Yuke Zhou

Comparative Estimation of Urban Development in China’s Cities Using Socioeconomic and DMSP/OLS Night Light Data

China has been undergoing a remarkably rapid urbanization process in the last several decades. Urbanization is a complicated phenomenon involving imbalanced transformation processes, such as population migrations, economic advancements and human activity dynamics. It is important to evaluate the imbalances between transformation processes to support policy making in the realms of environmental management and urban planning. The Defense Meteorological Satellite Program’s Operational Linescan System (DMSP/OLS) nighttime lights time series imagery provides a consistent and timely measure to estimate socioeconomic dynamics and changes in human activity. In this study, we jointly compared the annual ranks of three variables: the population, the gross domestic product (GDP) and the sum of weighted DMSP/OLS nighttime lights to estimate spatial and temporal imbalances in the urbanization processes of 226 cities in China between 1994 and 2011. We used ternary plots and a Euclidean distance-based method to quantitatively estimate the spatial and temporal imbalances between cities and to classify diverse urban development patterns in China. Our results suggest that, from 1994 to 2011, the imbalances of urbanization processes observed in the eastern, western and middle cities decreased, respectively, by 35.26%, 29.04% and 25.84%; however, imbalances in the northeast increased by 33.29%. The average decrement in imbalances across all urbanization processes in the 226 cities was 17.58%. Cities in the eastern region displayed relatively strong attractions to population, more rapid economic development processes and lower imbalances between socioeconomic and anthropogenic dynamics than cities in other regions. Several types of urban development patterns can be identified by comparing the morphological characteristics of temporal ternary plots of the 226 cities in China. More than one third (35.40%) of the 226 cities presented balanced states during the period studied; however, the remainder showed alternative urban development patterns.

Characterizing Spatio-Temporal Dynamics of Urbanization in China Using Time Series of DMSP/OLS Night Light Data

Stable nighttime light (NTL) data, derived from the Defense Meteorological Satellite Program’s Operational Linescan System (DMSP/OLS), are typically considered a proxy measure of the dynamics of human settlements and have been extensively used to quantitative estimates of demographic variables, economic activity, and land-use change in previous studies at both regional and global scales. The utility of DMSP data for characterizing spatio-temporal trends in urban development at a local scale, however, has received less attention. In this study, we utilize a time series of DMSP data to examine the spatio-temporal characteristics of urban development in 285 Chinese cities from 1992 to 2009, at both the local and national levels. We compare linear models and piecewise linear models to identify the turning points of nighttime lights and calculate the trends in nighttime light growth at the pixel level. An unsupervised classification is applied to identify the patterns in the nighttime light time series quantitatively. Our results indicate that nighttime light brightness in most areas of China exhibit a positive, multi-stage process over the last two decades; however, the average trends in nighttime light growth differ significantly. Through the piecewise linear model, we identify the saturation of nighttime light brightness in the urban center and significant increases in suburban areas. The maps of turning points indicate the greater the distance to the city center or sub-center, the later the turning point occurs. Six patterns derived from the classification illustrate the various characteristics of the nighttime light time series from the local to the national level. The results portray spatially explicit patterns and conspicuous temporal trends of urbanization dynamics for individual Chinese cities from 1992 to 2009.

Nighttime Light Derived Assessment of Regional Inequality of Socioeconomic Development in China

Satellite-derived nighttime light (NTL) data have been extensively used as an efficient proxy measure for monitoring urbanization dynamics and socioeconomic activity. This is because remotely sensed NTL signals can be quantitatively connected to demographic and socioeconomic variables at regional and global scales. The recently composited cloud-free NTL imagery derived from the Visible Infrared Imaging Radiometer Suite (VIIRS) aboard the Suomi National Polar-orbiting Partnership (Suomi-NPP) satellite provides spatially detailed observations of human settlements. We quantitatively estimated socioeconomic development inequalities across 30 provinces and municipalities in mainland China using VIIRS NTL data associated with both regional gross domestic product (GDP) and population census data. We quantitatively investigated relations between NTL, GDP, and population using a linear regression model. Our results suggest that NTL radiances have significant positive correlations with GDP and population at different levels. Several inequality coefficients, commonly used in economics, were derived from VIIRS NTL data and statistical data at multiple spatial scales. Compared with the statistical data, NTL-derived inequality coefficients enabled us to elicit more detailed information on differences in regional development at multiple levels. Our study of provinces and municipalities revealed that county-level inequality was more significant than city-level inequality. The results of population-weighted NTL inequality indicate an obvious regional disparity with NTL distribution being more unequal in China’s undeveloped western regions compared with more developed eastern regions. Our findings suggest that given the timely and spatially explicit advantages of VIIRS, NTL data are capable of providing comprehensive information regarding inequality at multiple levels, which is not possible through the use of traditional statistical sources.

Diverse relationships between Suomi-NPP VIIRS night-time light and multi-scale socioeconomic activity

Satellite-based observation of anthropogenic night-time light radiance is typically considered as a proxy measure for human spatial behaviour in terms of demographic and economic dynamics owing to quantitative connections between night-time light and socioeconomic activity. Most previous studies have focused on the monotonic response of artificial night-time lighting, primarily derived from the Defense Meteorological Satellite Programs (DMSP) with spatial resolution of 30 arc-seconds to socioeconomic variables at regional to county scales. Using ordinary least squares regression and quantile regression, we investigate the quantitative relationship between a finer resolution night-time light data than DMSP derived from the Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi National Polar-orbiting Partnership satellite (Suomi-NPP) with spatial resolution of 15 arc-seconds and several demographic and economic factors across three local scales: county, district and sub-district in Xian City. Our results show diverse responses of night-time light radiance to multiscale socioeconomic variables: (1) monotonic relationship following linear or log-linear models is most likely to occur at the county scale, (2) various responses of the conditional quantiles of night-time lights to socioeconomic variables is highly prominent at both the district scale and the sub-district scale in association with non-monotonic relationship. Our findings may provide insight into the practical applications of fine resolution night-time imagery such as VIIRS data for quantitatively estimating human activity and socioeconomic dynamics at a fine scale.

Changes in Spatial Patterns of Urban Landscape in Bohai Rim from 1992 to 2010 Using DMSP-OLS Data

The photoelectric amplification characteristics of Operational Linescan System(OLS) sensors on board of the Defense Meteorological Satellite Programs(DMSP) satellites make the instruments sensitive to low visible lights in the night which can distinguish the differences of light signals between urban and rural areas.Remotely sensed nighttime lights datasets derived from the DMSP-OLS sensors have been extensively applied to assess and monitor the process of urbanization and human activities,which has become an important data source for studies on regional urbanization and human activities.Methods used to extract urban built-up areas from DMSP-OLS data,such as empirical global thresholding-based methods and the sudden detection method,cannot avoid their own defects.The experience thresholding values are not universal in different regions and the sudden detection method cannot be applied in large scales.In this study,we corrected the experience thresholding values by introducing statistical data of some sample cities in the research area which combined with a calibration process to DMSP-OLS time serial data for extracting urban built-up area from satellite-based nighttime light data at large temporal and spatial scales.Nine landscape metrics: the number of patches(NP),the landscape total area(TA),the mean patch size(MPS),the largest patch index(LPI),the patches density of per hundred km2(PDh),the landscape shape index(LSI),the total edge length(TE),the edge density(ED) and the radius of gyration(GYRATE) are calculated by the FRAGSTATS3.3 software to analysis the spatial pattern change characteristics of urban area in Bohai Rim.The study showed that from 1992 to 2010,the urbanization in Bohai Rim experienced a continuing and rapid process.In this region,the total urban built-up areas expanded for 2.14 times,the average built-up area of cities increased for 76%,the gyrate of extracted urban patches expanded about 26.5% which suggested that the complexity of urban patch shapes were increased.The amount of detected urban patches got 82% increase but the number of isolate cities in each 100 km2 were decreased by about 76% which implied that the expansion of traditional cities was the dominant factor of the area increasing rather than continuously emerging towns.The expansions of metropolises were slower than small cities,and the overall landscape fragmentation degree was decreased gradually with the trend of urban area connection between core cities and their exurbs.

A new approach to the application of DMSP/OLS nighttime light data to urbanization assessment

In this study, we proposed a new method for extracting urban built-up area from satellite-based nighttime light data. Our methods are based on locally thresholding correction of nighttime lights in association with economic statistical data (termed TC-ESD). We grouped Chinas cities into a series of categories according to gross domestic product and geographical regions. Category-based thresholds of night light brightness used in extracting urban extent were obtained for different categories of cities from a comprehensive consideration of nighttime lights and economic activities. In comparison with uniform empirical thresholding method, our results show that TC-ESD method could markedly improve the recognition accuracy of urban built-up area from nightlight data for individual cities.

Spatial analysis of growing season peak control over gross primary production in northern ecosystems using modis-GPP dataset

The Northern Hemisphere terrestrial ecosystems play a key role in the global carbon cycle and climate change. Satellite-derived dataset makes it be available of continuous estimates of Gross Primary Production (GPP) across Earths entire vegetated land surface. The extended growing season length (GSL) and its impacts on carbon uptake is well documented in the literature, but how the amplitude of GPP (i.e., GPPmax) occurring in the vegetation growing peak contribute to the annual GPP is not understood well. Here we used Modis GPP dataset to explore the impacts of GSL and GPPmax on the developing trend of annual GPP. Our results indicate that GPPmax is more strongly correlated with annual GPP than GSL. These findings highlight the important contribution of maximum GPP to the annual GPP and suggest further studies are needed on the carbon uptake in the favorable growing season.

Profile human-induced vegetation change in ArHorqin banner of China using time series datasets

Discriminating human-induced vegetation change is essential for sustainable managements of arid and semi-arid ecosystems. Residual Trends method (RESTREND), an effective quantitative method, has been widely used to discriminate human-induced vegetation changes in specific arid and semi-arid ecosystems. However, how to define homogeneous spatial neighborhood to determine reference pixel for estimating potential climate-solely-induced vegetation growth is still a challenge. This paper firstly detected vegetation dynamics in ArHorqin Banner of China from 2000 to 2014 by Mann-Kendall method, and then used RESTREND to profile human-induced changes. We optimized strategy in RESTREND by using statistical analysis and trajectory analysis to automatically define flexible homogeneous neighborhood. Results indicated that 18.6% of study area had significantly changes. Both climate change and human activities contributed to the changes. The influence of human activities on vegetation dynamics is more than climate change, and it was the main driver for vegetation decrease in study area.