Identifying the urban-rural fringe using wavelet transform and kernel density estimation: A case study in Beijing City, China

Peng, Jian; Zhao, Sheng; Liu, Yanxu; Lan, Tian

doi:10.1016/j.envsoft.2016.06.007

Cited by 105 publications

(56 citation statements)

References 50 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Subsequently, by replacing temporal signals with a geospatial element sequence (S(x)), the CWT is reformed into spatial continuous wavelet transform (SCWT), described as follows [7,30,37,38]:…”

Section: Spatial Continuous Wavelet Transformmentioning

confidence: 99%

See 1 more Smart Citation

Integrating Spatial Continuous Wavelet Transform and Normalized Difference Vegetation Index to Map the Agro-Pastoral Transitional Zone in Northern China

et al. 2018

Self Cite

View full text Add to dashboard Cite

The agro-pastoral transitional zone (APTZ) in Northern China is one of the most important ecological barriers of the world. The commonly-used method to identify the spatial distribution of ATPZ is to apply a threshold rule on climatic or land use indicators. This approach is highly subjective, and the quantity standards vary among the studies. In this study, we adopted the spatial continuous wavelet transform (SCWT) technique to detect the spatial fluctuation in normalized difference vegetation index (NDVI) sequences, and as such identify the APTZ. To carry out this analysis, the Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI 1-month data (MODND1M) covering the period 2006-2015 were used. Based on the spatial variation in NDVI, we identified two sub-regions within the APTZ. The temporal change of APTZ showed that although vegetation spatial pattern changed annually, certain areas appeared to be stable, while others showed higher sensitivity to environmental variance. Through correlation analysis between the dynamics of APTZ and precipitation, we found that the mean center of the APTZ moved toward the southeast during dry years and toward the northwest during humid years. By comparing the APTZ spatial pattern obtained in the present study with the outcome following the traditional approach based on mean annual precipitation data, it can be concluded that our study provides a reliable basis to advance the methodological framework to identify accurately transitional zones. The identification framework is of high importance to support decision-making in land use management in Northern China as well as other similar regions around the world.

show abstract

Section: Spatial Continuous Wavelet Transformmentioning

confidence: 99%

“…The continuous wavelet transform (CWT) is efficient in detecting the dynamic trends and break points of continuous signals [7]. It can decompose signal vector (f(t)) by finite basis wavelet function (ϕ(t)) with a scale (a) and a shift (b) into wavelet coefficients (W f ), described as follows [36][37][38]:…”

Section: Spatial Continuous Wavelet Transformmentioning

confidence: 99%

Integrating Spatial Continuous Wavelet Transform and Normalized Difference Vegetation Index to Map the Agro-Pastoral Transitional Zone in Northern China

et al. 2018

Self Cite

View full text Add to dashboard Cite

show abstract

“…A more precise and dynamic approach for identifying the urban-rural fringe was presented by Peng et al [26]. They developed a model which combined spatial continuous wavelet transform for the detection of mutation points from a land use degree index map with a kernel density estimation.…”

Section: Other Approachesmentioning

confidence: 99%

Construction and Use of a Simple Index of Urbanisation in the Rural–Urban Interface of Bangalore, India

et al. 2017

View full text Add to dashboard Cite

Urbanisation is a global trend rapidly transforming the biophysical and socioeconomic structures of metropolitan areas. To better understand (and perhaps control) these processes, more interdisciplinary research must be dedicated to the rural-urban interface. This also calls for a common reference system describing intermediate stages along a rural-urban gradient. The present paper constructs a simple index of urbanisation for villages in the Greater Bangalore Area, using GIS analysis of satellite images, and combining basic measures of building density and distance. The correlation of the two parameters and discontinuities in the frequency distribution of the combined index indicate highly dynamic stages of transformation, spatially clustered in the rural-urban interface. This analysis is substantiated by a qualitative assessment of village morphologies. The index presented here serves as a starting point in a large, coordinated study of rural-urban transitions. It was used to stratify villages for random sampling in order to perform a representative socioeconomic household survey, along with agricultural experiments and environmental assessments in various subsamples. Later on, it will also provide a matrix against which the results can be aligned and evaluated. In this process, the measures and classification systems themselves can be further refined and elaborated.

show abstract

“…As an effective way to estimate the density of a random variable, kernel density [22] is able to converse independent points into continuous areas with a proper radius of influence. Previous studies have applied kernel density in identifying facility hotspots [23], flood assessment [24], delineating urban-rural boundary [25], and other applications. However, few studies utilise it to generate land cover regions.…”

Section: Land Cover Region Generation and Change Detectionmentioning

confidence: 99%

Rapid Detection of Land Cover Changes Using Crowdsourced Geographic Information: A Case Study of Beijing, China

2017

View full text Add to dashboard Cite

Land cover change (LCC) detection is a significant component of sustainability research including ecological economics and climate change. Due to the rapid variability of natural environment, effective LCC detection is required to capture sufficient change-related information. Although such information has been available through remotely sensed images, the complicated image processing and classification make it time consuming and labour intensive. In contrast, the freely available crowdsourced geographic information (CGI) contains easily interpreted textual information, and thus has the potential to be applied for capturing effective change-related information. Therefore, this paper presents and evaluates a method using CGI for rapid LCC detection. As a case study, Beijing is chosen as the study area, and CGI is applied to monitor LCC information. As one kind of CGI which is generated from commercial Internet maps, points of interest (POIs) with detailed textual information are utilised to detect land cover in 2016. Those POIs are first classified into land cover nomenclature based on their textual information. Then, a kernel density approach is proposed to effectively generate land cover regions in 2016. Finally, with GlobeLand30 in 2010 as baseline map, LCC is detected using the post-classification method in the period of 2010-2016 in Beijing. The result shows that an accuracy of 89.20% is achieved with land cover regions generated by POIs, indicating that POIs are reliable for rapid LCC detection. Additionally, an LCC detection comparison is proposed between remotely sensed images and CGI, revealing the advantages of POIs in terms of LCC efficiency. However, due to the uneven distribution, remotely sensed images are still required in areas with few POIs.

show abstract

Identifying the urban-rural fringe using wavelet transform and kernel density estimation: A case study in Beijing City, China

Cited by 105 publications

References 50 publications

Integrating Spatial Continuous Wavelet Transform and Normalized Difference Vegetation Index to Map the Agro-Pastoral Transitional Zone in Northern China

Integrating Spatial Continuous Wavelet Transform and Normalized Difference Vegetation Index to Map the Agro-Pastoral Transitional Zone in Northern China

Construction and Use of a Simple Index of Urbanisation in the Rural–Urban Interface of Bangalore, India

Rapid Detection of Land Cover Changes Using Crowdsourced Geographic Information: A Case Study of Beijing, China

Contact Info

Product

Resources

About