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Liang Cheng
Henry Fok College of Biology and Agriculture, Shaoguan University, Daxue Road 26, Shaoguan 512005, China

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Journal article
Published: 28 July 2021 in Land
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Population data are key indicators of policymaking, public health, and land use in urban and ecological systems; however, traditional censuses are time-consuming, expensive, and laborious. This study proposes a method of modelling population density estimations based on remote sensing data in Hefei. Four models with impervious surface (IS), night light (NTL), and point of interest (POI) data as independent variables are constructed at the township scale, and the optimal model was applied to pixels to obtain a finer population density distribution. The results show that: (1) impervious surface (IS) data can be effectively extracted by the linear spectral mixture analysis (LSMA) method; (2) there is a high potential of the multi-variable model to estimate the population density, with an adjusted R2 of 0.832, and mean absolute error (MAE) of 0.420 from 10-fold cross validation recorded; (3) downscaling the predicted population density from the township scale to pixels using the multi-variable stepwise regression model achieves a more refined population density distribution. This study provides a promising method for the rapid and effective prediction of population data in interval years, and data support for urban planning and population management.

ACS Style

Jinyu Zang; Ting Zhang; Longqian Chen; Long Li; Weiqiang Liu; Lina Yuan; Yu Zhang; Ruiyang Liu; Zhiqiang Wang; Ziqi Yu; Jia Wang. Optimization of Modelling Population Density Estimation Based on Impervious Surfaces. Land 2021, 10, 791 .

AMA Style

Jinyu Zang, Ting Zhang, Longqian Chen, Long Li, Weiqiang Liu, Lina Yuan, Yu Zhang, Ruiyang Liu, Zhiqiang Wang, Ziqi Yu, Jia Wang. Optimization of Modelling Population Density Estimation Based on Impervious Surfaces. Land. 2021; 10 (8):791.

Chicago/Turabian Style

Jinyu Zang; Ting Zhang; Longqian Chen; Long Li; Weiqiang Liu; Lina Yuan; Yu Zhang; Ruiyang Liu; Zhiqiang Wang; Ziqi Yu; Jia Wang. 2021. "Optimization of Modelling Population Density Estimation Based on Impervious Surfaces." Land 10, no. 8: 791.

Journal article
Published: 10 July 2021 in ISPRS International Journal of Geo-Information
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The remote-sensing ecological index (RSEI), which is built with greenness, moisture, dryness, and heat, has become increasingly recognized for its use in urban eco-environment quality assessment. To improve the reliability of such assessment, we propose a new RSEI-based urban eco-environment quality assessment method where the impact of RSEI indicators on the eco-environment quality and the seasonal change of RSEI are examined and considered. The northern Chinese municipal city of Tianjin was selected as a case study to test the proposed method. Landsat images acquired in spring, summer, autumn, and winter were obtained and processed for three different years (1992, 2005, and 2018) for a multitemporal analysis. Results from the case study show that both the contributions of RSEI indicators to eco-environment quality and RSEI values vary with the season and that such seasonal variability should be considered by normalizing indicator measures differently and using more representative remote-sensing images, respectively. The assessed eco-environment quality of Tianjin was, overall, improving owing to governmental environmental protection measures, but the damage caused by rapid urban expansion and sea reclamation in the Binhai New Area still needs to be noted. It is concluded that our proposed urban eco-environment quality assessment method is viable and can provide a reliable assessment result that helps gain a more accurate understanding of the evolution of the urban eco-environment quality over seasons and years.

ACS Style

Ting Zhang; Ruiqing Yang; Yibo Yang; Long Li; Longqian Chen. Assessing the Urban Eco-Environmental Quality by the Remote-Sensing Ecological Index: Application to Tianjin, North China. ISPRS International Journal of Geo-Information 2021, 10, 475 .

AMA Style

Ting Zhang, Ruiqing Yang, Yibo Yang, Long Li, Longqian Chen. Assessing the Urban Eco-Environmental Quality by the Remote-Sensing Ecological Index: Application to Tianjin, North China. ISPRS International Journal of Geo-Information. 2021; 10 (7):475.

Chicago/Turabian Style

Ting Zhang; Ruiqing Yang; Yibo Yang; Long Li; Longqian Chen. 2021. "Assessing the Urban Eco-Environmental Quality by the Remote-Sensing Ecological Index: Application to Tianjin, North China." ISPRS International Journal of Geo-Information 10, no. 7: 475.

Journal article
Published: 16 April 2021 in Polish Journal of Environmental Studies
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While they are an effective tool for studying landscape patterns and describing land-use change, landscape metrics are sensitive to variation in spatial grain sizes. It is therefore crucially important to select an optimal grain size for characterizing urban landscape patterns. Due to accelerated urbanization, Shanghai, the economic capital of China, has seen drastic changes in landscape patterns in recent decades and it would be interesting to take Shanghai as an example for examining the grain effect of landscape patterns. In this study, from Shanghai’s land use maps derived from Landsat images of 1998, 2007, and 2017 via random forest classification, a selection of landscape metrics was measured with 14 grain sizes ranging from 30 m to 460 m. Both the conventional first scale domain method and the information loss evaluation model were adopted to comprehensively determine an optimal grain size for characterizing Shanghai’s landscape pattern. After that, the land use dynamic degree model was used to explore the change in Shanghai’s landscape pattern under the optimal grain size. Results demonstrate that (1) the responses of landscape metrics varied with grain size, which could be divided into three categories, namely irregular trend, decreasing trend, and no clear change; that (2) the optimal spatial grain size for landscape pattern analysis was 60 m; and that (3) the degree of landscape aggregation decreased, whereas that of landscape diversity and fragmentation increased. This study shows a clear grain effect of landscape patterns and can provide useful insights for urban landscape planning.

ACS Style

Jia Wang; Long Li; Ting Zhang; Longqian Chen; Mingxin Wen; Weiqiang Liu; Sai Hu. Optimal Grain Size Based Landscape Pattern Analysis for Shanghai Using Landsat Images from 1998 to 2017. Polish Journal of Environmental Studies 2021, 30, 2799 -2813.

AMA Style

Jia Wang, Long Li, Ting Zhang, Longqian Chen, Mingxin Wen, Weiqiang Liu, Sai Hu. Optimal Grain Size Based Landscape Pattern Analysis for Shanghai Using Landsat Images from 1998 to 2017. Polish Journal of Environmental Studies. 2021; 30 (3):2799-2813.

Chicago/Turabian Style

Jia Wang; Long Li; Ting Zhang; Longqian Chen; Mingxin Wen; Weiqiang Liu; Sai Hu. 2021. "Optimal Grain Size Based Landscape Pattern Analysis for Shanghai Using Landsat Images from 1998 to 2017." Polish Journal of Environmental Studies 30, no. 3: 2799-2813.

Journal article
Published: 06 April 2021 in ISPRS International Journal of Geo-Information
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This study aims to integrate multisource data to model the relative soil moisture (RSM) over the Chinese Loess Plateau in 2017 by stepwise multilinear regression (SMLR) in order to improve the spatial coverage of our previously published RSM. First, 34 candidate variables (12 quantitative and 22 dummy variables) from the Moderate Resolution Imaging Spectroradiometer (MODIS) and topographic, soil properties, and meteorological data were preprocessed. Then, SMLR was applied to variables without multicollinearity to select statistically significant (p-value < 0.05) variables. After the accuracy assessment, monthly, seasonal, and annual spatial patterns of RSM were mapped at 500 m resolution and evaluated. The results indicate that there was a high potential of SMLR to model RSM with the desired accuracy (best fit of the model with Pearson’s r = 0.969, root mean square error = 0.761%, and mean absolute error = 0.576%) over the Chinese Loess Plateau. The variables of elevation (0–500 m and 2000–2500 m), precipitation, soil texture of loam, and nighttime land surface temperature can continuously be used in the regression models for all seasons. Including dummy variables improved the model fit both in calibration and validation. Moreover, the SMLR-modeled RSM achieved better spatial coverage than that of the reference RSM for almost all periods. This is a significant finding as the SMLR method supports the use of multisource data to complement and/or replace coarse resolution satellite imagery in the estimation of RSM.

ACS Style

Lina Yuan; Long Li; Ting Zhang; Longqian Chen; Weiqiang Liu; Sai Hu; Longhua Yang. Modeling Soil Moisture from Multisource Data by Stepwise Multilinear Regression: An Application to the Chinese Loess Plateau. ISPRS International Journal of Geo-Information 2021, 10, 233 .

AMA Style

Lina Yuan, Long Li, Ting Zhang, Longqian Chen, Weiqiang Liu, Sai Hu, Longhua Yang. Modeling Soil Moisture from Multisource Data by Stepwise Multilinear Regression: An Application to the Chinese Loess Plateau. ISPRS International Journal of Geo-Information. 2021; 10 (4):233.

Chicago/Turabian Style

Lina Yuan; Long Li; Ting Zhang; Longqian Chen; Weiqiang Liu; Sai Hu; Longhua Yang. 2021. "Modeling Soil Moisture from Multisource Data by Stepwise Multilinear Regression: An Application to the Chinese Loess Plateau." ISPRS International Journal of Geo-Information 10, no. 4: 233.

Journal article
Published: 07 February 2021 in Remote Sensing
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Accuracy soil moisture estimation at a relevant spatiotemporal scale is scarce but beneficial for understanding ecohydrological processes and improving weather forecasting and climate models, particularly in arid and semi-arid regions like the Chinese Loess Plateau (CLP). This study proposed Criterion 2, a new method to improve relative soil moisture (RSM) estimation by identification of normalized difference vegetation index (NDVI) thresholds optimization based on our previously proposed iteration procedure of Criterion 1. Apparent thermal inertia (ATI) and temperature vegetation dryness index (TVDI) were applied to subregional RSM retrieval for the CLP throughout 2017. Three optimal NDVI thresholds (NDVI0 was used for computing TVDI, and both NDVIATI and NDVITVDI for dividing the entire CLP) were firstly identified with the best validation results () of subregions for 8-day periods. Then, we compared the selected optimal NDVI thresholds and estimated RSM with each criterion. Results show that NDVI thresholds were optimized to robust RSM estimation with Criterion 2, which characterized RSM variability better. The estimated RSM with Criterion 2 showed increased accuracy (maximum of 0.82 ± 0.007 for Criterion 2 and of 0.75 ± 0.008 for Criterion 1) and spatiotemporal coverage (45 and 38 periods (8-day) of RSM maps and the total RSM area of 939.52 × 104 km2 and 667.44 × 104 km2 with Criterion 2 and Criterion 1, respectively) than with Criterion 1. Moreover, the additional NDVI thresholds we applied was another strategy to acquire wider coverage of RSM estimation. The improved RSM estimation with Criterion 2 could provide a basis for forecasting drought and precision irrigation management.

ACS Style

Lina Yuan; Long Li; Ting Zhang; Longqian Chen; Jianlin Zhao; Weiqiang Liu; Liang Cheng; Sai Hu; Longhua Yang; Mingxin Wen. Improving Soil Moisture Estimation by Identification of NDVI Thresholds Optimization: An Application to the Chinese Loess Plateau. Remote Sensing 2021, 13, 589 .

AMA Style

Lina Yuan, Long Li, Ting Zhang, Longqian Chen, Jianlin Zhao, Weiqiang Liu, Liang Cheng, Sai Hu, Longhua Yang, Mingxin Wen. Improving Soil Moisture Estimation by Identification of NDVI Thresholds Optimization: An Application to the Chinese Loess Plateau. Remote Sensing. 2021; 13 (4):589.

Chicago/Turabian Style

Lina Yuan; Long Li; Ting Zhang; Longqian Chen; Jianlin Zhao; Weiqiang Liu; Liang Cheng; Sai Hu; Longhua Yang; Mingxin Wen. 2021. "Improving Soil Moisture Estimation by Identification of NDVI Thresholds Optimization: An Application to the Chinese Loess Plateau." Remote Sensing 13, no. 4: 589.

Journal article
Published: 03 January 2021 in Sustainability
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The land ecosystem provides essential natural resources for the survival and development of human beings. Therefore, land ecological security (LES) acts as a vital part of the sustainable development of human society and economy. This study included a dynamic analysis of land use change in Chaohu Lake Basin (CLB) in China from 1998 to 2018, evaluating the spatiotemporal patterns of LES at both the administrative district scale and grid scale (200 m × 200 m). Then, geographic detector was applied to analyze the influence of the assessment index on LES. The results show that in the 2008–2018 period, land use changed more significantly compared to the 1998–2008 period. The continuous extension of urban land led to a decrease in the areas of other land use types. In the CLB (administrative district scale), the LES levels varied throughout the study period. In Changfeng, Feixi, and the other three regions, the LES has been significantly improved. However, the LES in six other regions showed different degrees of decline, particularly in Hexian and Urban Hefei. Simultaneously, the LES showed a gradual improvement at a 200 m × 200 m grid scale level. The influence of anthropogenic factors on the LES was stronger than natural factors. Findings from this study provide reliable guidance for improving the ecosystem environment in ecologically fragile areas.

ACS Style

Mingxin Wen; Ting Zhang; Long Li; Longqian Chen; Sai Hu; Jia Wang; Weiqiang Liu; Yu Zhang; Lina Yuan. Assessment of Land Ecological Security and Analysis of Influencing Factors in Chaohu Lake Basin, China from 1998–2018. Sustainability 2021, 13, 358 .

AMA Style

Mingxin Wen, Ting Zhang, Long Li, Longqian Chen, Sai Hu, Jia Wang, Weiqiang Liu, Yu Zhang, Lina Yuan. Assessment of Land Ecological Security and Analysis of Influencing Factors in Chaohu Lake Basin, China from 1998–2018. Sustainability. 2021; 13 (1):358.

Chicago/Turabian Style

Mingxin Wen; Ting Zhang; Long Li; Longqian Chen; Sai Hu; Jia Wang; Weiqiang Liu; Yu Zhang; Lina Yuan. 2021. "Assessment of Land Ecological Security and Analysis of Influencing Factors in Chaohu Lake Basin, China from 1998–2018." Sustainability 13, no. 1: 358.

Journal article
Published: 04 October 2020 in Atmosphere
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Urbanization is a key determinant of fine particulate matter (PM2.5) pollution variability. However, there is a limited understanding of different urbanization factors’ roles in PM2.5 pollution. Using satellite-derived PM2.5 data from 2002 to 2017, we investigated the spatiotemporal evolution and the spatial autocorrelation of PM2.5 pollution in the Yangtze River Delta (YRD) region. Afterwards, the impacts of three urbanization factors (population urbanization, land urbanization and economic urbanization) on PM2.5 pollution were estimated by a spatial Durbin panel data model (SDM). Obtained results showed that: (i) PM2.5 pollution was larger in the north than in the south of YRD; (ii) Lianyungang and Yancheng cities had significant increasing trends in PM2.5 pollution from 2002 to 2017; (iii) the regional median center of PM2.5 pollution was observed in the Nanjing city, with gradual shifting to the northwest during the 16-year period; (iv) PM2.5 pollution showed significant and positive spatial autocorrelation and spillover effect; (v) population urbanization contributed more to the increase in PM2.5 pollution than land urbanization, while economic urbanization had no significant impact. The present study highlights the impacts of three urbanization factors on PM2.5 pollution which represent valuable and relevant information for air pollution control and urban planning.

ACS Style

Liang Cheng; Ting Zhang; Longqian Chen; Long Li; Shangjiu Wang; Sai Hu; Lina Yuan; Jia Wang; Mingxin Wen. Investigating the Impacts of Urbanization on PM2.5 Pollution in the Yangtze River Delta of China: A Spatial Panel Data Approach. Atmosphere 2020, 11, 1058 .

AMA Style

Liang Cheng, Ting Zhang, Longqian Chen, Long Li, Shangjiu Wang, Sai Hu, Lina Yuan, Jia Wang, Mingxin Wen. Investigating the Impacts of Urbanization on PM2.5 Pollution in the Yangtze River Delta of China: A Spatial Panel Data Approach. Atmosphere. 2020; 11 (10):1058.

Chicago/Turabian Style

Liang Cheng; Ting Zhang; Longqian Chen; Long Li; Shangjiu Wang; Sai Hu; Lina Yuan; Jia Wang; Mingxin Wen. 2020. "Investigating the Impacts of Urbanization on PM2.5 Pollution in the Yangtze River Delta of China: A Spatial Panel Data Approach." Atmosphere 11, no. 10: 1058.

Journal article
Published: 17 September 2020 in Remote Sensing
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Timely and effective estimation and monitoring of soil moisture (SM) provides not only an understanding of regional SM status for agricultural management or potential drought but also a basis for characterizing water and energy exchange. The apparent thermal inertia (ATI) and Temperature Vegetation Dryness Index (TVDI) are two widely used indices to reflect SM from remote sensing data. While the ATI-based model is routinely used to estimate the SM of bare soil and sparsely vegetated areas, the TVDI-based model is more suitable for areas with dense vegetation coverage. In this study, we present an iteration procedure that allows us to identify optimal Normalized Difference Vegetation Index (NDVI) thresholds for subregions and estimate their relative soil moisture (RSM) using three models (the ATI-based model, the TVDI-based model, and the ATI/TVDI joint model) from January 1 to December 31, 2017, in the Chinese Loess Plateau. The initial NDVI (NDVI0) was first introduced to obtain TVDI value and two other thresholds of NDVIATI and NDVITVDI were designed for dividing the whole area into three subregions (the ATI subregion, the TVDI subregion, and the ATI/TVDI subregion). The NDVI values corresponding to maximum R-values (correlation coefficient) between estimated RSM and in situ RSM measurements were chosen as optimal NDVI thresholds after performing as high as 48,620 iterations with 10 rounds of 10-fold cross-calibration and validation for each period. An RSM map of the whole study area was produced by merging the RSM of each of the three subregions. The spatiotemporal and comparative analysis further indicated that the ATI/TVDI joint model has higher applicability (accounting for 36/38 periods) and accuracy than the ATI-based and TVDI-based models. The highest average R-value between the estimated RSM and in situ RSM measurements was 0.73±0.011 (RMSE—root mean square error, 3.43±0.071% and MAE—mean absolute error, 0.05±0.025) on the 137th day of 2017 (DOY—day of the year, 137). Although there is potential for improved mapping of RSM for the entire Chinese Loess Plateau, the iteration procedure of identifying optimal thresholds determination offers a promising method for achieving finer-resolution and robust RSM estimation in large heterogeneous areas.

ACS Style

Lina Yuan; Long Li; Ting Zhang; Longqian Chen; Jianlin Zhao; Sai Hu; Liang Cheng; Weiqiang Liu. Soil Moisture Estimation for the Chinese Loess Plateau using MODIS-derived ATI and TVDI. Remote Sensing 2020, 12, 3040 .

AMA Style

Lina Yuan, Long Li, Ting Zhang, Longqian Chen, Jianlin Zhao, Sai Hu, Liang Cheng, Weiqiang Liu. Soil Moisture Estimation for the Chinese Loess Plateau using MODIS-derived ATI and TVDI. Remote Sensing. 2020; 12 (18):3040.

Chicago/Turabian Style

Lina Yuan; Long Li; Ting Zhang; Longqian Chen; Jianlin Zhao; Sai Hu; Liang Cheng; Weiqiang Liu. 2020. "Soil Moisture Estimation for the Chinese Loess Plateau using MODIS-derived ATI and TVDI." Remote Sensing 12, no. 18: 3040.

Journal article
Published: 13 June 2020 in International Journal of Environmental Research and Public Health
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Land use change has a significant impact on the structure and function of ecosystems, and the transformation of ecosystems affects the mode and efficiency of land use, which reflects a mutual interaction relationship. The prediction and simulation of future land use change can enhance the foresight of land use planning, which is of great significance to regional sustainable development. In this study, future land use changes are characterized under an ecological optimization scenario based on the grey prediction (1,1) model (GM) and a future land use simulation (FLUS) model. In addition, the ecosystem service value (ESV) of Anhui Province from 1995 to 2030 were estimated based on the revised estimation model. The results indicate the following details: (1) the FLUS model was used to simulate the land use layout of Anhui Province in 2018, where the overall accuracy of the simulation results is high, indicating that the FLUS model is applicable for simulating future land use change; (2) the spatial layout of land use types in Anhui Province is stable and the cultivated land has the highest proportion. The most significant characteristic of future land use change is that the area of cultivated land continues to decrease while the area of built-up land continues to expand; and (3) the ESV of Anhui Province is predicted to increase in the future. The regulating service is the largest ESV contributor, and water area is the land use type with the highest proportion of ESV. These findings provide reference for the formulation of sustainable development policies of the regional ecological environment.

ACS Style

Sai Hu; Longqian Chen; Long Li; Ting Zhang; Lina Yuan; Liang Cheng; Jia Wang; Mingxin Wen. Simulation of Land Use Change and Ecosystem Service Value Dynamics under Ecological Constraints in Anhui Province, China. International Journal of Environmental Research and Public Health 2020, 17, 1 .

AMA Style

Sai Hu, Longqian Chen, Long Li, Ting Zhang, Lina Yuan, Liang Cheng, Jia Wang, Mingxin Wen. Simulation of Land Use Change and Ecosystem Service Value Dynamics under Ecological Constraints in Anhui Province, China. International Journal of Environmental Research and Public Health. 2020; 17 (12):1.

Chicago/Turabian Style

Sai Hu; Longqian Chen; Long Li; Ting Zhang; Lina Yuan; Liang Cheng; Jia Wang; Mingxin Wen. 2020. "Simulation of Land Use Change and Ecosystem Service Value Dynamics under Ecological Constraints in Anhui Province, China." International Journal of Environmental Research and Public Health 17, no. 12: 1.

Journal article
Published: 22 April 2020 in ISPRS International Journal of Geo-Information
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Volcanic activity remains highly detrimental to populations, property and activities in the range of its products. In order to reduce the impact of volcanic processes and products, it is critically important to conduct comprehensive volcanic risk assessments on volcanically active areas. This study tests a volcanic risk assessment methodology based on numerical simulations of volcanic hazards and quantitative analysis of social vulnerability in the Spanish island of Tenerife, a well-known tourist destination. We first simulated the most likely volcanic hazards in the two eruptive scenarios using the Volcanic Risk Information System (VORIS) tool and then evaluated the vulnerability using a total of 19 socio-economic indicators within the Vulnerability Scoping Diagram (VSD) framework by combining the analytic hierarchy process (AHP) and the entropy method. Our results show good agreement with previous assessments. In two eruptive scenarios, the north and northwest of the island were more exposed to volcanic hazards, and the east registered the highest vulnerability. Overall, the northern municipalities showed the highest volcanic risk in two scenarios. Our test indicates that disaster risk varies greatly across the island, and that risk reduction strategies should be prioritized on the north areas. While refinements to the model will produce more accurate results, the outputs will still be beneficial to the local authorities when designing policies for volcanic risk reduction policies in Tenerife. This study tests a comprehensive volcanic risk assessment for Tenerife, but it also provides a framework that is applicable to other regions threatened by volcanic hazards.

ACS Style

Weiqiang Liu; Long Li; Longqian Chen; Mingxin Wen; Jia Wang; Lina Yuan; Yunqiang Liu; Han Li. Testing a Comprehensive Volcanic Risk Assessment of Tenerife by Volcanic Hazard Simulations and Social Vulnerability Analysis. ISPRS International Journal of Geo-Information 2020, 9, 273 .

AMA Style

Weiqiang Liu, Long Li, Longqian Chen, Mingxin Wen, Jia Wang, Lina Yuan, Yunqiang Liu, Han Li. Testing a Comprehensive Volcanic Risk Assessment of Tenerife by Volcanic Hazard Simulations and Social Vulnerability Analysis. ISPRS International Journal of Geo-Information. 2020; 9 (4):273.

Chicago/Turabian Style

Weiqiang Liu; Long Li; Longqian Chen; Mingxin Wen; Jia Wang; Lina Yuan; Yunqiang Liu; Han Li. 2020. "Testing a Comprehensive Volcanic Risk Assessment of Tenerife by Volcanic Hazard Simulations and Social Vulnerability Analysis." ISPRS International Journal of Geo-Information 9, no. 4: 273.

Journal article
Published: 13 February 2020 in Remote Sensing
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Global Navigation Satellite System (GNSS) tomography is a popular method for measuring and modelling water vapor in the troposphere. Presently, most studies use a cuboid-shaped tomographic region in their modelling, which represents the modelling region for all measurement epochs. This region is defined by the distribution of the GNSS signals skywards from a network of ground based GNSS stations for all epochs of measurements. However, in reality at each epoch the shape of the GNSS tomographic region is more likely to be an inverted cone. Unfortunately, this fixed conic tomographic region does not properly reflect the fact that the GNSS signal changes quickly over time. Therefore a dynamic or adaptive tomographic region is better suited. In this study, a new approach that adjusts the GNSS tomographic model to adapt the size of the GNSS network is proposed, which referred to as The High Flexibility GNSS Tomography (HFGT). Test data from different numbers of the GNSS stations are used and the results from HFGT are compared against that of radiosonde data (RS) to assess the accuracy of the HFGT approach. The results showed that the new approach is feasible for different numbers of the GNSS stations when a sufficient and uniformed distribution of GNSS signals is used. This is a novel approach for GNSS tomography.

ACS Style

Yuchen Wang; Nan Ding; Yu Zhang; Long Li; Xiaoyan Yang; Qingzhi Zhao. A New Approach of the Global Navigation Satellite System Tomography for Any Size of GNSS Network. Remote Sensing 2020, 12, 617 .

AMA Style

Yuchen Wang, Nan Ding, Yu Zhang, Long Li, Xiaoyan Yang, Qingzhi Zhao. A New Approach of the Global Navigation Satellite System Tomography for Any Size of GNSS Network. Remote Sensing. 2020; 12 (4):617.

Chicago/Turabian Style

Yuchen Wang; Nan Ding; Yu Zhang; Long Li; Xiaoyan Yang; Qingzhi Zhao. 2020. "A New Approach of the Global Navigation Satellite System Tomography for Any Size of GNSS Network." Remote Sensing 12, no. 4: 617.

Journal article
Published: 21 January 2020 in Forests
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Urban vegetation biomass is a key indicator of the carbon storage and sequestration capacity and ecological effect of an urban ecosystem. Rapid and effective monitoring and measurement of urban vegetation biomass provide not only an understanding of urban carbon circulation and energy flow but also a basis for assessing the ecological function of urban forest and ecology. In this study, field observations and Sentinel-2A image data were used to construct models for estimating urban vegetation biomass in the case study of the east Chinese city of Xuzhou. Results show that (1) Sentinel-2A data can be used for urban vegetation biomass estimation; (2) compared with the Boruta based multiple linear regression models, the stepwise regression models—also multiple linear regression models—achieve better estimations (RMSE = 7.99 t/hm2 for low vegetation, 45.66 t/hm2 for broadleaved forest, and 6.89 t/hm2 for coniferous forest); (3) the models for specific vegetation types are superior to the models for all-type vegetation; and (4) vegetation biomass is generally lowest in September and highest in January and December. Our study demonstrates the potential of the free Sentinel-2A images for urban ecosystem studies and provides useful insights on urban vegetation biomass estimation with such satellite remote sensing data.

ACS Style

Long Li; Xisheng Zhou; Longqian Chen; Yu Zhang; Yunqiang Liu. Estimating Urban Vegetation Biomass from Sentinel-2A Image Data. Forests 2020, 11, 125 .

AMA Style

Long Li, Xisheng Zhou, Longqian Chen, Yu Zhang, Yunqiang Liu. Estimating Urban Vegetation Biomass from Sentinel-2A Image Data. Forests. 2020; 11 (2):125.

Chicago/Turabian Style

Long Li; Xisheng Zhou; Longqian Chen; Yu Zhang; Yunqiang Liu. 2020. "Estimating Urban Vegetation Biomass from Sentinel-2A Image Data." Forests 11, no. 2: 125.

Journal article
Published: 13 December 2019 in International Journal of Environmental Research and Public Health
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Urbanization-induced land-use change will lead to variations in the demand and supply of ecosystem services, thus significantly affecting regional ecosystem services. The continuous degradation of ecosystem functions has become a serious problem for humanity to solve. Therefore, quantitative analysis of the corresponding impact of land-use change on ecosystem service value (ESV) is important to socio-economic development and ecological protection. The Anhui province in China has experienced rapid urbanization in recent years, and ecological environmental remediation and protection have become important goals for regional development. In this paper, the province of Anhui has been selected as a case of study, we analyzed the land-use change using Landsat images from 2000, 2005, 2010, and 2015. We then adjusted the equivalent factor of ESV per unit area and estimated the ESV of Anhui province from 2000 to 2015 to analyze the impact of land-use change on ESV. Our results show that (1) paddy field is the main land-use type in Anhui province, the built-up land area has continuously increased, and the water area has continuously decreased; (2) the total ESV of Anhui province decreased from 30,015.58 × 107 CNY in 2000 to 29,683.74 × 107 CNY in 2015 (the rate of change was −1.11%), and regulating services make the greatest contribution to ESV; and (3) land-use change has led to severe ESV variations, especially for the expansion of water area and built-up land. Our study results provide useful insights for the development of land-use management and environmental protection policies in Anhui province.

ACS Style

Sai Hu; Longqian Chen; Long Li; Bingyi Wang; Lina Yuan; Liang Cheng; Ziqi Yu; Ting Zhang. Spatiotemporal Dynamics of Ecosystem Service Value Determined by Land-Use Changes in the Urbanization of Anhui Province, China. International Journal of Environmental Research and Public Health 2019, 16, 5104 .

AMA Style

Sai Hu, Longqian Chen, Long Li, Bingyi Wang, Lina Yuan, Liang Cheng, Ziqi Yu, Ting Zhang. Spatiotemporal Dynamics of Ecosystem Service Value Determined by Land-Use Changes in the Urbanization of Anhui Province, China. International Journal of Environmental Research and Public Health. 2019; 16 (24):5104.

Chicago/Turabian Style

Sai Hu; Longqian Chen; Long Li; Bingyi Wang; Lina Yuan; Liang Cheng; Ziqi Yu; Ting Zhang. 2019. "Spatiotemporal Dynamics of Ecosystem Service Value Determined by Land-Use Changes in the Urbanization of Anhui Province, China." International Journal of Environmental Research and Public Health 16, no. 24: 5104.

Research article
Published: 07 November 2019 in PLoS ONE
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As uncontrolled urban growth has increasingly challenged the sustainable use of urban land, it is critically important to model urban growth from different perspectives. Using the SLEUTH (Slope, Land use, Exclusion, Urban, Transportation, and Hill-shade) model, the historical data of Hefei in 2000, 2005, 2010, and 2015 were collected and input to simulate urban growth from 2015 to 2040. Three different urban growth scenarios were considered, namely a historical growth scenario, an urban planning growth scenario, and a land suitability growth scenario. Prediction results show that by 2040 urban built-up land would increase to 1434 km2 in the historical growth scenario, to 1190 km2 in the urban planning growth scenario, and to 1217 km2 in the land suitability growth scenario. We conclude that (1) exclusion layers without effective limits might result in unreasonable prediction of future built-up land; (2) based on the general land use map, the urban growth prediction took the governmental policies into account and could reveal the development hotspots in urban planning; and (3) the land suitability scenario prediction was the result of the trade-off between ecological land and built-up land as it used the MCR -based (minimum cumulative resistance model) land suitability assessment result. It would help to form a compact urban space and avoid excessive protection of farmland and ecological land. Findings derived from this study may provide urban planners with interesting insights on formulating urban planning strategies.

ACS Style

Yunqiang Liu; Long Li; Longqian Chen; Liang Cheng; Xisheng Zhou; Yifan Cui; Han Li; Weiqiang Liu. Urban growth simulation in different scenarios using the SLEUTH model: A case study of Hefei, East China. PLoS ONE 2019, 14, e0224998 .

AMA Style

Yunqiang Liu, Long Li, Longqian Chen, Liang Cheng, Xisheng Zhou, Yifan Cui, Han Li, Weiqiang Liu. Urban growth simulation in different scenarios using the SLEUTH model: A case study of Hefei, East China. PLoS ONE. 2019; 14 (11):e0224998.

Chicago/Turabian Style

Yunqiang Liu; Long Li; Longqian Chen; Liang Cheng; Xisheng Zhou; Yifan Cui; Han Li; Weiqiang Liu. 2019. "Urban growth simulation in different scenarios using the SLEUTH model: A case study of Hefei, East China." PLoS ONE 14, no. 11: e0224998.

Journal article
Published: 20 September 2019 in International Journal of Environmental Research and Public Health
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Large amounts of aerosol particles suspended in the atmosphere pose a serious challenge to the climate and human health. In this study, we produced a dataset through merging the Moderate Resolution Imaging Spectrometers (MODIS) Collection 6.1 3-km resolution Dark Target aerosol optical depth (DT AOD) with the 10-km resolution Deep Blue aerosol optical depth (DB AOD) data by linear regression and made use of it to unravel the spatiotemporal characteristics of aerosols over the Pan Yangtze River Delta (PYRD) region from 2014 to 2017. Then, the geographical detector method and multiple linear regression analysis were employed to investigate the contributions of influencing factors. Results indicate that: (1) compared to the original Terra DT and Aqua DT AOD data, the average daily spatial coverage of the merged AOD data increased by 94% and 132%, respectively; (2) the values of four-year average AOD were high in the north-east and low in the south-west of the PYRD; (3) the annual average AOD showed a decreasing trend from 2014 to 2017 while the seasonal average AOD reached its maximum in spring; and that (4) Digital Elevation Model (DEM) and slope contributed most to the spatial distribution of AOD, followed by precipitation and population density. Our study highlights the spatiotemporal variability of aerosol optical depth and the contributions of different factors over this large geographical area in the four-year period, and can, therefore, provide useful insights into the air pollution control for decision makers.

ACS Style

Liang Cheng; Long Li; Longqian Chen; Sai Hu; Lina Yuan; Yunqiang Liu; Yifan Cui; Ting Zhang. Spatiotemporal Variability and Influencing Factors of Aerosol Optical Depth over the Pan Yangtze River Delta During the 2014–2017 Period. International Journal of Environmental Research and Public Health 2019, 16, 3522 .

AMA Style

Liang Cheng, Long Li, Longqian Chen, Sai Hu, Lina Yuan, Yunqiang Liu, Yifan Cui, Ting Zhang. Spatiotemporal Variability and Influencing Factors of Aerosol Optical Depth over the Pan Yangtze River Delta During the 2014–2017 Period. International Journal of Environmental Research and Public Health. 2019; 16 (19):3522.

Chicago/Turabian Style

Liang Cheng; Long Li; Longqian Chen; Sai Hu; Lina Yuan; Yunqiang Liu; Yifan Cui; Ting Zhang. 2019. "Spatiotemporal Variability and Influencing Factors of Aerosol Optical Depth over the Pan Yangtze River Delta During the 2014–2017 Period." International Journal of Environmental Research and Public Health 16, no. 19: 3522.

Journal article
Published: 29 August 2019 in Water
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It is generally acknowledged that soil erosion has become one of the greatest global threats to the human–environment system. Although the Revised Universal Soil Loss Equation (RUSLE) has been widely used for soil erosion estimation, the algorithm for calculating soil erodibility factor (K) in this equation remains limited, particularly in the context of China, which features highly diverse soil types. In order to address the problem, a modified algorithm describing the piecewise function of gravel content and relative soil erosion was used for the first time to modify the soil erodibility factor, because it has been proven that gravel content has an important effect on soil erosion. The Chaohu Lake Basin (CLB) in East China was used as an example to assess whether our proposal can improve the accuracy of soil erodibility calculation and soil erosion estimation compared with measured data. Results show that (1) taking gravel content into account helps to improve the calculation of soil erodibility and soil erosion estimation due to its protection to topsoil; (2) the overall soil erosion in the CLB was low (1.78 Mg·ha−1·year−1) the majority of which was slight erosion (accounting for 85.6%) and no extremely severe erosion; and (3) inappropriate land use such as steep slope reclamation and excessive vegetation destruction are the main reasons for soil erosion of the CLB. Our study will contribute to decision-makers to develop soil and water conservation policies.

ACS Style

Sai Hu; Long Li; Longqian Chen; Liang Cheng; Lina Yuan; Xiaodong Huang; Ting Zhang. Estimation of Soil Erosion in the Chaohu Lake Basin through Modified Soil Erodibility Combined with Gravel Content in the RUSLE Model. Water 2019, 11, 1806 .

AMA Style

Sai Hu, Long Li, Longqian Chen, Liang Cheng, Lina Yuan, Xiaodong Huang, Ting Zhang. Estimation of Soil Erosion in the Chaohu Lake Basin through Modified Soil Erodibility Combined with Gravel Content in the RUSLE Model. Water. 2019; 11 (9):1806.

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Sai Hu; Long Li; Longqian Chen; Liang Cheng; Lina Yuan; Xiaodong Huang; Ting Zhang. 2019. "Estimation of Soil Erosion in the Chaohu Lake Basin through Modified Soil Erodibility Combined with Gravel Content in the RUSLE Model." Water 11, no. 9: 1806.

Journal article
Published: 31 May 2019 in Forests
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Urban forests are an important component of the urban ecosystem. Urban forest types are a key piece of information required for monitoring the condition of an urban ecosystem. In this study, we propose an urban forest type discrimination method based on linear spectral mixture analysis (LSMA) and a support vector machine (SVM) in the case study of Xuzhou, east China. From 10-m Sentinel-2A imagery data, three different vegetation endmembers, namely broadleaved forest, coniferous forest, and low vegetation, and their abundances were extracted through LSMA. Using a combination of image spectra, topography, texture, and vegetation abundances, four SVM classification models were performed and compared to investigate the impact of these features on classification accuracy. With a particular interest in the role that vegetation abundances play in classification, we also compared SVM and other classifiers, i.e., random forest (RF), artificial neural network (ANN), and quick unbiased efficient statistical tree (QUEST). Results indicate that (1) the LSMA method can derive accurate vegetation abundances from Sentinel-2A image data, and the root-mean-square error (RMSE) was 0.019; (2) the classification accuracies of the four SVM models were improved after adding topographic features, textural features, and vegetation abundances one after the other; (3) the SVM produced higher classification accuracies than the other three classifiers when identical classification features were used; and (4) vegetation endmember abundances improved classification accuracy regardless of which classifier was used. It is concluded that Sentinel-2A image data has a strong capability to discriminate urban forest types in spectrally heterogeneous urban areas, and that vegetation abundances derived from LSMA can enhance such discrimination.

ACS Style

Xisheng Zhou; Long Li; Longqian Chen; Yunqiang Liu; Yifan Cui; Yu Zhang; Ting Zhang. Discriminating Urban Forest Types from Sentinel-2A Image Data through Linear Spectral Mixture Analysis: A Case Study of Xuzhou, East China. Forests 2019, 10, 478 .

AMA Style

Xisheng Zhou, Long Li, Longqian Chen, Yunqiang Liu, Yifan Cui, Yu Zhang, Ting Zhang. Discriminating Urban Forest Types from Sentinel-2A Image Data through Linear Spectral Mixture Analysis: A Case Study of Xuzhou, East China. Forests. 2019; 10 (6):478.

Chicago/Turabian Style

Xisheng Zhou; Long Li; Longqian Chen; Yunqiang Liu; Yifan Cui; Yu Zhang; Ting Zhang. 2019. "Discriminating Urban Forest Types from Sentinel-2A Image Data through Linear Spectral Mixture Analysis: A Case Study of Xuzhou, East China." Forests 10, no. 6: 478.

Surveying and geo spatial engineering
Published: 16 April 2019 in KSCE Journal of Civil Engineering
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This study uses monocular digital photography and a measurement robot (MDP&MR) to monitor the sluice vibration deformation in the gate lift test and in the sluicing test. The photographing scale transformation and time baseline parallax (PST-TBP) method is proposed in the field of monocular digital photography. Results show that the PST-TBP method improves measurement accuracy slightly. Measurement accuracies on the reference plane were 0.62 pixels (0.40 mm), 0.76 pixels (0.49 mm), and 1.10 pixels (0.71 mm) in the X, Z, and comprehensive-directions, respectively. The PST-TBP method overcomes the limitation that the photographing direction must be perpendicular to the sluice plane when monocular digital photography is used to monitor the sluice. MDP&MR proves an effective method in monitoring the sluice vibration deformation as MDP can be used to monitor the trend of the sluice vibration deformation and the MR allows high-accuracy monitoring of the short periodic deformation of the sluice. They have complementary advantages to achieve better results. Thus, MDP&MR can provide a new way to assess sluice health in vibration.

ACS Style

Guojian Zhang; Chengxin Yu; Guangli Guo; Long Li; Yongqian Zhao; Huaizhan Li; Yaqiang Gong. Monitoring Sluice Health in Vibration by Monocular Digital Photography and a Measurement Robot. KSCE Journal of Civil Engineering 2019, 23, 2666 -2678.

AMA Style

Guojian Zhang, Chengxin Yu, Guangli Guo, Long Li, Yongqian Zhao, Huaizhan Li, Yaqiang Gong. Monitoring Sluice Health in Vibration by Monocular Digital Photography and a Measurement Robot. KSCE Journal of Civil Engineering. 2019; 23 (6):2666-2678.

Chicago/Turabian Style

Guojian Zhang; Chengxin Yu; Guangli Guo; Long Li; Yongqian Zhao; Huaizhan Li; Yaqiang Gong. 2019. "Monitoring Sluice Health in Vibration by Monocular Digital Photography and a Measurement Robot." KSCE Journal of Civil Engineering 23, no. 6: 2666-2678.

Journal article
Published: 26 February 2019 in Sustainability
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As an effective indicator of urbanization, impervious surfaces play a significant role in urban planning and ecological protection. It is, therefore, important to characterize impervious surfaces in urban geographical studies. As a key city in East China, Xuzhou has experienced rapid urbanization in recent decades and is now becoming an environmentally friendly city. To better understand the spatiotemporal heterogeneity of Xuzhou’s urban development, we extracted its impervious surfaces from Landsat images of 1995, 2003, 2010, and 2018 by a linear spectral mixture analysis. Then, a range of complementary methods including landscape indices, profile lines, median centers, standard deviational ellipses, and spatial autocorrelation were adopted to analyze the landscape pattern and expansion of impervious surfaces on both city and district scales. Results show that (1) there was a constant impervious surface expansion, originating in downtown Xuzhou; (2) promoting ecological protection in urban areas fragmented impervious surfaces with increasing heterogeneity and diversity overall; and (3) expansion directions and rates of impervious surfaces varied with district and town, and the central urban area expanded towards east and southeast, which could be related to their own resources and governmental policies. Findings from this study provide useful insights into urban planning of this economically prospective region.

ACS Style

Han Li; Long Li; Longqian Chen; Xisheng Zhou; Yifan Cui; Yunqiang Liu; Weiqiang Liu. Mapping and Characterizing Spatiotemporal Dynamics of Impervious Surfaces Using Landsat Images: A Case Study of Xuzhou, East China from 1995 to 2018. Sustainability 2019, 11, 1224 .

AMA Style

Han Li, Long Li, Longqian Chen, Xisheng Zhou, Yifan Cui, Yunqiang Liu, Weiqiang Liu. Mapping and Characterizing Spatiotemporal Dynamics of Impervious Surfaces Using Landsat Images: A Case Study of Xuzhou, East China from 1995 to 2018. Sustainability. 2019; 11 (5):1224.

Chicago/Turabian Style

Han Li; Long Li; Longqian Chen; Xisheng Zhou; Yifan Cui; Yunqiang Liu; Weiqiang Liu. 2019. "Mapping and Characterizing Spatiotemporal Dynamics of Impervious Surfaces Using Landsat Images: A Case Study of Xuzhou, East China from 1995 to 2018." Sustainability 11, no. 5: 1224.

Journal article
Published: 09 January 2019 in International Journal of Environmental Research and Public Health
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As an important contributor to pollutant emissions to the atmosphere, land use can degrade environmental quality. In order to assess the impact of land-use planning on the atmosphere, we propose a methodology combining the land-use-based emission inventories of airborne pollutants and the long-term air pollution multi-source dispersion (LAPMD) model in this study. Through a case study of the eastern Chinese city of Lianyungang, we conclude that (1) land-use-based emission inventorying is a more economical way to assess the overall pollutant emissions compared with the industry-based method, and the LAPMD model can map the spatial variability of airborne pollutant concentrations that directly reflects how the implementation of the land-use planning (LUP) scheme impacts on the atmosphere; (2) the environmental friendliness of the LUP scheme can be assessed by an overlay analysis based on the pollution concentration maps and land-use planning maps; (3) decreases in the emissions of SO2 and PM10 within Lianyungang indicate the overall positive impact of land-use planning implementation, while increases in these emissions from certain land-use types (i.e., urban residential and transportation lands) suggest the aggravation of airborne pollutants from these land parcels; and (4) the city center, where most urban population resides, and areas around key plots would be affected by high pollution concentrations. Our methodology is applicable to study areas for which meteorological data are accessible, and is, therefore, useful for decision making if land-use planning schemes specify the objects of airborne pollutant concentration.

ACS Style

Longgao Chen; Long Li; Xiaoyan Yang; Yu Zhang; Longqian Chen; Xiaodong Ma. Assessing the Impact of Land-Use Planning on the Atmospheric Environment through Predicting the Spatial Variability of Airborne Pollutants. International Journal of Environmental Research and Public Health 2019, 16, 172 .

AMA Style

Longgao Chen, Long Li, Xiaoyan Yang, Yu Zhang, Longqian Chen, Xiaodong Ma. Assessing the Impact of Land-Use Planning on the Atmospheric Environment through Predicting the Spatial Variability of Airborne Pollutants. International Journal of Environmental Research and Public Health. 2019; 16 (2):172.

Chicago/Turabian Style

Longgao Chen; Long Li; Xiaoyan Yang; Yu Zhang; Longqian Chen; Xiaodong Ma. 2019. "Assessing the Impact of Land-Use Planning on the Atmospheric Environment through Predicting the Spatial Variability of Airborne Pollutants." International Journal of Environmental Research and Public Health 16, no. 2: 172.