to low carbon areas, improving soil carbon management, and preparing an urban forestry and greenery strategy. All in all, the study indicates that data and methods are available for monitoring and predicting the phenomenon in Sub-Saharan Africa. Research based on a comparable methodology should be produced from all the main cities in the region that are surrounded by significant carbon storages and facing high urban expansion rates to support climate change mitigation.

Modeling direct above-ground carbon loss due to urban expansion in Zanzibar City Region, Tanzania

Expansion of urban fabric on carbon storages is estimated to cause loss of 1.38 Pg of Above-Ground Carbon (AGC) in pan-tropics between 2000 and 2030. This would be approximately 5% of all emissions caused by tropical land use changes. Despite the significance of the phenomenon, these emissions are rarely measured, monitored, or addressed in climate change mitigation plans, especially in Sub-Saharan Africa. Therefore, we demonstrated a state-of-the-art approach predicting AGC loss of Zanzibar City Region under multiple alternative urban planning scenarios between 2013 and 2030. The AGC information was modeled based on field measured forest inventory sample plots and RapidEye satellite data from 2013, while the future urban expansion model was calibrated with data of happened expansion between 2004, 2009 and 2013, and geospatial independent variables influencing the expansion patterns. This model was then projected until 2030, while alternative urban planning scenarios were integrated to the model by modifying the geospatial variables. The combination of these two models indicates that 42,000 Mg or 15% of total AGC in Zanzibar City Region can be anticipated to be lost by 2030 due to urban expansion. Majority of the loss will take place in the agroforest and fruit tree plantations surrounding the city, while natural forest face limited impacts. None of the tested alternative urban planning scenarios significantly impact the loss of AGC compared to the business-as-usual scenario. Therefore, alternative policies and plans are seriously needed to address the issue in Zanzibar. These could include promoting urban densification, directing urban expansion to low carbon areas, improving soil carbon management, and preparing an urban forestry and greenery strategy. All in all, the study indicates that data and methods are available for monitoring and predicting the phenomenon in Sub-Saharan Africa. Research based on a comparable methodology should be produced from all the main cities in the region that are surrounded by significant carbon storages and facing high urban expansion rates to support climate change mitigation.