Spatio-Temporal Urban Land Use/Cover Change Analysis in a Hill Station: The Case of Baguio City, Philippines

AbstractThis study explores the spatial and temporal characteristics of land use/cover (LUC) changes in Baguio city, the only American hill station in Asia and the summer capital of the Philippines. Remote sensing (RS) satellite images were used to develop the 1988, 1998, and 2009 LUC maps of the city in a Geographic Information Systems (GIS) platform. Results reveal that the city has undergone a major physical landscape transformation for the last 21 years as indicated by a rapid built-up area expansion and substantial changes in its other land uses/covers. This study also analyzes the spatial pattern of urban growth in Baguio city. Furthermore, it presents insights in planning for the future sustainable urbanization of this highly valued city

〈Original Papers〉Measurement of urban built-up volume using remote sensing data and geospatial techniques

The vertical analysis is becoming more important to capture rapid changes in urban growth. It helps to measure the urban intensity of complex urban land use pattern. The development of geospatial technology provides a sophisticated methodology to examine the changing urban environment. At present, the satellite images of medium resolution including ALOS PRISM DSM have become more popular due to the availability and vast range of coverage. The grid-based method has been used to obtain the urban volume (UV) with the surface feature height (SFH) which was extracted from the difference between digital terrain model (DTM) and digital surface model (DSM). In this study, an attempt was made to develop a new method to generate DTM based on ALOS PRISM DSM by using buffer distance from building footprint data. The buffer distances of 5 m, 10 m, and 15 m were used to select minimum DSM points generated by the grid-based method. The selected points were used to produce DTM by employing empirical Bayesian Kriging surface interpolation method. The SFH derived from the 10 m buffer zone of each building showed the lowest rootmean-square error (RMSE). This modified approach is valuable to grasp changing urban dynamics

〈Research Reports〉Spontaneous simulation of land surface temperature in Tianjin city, China

Monitoring and simulating land surface temperature (LST) by using satellite images is an essential approach to understand land use/cover changes, especially in developing countries where the availability of ground truth and statistical data is limited. This study analyzed the relationship between LST and land use/cover types in Tianjin city from 2005 to 2015. Then, based on the LST distribution maps, we simulated LST in 2025 by employing a hybrid model of the artificial neural network and the cellular automata. The results show that the LST is gradually increasing from 2005 to 2025 with the changes in the land use/cover. This study provides significative information for sustainable development and environmental protection in the future

Land evaluation for peri-urban agriculture using analytical hierarchical process and geographic information system techniques: A case study of Hanoi

This paper presents an integrated technique of analytical hierarchical process (AHP) and geographic information system (GIS) to evaluate the land for peri-urban agriculture. Hanoi province, Vietnam was selected for the case study. Transformation of conventional agriculture to modern cash crops is the current trend in peri-urban Hanoi. A field survey with focused group discussions was conducted. Based on field survey data analysis, soil, land use, water resources, road network and market were chosen as major factors affecting the peri-urban agriculture. A map of each factor with different logical criteria was prepared. The AHP method was applied to identify the priority weight of each factor. Five spatial layers with their corresponding weights were linearly combined to prepare the suitability map. The map was further scaled as high suitable, medium suitable, low suitable and unsuitable land for the peri-urban agriculture. This empirical scenario provides a cost effective, rapid land evaluation framework which may help policy makers, urban and regional planners and researchers working in developing countries

Spatiotemporal Simulation of Future Land Use/Cover Change Scenarios in the Tokyo Metropolitan Area

Simulating future land use/cover changes is of great importance for urban planners and decision-makers, especially in metropolitan areas, to maintain a sustainable environment. This study examines the changes in land use/cover in the Tokyo metropolitan area (TMA) from 2007 to 2017 as a first step in using supervised classification. Second, based on the map results, we predicted the expected patterns of change in 2027 and 2037 by employing a hybrid model composed of cellular automata and the Markov model. The next step was to decide the model inputs consisting of the modeling variables affecting the distribution of land use/cover in the study area, for instance distance to central business district (CBD) and distance to railways, in addition to the classified maps of 2007 and 2017. Finally, we considered three scenarios for simulating land use/cover changes: spontaneous, sub-region development, and green space improvement. Simulation results show varied patterns of change according to the different scenarios. The sub-region development scenario is the most promising because it balances between urban areas, resources, and green spaces. This study provides significant insight for planners about change trends in the TMA and future challenges that might be encountered to maintain a sustainable region

Scenario-Based Simulation of Tianjin City Using a Cellular Automata–Markov Model

Rapid urbanization is occurring throughout China, especially in megacities. Using a land use model to obtain future land use/cover conditions is an essential method to prevent chaotic urban sprawl and imbalanced development. This study utilized historical Landsat images to create land use/cover maps to predict the land use/cover changes of Tianjin city in 2025 and 2035. The cellular automata–Markov (CA–Markov) model was applied in the simulation under three scenarios: the environmental protection scenario (EPS), crop protection scenario (CPS), and spontaneous scenario (SS). The model achieved a kappa value of 86.6% with a figure of merit (FoM) of 12.18% when compared to the empirical land use/cover map in 2015. The results showed that the occupation of built-up areas increased from 29.13% in 2015 to 38.68% (EPS), 36.18% (CPS), and 47.94% (SS) in 2035. In this context, current urbanization would bring unprecedented stress on agricultural resources and forest ecosystems, which could be attenuated by implementing protection policies along with decelerating urban expansion. The findings provide valuable information for urban planners to achieve sustainable development goals