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.

Exploring the relationships between urban form metrics and the vegetation biomass loss under urban expansion in China

2018 ◽  
Vol 47 (3) ◽  
pp. 363-380
Author(s):  
Tong Zhang ◽  
Sophia Shuang Chen ◽  
Guangyu Li
Keyword(s):  
Urban Form ◽  
Urban Areas ◽  
Yangtze River ◽  
Green Space ◽  
Yangtze River Delta ◽  
Urban Morphology ◽  
Total Biomass ◽  
Urban Metrics ◽  
Biomass Loss ◽  
Loss Index

Compact urban form has been applied as a strategy to reduce the loss of green space that occurs from development, but the impact of this policy on the provision of green space still presents many uncertainties. This research investigated the statistical relationship between urban form indicators and the loss of vegetation biomass to understand the response of quality green space provision to changes in urban morphology. A methodology combining multi-source data assimilation, statistical analysis, and spatial analysis was adopted for the Yangtze River Delta cities of China. First, six urban metrics were selected to describe the shape and layout of urban patches in each city, and the total biomass loss index was then introduced as a parameter. The values of urban metrics and total biomass loss index were calculated for the 50 Yangtze River Delta cities. Second, ordinary least squares regression and geographically weighted regression analyses were then used to establish a quantitative relationship between total biomass loss index and urban form indicators. The results revealed an extremely negative correlation between total biomass loss index and the three urban variables of Richard compactness, density gradient, and the Gini coefficient; moreover, the parameter estimates for the three variables in the geographically weighted regression model were local and varied over space. Third, the mechanisms by which the urban form influences biomass loss were discussed and different urban form planning strategies for particular urban areas were suggested. In conclusion, compact urban form in a clustered layout of urban areas with a dense central agglomeration was verified to be ecologically superior and conducive to green space protection. For the physical interpretation of the statistical relationship between urban morphology and vegetation loss, the interface effect of urban agglomeration on vegetation merits further study.

scholarly journals Assessing the Impacts of Urban Expansion on Habitat Quality by Combining the Concepts of Land Use, Landscape, and Habitat in Two Urban Agglomerations in China

2020 ◽  
Vol 12 (11) ◽  
pp. 4346 ◽  
Author(s):  
Huina Wang ◽  
Lina Tang ◽  
Quanyi Qiu ◽  
Huaxiang Chen
Keyword(s):  
Land Use ◽  
Habitat Quality ◽  
Habitat Degradation ◽  
Early Stage ◽  
Urban Expansion ◽  
Land Use Changes ◽  
Yangtze River Delta ◽  
Spatiotemporal Variability ◽  
Quality Model ◽  
Urban Agglomerations

Understanding the spatiotemporal variability of habitat quality as a function of land-use changes is important for expanding scientific knowledge of ecological conservation. In this study, the impacts of land-use change on habitat quality were assessed in two urban agglomerations in China at different stages of development, namely (1) the Yangtze River Delta Urban Agglomeration (YRDUA), which has reached the middle and late stage of urbanization, and (2) the Golden Triangle of Southern Fujian (GTSF), which has reached the middle and early stage. The Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) habitat quality model was applied to determine the habitat quality and the degree of habitat degradation in these two agglomerations. Overall, the habitat quality in the YRDUA was found to be clearly inferior to that in the GTSF. In the GTSF, more than 65% of the habitat was of good or excellent quality, whereas in the YRDUA, less than 45% of the habitat reached this quality. By combining the concepts of land use, landscape, and habitat, the boundary of degradation and the general increase in habitat quality from 2000 to 2015 were found to be mainly related to the landform, the dominant landscape, and the concentration of non-habitat areas. Additionally, the type, distribution, and fragmentation of the dominant habitat were shown to play important roles in habitat quality. Moreover, changes in industrial composition over time were demonstrated to be critical drivers of changes in areas of construction land.

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 Componential coding in the condition monitoring of electrical machines Part 1: Principles and illustrations using simulated typical faults

2003 ◽  
Vol 217 (8) ◽  
pp. 883-899 ◽  
Author(s):  
C J S Webber ◽  
B S Payne ◽  
F Gu ◽  
A D Ball
Keyword(s):  
Condition Monitoring ◽  
Input Data ◽  
Angular Position ◽  
Principal Component ◽  
Real Data ◽  
Companion Paper ◽  
Reference Points ◽  
Electrical Machines ◽  
Efficient Manner ◽  
Data Signal

This paper (Part 1) describes the principles of a novel unsupervised adaptive neural network anomaly detection technique, called componential coding, in the context of condition monitoring of electrical machines. Numerical examples are given to illustrate the technique's capabilities. The companion paper (Part 2), which follows, assesses componential coding in its application to real data recorded from a known machine and an entirely unseen machine (a conventional induction motor and a novel transverse flux motor respectively). Componential coding is particularly suited to applications in which no machine-specific tailored techniques have been developed or in which no previous monitoring experience is available. This is because componential coding is an unsupervised technique that derives the features of the data during training, and so requires neither labelling of known faults nor pre-processing to enhance known fault characteristics. Componential coding offers advantages over more familiar unsupervised data processing techniques such as principal component analysis. In addition, componential coding may be implemented in a computationally efficient manner by exploiting the periodic convolution theorem. Periodic convolution also gives the algorithm the advantage of time invariance; i.e. it will work equally well even if the input data signal is offset by arbitrary displacements in time. This means that there is no need to synchronize the input data signal with respect to reference points or to determine the absolute angular position of a rotating part.

Comparative Study of Change Detection and Urban Expansion Using Multi-Date Multi-Source Data: A Case Study of Greater Khartoum

2012 ◽  
Vol 23 (2) ◽  
pp. 139-172
Author(s):  
Abdullah Salman Alsalman Abdullah Salman Alsalman
Keyword(s):  
Image Processing ◽  
Change Detection ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Urban Expansion ◽  
Remote Sensing Data ◽  
Principal Component ◽  
Test Area ◽  
Image Differencing ◽  
Erdas Imagine

Noting that Khartoum represents the most rapidly expanding city in the Sudan and taking into account that change detection operations are seldom , the present study has been initiated to attempt to produce work that synthesizes land use/land cover (LULC) to investigate change detection using GIS, remote sensing data and digital image processing techniques; estimate, evaluate and map changes that took place in the city from 1975 to 2003. The experiment used the techniques of visual inspection, write-function-memoryinsertion, image differencing, image transformation i.e. normalized difference vegetation index (NDVI), tasseled cap, principal component analysis (PCA), post-classification comparison and GIS. The results of all these various techniques were used by the authors to study change detection of the geographic locale of the test area. Image processing and GIS techniques were performed using Intergraph Image analyst 8.4 and GeoMedia professional version 6, ERDAS Imagine 8.7, and ArcGIS 9.2. Results obtained were discussed and analyzed in a comparative manner and a conclusion regarding the best method for change detection of the test area was derived.

scholarly journals Estimation of Hydrologic Alteration in Kaligandaki River Using Representative Hydrologic Indices

Water ◽  
2019 ◽  
Vol 11 (4) ◽  
pp. 688 ◽  
Author(s):  
Gao Yuqin ◽  
Kamal Prasad Pandey ◽  
Xianfeng Huang ◽  
Naresh Suwal ◽  
Khem Prasad Bhattarai
Keyword(s):  
Anthropogenic Activities ◽  
Principal Component ◽  
Data Sets ◽  
Large Set ◽  
River Section ◽  
Comparison Approach ◽  
Daunting Task ◽  
Natural Flow ◽  
Hydrologic Indices ◽  
Value Changes

Anthropogenic activities have led to the transformation of river basins and natural flow alteration around the world. Alteration in flow regimes have adverse effects on river ecosystems. Flow value changes signify the alteration extent and a number of flow related indices can be used to assess the extent of alteration in a river ecosystem. Selection of a few and ecologically relevant indices from a large set of available indices is a daunting task. Principal Component Analysis helps to reduce these large indices to a few ecologically significant indices and removes statistical redundancy of data to give uncorrelated data sets. These representative indices are useful in the primary investigation of a less studied area like the Kaligandaki River basin, Nepal. This paper uses reduced indices from the Kaligandaki River to calculate the alteration on the river section downstream of a hydropower facility using the Histogram Comparison Approach (HCA) combined with Hydrologic Year Types (HYT). The combined approach eliminates the potential underestimation of alteration values which may occur due to the exemption of hydrologic year types from the analysis, a feature equally relevant in river ecology. A new metric is used for the calculation of combined alteration using HCA-HYT in this paper. The analysis showed 60.71 percent alteration in the natural flow regime in the area past a hydropower construction, which is classified in the high alteration category. The study can be a guide for further analysis of the ecological flow management of a river section and a parsimonious approach to other areas where hydrological data is limited to historical flow records only.

scholarly journals Comparison of Changes in Urban Land Use/Cover and Efficiency of Megaregions in China from 1980 to 2015

2019 ◽  
Vol 11 (15) ◽  
pp. 1834 ◽  
Author(s):  
Shu Zhang ◽  
Chuanglin Fang ◽  
Wenhui Kuang ◽  
Fengyun Sun
Keyword(s):  
Land Use ◽  
Hong Kong ◽  
Urban Expansion ◽  
Yangtze River Delta ◽  
Urban Land ◽  
Urban Land Use ◽  
Theil Index ◽  
Valuable Insight ◽  
Bay Area ◽  
Great Bay

Urban land use/cover and efficiency are important indicators of the degree of urbanization. However, research about comparing their changes at the megaregion level is relatively rare. In this study, we depicted the differences and inequalities of urban land and efficiency among megaregions in China using China’s Land Use/cover Dataset (CLUD) and China’s Urban Land Use/cover Dataset (CLUD-Urban). Furthermore, we analyzed regional inequality using the Theil index. The results indicated that the Guangdong-Hong Kong-Macao Great Bay Area had the highest proportion of urban land (8.03%), while the Chengdu-Chongqing Megaregion had the highest proportion of developed land (64.70%). The proportion of urban impervious surface area was highest in the Guangdong-Hong Kong-Macao Great Bay Area (75.16%) and lowest in the Chengdu-Chongqing Megaregion (67.19%). Furthermore, the highest urban expansion occurred in the Yangtze River Delta (260.52 km2/a), and the fastest period was 2000–2010 (298.19 km2/a). The decreasing Theil index values for the urban population and economic density were 0.305 and 1.748, respectively, in 1980–2015. This study depicted the development trajectory of different megaregions, and will expect to provide a valuable insight and new knowledge on reasonable urban growth modes and sustainable goals in urban planning and management.

scholarly journals Integrating Ecosystem Services Supply–Demand and Spatial Relationships for Intercity Cooperation: A Case Study of the Yangtze River Delta

2020 ◽  
Vol 12 (10) ◽  
pp. 4131
Author(s):  
Wenbo Cai ◽  
Tong Wu ◽  
Wei Jiang ◽  
Wanting Peng ◽  
Yongli Cai
Keyword(s):  
Ecosystem Services ◽  
Yangtze River ◽  
Urban Expansion ◽  
Supply And Demand ◽  
Spatial Relations ◽  
Yangtze River Delta ◽  
River Delta ◽  
Spatial Relationships ◽  
Environmental Cooperation ◽  
The Yrd

Transboundary environmental problems caused by urban expansion and economic growth cannot be solved by individual cities. Successful intercity environmental cooperation relies on the clear identification and definition of the rights and obligations of each city. An Ecosystem services (ES) approach not only budgets the ES supply and demand of a city, but also defines the spatial relationships between Services Provisioning Areas (SPA) and Services Benefiting Areas (SBA). However, to date, quantitative studies integrating ES budgets and spatial relations have been scarce. This study integrates ecosystem services supply–demand budgeting with flow direction analysis to identify intercity environmental cooperation in the highly urbanized Yangtze River Delta (YRD) region of China for water-related ecosystem services (flood protection, erosion regulation and water purification). The results demonstrated that there were significant spatial mismatches in the supply and demand of three water-related ES among 16 core cities in the YRD region: five to six cities in the southern part of the region had significant service surpluses, while ten to 11 cities in the north–central part had significant service deficits. We then went on to offer definitions for Ecosystem Services Surplus City, Ecosystem Services Deficit City and Ecosystem Services Balance City, as well as Service Provisioning City, Service Benefiting City and Service Connecting City in which to categorize cities in the YRD Region. Furthermore, we identified two intercity cooperation types and two non-cooperation types. This framework can be used to promote ecological integration in highly urbanized regions to advance sustainable development.

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