scholarly journals Assessing the Potential of Solar PV Installation based on Urban Land Cover Analysis

2021 ◽  
Vol 933 (1) ◽  
pp. 012024
Author(s):  
A Zakiah ◽  
R B Aditya
Keyword(s):  
Solar Energy ◽  
Land Cover ◽  
Urban Areas ◽  
Energy Production ◽  
Urban Land ◽  
Tree Canopy ◽  
Solar Photovoltaic ◽  
Solar Pv ◽  
Land Cover Types ◽  
Urban Land Cover

Abstract This paper presents a technical assessment of solar photovoltaic (PV) installation potential in urban areas based on its urban land cover type, using a case study of Indonesian cities including Yogyakarta, Kupang and Tomohon. The assessment was performed using a free online application to assess the urban land cover types, i-Tree Canopy. This application can be used to identify and distinguish urban land cover types such as building rooftop, vegetation, grass, soil, road and water, which then can be used to assess the suitable area for Solar PV installation. Additionally, solar photovoltaic power output data from Global Solar Atlas is used to calculate potential energy production from PV installations in each city. The result shows that in an urbanised city such as Yogyakarta, the most suitable PV installation is in building rooftops. Meanwhile, Kupang and Tomohon have higher potential for ground-mounted PV installation in bare ground or grass. The approach and result of this study could be used for planners and policymakers to determine city-scale solar PV installation planning to maximise solar energy production. It can also be used to calculate the solar energy estimation using free online applications, which is easy to use and more accessible for stakeholders.

scholarly journals Quantifying Short-Term Urban Land Cover Change with Time Series Landsat Data: A Comparison of Four Different Cities

Sensors ◽  
2018 ◽  
Vol 18 (12) ◽  
pp. 4319 ◽  
Author(s):  
Hongsheng Zhang ◽  
Ting Wang ◽  
Yuhan Zhang ◽  
Yiru Dai ◽  
Jiangjie Jia ◽  
...  
Keyword(s):  
Land Cover ◽  
Land Cover Change ◽  
Urban Areas ◽  
Urban Land ◽  
Sao Paulo ◽  
São Paulo ◽  
Short Term ◽  
Land Cover Types ◽  
Urban Land Cover ◽  
Urban Land Cover Change

Short-term characteristics of urban land cover change have been observed and reported from satellite images, although urban landscapes are mainly influenced by anthropogenic factors. These short-term changes in urban areas are caused by rapid urbanization, seasonal climate changes, and phenological ecological changes. Quantifying and understanding these short-term characteristics of changes in various land cover types is important for numerous urban studies, such as urbanization assessments and management. Many previous studies mainly investigated one study area with insufficient datasets. To more reliably and confidently investigate temporal variation patterns, this study employed Fourier series to quantify the seasonal changes in different urban land cover types using all available Landsat images over four different cities, Melbourne, Sao Paulo, Hamburg, and Chicago, within a five-year period (2011–2015). The overall accuracy was greater than 86% and the kappa coefficient was greater than 0.80. The R-squared value was greater than 0.80 and the root mean square error was less than 7.2% for each city. The results indicated that (1) the changing periods for water classes were generally from half a year to one and a half years in different areas; and, (2) urban impervious surfaces changed over periods of approximately 700 days in Melbourne, Sao Paulo, and Hamburg, and a period of approximately 215 days in Chicago, which was actually caused by the unavoidable misclassification from confusions between various land cover types using satellite data. Finally, the uncertainties of these quantification results were analyzed and discussed. These short-term characteristics provided important information for the monitoring and assessment of urban areas using satellite remote sensing technology.

Identifying land cover suitability factors for photovoltaic installations with focus on cropland and urban areas

2021 ◽  
Author(s):  
Madhura Yeligeti ◽  
Wenxuan Hu ◽  
Yvonne Scholz ◽  
Kai von Krbek
Keyword(s):  
Land Cover ◽  
Urban Areas ◽  
Energy Systems ◽  
Energy System ◽  
Climatic Conditions ◽  
System Modelling ◽  
Solar Photovoltaic ◽  
Land Cover Types ◽  
The World ◽  
Urban Settlements

<p>Solar photovoltaic (PV) systems will foreseeably be an integral part of future energy systems. Land cover area analysis has a large influence on estimatiin of long-term solar photovoltaic potential of the world in high spatial detail. In this regard, it is often seen in contemporary works, that the suitability of various land cover categories for PV installation is considered in a yes/no binary response. While some areas like natural parks, sanctuaries, forests are usually completely exempted from PV potential calculations, other land over categories like urban settlements, bare, sparsely vegetated areas, and even cropland can principally support PV installations to varying degrees. This depends on the specific land use competition, social, economic and climatic conditions, etc. In this study, we attempt to evaluate these ‘factors of suitability’ of different land cover types for PV installations.</p><p>As a basis, the openly available global land cover datasets from the Copernicus Land Monitoring Service were used to identify major land cover types like cropland, shrubland, bare, wetlands, urban settlements, forests, moss and snow etc. For open area PV installations, with a focus on cropland, we incorporated the promising technology of ‘Agri-voltaics’ in our investigation. Different crops have shown to respond positively or negatively, so far, to growing under PV panels according to various experimental and commercial sources. Hence, we considered 18 major crops of the world (covering 85% of world cropland) individually and consequently, evaluated a weighted overall suitability factor of cropland cover for PV, for three acceptance scenarios of future.</p><p>For rooftop PV installations in urban areas, various socio-economic and geographical influences come in play. The rooftop area available and further usable for PV depends on housing patterns (roof type, housing density) which vary with climate, population density and socio-economic lifestyle. We classified global urban areas into several clusters based on combinations of these factors. For each cluster, rooftop area suitability is evaluated at a representative location using the land cover maps, the Open Street Map and specific characteristics of the cluster.</p><p>Overall, we present an interdisciplinary approach to integrate technological, social and economic aspects in land cover analysis to estimate PV potentials. While the intricacies may still be insufficient for planning small localized energy systems, this can reasonably benefit energy system modelling from a regional to international scale.</p>

scholarly journals ADVANCED CLASSIFICATION OF OPTICAL AND SAR IMAGES FOR URBAN LAND COVER MAPPING

2020 ◽  
Vol XLIII-B3-2020 ◽  
pp. 1417-1421
Author(s):  
D. Amarsaikhan
Keyword(s):  
Land Cover ◽  
Urban Land ◽  
Landsat 8 ◽  
Data Sets ◽  
Contextual Knowledge ◽  
Rule Based ◽  
Land Cover Types ◽  
Urban Land Cover ◽  
Land Cover Map

Abstract. The aim of this research is to classify urban land cover types using an advanced classification method. As the input bands to the classification, the features derived from Landsat 8 and Sentinel 1A SAR data sets are used. To extract the reliable urban land cover information from the optical and SAR features, a rule-based classification algorithm that uses spatial thresholds defined from the contextual knowledge is constructed. The result of the constructed method is compared with the results of a standard classification technique and it indicates a higher accuracy. Overall, the study demonstrates that the multisource data sets can considerably improve the classification of urban land cover types and the rule-based method is a powerful tool to produce a reliable land cover map.

scholarly journals A 30-meter resolution national urban land-cover dataset of China, 2000–2015

2019 ◽  
Author(s):  
Wenhui Kuang ◽  
Shu Zhang ◽  
Xiaoyong Li ◽  
Dengsheng Lu
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Urban Areas ◽  
Vegetation Index ◽  
Urban Land ◽  
Google Earth ◽  
Urban Environments ◽  
Urban Land Use ◽  
Environmental Research ◽  
Urban Land Cover

Abstract. Accurate urban land-cover datasets are essential for mapping urban environments. However, a series of national urban land-cover data covering more than 15 years that characterizes urban environments is relatively rare. Here we propose a hierarchical principle on remotely sensed urban land-use/cover classification for mapping intra-urban structure/component dynamics. China's Land Use/cover Dataset (CLUD) is updated, delineating the imperviousness, green surface, waterbody and bare land conditions in cities. A new data subset called CLUD-Urban is created from 2000 to 2015 at five-year intervals with a medium spatial resolution (30 m). The first step is a prerequisite to extract the vector boundaries covered with urban areas from CLUD. A new method is then proposed using logistic regression between urban impervious surface area (ISA) and the annual maximum Normalized Difference Vegetation Index (NDVI) value retrieved from Landsat images based on a big-data platform with Google Earth Engine. National ISA and urban green space (UGS) fraction datasets for China are generated at 30-meter resolution with five-year intervals from 2000 to 2015. The overall classification accuracy of national urban areas is 92 %. The root mean square error values of ISA and UGS fractions are 0.10 and 0.14, respectively. The datasets indicate that the total urban area of China was 6.28 × 104 km2 in 2015, with average fractions of 70.70 % and 26.54 % for ISA and UGS, respectively. The ISA and UGS increased between 2000 and 2015 with unprecedented annual rates of 1,311.13 km2/yr and 405.30 km2/yr, respectively. CLUD-Urban can be used to enhance our understanding of urbanization impacts on ecological and regional climatic conditions and urban dwellers' environments. CLUD-Urban can be applied in future researches on urban environmental research and practices in the future. The datasets can be downloaded from https://doi.org/10.5281/zenodo.2644932.

scholarly journals Assessing the thermal contributions of urban land cover types

2020 ◽  
Vol 204 ◽  
pp. 103927
Author(s):  
Jiacheng Zhao ◽  
Xiang Zhao ◽  
Shunlin Liang ◽  
Tao Zhou ◽  
Xiaozheng Du ◽  
...  
Keyword(s):  
Land Cover ◽  
Urban Land ◽  
Land Cover Types ◽  
Urban Land Cover

scholarly journals Comparison of the impacts of urban development and climate change in exposing European cities to pluvial flooding

2017 ◽  
Author(s):  
Per Skougaard Kaspersen ◽  
Nanna Høegh Ravn ◽  
Karsten Arnbjerg-Nielsen ◽  
Henrik Madsen ◽  
Martin Drews
Keyword(s):  
Climate Change ◽  
Land Cover ◽  
Urban Development ◽  
Extreme Precipitation ◽  
Urban Areas ◽  
Urban Land ◽  
European Cities ◽  
Urban Land Cover ◽  
Pluvial Flooding ◽  
Rcp 8.5

Abstract. The economic and human consequences of extreme precipitation and the related flooding of urban areas have increased rapidly over the past decades. Some of the key factors that affect the risks to urban areas include climate change, the densification of assets within cities and the general expansion of urban areas. In this paper, we examine and compare quantitatively the impact of climate change and recent urban development patterns on the exposure of four European cities to pluvial flooding. In particular, we investigate the degree to which pluvial floods of varying severity and in different geographical locations are influenced to the same extent by changes in urban land cover and climate change. We have selected the European cities of Odense, Vienna, Strasbourg and Nice for analyses to represent, different climatic conditions, trends in urban development and topographical characteristics. We develop and apply a combined remote-sensing and flood-modelling approach to simulate the extent of pluvial flooding for a range of extreme precipitation events for historical (1984) and present-day (2014) urban land cover and for two climate-change scenarios (RCP 4.5 and RCP 8.5). Changes in urban land cover are estimated using Landsat satellite imagery for the period 1984–2014. We combine the remote-sensing analyses with regionally downscaled estimates of precipitation extremes of current and expected future climate to enable 2D overland flow simulations and flood-hazard assessments. The individual and combined impacts of urban development and climate change are quantified by examining the variations in flooding between the different simulations along with the corresponding uncertainties. For all four cities, we find an increase in flood exposure corresponding to an observed absolute growth in impervious surfaces of 7–12 % during the past thirty years of urban development. Similarly, we find that climate change increases exposure to pluvial flooding under both the RCP 4.5 and RCP 8.5 scenarios. The relative importance of urban development and climate change on flood exposure varies considerably between the cities. For Odense, the impact of urban development is comparable to that of climate change under an RCP 8.5 scenario (2081–2100), while for Vienna and Strasbourg it is comparable to the impacts of an RCP 4.5 scenario. For Nice, climate change dominates urban development as the primary driver of changes in exposure to flooding. The variation between geographical locations is caused by differences in soil infiltration properties, historical trends in urban development and the projected regional impacts of climate change on extreme precipitation.

Mapping urban land cover types using object-based multiple endmember spectral mixture analysis

2014 ◽  
Vol 5 (6) ◽  
pp. 521-529 ◽  
Author(s):  
Caiyun Zhang ◽  
Hannah Cooper ◽  
Donna Selch ◽  
Xuelian Meng ◽  
Fang Qiu ◽  
...  
Keyword(s):  
Land Cover ◽  
Urban Land ◽  
Spectral Mixture Analysis ◽  
Mixture Analysis ◽  
Land Cover Types ◽  
Urban Land Cover ◽  
Object Based ◽  
Spectral Mixture

scholarly journals MONITORING URBAN LAND COVER/LAND USE CHANGE IN ALGIERS CITY USING LANDSAT IMAGES (1987–2016)

2017 ◽  
Vol XLII-2/W7 ◽  
pp. 1083-1090 ◽  
Author(s):  
B. Bouchachi ◽  
Y. Zhong
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Land Cover ◽  
Environmental Sustainability ◽  
Urban Areas ◽  
Driving Forces ◽  
Urban Land ◽  
Support Vector ◽  
Urban Land Cover ◽  
The Impact

Monitoring the Urban Land Cover/Land Use change detection is important as one of the main driving forces of environmental change because Urbanization is the biggest changes in form of Land, resulting in a decrease in cultivated areas. Using remote sensing ability to solve land resources problems. The purpose of this research is to map the urban areas at different times to monitor and predict possible urban changes, were studied the annual growth urban land during the last 29 years in Algiers City. Improving the productiveness of long-term training in land mapping, were have developed an approach by the following steps: 1) pre-processing for improvement of image characteristics; 2) extract training sample candidates based on the developed methods; and 3) Derive maps and analyzed of Algiers City on an annual basis from 1987 to 2016 using a Supervised Classifier Support Vector Machine (SVMs). Our result shows that the strategy of urban land followed in the region of Algiers City, developed areas mostly were extended to East, West, and South of Central Regions. The urban growth rate is linked with National Office of Statistics data. Future studies are required to understand the impact of urban rapid lands on social, economy and environmental sustainability, it will also close the gap in data of urbanism available, especially on the lack of reliable data, environmental and urban planning for each municipality in Algiers, develop experimental models to predict future land changes with statistically significant confidence.

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