Xiang Chen
I am an Assistant Professor in the Department of Geography at the University of Connecticut, Storrs, CT, USA. My research examines food access and their socioeconomic correlates in urban areas using innovative geospatial techniques, including Geographic Information Systems (GIS), spatial analysis, geovisualization, and space-time modeling. My latest project solicits individual food-themed activities from social media. My other research interest is emergency preparedness for natural disasters and terrorist attacks by assessing the vulnerability of urban transport infrastructure and by deriving the optimal placement of shelters.
My public website is: chenx.org
Address: Russellville, Arkansas, United States
My public website is: chenx.org
Address: Russellville, Arkansas, United States
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Papers by Xiang Chen
accessibility to Supplemental Nutrition Assistance Program (SNAP)-authorized retailers. First, the proposed method con-
siders the interaction between the food supply (in terms of categorized benefit redemptions) and demand (in terms of
benefit-receiving households). Second, the model is used to visualize food access patterns at the level of refined administra-
tive units (i.e., census block groups). The developed food access metric was compared to the U.S. Department of
Agriculture (USDA) Food Access Research Atlas, justifying the validity of this new method for small area estimation. The
following are important observations: (1) the choice of catchment size had a considerable impact on the accessibility
measure in urban areas (or when small statistical units are used); (2) the 2SFCA measurement had a higher level of corres-
pondence with that of the USDA Atlas at a smaller catchment size for identifying low food access units; and (3) there was
no significant inequality regarding SNAP accessibility with respect to different socioeconomic deprivation variables. This
new method can better assist the SNAP administration with store authorization on a refined geographic scale.
misperception in remote-sensing images that certain types of terrains are
visually interpreted as other types in rugged lands, for example, valleys as
ridges and troughs as peaks. For this reason, the FTPP can influence the
visualization and interpretation of images to a great extent. To scrutinize
this problem, the paper firstly reviews and tests the existing FTPP-
correction
techniques
and
identifies
the
inverse
slope-matching
technique as an effective approach to visually enhance remote-sensing
images and retain the colour information. The paper then proposes an
improved FTPP-correction procedure that incorporates other image-
processing techniques (e.g. linear stretch, histogram matching, and flat-
area replacement) to enhance the performance of this technique. A
further evaluation of the proposed technique is conducted by applying
the technique to various study areas and using different types of
remote-sensing images. The result indicates the method is relatively
robust and will be a significant extension to geovisual analytics in digital
earth research.
pathogens. An important factor that affects the mosquitoes’ development and spreading is climate, such as
temperature, precipitation and photoperiod. Existing climate-driven mechanistic models overlook the seasonal
pattern of diapause, referred to as the survival strategy of mosquito eggs being dormant and unable to hatch
under extreme weather. With respect to diapause, several issues remain unaddressed, including identifying the time
when diapause eggs are laid and hatched under different climatic conditions, demarcating the thresholds of
diapause and non-diapause periods, and considering the mortality rate of diapause eggs.
Methods: Here we propose a generic climate-driven mechanistic population model of Ae. albopitus applicable to
most Ae. albopictus-colonized areas. The new model is an improvement over the previous work by incorporating
the diapause behaviors with many modifications to the stage-specific mechanism of the mosquitoes’ life-cycle.
monthly Container Index (CI) of Ae. albopitus collected in two Chinese cities, Guangzhou and Shanghai is used for
model validation.
Results: The simulation results by the proposed model is validated with entomological field data by the Pearson
correlation coefficient r2in Guangzhou (r2=0.84) and in Shanghai (r2= 0.90). In addition, by consolidating the effect
of diapause-related adjustments and temperature-related parameters in the model, the improvement is significant
over the basic model.
Conclusions: The model highlights the importance of considering diapause in simulating Ae. albopitus population.
It also corroborates that temperature and photoperiod are significant in affecting the population dynamics of the
mosquito. By refining the relationship between Ae. albopitus population and climatic factors, the model serves to
establish a mechanistic relation to the growth and decline of the species. Understanding this relationship in a
better way will benefit studying the transmission and the spatiotemporal distribution of mosquito-borne epidemics
and eventually facilitating the early warning and control of the diseases.
food access through an analytic framework of the uncertain geographic context problem (UGCoP). We first examined the
compounding effects of two kinds of spatiotemporal uncertainties on people’s everyday efforts to procure food
and then outlined three key dimensions (food access in real time, temporality of the food environment, and perceived
nutrition environment) in which research on food access must improve to better represent the contributing environmental influences that operate at the individual level. Guidelines to address the UGCoP in future food access research are
provided to account for the multidimensional influences of the food environment on dietary behaviors.
accessibility to Supplemental Nutrition Assistance Program (SNAP)-authorized retailers. First, the proposed method con-
siders the interaction between the food supply (in terms of categorized benefit redemptions) and demand (in terms of
benefit-receiving households). Second, the model is used to visualize food access patterns at the level of refined administra-
tive units (i.e., census block groups). The developed food access metric was compared to the U.S. Department of
Agriculture (USDA) Food Access Research Atlas, justifying the validity of this new method for small area estimation. The
following are important observations: (1) the choice of catchment size had a considerable impact on the accessibility
measure in urban areas (or when small statistical units are used); (2) the 2SFCA measurement had a higher level of corres-
pondence with that of the USDA Atlas at a smaller catchment size for identifying low food access units; and (3) there was
no significant inequality regarding SNAP accessibility with respect to different socioeconomic deprivation variables. This
new method can better assist the SNAP administration with store authorization on a refined geographic scale.
misperception in remote-sensing images that certain types of terrains are
visually interpreted as other types in rugged lands, for example, valleys as
ridges and troughs as peaks. For this reason, the FTPP can influence the
visualization and interpretation of images to a great extent. To scrutinize
this problem, the paper firstly reviews and tests the existing FTPP-
correction
techniques
and
identifies
the
inverse
slope-matching
technique as an effective approach to visually enhance remote-sensing
images and retain the colour information. The paper then proposes an
improved FTPP-correction procedure that incorporates other image-
processing techniques (e.g. linear stretch, histogram matching, and flat-
area replacement) to enhance the performance of this technique. A
further evaluation of the proposed technique is conducted by applying
the technique to various study areas and using different types of
remote-sensing images. The result indicates the method is relatively
robust and will be a significant extension to geovisual analytics in digital
earth research.
pathogens. An important factor that affects the mosquitoes’ development and spreading is climate, such as
temperature, precipitation and photoperiod. Existing climate-driven mechanistic models overlook the seasonal
pattern of diapause, referred to as the survival strategy of mosquito eggs being dormant and unable to hatch
under extreme weather. With respect to diapause, several issues remain unaddressed, including identifying the time
when diapause eggs are laid and hatched under different climatic conditions, demarcating the thresholds of
diapause and non-diapause periods, and considering the mortality rate of diapause eggs.
Methods: Here we propose a generic climate-driven mechanistic population model of Ae. albopitus applicable to
most Ae. albopictus-colonized areas. The new model is an improvement over the previous work by incorporating
the diapause behaviors with many modifications to the stage-specific mechanism of the mosquitoes’ life-cycle.
monthly Container Index (CI) of Ae. albopitus collected in two Chinese cities, Guangzhou and Shanghai is used for
model validation.
Results: The simulation results by the proposed model is validated with entomological field data by the Pearson
correlation coefficient r2in Guangzhou (r2=0.84) and in Shanghai (r2= 0.90). In addition, by consolidating the effect
of diapause-related adjustments and temperature-related parameters in the model, the improvement is significant
over the basic model.
Conclusions: The model highlights the importance of considering diapause in simulating Ae. albopitus population.
It also corroborates that temperature and photoperiod are significant in affecting the population dynamics of the
mosquito. By refining the relationship between Ae. albopitus population and climatic factors, the model serves to
establish a mechanistic relation to the growth and decline of the species. Understanding this relationship in a
better way will benefit studying the transmission and the spatiotemporal distribution of mosquito-borne epidemics
and eventually facilitating the early warning and control of the diseases.
food access through an analytic framework of the uncertain geographic context problem (UGCoP). We first examined the
compounding effects of two kinds of spatiotemporal uncertainties on people’s everyday efforts to procure food
and then outlined three key dimensions (food access in real time, temporality of the food environment, and perceived
nutrition environment) in which research on food access must improve to better represent the contributing environmental influences that operate at the individual level. Guidelines to address the UGCoP in future food access research are
provided to account for the multidimensional influences of the food environment on dietary behaviors.