19 results on '"Yu, Danlin"'
Search Results
2. Coastal vulnerability: Evolving concepts in understanding vulnerable people and places.
- Author
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Bevacqua, Anthony, Yu, Danlin, and Zhang, Yaojun
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COASTAL ecology ,NATURAL disasters ,ECOLOGICAL resilience ,COASTAL changes ,PHYSICAL geography - Abstract
Coastal vulnerability is a spatial concept that identifies people and places that are susceptible to disturbances resulting from coastal hazards. Hazards in the coastal environment, such as coastal storms and erosion, pose significant threats to coastal physical, economic, and social systems. The theory of vulnerability has been an evolving idea over the past hundred years. In recent decades, improved technology and high-profile disaster events, has caused an increase in publications in the coastal hazards field. Modern approaches to understanding coastal vulnerability examine the complex systems that determine the spatial distribution of hazards, risks, and exposure. Consensus among today’s researchers shows that coastal vulnerability is geographically dependent and requires place based investigations. This review examines over 200 coastal vulnerability related works. Through this extensive literature review, this research describes the evolution of vulnerability concepts, and the modern definition of vulnerability with the goal of providing a well-informed body of knowledge to be used in the advancement of resilience and increased sustainability in coastal areas. [ABSTRACT FROM AUTHOR]
- Published
- 2018
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3. Urban agglomeration: An evolving concept of an emerging phenomenon.
- Author
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Fang, Chuanglin and Yu, Danlin
- Subjects
ECONOMIES of agglomeration ,ECONOMIC development ,URBANIZATION ,SUSTAINABLE development ,LITERATURE reviews - Abstract
Urban agglomeration is a highly developed spatial form of integrated cities. It occurs when the relationships among cities shift from mainly competition to both competition and cooperation. Cities are highly integrated within an urban agglomeration, which renders the agglomeration one of the most important carriers for global economic development. Studies on urban agglomerations have increased in recent decades. In the research community, a consensus with regard to what an urban agglomeration is, how an urban agglomeration is delineated in geographic space, what efficient models for urban agglomeration management are, etc. is not reached. The current review examines 32,231 urban agglomeration-related works from the past 120 years in an attempt to provide a theoretically supported and practically based definition of urban agglomeration. In addition, through this extensive literature review and fieldwork in China, the current research identifies the four stages of an urban agglomeration’s spatial expansion and further proposes operable approaches and standards to define urban agglomerations. The study aims to provide a scientifically sound basis for the healthy and sustainable development of urban agglomerations. [ABSTRACT FROM AUTHOR]
- Published
- 2017
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4. Investigating the spatiotemporal pattern of urban vibrancy and its determinants: Spatial big data analyses in Beijing, China.
- Author
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Wang, Xiaoxi, Zhang, Yaojun, Yu, Danlin, Qi, Jinghan, and Li, Shujing
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BIG data ,URBAN land use ,DATA analysis ,INFORMATION & communication technologies ,URBAN planning ,GEOTAGGING - Abstract
Investigating urban vibrancy and factors that impact urban vibrancy aids the understanding of urban land use policies, provides solid foundation for scientific urban planning. The boom in information and communication technologies and the advancement of big data extraction provides new sources of data and make it possible to measure and analyze urban vibrancy at a finer spatial and temporal scale. This study aims to portray the spatiotemporal variation patterns of urban vibrancy in 24 h and investigate the potential influence mechanism of it. The central districts of Beijing consisting of 135 subdistricts are selected as the study area. Massive and spontaneous geo-tagged check-in data released from social media platforms has attracted increasing attentions in urban vibrancy studies because it reflects well people's activities at a certain time, which is a good proxy for urban vibrancy. This study hence uses the check-in data from Weibo, the largest microblogging platform in China, to proxy urban vibrancy. We also extract from multisource spatial big data to explore potential determinants of urban vibrancy. This study seeks to reveal the global and local varying impacts of different factors on urban vibrancy by employ spatial lag model (SLM) and multiscale geographically weighted regression (MGWR) model. Results show that the increase in the number of different point of interests (POIs) improves urban vibrancy. Their effects on vibrancy vary at different times but have no obvious spatial scale variation. Splitting effect and attraction effect of land use diversity are introduced to explain its significantly negative effect on the intensity and fluctuation of urban vibrancy. It requires the wisdom of urban planners to balance these two effects of land use diversity in the process of urban construction. The guidance strategy of "highlighting the main functions and enriching the auxiliary functions" is helpful to build vibrant cities. Socioeconomical conditions, location and accessibility have different spatial scale effects on urban vibrancy at subdistrict level. These findings enable us to have a deeper understanding of the variation patterns and influence mechanism of urban vibrancy in China's megacities and benefit the urban land use policy research and management community. • Weibo check-ins are used to represent urban vibrancy in Beijing at subdistrict level. • We investigated point of interests, socioeconomic and locational factors' impact on urban vibrancy. • Spatial big data provides in-depth understanding of urban vibrancy and its determinants. • Multiscale geographically weighted regression analysis was applied. • Determinants' impacts varying over places and scales. [ABSTRACT FROM AUTHOR]
- Published
- 2022
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5. Vegetation response to intensive commercial horticulture and environmental changes within watersheds in central highlands, Kenya, using AVHRR NDVI data
- Author
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Muriithi, Faith K., Yu, Danlin, and Robila, Stefan
- Abstract
Expansion and heterogeneous clustering of commercial horticulture within the central highlands of Kenya after the mid-1990s impact watersheds and the sustainable resource management. This is distressing since climate conditions for world horticultural regions are projected to change, making such farming extremely difficult and costly to the environment. To understand the scope of impact on vegetation, the study evaluated (1) interannual variability in averaged normalized difference vegetation index (NDVI); (2) trends in average annual NDVI before and after 1990 – the presumed onset of rapid horticulture; and (3) relationship between the average annual NDVI and large-scale commercial farms, population density, and mean annual rainfall in subwatersheds. Time-series analysis of long-term Global Inventory Modeling and Mapping Studies NDVI data were analyzed as indicator of vegetation condition. NDVI trends before 1990s (1982–1989) and after 1990s (1990–2006) were evaluated to determine the slope (sign), and the Spearman’s correlation coefficient (strength). Overall, results show considerable variations in vegetation condition due largely to mixed factors including intensive farming activities, drought, and rainfall variation. Statistical analysis shows significant differences in slopes before 1990 and after 1990 (p < 0.05 and p < 0.1 respectively). Negative (decline) trends were common after 1990, linked to increased commercial horticulture and related anthropogenic disturbances on land cover. There was decline in vegetation over densely populated subwatersheds, though low NDVI values in 1984 and 2000 were the effect of severe droughts. Understanding the linkage between vegetation responses to the effects of human-induced pressure at the subwatershed scale can help natural resource managers approach conservation measures more effectively.
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- 2016
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6. Dielectric properties of saline soil based on a modified Dobson dielectric model
- Author
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Tashpolat, Nigara, Ding, Jianli, and Yu, Danlin
- Abstract
Soil salinization is a major concern for agricultural development in arid areas. In this paper, a modified Dobson dielectric model was applied to simulate the dielectric constant of saline soil in the Ugan-Kuqa river delta oasis of Xinjiang Uygur autonomous region, northwestern China. The model performance was examined through analyzing the influences of its parameters on the soil dielectric constant and the relationship between radar backscattering coefficient and the dielectric constant of saline soil. The results of the study indicate that: (1) The real part of the soil dielectric constant is affected by soil water content at low radar frequencies; the imaginary part is closely related with both the soil water content and soil salt content. (2) The soil water and salt contents are related with the coefficient of dialectical loss, which is consistent with the natural conditions of saline soil in arid areas and provides valuable references for the study of soil dielectric properties. (3) The changes of soil water content and soil salt content have instant influences on the dielectric constant of saline soil. Subsequently, the radar backscattering coefficient is affected to respond to the dielectric constant of saline soil. The radar backscattering coefficient is most responsible to the radar’s cross polarization pattern with a correlation coefficient of R2=0.75. This study provides a potential method to monitor soil salinization and soil water content by using a soil dielectric model and radar techniques.
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- 2015
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7. Incorporating Remote Sensing Information in Modeling House Values: A Regression Tree Approach.
- Author
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Yu, Danlin and Wu, Changshan
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REMOTE sensing ,AERIAL photogrammetry ,DETECTORS ,TECHNOLOGY ,SCIENTIFIC errors ,STATISTICAL correlation ,HOUSING - Abstract
This paper explores the possibility of incorporating remote sensing information in modeling house values in the City of Milwaukee, Wisconsin, U.S.A. In particular, a Landsat ETM+ image was utilized to derive environmental characteristics, including the fractions of vegetation, impervious surface, and soil, with a linear spectral mixture analysis approach. These environmental characteristics, together with house structural attributes, were integrated to house value models. Two modeling techniques, a global OLS regression and a regression tree approach, were employed to build the relationship between house values and house structural and environmental characteristics. Analysis of results indicates that environmental characteristics generated from remote sensing technologies have strong influences on house values, and the addition of them improves house value modeling performance significantly. Moreover, the regression tree model proves as a better alternative to the OLS regression models in terms of predicting accuracy. In particular, based on the testing dataset, the mean average error (MAE) and relative error (RE) dropped from 0.202 and 0.434 for the OLS model to 0.134 and 0.280 for the regression tree model, while the correlation coefficient between the predicted and observed values increased from 0.903 to 0.960. Further, as a nonparametric and local model, the regression tree method alleviates the problems with the OLS techniques and provides a means in delineating urban housing submarkets. [ABSTRACT FROM AUTHOR]
- Published
- 2006
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8. Community pharmacies and addictive products: sociodemographic predictors of accessibility from a mixed GWR perspective
- Author
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Yu, Danlin, Morton, Cory M., and Peterson, N. Andrew
- Abstract
Community pharmacies selling potentially harmful products may contradict their role in health promotion. From a spatial analysis perspective, this study investigated the sale of alcohol, tobacco, and lottery tickets by community pharmacies in Passaic County, New Jersey, and assessed the relationship between sociodemographic factors of community residents and their potential accessibility to those community pharmacies. A mixed geographically weighted regression analysis revealed that census block groups with higher median household income tend to have less accessibility to pharmacies that sell addictive products. Relationships between Latino population and those pharmacies are mixed. No significant relationship was found for African American population.
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- 2014
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9. Exploring the Impact of Non-normality on Spatial Non-stationarity in Geographically Weighted Regression Analyses: Tobacco Outlet Density in New Jersey
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Yu, Danlin, Peterson, N.Andrew, and Reid, RobertJ.
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The principal rationale for applying geographically weighted regression (GWR) techniques is to investigate the potential spatial non-stationarity of the relationship between the dependent and independent variables—i.e., that the same stimulus would provoke different responses in different locations. The calibration of GWR employs a geographically weighted local least squares regression approach. To obtain meaningful inference, it assumes that the regression residual follows a normal or asymptotically normal distribution. In many classical econometric analyses, the assumption of normality is often readily relaxed, although it has been observed that such relaxation might lead to unreliable inference of the estimated coefficients' statistical significance. No studies, however, have examined the behavior of residual non-normality and its consequences for the modeled relationships in GWR. This study attempts to address this issue for the first time by examining a set of tobacco-outlet-density and demographic variables (i.e., percent African American residents, percent Hispanic residents, and median household income) at the census tract level in New Jersey in a GWR analysis. The regression residual using the raw data is apparently non-normal. When GWR is estimated using the raw data, we find that there is no significant spatial variation of the coefficients between tobacco outlet density and percentage of African American and Hispanics. After transforming the dependent variable and making the residual asymptotically normal, all coefficients exhibit significant variation across space. This finding suggests that relaxation of the normality assumption could potentially conceal the spatial non-stationarity of the modeled relationships in GWR. The empirical evidence of the current study implies that researchers should verify the normality assumption prior to applying GWR techniques in analyses of spatial non-stationarity.
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- 2009
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10. Modeling Urban Growth Using GIS and Remote Sensing
- Author
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Luo, Jun, Yu, Danlin, and Xin, Miao
- Abstract
Based on remote sensing and GIS, this study models the spatial variations of urban growth patterns with a logistic geographically weighted regression (GWR) technique. Through a case study of Springfield, Missouri, the research employs both global and local logistic regression to model the probability of urban land expansion against a set of spatial and socioeconomic variables. The logistic GWR model significantly improves the global logistic regression model in three ways: (1) the local model has higher PCP (percentage correctly predicted) than the global model; (2) the local model has a smaller residual than the global model; and (3) residuals of the local model have less spatial dependence. More importantly, the local estimates of parameters enable us to investigate spatial variations in the influences of driving factors on urban growth. Based on parameter estimates of logistic GWR and using the inverse distance weighted (IDW) interpolation method, we generate a set of parameter surfaces to reveal the spatial variations of urban land expansion. The geographically weighted local analysis correctly reveals that urban growth in Springfield, Missouri is more a result of infrastructure construction, and an urban sprawl trend is observed from 1992 to 2005.
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- 2008
- Full Text
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11. Modeling Owner-Occupied Single-Family House Values in the City of Milwaukee: A Geographically Weighted Regression Approach
- Author
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Yu, Danlin
- Abstract
This study investigates the spatial non-stationarity of the relationship between house values and various attributes in the City of Milwaukee. From the 2003 Master Property (MPROP) data file of the City of Milwaukee, a set of owner-occupied single family houses were randomly selected (representing 99% of confidence within a ±2% range of accuracy of the total population) to model how house values are related to various house attributes. Remote sensing information (the fraction of soil and impervious surface that represent degraded neighborhood environmental conditions) is added to fine-tune the relationship. A geographically weighted regression (GWR) approach is used to investigate spatial non-stationarity. The modeling revealed that significant spatial non-stationarity existed between house values and the predictors. Specifically, the study found that those house attributes—including floor size, number of bathrooms, air conditioners, and fire-places—add more value to houses in the more affluent areas (especially on the east side near Lake Michigan and in suburban areas) than in the relatively poor areas. In addition, older houses in the historical area are more expensive, which differs from other areas. Environmental conditions, though expected to have a negative impact on house values in most areas, did not affect house values in the historical area.
- Published
- 2007
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12. Understanding Population Segregation from Landsat ETM+ Imagery: A Geographically Weighted Regression Approach
- Author
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Yu, Danlin and Wu, Changshan
- Abstract
This study attempts to understand population segregation issues in Milwaukee County, Wisconsin utilizing remote sensing and regression technologies. Population segregation was measured with a local segregation index Dibased on the theory of the index of dissimilarity. Remote sensing information was extracted from a Landsat ETM+ image through spectral mixture analysis, unsupervised classification, and texture analysis. Global ordinary least squares (OLS) regression and geographically weighted regression (GWR) analyses were applied to explore the relationships between population segregation and remote sensing variables. Results indicate that remote sensing information has the potential to increase our understanding of socio-cultural issues such as population segregation.
- Published
- 2004
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13. Analyzing Regional Inequality in Post-Mao China in a GIS Environment
- Author
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Yu, Danlin and Wei, YehuaDennis
- Abstract
Regional inequality in China has attracted considerable scholarly attention, but the use of geographic information system (GIS) techniques for rigorous analysis remains limited. This paper utilizes recent data and GIS and spatial statistical techniques to analyze changing patterns of regional inequality in China from 1978 to 2000. It also identifies the changing clusters of regional development in China. We illustrate that regional inequality in China is sensitive to development trajectories of the provinces, and that conventional measures of regional inequality mask geographical clustering. Patterns of change are explained by both contextual and regression analyses. Journal of Economic Literature, Classification Numbers: F21, G32, P31. 16 figures, 3 tables, 30 references.
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- 2003
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14. Transit User Perceptions of the Benefits of Automatic Vehicle Location
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Peng, Zhong-Ren, Yu, Danlin, and Beimborn, Edward
- Abstract
An attitudinal survey on transit riders’ perception of the importance transit users place on features of an automatic vehicle location (AVL) system is reported. Onboard surveys and on-time field checks were conducted in the cities of Manitowoc and Racine, Wisconsin, to determine how users in those cities perceive their transit systems and how well each transit system performs. The surveys indicate that transit riders put a great value on increased on-time performance and improved schedule reliability. Passengers value features that AVL technology could bring, such as improving on-time performance, knowing when the next bus will arrive, knowing how long the delay is in case of delay, and knowing that another bus could be dispatched in case of breakdown. The surveys indicate that AVL technology could improve transit services and add value to passengers. The survey also found the expected ridership increase resulting from the AVL technology to be moderate. On-time performance surveys conducted in each city indicate that transit services in these communities generally operate on time at the route level. Although there are bigger variations at the timepoint level, transit services are usually on time. The implementation of AVL could further improve on-time performance, but maybe only marginally.
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- 2002
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15. Transit User Perceptions of the Benefits of Automatic Vehicle Location
- Author
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Peng, Zhong-Ren, Yu, Danlin, and Beimborn, Edward
- Abstract
An attitudinal survey on transit riders' perception of the importance transit users place on features of an automatic vehicle location (AVL) system is reported. Onboard surveys and on-time field checks were conducted in the cities of Manitowoc and Racine, Wisconsin, to determine how users in those cities perceive their transit systems and how well each transit system performs. The surveys indicate that transit riders put a great value on increased on-time performance and improved schedule reliability. Passengers value features that AVL technology could bring, such as improving on-time performance, knowing when the next bus will arrive, knowing how long the delay is in case of delay, and knowing that another bus could be dispatched in case of breakdown. The surveys indicate that AVL technology could improve transit services and add value to passengers. The survey also found the expected ridership increase resulting from the AVL technology to be moderate. On-time performance surveys conducted in each city indicate that transit services in these communities generally operate on time at the route level. Although there are bigger variations at the timepoint level, transit services are usually on time. The implementation of AVL could further improve on-time performance, but maybe only marginally.
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- 2002
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16. The varying effects of accessing high-speed rail system on China's county development: A geographically weighted panel regression analysis.
- Author
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Yu, Danlin, Zhang, Yaojun, Wu, Xiwei, Li, Ding, and Li, Guangdong
- Subjects
HIGH speed trains ,PANEL analysis ,REGRESSION analysis ,CENTROID ,EUCLIDEAN distance - Abstract
• Four HSR accessibility measurements are developed with GIS. • Geographically weighted panel regression method is developed. • HSR accessibility's impact on county development vary over space. • HSR has wider economic impact on county development. • HSR construction facilitates the balanced development landscape in China. The construction of high-speed rail in China was initiated to answer increasing demand for fast and convenient transportation systems connecting large economic centers. After the first high-speed rail was open for operation and the initial adjustment period, access to high-speed rail starts to bring fundamental changes in regional economic operation modes in China and drastically increase interconnectivity among places that are used to be farther apart. It is commonly understood that access to HSR will have significant impact on economic development. It is, however, also quite possible that the benefits to economic development brought by HSR will have a diminishing marginal effect. That is to say, the benefits brought by HSR to economic development tend to be the greatest when access to HSR is scarce. The benefits will decrease once access to HSR becomes more frequent. With data of HSR stations distribution and a set of panel data of socioeconomic information at county-level from 2008 – 2015 in China, this study creates four HSR accessibility indices and attempts to provide insights on how access to the HSR system supports China's county-level development. The first one simply measures the geographic distributions of HSR stations and feed the data to a global spatial panel model to investigate whether the presence of an HSR station will have significant impact on county development. The second one directly measures the accessibility to HSR based on road network travel time. The third one measures a Euclidean distance from the geometric center of the county to the nearest HSR station. The fourth one is an inclusive and inversed distance measure attempting to capture HSR's geographic influence. The last three indices will be used in a geographically weighted panel regression model to test the potential varying relationships between HSR accessibility and county development, controlling other socioeconomic factors. Our results suggest that on average the presence of an HSR station suggests about 2.7 % increase of that county's per capita GDP. The geographically weighted panel regression suggests that in places where HSR is sparsely distributed (access to HSR is scarce and less frequent), the relationship between HSR accessibility and GDP per capita is significant and positive. In places where HSR is densely distributed (access to HSR is more frequent), the relationship is less apparent. The current study explores the distribution of HSR and its contribution to county development in China. We hope the results will offer significant insights of the relationships between infrastructure construction and county economic development in both China and beyond. [ABSTRACT FROM AUTHOR]
- Published
- 2021
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17. Ensemble machine-learning-based framework for estimating total nitrogen concentration in water using drone-borne hyperspectral imagery of emergent plants: A case study in an arid oasis, NW China.
- Author
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Wang, Jingzhe, Shi, Tiezhu, Yu, Danlin, Teng, Dexiong, Ge, Xiangyu, Zhang, Zipeng, Yang, Xiaodong, Wang, Hanxi, and Wu, Guofeng
- Subjects
NITROGEN removal (Water purification) ,NITROGEN in water ,WATER quality monitoring ,WATER treatment plants ,WATER use ,CHLOROPHYLL in water - Abstract
In arid and semi-arid regions, water-quality problems are crucial to local social demand and human well-being. However, the conventional remote sensing-based direct detection of water quality parameters, especially using spectral reflectance of water, must satisfy certain preconditions (e.g., flat water surface and ideal radiation geometry). In this study, we hypothesized that drone-borne hyperspectral imagery of emergent plants could be better applied to retrieval total nitrogen (TN) concentration in water regardless of preconditions possibly due to the spectral responses of emergent plants on nitrogen removal and water purification. To test this hypothesis, a total of 200 groups of bootstrap samples were used to examine the relationship between the extracted TN concentrations from the drone-borne hyperspectral imagery of emergent plants and the experimentally measured TN concentrations in Ebinur Lake Oasis using four machine learning (ML) models (Partial Least Squares (PLS), Random Forest (RF), Extreme Learning Machine (ELM), and Gaussian Process (GP)). Through the introduction of the fractional order derivative (FOD), we build a decision-level fusion (DLF) model to minimize the regression results' biases of individual ML models. For individual ML model, GP performed the best. Still, the amount of uncertainty in individual ML models renders their performance to be subpar. The introduction of the DLF model greatly minimizes the regression results' biases. The DLF model allows to reduce potential uncertainties without sacrificing accuracy. In conclusion, the spectral response caused by nitrogen removal and water purification on emergent plants could be used to retrieve TN concentration in water with a DLF model framework. Our study offers a new perspective and a basic scientific support for water quality monitoring in arid regions. Image 1 • An indirect remote sensed method for retrieving total nitrogen concentration in water are proposed. • Fractional order derivative is an effective data mining technology for drone-borne hyperspectral data. • Decision-level fusion (DLF) model allows to reduce potential uncertainties without sacrificing accuracy. • Combined use of Bootstrap and DLF model is effective when dealing with small sample size. [ABSTRACT FROM AUTHOR]
- Published
- 2020
- Full Text
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18. Everyday Modernity in China. Madeleine Yue Dong and Joshua Goldstein, eds
- Author
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Yu, Danlin
- Published
- 2007
- Full Text
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19. The livable urban landscape: GIS and remote sensing extracted land use assessment for urban livability in Changchun Proper, China.
- Author
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Fu, Bo, Yu, Danlin, and Zhang, Yaojun
- Subjects
LAND use ,CITIES & towns ,REMOTE sensing ,GEOGRAPHIC information systems - Abstract
• Urban livability indicators are constructed using GIS and remote sensing techniques. • Principal component analysis-based method construct an urban livability index. • Standard values are suggested for urban livability as a benchmark. • Changchun's livability is assessed and discussed. Despite the popularity of the term urban livability, it is often used by different groups under different circumstances. A broader understanding of urban livability is that it concerns the quality of life in any human living environment. The World Health Organization, among many others, suggests a four-dimension assessment system based on the concepts of convenience, amenity, health and safety that can be used to evaluate any cities' potential livability. Following this proposal, the current study taps into the power of GIS and Remote Sensing technologies to generate a set of urban livability evaluating indicators via extracted land use information. Using the city proper of Changchun, Jilin Province of China as an example, the study extracts fifteen individual land use indicators from topographic maps and a remote sensing imagery. A principal component analysis-based approach was used to build an urban livability index with the fifteen indicators. Furthermore, with detailed examination of relevant studies, national documents and local fieldwork, this research also establishes potential benchmark values for all fifteen livability evaluating indicators for comparison purposes. Results suggest that slightly more than half of Changchun's city proper is above the livability benchmark in the framework of the current study. Residents' access to parks and open spaces is a major lagging factor for the city proper's livability. The study provides an alternative of quantifiable and verifiable approach for sustainable urban planning, especially from a land use policy perspective. [ABSTRACT FROM AUTHOR]
- Published
- 2019
- Full Text
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