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

An Urban Heat Island Study of the Colombo Metropolitan Area, Sri Lanka, Based on Landsat Data (1997–2017)

One of the major impacts associated with unplanned rapid urban growth is the decrease of urban vegetation, which is often replaced with impervious surfaces such as buildings, parking lots, roads, and pavements. Consequently, as the percentage of impervious surfaces continues to increase at the expense of vegetation cover, surface urban heat island (SUHI) forms and becomes more intense. The Colombo Metropolitan Area (CMA), Sri Lanka, is one of the rapidly urbanizing metropolitan regions in South Asia. In this study, we examined the spatiotemporal variations of land surface temperature (LST) in the CMA in the context of the SUHI phenomenon using Landsat data. More specifically, we examined the relationship of LST with the normalized difference vegetation index (NDVI) and the normalized difference built-up index (NDBI) at three time points (1997, 2007 and 2017). In addition, we also identified environmentally critical areas based on LST and NDVI. We found significant correlations of LST with NDVI (negative) and NDBI (positive) (p < 0.001) across all three time points. Most of the environmentally critical areas are located in the central business district (CBD), near the harbor, across the coastal belt, and along the main transportation network. We recommend that those identified environmentally critical areas be considered in the future urban planning and landscape development of the city. Green spaces can help improve the environmental sustainability of the CMA

Spatiotemporal pattern of global forest change over the past 60 years and the forest transition theory

Forest ecosystems play an indispensable role in addressing various pressing sustainability and social-ecological challenges such as climate change and biodiversity loss. However, global forest loss has been, and still is today, an important issue. Here, based on spatially explicit data, we show that over the past 60 years (1960–2019), the global forest area has declined by 81.7 million ha (i.e. 10% more than the size of the entire Borneo island), with forest loss (437.3 million ha) outweighing forest gain (355.6 million ha). With this forest decline and the population increase (4.68 billion) over the period, the global forest per capita has decreased by over 60%, from 1.4 ha in 1960 to 0.5 ha in 2019. The spatiotemporal pattern of forest change supports the forest transition theory, with forest losses occurring primarily in the lower income countries in the tropics and forest gains in the higher income countries in the extratropics. Furthermore, economic growth has a stronger association with net forest gain than with net forest loss. Our results highlight the need to strengthen the support given to lower income countries, especially in the tropics, to help improve their capacity to minimize or end their forest losses. To help address the displacement of forest losses to the lower income countries in the tropics, higher income nations need to reduce their dependence on imported tropical forest products

Quantifying Surface Urban Heat Island Formation in the World Heritage Tropical Mountain City of Sri Lanka

Presently, the urban heat island (UHI) phenomenon, and its adverse impacts, are becoming major research foci in various interrelated fields due to rapid changes in urban ecological environments. Various cities have been investigated in previous studies, and most of the findings have facilitated the introduction of proper mitigation measures to overcome the negative impact of UHI. At present, most of the mountain cities of the world have undergone rapid urban development, and this has resulted in the increasing surface UHI (SUHI) phenomenon. Hence, this study focuses on quantifying SUHI in Kandy City, the world heritage tropical mountain city of Sri Lanka, using Landsat data (1996 and 2017) based on the mean land surface temperature (LST), the difference between the fraction of impervious surfaces (IS), and the fraction of green space (GS). Additionally, we examined the relationship of LST to the green space/impervious surface fraction ratio (GS/IS fraction ratio) and the magnitude of the GS/IS fraction ratio. The SUHI intensity (SUHII) was calculated based on the temperature difference between main land use/cover categories and the temperature difference between urban-rural zones. We demarcated the rural zone based on the fraction of IS recorded, <10%, along with the urban-rural gradient zone. The result shows a SUHII increase from 3.9 °C in 1996 to 6.2 °C in 2017 along the urban-rural gradient between the urban and rural zones (10 < IS). These results relate to the rapid urban expansion of the study areas from 1996 to 2017. Most of the natural surfaces have changed to impervious surfaces, causing an increase of SUHI in Kandy City. The mean LST has a positive relationship with the fraction of IS and a negative relationship with the fraction of GS. Additionally, the GS/IS fraction ratio shows a rapid decline. Thus, the findings of this study can be considered as a proxy indicator for introducing proper landscape and urban planning for the World Heritage tropical mountain city of Kandy in Sri Lanka

〈Original Papers〉Validating ALOS PRISM DSM-derived surface feature height: Implications for urban volume estimation

Urban volume, such as urban built volume (UBV), can be used as a proxy indicator for measuring the intensity and spatial pattern of urban development, and for characterizing social structure, intensity of economic activity, levels of economic supremacy, and levels of resource consumption. Urban volume estimation requires two basic input data: (1) urban footprint (built footprint for UBV and green footprint for urban green volume (UGV)); and (2) height data for urban features (herein called surface feature height (SFH)). A digital surface model (DSM) and a digital terrain model (DTM) can be used to extract SFH, i.e., by subtracting the DTM from the DSM. Light Detection and Ranging (LiDAR) data are often used to generate DSMs and DTMs. However, the availability of LiDAR data remains limited. The recent release of ALOS World 3D topographic data provides an alternative data source for DSMs and potentially for DTMs. However, the potential of ALOS PRISM DSM for deriving SFH has not been rigorously assessed, especially at the micro level. In this study, we validated six sets of 5 m ALOS PRISM DSM-derived SFH data across six test sites (Tokyo (Japan), Beijing (China), Shanghai (China), Surabaya (Indonesia), Tsukuba (Japan), and Lusaka (Zambia)). We described the grid-based method used to derive a DTM from a DSM and how this method was applied. We then validated the derived SFH data through comparison with recorded building height (RBH) data. Across the six test sites, the root-mean-square error (RMSE) of the ALOS PRISM DSM-derived SFH data ranged from 7 m (Tsukuba) (approximately 2 building floors) to 81 m (Beijing) (approximately 27 building floors). The ALOS PRISM DSM-derived SFH data for lower buildings (e.g., RBH 100 m) and larger and denser cities (Tokyo, Beijing and Shanghai). Factors that may have influenced the validation results were considered, as were the implications of the findings on urban volume estimation

Prioritizing Areas for Rehabilitation by Monitoring Change in Barangay-Based Vegetation Cover

Analysis of spatial and temporal changes of vegetation cover using remote sensing (RS) technology, in conjunction with Geographic Information Systems (GIS), is becoming increasingly important in environmental conservation. The objective of this study was to use RS data and GIS techniques to assess the vegetation cover in 1989 and 2009, in the barangays (smallest administrative units) of the city of San Fernando, La Union, the Philippines, for planning vegetation rehabilitation. Landsat images were used to prepare both the 1989 and 2009 land cover maps, which were then used to detect changes in the vegetation cover for the barangays. In addition to conventional accuracy assessment parameters such as; proportion correct, and standard Kappa index of agreement, two other parameters; quantity, and allocation disagreements were used to assess the accuracy of the land cover classification. Results revealed that there were gains and losses of vegetation cover in most of the barangays, but overall vegetation cover increased by 11% (around 625 ha) based on the original extent of 1989. Those barangays that showed substantial net losses in vegetation cover need to be prioritised for rehabilitation planning. As exemplified in this study, the collection, processing and analysis of relevant RS and GIS information, can facilitate priority-setting in the planning of environmental rehabilitation and conservation by the local government at both city and barangay levels

An Urban Heat Island Study of the Colombo Metropolitan Area, Sri Lanka, Based on Landsat Data (1997–2017)

One of the major impacts associated with unplanned rapid urban growth is the decrease of urban vegetation, which is often replaced with impervious surfaces such as buildings, parking lots, roads, and pavements. Consequently, as the percentage of impervious surfaces continues to increase at the expense of vegetation cover, surface urban heat island (SUHI) forms and becomes more intense. The Colombo Metropolitan Area (CMA), Sri Lanka, is one of the rapidly urbanizing metropolitan regions in South Asia. In this study, we examined the spatiotemporal variations of land surface temperature (LST) in the CMA in the context of the SUHI phenomenon using Landsat data. More specifically, we examined the relationship of LST with the normalized difference vegetation index (NDVI) and the normalized difference built-up index (NDBI) at three time points (1997, 2007 and 2017). In addition, we also identified environmentally critical areas based on LST and NDVI. We found significant correlations of LST with NDVI (negative) and NDBI (positive) (p &lt; 0.001) across all three time points. Most of the environmentally critical areas are located in the central business district (CBD), near the harbor, across the coastal belt, and along the main transportation network. We recommend that those identified environmentally critical areas be considered in the future urban planning and landscape development of the city. Green spaces can help improve the environmental sustainability of the CMA

Ecosystem Service and Land-Use Changes in Asia: Implications for Regional Sustainability

This Special Issue focuses on qualitative and quantitative analyses of ecosystem services (ESs) specifically toward sustainability in Asia [...