Accuracy Assessment in an Urban Expansion Model

2009 ◽  
pp. 107-115 ◽  
Author(s):  
Amin Tayyebi ◽  
Mahmoud Delavar ◽  
Bryan Pijanowski ◽  
Mohammad Yazdanpanah
Keyword(s):  
Accuracy Assessment ◽  
Urban Expansion ◽  
Expansion Model

scholarly journals Estimation of Building Heights and DEM Accuracy Assessment Using ICESat-2 Data Products

2021 ◽  
Vol 10 (1) ◽  
pp. 37
Author(s):  
Goddu Pavan Sai Goud ◽  
Ashutosh Bhardwaj
Keyword(s):  
Spatial Data ◽  
Rural Areas ◽  
Urban Areas ◽  
Accuracy Assessment ◽  
Urban Expansion ◽  
Population Expansion ◽  
Cost Effective ◽  
Absolute Error ◽  
Google Earth ◽  
Surface Geometry

The use of remote sensing for urban monitoring is a very reliable and cost-effective method for studying urban expansion in horizontal and vertical dimensions. The advantage of multi-temporal spatial data and high data accuracy is useful in mapping urban vertical aspects like the compactness of urban areas, population expansion, and urban surface geometry. This study makes use of the ‘Ice, cloud, and land elevation satellite-2′ (ICESat-2) ATL 03 photon data for building height estimation using a sample of 30 buildings in three experimental sites. A comparison of computed heights with the heights of the respective buildings from google image and google earth pro was done to assess the accuracy and the result of 2.04 m RMSE was obtained. Another popularly used method by planners and policymakers to map the vertical dimension of urban terrain is the Digital Elevation Model (DEM). An assessment of the openly available DEM products—TanDEM-X and Cartosat-1 has been done over Urban and Rural areas. TanDEM-X is a German earth observation satellite that uses InSAR (Synthetic Aperture Radar Interferometry) technique to acquire DEM while Cartosat-1 is an optical stereo acquisition satellite launched by the Indian Space Research Organization (ISRO) that uses photogrammetric techniques for DEM acquisition. Both the DEMs have been compared with ICESat-2 (ATL-08) Elevation data as the reference and the accuracy has been evaluated using Mean error (ME), Mean absolute error (MAE) and Root mean square error (RMSE). In the case of Greater Hyderabad Municipal Corporation (GHMC), RMSE values 5.29 m and 7.48 m were noted for TanDEM-X 90 and CartoDEM V3 R1 respectively. While the second site of Bellampalli Mandal rural area observed 5.15 and 5.48 RMSE values for the same respectively. Therefore, it was concluded that TanDEM-X has better accuracy as compared to the CartoDEM V3 R1.

scholarly journals FORECASTING URBAN EXPANSION BASED ON NIGHT LIGHTS

2016 ◽  
Vol XLI-B8 ◽  
pp. 1049-1054 ◽  
Author(s):  
D. Stathakis
Keyword(s):  
Time Series ◽  
Linear Regression ◽  
Correlation Coefficient ◽  
Urban Expansion ◽  
Image Correlation ◽  
Spatially Explicit ◽  
Expansion Model ◽  
Night Lights

Forecasting urban expansion models are a very powerful tool in the hands of urban planners in order to anticipate and mitigate future urbanization pressures. In this paper, a linear regression forecasting urban expansion model is implemented based on the annual composite night lights time series available from National Oceanic and Atmospheric Administration (NOAA). The product known as 'stable lights' is used in particular, after it has been corrected with a standard intercalibration process to reduce artificial year-to-year fluctuations as much as possible. Forecasting is done for ten years after the end of the time series. Because the method is spatially explicit the predicted expansion trends are relatively accurately mapped. Two metrics are used to validate the process. The first one is the year-to-year Sum of Lights (SoL) variation. The second is the year-to-year image correlation coefficient. Overall it is evident that the method is able to provide an insight on future urbanization pressures in order to be taken into account in planning. The trends are quantified in a clear spatial manner.

scholarly journals Urban Land Expansion Simulation Considering the Diffusional and Aggregated Growth Simultaneously: A Case Study of Luoyang City

2021 ◽  
Vol 13 (17) ◽  
pp. 9781
Author(s):  
Renyang Wang ◽  
Weishan He ◽  
Dang Wu ◽  
Lu Zhang ◽  
Yujia Li
Keyword(s):  
Urban Form ◽  
Cell Transformation ◽  
Urban Expansion ◽  
Diffusional Growth ◽  
Neighborhood Conditions ◽  
Urban Status ◽  
Ca Model ◽  
Probability Spaces ◽  
Expansion Model

Restricted by urban development stages, natural conditions, urban form and structure, diffusional growth occupies a large proportion of area in many cities. Traditional cellular automata (CA) has been widely applied in urban growth studies because it can simulate complex system evolution with simple rules. However, due to the limitation of neighborhood conditions, it is insufficient for simulating urban diffusional growth process. A maximum entropy mode was used to estimate three layers of probability spaces: the probability layer of cell transformation from non-urban status to urban status (PLCT), the probability layer for aggregated growth (PLAP), and the probability layer for diffusional growth (PLOP). At the same time, a maxent category selected CA model (MaxEnt-CSCA) was designed to simulate aggregated and diffusional urban expansion processes simultaneously. Luoyang City, with a large proportion of diffusional urban expansion (65.29% in 2009–2018), was used to test the effectiveness of MaxEnt-CSCA. The results showed that: (1) MaxEnt-CSCA accurately simulated aggregated growth of 47.40% and diffusional growth of 37.13% in Luoyang from 2009 to 2018, and the overall Kappa coefficient was 0.78; (2) The prediction results for 2035 showed that future urban expansion will mainly take place in Luolong District and the counties around the main urban area, and the distribution pattern of Luolong District will change from the relative diffusion state to the aggregation stage. This paper also discusses the applicable areas of MaxEnt-CSCA and illustrates the importance of selecting an appropriate urban expansion model in a region with a large amount of diffusional growth.

scholarly journals A Methodology to Monitor Urban Expansion and Green Space Change Using a Time Series of Multi-Sensor SPOT and Sentinel-2A Images

2019 ◽  
Vol 11 (10) ◽  
pp. 1230 ◽  
Author(s):  
Jinsong Deng ◽  
Yibo Huang ◽  
Binjie Chen ◽  
Cheng Tong ◽  
Pengbo Liu ◽  
...  
Keyword(s):  
Green Space ◽  
Accuracy Assessment ◽  
Urban Expansion ◽  
Principal Component ◽  
Transformation Method ◽  
Yangtze River Delta ◽  
Reference Points ◽  
Hybrid Classifier ◽  
Comparison Approach ◽  
Sentinel 2A

Monitoring urban expansion and greenspace change is an urgent need for planning and decision-making. This paper presents a methodology integrating Principal Component Analysis (PCA) and hybrid classifier to undertake this kind of work using a sequence of multi-sensor SPOT images (SPOT-2,3,5) and Sentinel-2A data from 1996 to 2016 in Hangzhou City, which is the central metropolis of the Yangtze River Delta in China. In this study, orthorectification was first applied on the SPOT and Sentinel-2A images to guarantee precise geometric correction which outperformed the conventional polynomial transformation method. After pre-processing, PCA and hybrid classifier were used together to enhance and extract change information. Accuracy assessment combining stratified random and user-defined plots sampling strategies was performed with 930 reference points. The results indicate reasonable high accuracies for four periods. It was further revealed that the proposed method yielded higher accuracy than that of the traditional post-classification comparison approach. On the whole, the developed methodology provides the effectiveness of monitoring urban expansion and green space change in this study, despite the existence of obvious confusions that resulted from compound factors.

scholarly journals A study of developing a spatial entity greenway in the case of Irbid City – Jordan

2021 ◽  
Vol 18 ◽  
pp. 104-112
Author(s):  
Ansam Bzour ◽  
Istvan Valanszki
Keyword(s):  
Rural Areas ◽  
Urban Expansion ◽  
Outer Part ◽  
City Development ◽  
Agricultural Lands ◽  
Rural And Urban ◽  
Urban Territories ◽  
To Come ◽  
Expansion Model ◽  
The City

Greenways are urban elements that are designed to show the linear consistency and connectivity between open green spaces and cause a development in the urban texture. As a city starts to grow, the absolute metropolitan development should be followed by an ongoing protection of the rural and urban territories. The nexus between the city development and the fortification of the open agricultural and rural lands is deemed a good strategy in order to result in a homogenous urban fabric of the city. The study aims to present a greenway model of development to work as a prototype applied on an existing route in Irbid City-Jordan by using the methods of testing and analyzing the route during the site visit and by using GIS base maps in order to come up with an absolute combination between monitoring the city growth, maintaining the quality of the agricultural lands and serving the public and local needs in order to result in a more balanced and controlled growth of the city. Irbid city is located in the northern part of Jordan with a radial urban expansion model of growth extending from the historical center and spreading toward the outskirts of the city. Regarding the significant increase in the number of population in Irbid City-Jordan since the 1970s until nowadays and the continuous need for habitats, there was a huge number of housing projects in the inner part of the city that expanded toward the outer part including the rural areas, resulting in a huge lack of agricultural lands and open recreational spaces where people can benefit from. Those spaces form an outlet of the city connected with the inner part by a route. Establishing a greenway along the route raises the integration between people and their lands and encourages farmers to develop and harvest. According to this study, the greenway development, which forms a breath out to the highly built-up area in the city, has become a great tool to result in tremendous beneficial outcomes to the city development.

scholarly journals Evaluating the Influences of Urban Expansion on the Concurrent Loss of Multiple Ecosystem Services in Drylands

2021 ◽  
Author(s):  
Shixiong Song ◽  
Chunyang He ◽  
Zhifeng Liu ◽  
Tao Qi
Keyword(s):  
Ecosystem Services ◽  
Air Quality ◽  
Habitat Quality ◽  
Food Production ◽  
Water Retention ◽  
Urban Expansion ◽  
Natural Habitat ◽  
Land Planning ◽  
Quality Regulation ◽  
Expansion Model

Abstract Context Effectively 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 the concurrent loss of multiple ESs.Objectives This study sought to effectively estimate the influences of urban expansion on the concurrent loss of multiple ESs in drylands.Methods We combined the improved the urban expansion model and ES models to estimate the influences of urban expansion on five key ESs, including food production (FP), water retention (WR), air quality regulation (AQR), natural habitat quality (NHQ), and landscape aesthetic (LA).Results The results showed that (1) our method can effectively evaluate the influences of urban expansion on the concurrent loss of multiple ESs in drylands, and the accuracy increased by more than 20% on average. (2) Under the effect of future urban expansion, FP, WR, AQR, NHQ and LA will accelerate the decline. (3) These five ESs will show concurrent degradation, and the degree will be further intensified. (4) Future urban expansion will occupy more cropland and grassland which will be the dominating reason for the intensified degradation of multiple ESs. Conclusions We suggest that urban expansion through occupying a large amount of cropland and grassland should be strictly controlled via urban land planning to alleviate the potential influences of future urbanization on the concurrent loss of multiple ESs.

scholarly journals Monitoring Urban Expansion Using Remote-Sensing Data Aided by Google Earth Engine

2021 ◽  
Vol 3 (1) ◽  
pp. 1-8
Author(s):  
Majid Aghlmand ◽  
Gordana Kaplan
Keyword(s):  
Remote Sensing ◽  
Accuracy Assessment ◽  
Urban Expansion ◽  
Remote Sensing Data ◽  
Google Earth ◽  
Support Vector ◽  
Sensing Data ◽  
Google Earth Engine ◽  
Landsat Satellite ◽  
The City

Urbanizationis accompanied by rapid social and economic development, while the process of urbanization causes the degradation of the natural ecology. Direct loss in vegetation biomass from areas with a high probability of urban expansion can contribute to the total emissions from tropical deforestation and land-use change. Monitoring of urban expansion is essential for more efficient urban planning, protecting the ecosystem and the environment. In this paper, we use remote sensing data aided by Google Earth Engine (GEE) to evaluate the urban expansion of the city of Isfahan in the last thirty years. Thus, in this paper we use Landsat satellite images from 1986 and 2019, integrated into GEE, implementing Support vector machine (SVM) classification method. The accuracy assessment for the classified images showed high accuracy (95-96%), while the results showed a significant increase in the urban area of the city of Isfahan, occupying more than 70% of the study area. For future studies, we recommend a more detailed investigation about the city expansion and the negative impacts that may occur due to urban expansion.

scholarly journals Modeling Intersecting Processes of Wetland Shrinkage and Urban Expansion by a Time-Varying Methodology

2019 ◽  
Vol 11 (18) ◽  
pp. 4953 ◽  
Author(s):  
Erqi Xu ◽  
Yimeng Chen
Keyword(s):  
Development Strategy ◽  
Urban Areas ◽  
Accuracy Assessment ◽  
Urban Expansion ◽  
Wetland Loss ◽  
Historical Change ◽  
Time Varying ◽  
Actual Distribution ◽  
Urban Dynamics ◽  
Wetland Distribution

Continuous urban expansion worldwide has resulted in significant wetland degradation and loss. A limited number of studies have addressed the coupling of wetland and urban dynamics, but this relationship remains unclear. In this study, a time-varying methodology of predicting wetland distribution was developed to support decision-making. The novelty of the methodology is its ability to dynamically simulate wetland shrinkage together with urban expansion and reveal conflicts and potential tradeoffs under different scenarios. The developed methodology consists of three modules: a historical change detection of wetland and urban areas module, a spatial urban sprawl simulation and forecasting module that can accommodate different development priorities, and a wetland distribution module with time-varying logistic regression. The methodology was applied and tested in the Tonghu Wetland as a case study. The wetland and urban extents presented a spatially intersecting shift, where wetlands lost more than 40% of their area from 1977 to 2017, while urban areas expanded by 10-fold, threatening wetlands. The increase in the relative importance metric of the time-varying regression model indicated an enhanced influence of urban expansion on the wetland. An accuracy assessment validated a robust statistical result and a good visual fit between spatially distributed wetland occurrence probabilities and the actual distribution of wetland. Incorporating the new variable of urban expansion improved modeling performance and, particularly, realized a greater ability to predict potential wetland loss than provided by the traditional method. Future wetland loss probabilities were visualized under different scenarios. The historical trend scenario predicted continuously expanding urban growth and wetland shrinkage to 2030. However, a specific urban development strategy scenario was designed interactively to control the potential wetland loss. Consideration of such scenarios can facilitate identifying tradeoffs to support wetland conservation.

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