scholarly journals Geospatial analysis-based approach for assessing urban forests under the influence of different human settlement extents in Ibadan city, Nigeria

2020 ◽  
Vol 12 (4) ◽  
pp. 959-971
Author(s):  
Oluwayemisi S. OLOKEOGUN ◽  
Abiodun O. OLADOYE ◽  
Oluwatoyin O. AKINTOLA
Keyword(s):  
Urban Area ◽  
Urban Areas ◽  
Forest Cover ◽  
Urban Forest ◽  
Urban Forests ◽  
Remotely Sensed ◽  
Google Earth ◽  
Human Settlement ◽  
Remotely Sensed Data ◽  
The Status

Urban forests are an essential component of urban areas as they provide many environmental and social services that contribute to the quality of life in cities. Urban forests in most cities of Nigeria are gradually becoming bitty as a result of urbanization activities, thereby posing adverse effects. In this study, we assessed the changes in the urban forests cover under the influence of different human settlement (HS) extents across the urban area of Ibadan city using remotely sensed data. The pattern of change(s) in the urban forests cover over 20 years were examined by analysing and manipulating Landsat and Sentinel-2 datasets using Google Earth Engine, ArcGIS 10.1, and Erdas 2014 software. The extents of human settlement (for the year 2000, 2005, 2010, 2015, and 2020) were extracted (from Landsat datasets), analysed, and mapped to evaluate the status of the urban forests cover under different human settlement extents. The result reveals a substantial land cover changes within the urban area of Ibadan.  The urban forest cover decreased from 24.14% to 7.99%. Also, there is a significant decrease in the urban forests cover as a result of a substantial increase in human settlement extent (102,806 to 122,572 pixels). The study provides an opportunity to map the status of urban forest cover and extents of HS in a developing city using remotely sensed data and applications of GIS tools.

scholarly journals Understanding the Spatial Distribution of Urban Forests in China Using Sentinel-2 Images with Google Earth Engine

Forests ◽  
2019 ◽  
Vol 10 (9) ◽  
pp. 729 ◽  
Author(s):  
Qianwen Duan ◽  
Minghong Tan ◽  
Yuxuan Guo ◽  
Xue Wang ◽  
Liangjie Xin
Keyword(s):  
High Resolution ◽  
Forest Cover ◽  
Urban Forest ◽  
Urban Forests ◽  
Well Being ◽  
Google Earth ◽  
Machine Learning Algorithms ◽  
Sustainable Urban Development ◽  
Google Earth Engine ◽  
Sentinel 2

Urban forests are vitally important for sustainable urban development and the well-being of urban residents. However, there is, as yet, no country-level urban forest spatial dataset of sufficient quality for the scientific management of, and correlative studies on, urban forests in China. At present, China attaches great importance to the construction of urban forests, and it is necessary to map a high-resolution and high-accuracy dataset of urban forests in China. The open-access Sentinel images and the Google Earth Engine platform provide a significant opportunity for the realization of this work. This study used eight bands (B2–B8, B11) and three indices of Sentinel-2 in 2016 to map the urban forests of China using the Random Forest machine learning algorithms at the pixel scale with the support of Google Earth Engine (GEE). The 7317 sample points for training and testing were collected from field visits and very high resolution images from Google Earth. The overall accuracy, producer’s accuracy of urban forest, and user’s accuracy of urban forest assessed by independent validation samples in this study were 92.30%, 92.27%, and 92.18%, respectively. In 2016, the percentage of urban forest cover was 19.2%. Nearly half of the cities had an urban forest cover between 10% and 20%, and the average percentage of large cities whose urban populations were over 5 million was 24.8%. Cities with less than half of the average were mainly distributed in northern and western parts of China, which should be focused on in urban greening planning.

The Status of Livelihood Vulnerability and Its CopingCapacities of Urban Squatters in Kathmandu Metropolitan City, Nepal

Patan Pragya ◽  
2019 ◽  
Vol 5 (1) ◽  
pp. 19-32
Author(s):  
Chhabi Ram Baral
Keyword(s):  
Data Collection ◽  
Urban Area ◽  
Urban Areas ◽  
Quantitative Methods ◽  
Urban Poverty ◽  
Rural Poverty ◽  
Poor People ◽  
Qualitative And Quantitative ◽  
Qualitative And Quantitative Methods ◽  
The Status

Urban poverty is one of multidimensional issue in Nepal. Increasing immigration from the outer parts of Kathmandu due to rural poverty, unemployment and weak security of the lives and the properties are core causes pushing people into urban areas. In this context how squatter urban area people sustain their livelihoods is major concern. The objectives of the study are to find out livelihood assets and capacities squatters coping with their livelihood vulnerability in adverse situation. Both qualitative and quantitative methods are applied for data collection. It is found that squatters social security is weak, victimized by severe health problems earning is not regular with lack of physical facilities and overall livelihood is critical. This study helps to understand what the changes that have occurred in livelihood patterns and how poor people survive in urban area.

scholarly journals An automated classification system for urban areas matching the ‘city country fingers’ pattern: the cases of Kamakura (Japan) and Acireale (Italy) cities

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Roberto Spina ◽  
Emiliano Tramontana
Keyword(s):  
Urban Area ◽  
Urban Areas ◽  
Agricultural Land ◽  
Google Earth ◽  
Classification Model ◽  
Complete Analysis ◽  
City Development ◽  
Essential Condition ◽  
Green Areas ◽  
The City

Abstract The uncontrolled expansion of urban areas is one of the main factors that reduce the liveability of cities. In recent years, to contrast urban sprawl, several nations have promoted policies aimed at developing urban green spaces. The importance of green oases within cities had already been highlighted, in 1977, by the architect Christopher Alexander who had developed a series of patterns including ‘City Country Fingers’ claiming that city development should consider the prolongation of country land in to the urban area. In several cities, especially in Japan, it is possible to recognize the imprint of urban development based on country fingers. This term refers to extensive urban intersections of agricultural land or wooded hills which, from the peripheral areas, penetrate the city. Inside them, there are urban windows, called city fingers, whose development direction is opposite to those of the country fingers. To recognize and analyze, in an automated way, these particular structures, a Python-based application was created. Starting from the original high-resolution image of Google Earth, a complete analysis was performed, labeling and delimiting urban and vegetational areas and extrapolating the main geometric parameters of the country and city fingers. The finalization of the results obtained was carried out through a classification model whose criteria were based on Alexander’s pattern. Thanks to this classification scheme, the distinction between Active Green Areas (country fingers) and Passive Green Areas (gardens and public parks) have been revealed for the analyzed cities. The tests performed showed almost ideal conditions for the city of Kamakura and a limited match for the urban area of Acireale. The proposed method is suitable for fields of application that require a qualitative and quantitative determination of the vegetation cover present within the city, an essential condition for correct territorial planning.

scholarly journals URBAN GROWTH AND WATER QUALITY IN THIMPHU, BHUTAN

2013 ◽  
pp. 82-95 ◽  
Author(s):  
Nandu Giri ◽  
O. P. Singh
Keyword(s):  
Water Quality ◽  
Urban Area ◽  
Water Samples ◽  
Urban Areas ◽  
Forest Cover ◽  
Rapid Development ◽  
Oxygen Demand ◽  
Capital City ◽  
Quality Data ◽  
Water Quality Data

Detailed study was undertaken in 2008 and 2009 on assessment of water quality of River Wang Chhu which flows through Thimphu urban area, the capital city of Bhutan. The water samples were examined at upstream of urban area, within the urban area and its downstream. The water samples were analyzed by studying the physico-chemical, biological and benthic macro-invertebrates. The water quality data obtained during present study are discussed in relation to land use/land cover changes(LULC) and various ongoing human activities at upstream, within the each activity areas and it’s downstream. Analyses of satellite imagery of 1990 and 2008 using GIS revealed that over a period of eighteen years the forest, scrub and agricultural areas have decreased whereas urban area and road network have increased considerably. The forest cover, agriculture area and scrub decreased from 43.3% to 42.57%, 6.88% to 5.33% and 42.55% to 29.42%, respectively. The LULC changes effect water quality in many ways. The water temperature, pH, conductivity, total dissolved solids, turbidity, nitrate, phosphate, chloride, total coliform, and biological oxygen demand were lower at upstream and higher in urban area. On the other hand dissolved oxygen was found higher at upstream and lower in urban area. The pollution sensitive benthic macro-invertebrates population were dominant at upstream sampling sites whereas pollution tolerant benthic macro-invertebrates were found abundant in urban area and its immediate downstream. The rapid development of urban infrastructure in Thimphu city may be posing serious threats to water regime in terms of its quality. Though the deterioration of water quality is restricted to a few localized areas, the trend is serious and needs proper attention of policy planners and decision makers. Proper treatment of effluents from urban areas is urgently needed to reduce water pollution in such affected areas to check further deterioration of water quality. This present study which is based on upstream, within urban area and downstream of Thimphu city can be considered as an eye opener.

Landscape fragmentation

2010 ◽  
Author(s):  
Ned Horning ◽  
Julie A. Robinson ◽  
Eleanor J. Sterling ◽  
Woody Turner ◽  
Sacha Spector
Keyword(s):  
Forest Fragmentation ◽  
Landscape Metrics ◽  
Forest Cover ◽  
Remotely Sensed ◽  
Clear Understanding ◽  
Remotely Sensed Data ◽  
Deforestation Rates ◽  
Habitat Conversion ◽  
Conservation Organizations ◽  
Total Core Area

The country of Vietnam has long been recognized as an important region for biodiversity (Sterling et al. 2006). High-profile discoveries in the 1990s of many species new to science including large ones such as the Saola (Pseudoryx nghetinhensis), an 85 kg basal member of the cattle subfamily Bovinae and the first new genus of large land-dwelling mammal described since the okapi (Okapia johnstoni) in 1901, have focused the attention of national and international conservation organizations on Vietnam and surrounding countries in mainland Southeast Asia (Hurley et al. in prep.). Conservation action for these endemic, endangered species relies on a clear understanding of trends in habitat conversion. To track deforestation rates through time in Vietnam, Meyfroidt and Lambin (2008) combined remotely sensed data with landscape metrics such as number of patches, mean patch size, mean proximity index, and total core area index. They tested their analyses across a variety of land cover studies including those using Advanced Very High Resolution Radiometer (AVHRR), Landsat, SPOT, and MODIS data sources. They found that forest cover decreased nationally from the 1980s to the 1990s and then showed an increase between 1990 and 2000, due to plantation forests as well as natural forest regeneration. However, the effects of this forest transition on fragmentation metrics noted above differed across the country. For instance, in some places, such as central Vietnam where forest cover is relatively large and well connected, reforestation led to a decrease in forest fragmentation and secondary forests recovered rapidly. However in others, such as areas in the north where forest fragmentation dates back centuries and forests have therefore long been isolated, reforestation did not seem to have an impact on continued fragmentation and habitat loss. In this chapter we detail the importance of fragmentation and landscape metrics to ecology and conservation, outlining when and where remotely sensed data can help in these analyses. We then discuss a subset of fragmentation metrics and point to some challenges in processing fragmentation data. We provide examples of composition and connectivity metrics illuminated with examples from the remote sensing literature.

scholarly journals An Effect of Urban Forest on Urban Thermal Environment in Seoul, South Korea, Based on Landsat Imagery Analysis

Forests ◽  
2020 ◽  
Vol 11 (6) ◽  
pp. 630
Author(s):  
Peter Sang-Hoon Lee ◽  
Jincheol Park
Keyword(s):  
South Korea ◽  
Vegetation Cover ◽  
Land Surface ◽  
Urban Areas ◽  
Vegetation Index ◽  
Urban Forest ◽  
Thermal Environment ◽  
Urban Forests ◽  
Cooling Effect ◽  
Surrounding Areas

The urban heat island effect has posed negative impacts on urban areas with increased cooling energy demand followed by an altered thermal environment. While unusually high temperature in urban areas has been often attributed to complex urban settings, the function of urban forests has been considered as an effective heat mitigation strategy. To investigate the cooling effect of urban forests and their influence range, this study examined the spatiotemporal changes in land surface temperature (LST) of urban forests and surrounding areas by using Landsat imageries. LST, the size of the urban forest, its vegetation cover, and Normalized Difference Vegetation Index (NDVI) were investigated for 34 urban forests and their surrounding areas at a series of buffer areas in Seoul, South Korea. The mean LST of urban forests was lower than that of the overall city, and the threshold distance from urban forests for cooling effect was estimated to be roughly up to 300 m. The group of large-sized urban forests showed significantly lower mean LST than that of small-sized urban forests. The group of urban forests with higher NDVI showed lower mean LST than that of urban forests with lower mean NDVI in a consistent manner. A negative linear relationship was found between the LST and size of urban forest (r = −0.36 to −0.58), size of vegetation cover (r = −0.39 to −0.61), and NDVI (r = −0.42 to −0.93). Temporal changes in NDVI were examined separately on a specific site, Seoul Forest, that has experienced urban forest dynamics. LST of the site decreased as NDVI improved by a land-use change from a barren racetrack to a city park. It was considered that NDVI could be a reliable factor for estimating the cooling effect of urban forest compared to the size of the urban forest and/or vegetation cover.

scholarly journals Monitoring Mining Disturbance and Restoration over RBM Site in South Africa Using LandTrendr Algorithm and Landsat Data

2019 ◽  
Vol 11 (24) ◽  
pp. 6916 ◽  
Author(s):  
Lubanzi Z. D. Dlamini ◽  
Sifiso Xulu
Keyword(s):  
Negative Impact ◽  
Google Earth ◽  
Remotely Sensed Data ◽  
Mining Areas ◽  
Surface Mines ◽  
Automated Method ◽  
Observation Strategy ◽  
Petroleum Resources ◽  
The Status ◽  
Disturbance And Recovery

Considering the negative impact of mining on ecosystems in mining areas, the South African government legislated the Mineral and Petroleum Resources Development Act (No. 28 of 2002), to compel mining companies to restore the land affected by mining. Several studies have used remotely sensed data to observe the status and dynamics of surface mines. Advances in remote sensing along the cloud-based Google Earth Engine (GEE) now promise an enhanced observation strategy for improved monitoring of mine environments. Despite these advances, land rehabilitation at Richards Bay Minerals (RBM) is mainly restricted to field-based approaches which are unable to reveal seamless patterns of disturbance and restoration. Here, we illustrate the value of the trajectory-based LandTrendr algorithm in conjunction with GEE for mine rehabilitation studies. Our automated method produced disturbance and recovery patterns (1984–2018) over the RBM site. The study revealed that RBM has progressively been mining different portions of the mineral-rich coastal area after which restoration was undertaken. The duration of mining over each site ranged from 2 to 6 years. The LandTrendr outputs correspond with independent reference datasets that were classified with an overall accuracy of 99%; it captures mine-induced disturbance efficiently and offers a practical tool for mine restoration management.

Mapping Urban Areas by Fusing Multiple Sources of Coarse Resolution Remotely Sensed Data

2003 ◽  
Vol 69 (12) ◽  
pp. 1377-1386 ◽  
Author(s):  
Annemarie Schneider ◽  
Mark A. Friedl ◽  
Douglas K. McIver ◽  
Curtis E. Woodcock
Keyword(s):  
Urban Areas ◽  
Remotely Sensed ◽  
Multiple Sources ◽  
Remotely Sensed Data ◽  
Coarse Resolution
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