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Xingpeng Liu
Key Laboratory for Vegetation Ecology, Ministry of Education, Changchun 130024, China

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Journal article
Published: 22 July 2021 in Atmosphere
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This research assessed the changes in spatial patterns and the seasonal trends in temperature, precipitation, and relative humidity over 36 years (1979–2014) using Climate Forecast System Reanalysis (CFSR) datasets. The evaluation of climate deviations was the prime objective of this research. The augmented Dickey–Fuller Test (ADF) was used to scrutinize whether the data was either stationary or non-stationary. The results of the ADF test showed that all the datasets were found to be stationary at lag order 3. To observe undulations in the time series data, trend analyses were done using Sen’s slope (SS), Mann–Kendall (MK), and Cox and Stuart (CS) tests. For all the statistical analyses, we considered the 5% significance level (α = 0.05) and p< 0.05 to be statistically significant. We observed significant (p< 0.05) trends in spring (MAM) and autumn (SON) for minimum temperature (Tmin) in Punjab. We also noted a significant (p< 0.05) trend in precipitation during autumn (SON). Annually, all the variables showed a non-significant (p > 0.05) trend for Punjab, Pakistan, during the period 1979–2014. Climate variability, such as a decrease in precipitation, higher temperature, and relative humidity fluctuations, were the reasons for the imbalance in the sustainability of Punjab, Pakistan.

ACS Style

Alishbah Syed; Xingpeng Liu; Moniruzzaman; Iman Rousta; Warda Syed; Jiquan Zhang; Haraldur Olafsson. Assessment of Climate Variability among Seasonal Trends Using In Situ Measurements: A Case Study of Punjab, Pakistan. Atmosphere 2021, 12, 939 .

AMA Style

Alishbah Syed, Xingpeng Liu, Moniruzzaman, Iman Rousta, Warda Syed, Jiquan Zhang, Haraldur Olafsson. Assessment of Climate Variability among Seasonal Trends Using In Situ Measurements: A Case Study of Punjab, Pakistan. Atmosphere. 2021; 12 (8):939.

Chicago/Turabian Style

Alishbah Syed; Xingpeng Liu; Moniruzzaman; Iman Rousta; Warda Syed; Jiquan Zhang; Haraldur Olafsson. 2021. "Assessment of Climate Variability among Seasonal Trends Using In Situ Measurements: A Case Study of Punjab, Pakistan." Atmosphere 12, no. 8: 939.

Journal article
Published: 16 July 2021 in Water
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Land use change is an important driving force factor affecting the river water environment and directly affecting water quality. To analyze the impact of land use change on water quality change, this study first analyzed the land use change index of the study area. Then, the study area was divided into three subzones based on surface runoff. The relationship between the characteristics of land use change and the water quality grade was obtained by grey correlation analysis. The results showed that the land use types changed significantly in the study area since 2000, and water body and forest land were the two land types with the most significant changes. The transfer rate is cultivated field > forest land > construction land > grassland > unused land > water body. The entropy value of land use information is represented as Area I > Area III > Area II. The shift range of gravity center is forest land > grassland > water body > unused land > construction land > cultivated field. There is a strong correlation between land use change index and water quality, which can be improved and managed by changing the land use type. It is necessary to establish ecological protection areas or functional areas in Area I, artificial lawns or plantations shall be built in the river around the water body to intercept pollutants from non-point source pollution in Area II, and scientific and rational farming in the lower reaches of rivers can reduce non-point source pollution caused by farming.

ACS Style

Mingxi Zhang; Guangzhi Rong; Aru Han; Dao Riao; Xingpeng Liu; Jiquan Zhang; Zhijun Tong. Spatial-Temporal Change of Land Use and Its Impact on Water Quality of East-Liao River Basin from 2000 to 2020. Water 2021, 13, 1955 .

AMA Style

Mingxi Zhang, Guangzhi Rong, Aru Han, Dao Riao, Xingpeng Liu, Jiquan Zhang, Zhijun Tong. Spatial-Temporal Change of Land Use and Its Impact on Water Quality of East-Liao River Basin from 2000 to 2020. Water. 2021; 13 (14):1955.

Chicago/Turabian Style

Mingxi Zhang; Guangzhi Rong; Aru Han; Dao Riao; Xingpeng Liu; Jiquan Zhang; Zhijun Tong. 2021. "Spatial-Temporal Change of Land Use and Its Impact on Water Quality of East-Liao River Basin from 2000 to 2020." Water 13, no. 14: 1955.

Journal article
Published: 29 June 2021 in Agriculture
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Tea trees are the main economic crop in Zhejiang Province. However, spring cold is a frequent occurrence there, causing frost damage to the valuable tea buds. To address this, a regional frost-hazard early-warning system is needed. In this study, frost damage area was estimated based on topography and meteorology, as well as longitude and latitude. Based on support vector machine (SVM) and artificial neural networks (ANNs), a multi-class classification model was proposed to estimate occurrence of regional frost disasters using tea frost cases from 2017. Results of the two models were compared, and optimal parameters were adjusted through multiple iterations. The highest accuracies of the two models were 83.8% and 75%, average accuracies were 79.3% and 71.3%, and Kappa coefficients were 79.1% and 67.37%. The SVM model was selected to establish spatial distribution of spring frost damage to tea trees in Zhejiang Province in 2016. Pearson’s correlation coefficient between prediction results and meteorological yield was 0.79 (p< 0.01), indicating consistency. Finally, the importance of model factors was assessed using sensitivity analysis. Results show that relative humidity and wind speed are key factors influencing accuracy of predictions. This study supports decision-making for hazard prediction and defense for tea trees facing frost.

ACS Style

Jie Xu; Suri Guga; Guangzhi Rong; Dao Riao; Xingpeng Liu; Kaiwei Li; Jiquan Zhang. Estimation of Frost Hazard for Tea Tree in Zhejiang Province Based on Machine Learning. Agriculture 2021, 11, 607 .

AMA Style

Jie Xu, Suri Guga, Guangzhi Rong, Dao Riao, Xingpeng Liu, Kaiwei Li, Jiquan Zhang. Estimation of Frost Hazard for Tea Tree in Zhejiang Province Based on Machine Learning. Agriculture. 2021; 11 (7):607.

Chicago/Turabian Style

Jie Xu; Suri Guga; Guangzhi Rong; Dao Riao; Xingpeng Liu; Kaiwei Li; Jiquan Zhang. 2021. "Estimation of Frost Hazard for Tea Tree in Zhejiang Province Based on Machine Learning." Agriculture 11, no. 7: 607.

Journal article
Published: 18 May 2021 in Remote Sensing
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Plant phenology depends largely on temperature, but temperature alone cannot explain the Northern Hemisphere shifts in the start of the growing season (SOS). The spatio–temporal distribution of SOS sensitivity to climate variability has also changed in recent years. We applied the partial least squares regression (PLSR) method to construct a standardized SOS sensitivity evaluation index and analyzed the combined effects of air temperature (Tem), water balance (Wbi), radiation (Srad), and previous year’s phenology on SOS. The spatial and temporal distributions of SOS sensitivity to Northern Hemisphere climate change from 1982 to 2014 were analyzed using time windows of 33 and 15 years; the dominant biological and environmental drivers were also assessed. The results showed that the combined sensitivity of SOS to climate change (SCom) is most influenced by preseason temperature sensitivity. However, because of the asymmetric response of SOS to daytime/night temperature (Tmax/Tmin) and non-negligible moderating of Wbi and Srad on SOS, SCom was more effective in expressing the effect of climate change on SOS than any single climatic factor. Vegetation cover (or type) was the dominant factor influencing the spatial pattern of SOS sensitivity, followed by spring temperature (Tmin > Tmax), and the weakest was water balance. Forests had the highest SCom absolute values. A significant decrease in the sensitivity of some vegetation (22.2%) led to a decreasing trend in sensitivity in the Northern Hemisphere. Although temperature remains the main climatic factor driving temporal changes in SCom, the temperature effects were asymmetric between spring and winter (Tems/Temw). More moisture might mitigate the asymmetric response of SCom to spring/winter warming. Vegetation adaptation has a greater influence on the temporal variability of SOS sensitivity relative to each climatic factor (Tems, Temw, Wbi, Srad). More moisture might mitigate the asymmetric response of SCom to spring/winter warming. This study provides a basis for vegetation phenology sensitivity assessment and prediction.

ACS Style

Kaiwei Li; Chunyi Wang; Qing Sun; Guangzhi Rong; Zhijun Tong; Xingpeng Liu; Jiquan Zhang. Spring Phenological Sensitivity to Climate Change in the Northern Hemisphere: Comprehensive Evaluation and Driving Force Analysis. Remote Sensing 2021, 13, 1972 .

AMA Style

Kaiwei Li, Chunyi Wang, Qing Sun, Guangzhi Rong, Zhijun Tong, Xingpeng Liu, Jiquan Zhang. Spring Phenological Sensitivity to Climate Change in the Northern Hemisphere: Comprehensive Evaluation and Driving Force Analysis. Remote Sensing. 2021; 13 (10):1972.

Chicago/Turabian Style

Kaiwei Li; Chunyi Wang; Qing Sun; Guangzhi Rong; Zhijun Tong; Xingpeng Liu; Jiquan Zhang. 2021. "Spring Phenological Sensitivity to Climate Change in the Northern Hemisphere: Comprehensive Evaluation and Driving Force Analysis." Remote Sensing 13, no. 10: 1972.

Journal article
Published: 11 May 2021 in Remote Sensing
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Urban flooding has been an alarming issue in the past around the globe, particularly in South Asia. Pakistan is no exception from this situation where urban floods with associated damages are frequently occurring phenomena. In Pakistan, rapid urbanization is the key factor for urban flooding, which is not taken into account. This study aims to identify flood sensitivity and coping capacity while assessing urban flood resilience and move a step toward the initialization of resilience, specifically for Peshawar city and generally for other cities of Pakistan. To achieve this aim, an attempt has been made to propose an integrated approach named the “urban flood resilience model (UFResi-M),” which is based on geographical information system(GIS), remote sensing (RS), and the theory of analytical hierarchy process (AHP). The UFResi-M incorporates four main factors—urban flood hazard, exposure, susceptibility, and coping capacity into two parts, i.e., sensitivity and coping capacity. The first part consists of three factors—IH , IE , and IS —that represent sensitivity, while the second part represents coping capacity (ICc ). All four indicators were weighted through AHP to obtain product value for each indicator. The result showed that in the Westzone of the study area, the northwestern and central parts have very high resilience, whereas the southern and southwestern parts have very low resilience. Similarly, in the East zone of the study area, the northwest and southwest parts have very high resilience, while the northern and western parts have very low resilience. The likelihood of the proposed model was also determined using the receiver operating characteristic (ROC) curve method; the area under the curve acquired for the model was 0.904. The outcomes of these integrated assessments can help in tracking community performance and can provide a tool to decision makers to integrate the resilience aspect into urban flood management, urban development, and urban planning.

ACS Style

Muhammad Tayyab; Jiquan Zhang; Muhammad Hussain; Safi Ullah; Xingpeng Liu; Shah Khan; Muhammad Baig; Waqas Hassan; Bazel Al-Shaibah. GIS-Based Urban Flood Resilience Assessment Using Urban Flood Resilience Model: A Case Study of Peshawar City, Khyber Pakhtunkhwa, Pakistan. Remote Sensing 2021, 13, 1864 .

AMA Style

Muhammad Tayyab, Jiquan Zhang, Muhammad Hussain, Safi Ullah, Xingpeng Liu, Shah Khan, Muhammad Baig, Waqas Hassan, Bazel Al-Shaibah. GIS-Based Urban Flood Resilience Assessment Using Urban Flood Resilience Model: A Case Study of Peshawar City, Khyber Pakhtunkhwa, Pakistan. Remote Sensing. 2021; 13 (10):1864.

Chicago/Turabian Style

Muhammad Tayyab; Jiquan Zhang; Muhammad Hussain; Safi Ullah; Xingpeng Liu; Shah Khan; Muhammad Baig; Waqas Hassan; Bazel Al-Shaibah. 2021. "GIS-Based Urban Flood Resilience Assessment Using Urban Flood Resilience Model: A Case Study of Peshawar City, Khyber Pakhtunkhwa, Pakistan." Remote Sensing 13, no. 10: 1864.

Journal article
Published: 06 May 2021 in Sensors
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Proximal sensing offers a novel means for determination of the heavy metal concentration in soil, facilitating low cost and rapid analysis over large areas. In this respect, spectral data and model variables play an important role. Thus far, no attempts have been made to estimate soil heavy metal content using continuum-removal (CR), different preprocessing and statistical methods, and different modeling variables. Considering the adsorption and retention of heavy metals in spectrally active constituents in soil, this study proposes a method for determining low heavy metal concentrations in soil using spectral bands associated with soil organic matter (SOM) and visible–near-infrared (Vis–NIR). To rapidly determine the concentration of heavy metals using hyperspectral data, partial least squares regression (PLSR), principal component regression (PCR), and support vector machine regression (SVMR) statistical methods and 16 preprocessing combinations were developed and explored to determine an optimal combination. The results showed that the multiplicative scatter correction and standard normal variate preprocessing methods evaluated with the second derivative spectral transformation method could accurately determine soil Cr and Ni concentrations. The root-mean-square error (RMSE) values of Vis–NIR model combinations with PLSR, PCR, and SVMR were 0.34, 3.42, and 2.15 for Cr, and 0.07, 1.78, and 1.14 for Ni, respectively. Soil Cr and Ni showed strong spectral responses to the Vis–NIR spectral band. The R2 value of the Vis–NIR-based PLSR model was higher than 0.99, and the RMSE value was 0.07–0.34, suggesting higher stability and accuracy. The results were more accurate for Ni than Cr, and PLSR showed the best performance, followed by SVMR and PCR. This perspective has critical implications for guiding quantitative biogeochemical analysis using proximal sensing data.

ACS Style

Aru Han; Xiaoling Lu; Song Qing; Yongbin Bao; Yuhai Bao; Qing Ma; Xingpeng Liu; Jiquan Zhang. Rapid Determination of Low Heavy Metal Concentrations in Grassland Soils around Mining Using Vis–NIR Spectroscopy: A Case Study of Inner Mongolia, China. Sensors 2021, 21, 3220 .

AMA Style

Aru Han, Xiaoling Lu, Song Qing, Yongbin Bao, Yuhai Bao, Qing Ma, Xingpeng Liu, Jiquan Zhang. Rapid Determination of Low Heavy Metal Concentrations in Grassland Soils around Mining Using Vis–NIR Spectroscopy: A Case Study of Inner Mongolia, China. Sensors. 2021; 21 (9):3220.

Chicago/Turabian Style

Aru Han; Xiaoling Lu; Song Qing; Yongbin Bao; Yuhai Bao; Qing Ma; Xingpeng Liu; Jiquan Zhang. 2021. "Rapid Determination of Low Heavy Metal Concentrations in Grassland Soils around Mining Using Vis–NIR Spectroscopy: A Case Study of Inner Mongolia, China." Sensors 21, no. 9: 3220.

Journal article
Published: 24 April 2021 in Sustainability
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The bottlenecks in enhancing regional green development are resource shortages, environmental pollution, and ecological degradation. Taking the Dongliao River Basin (DRB) of Jilin Province as an example, this study explored green development from a multidimensional perspective. Based on the dimension evaluation results of REECC (resources, environment, and ecological carrying capacity), PLES (production–living–ecological space), and ER (ecological redline), the coupling coordination degree model and spatial autocorrelation model were constructed to explore the coupling coordination degree and spatial distribution of green development. The results showed that REECC had significant spatial differences, and the REECC index showed an increasing trend from northwest to southeast. In 2018, the overall level of green development in the DRB has obvious spatial dependence, but there were spatial differences, with a more obvious polarization from northwest to southeast. The spatial distribution of the coupling degree and coupling coordination degree is roughly the same, and there is a clustering distribution. The conclusions have practical significance for future environmental protection and economic production in the DRB.

ACS Style

Aoyang Wang; Zhijun Tong; Walian Du; Jiquan Zhang; Xingpeng Liu; Zhiyi Yang. Comprehensive Evaluation of Green Development in Dongliao River Basin from the Integration System of “Multi-Dimensions”. Sustainability 2021, 13, 4785 .

AMA Style

Aoyang Wang, Zhijun Tong, Walian Du, Jiquan Zhang, Xingpeng Liu, Zhiyi Yang. Comprehensive Evaluation of Green Development in Dongliao River Basin from the Integration System of “Multi-Dimensions”. Sustainability. 2021; 13 (9):4785.

Chicago/Turabian Style

Aoyang Wang; Zhijun Tong; Walian Du; Jiquan Zhang; Xingpeng Liu; Zhiyi Yang. 2021. "Comprehensive Evaluation of Green Development in Dongliao River Basin from the Integration System of “Multi-Dimensions”." Sustainability 13, no. 9: 4785.

Journal article
Published: 21 April 2021 in Remote Sensing
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Erlong Lake is considered one of the largest lakes in midwest Jilin, China, and one of the drinking water resources in neighboring cities. The present study aims to explore the usage of Landsat TM5, ETM7, and OLI8 images to assess water quality (V-phenol, dissolved oxygen (DO), NH4-N, NO3-N) in Erlong Lake, Jilin province, northeast China. Thirteen multispectral images were used in this study for May, July, August, and September in 2000, 2001, 2002, and October 2020. Radiometric and atmospheric corrections were applied to all images. All in situ water quality parameters were strongly correlated to each other, except DO. The in situ measurements (V-phenol, dissolved oxygen, NH4-N, NO3-N) were statistically correlated with various spectral band combinations (blue, green, red, and NIR) derived from Landsat imagery. Regression analysis reported that there are strong relationships between the estimated and retrieved water quality from the Landsat images. Moreover, in calibrations, the highest value of the coefficient of determination (R2) was ≥0.85 with (RMSE) = 0.038; the lowest value of R2 was >0.30 with RMSE= 0.752. All generated models were validated in different statistical indices; R2 was up to 0.95 for most cases, with RMSE ranging from 1.390 to 0.050. Finally, the empirical algorithms were successfully assessed (V-phenol, dissolved oxygen, NH4-N, NO3-N) in Erlong Lake, using Landsat images with very good accuracy. Both in situ and model retrieved results showed the same trends with non-significant differences. September of 2000, 2001, and 2002 and October of 2020 were selected to assess the spatial distributions of V-phenol, DO, NH4-N, and NO3-N in the lake. V-phenol, NH4-N, and NO3-N were reported low in shallow water but high in deep water, while DO was high in shallow water but low in deep water of the lake. Domestic sewage, agricultural, and urban industrial pollution are the most common sources of pollution in the Erlong Lake.

ACS Style

Bazel Al-Shaibah; Xingpeng Liu; Jiquan Zhang; Zhijun Tong; Mingxi Zhang; Ahmed El-Zeiny; Cheechouyang Faichia; Muhammad Hussain; Muhammad Tayyab. Modeling Water Quality Parameters Using Landsat Multispectral Images: A Case Study of Erlong Lake, Northeast China. Remote Sensing 2021, 13, 1603 .

AMA Style

Bazel Al-Shaibah, Xingpeng Liu, Jiquan Zhang, Zhijun Tong, Mingxi Zhang, Ahmed El-Zeiny, Cheechouyang Faichia, Muhammad Hussain, Muhammad Tayyab. Modeling Water Quality Parameters Using Landsat Multispectral Images: A Case Study of Erlong Lake, Northeast China. Remote Sensing. 2021; 13 (9):1603.

Chicago/Turabian Style

Bazel Al-Shaibah; Xingpeng Liu; Jiquan Zhang; Zhijun Tong; Mingxi Zhang; Ahmed El-Zeiny; Cheechouyang Faichia; Muhammad Hussain; Muhammad Tayyab. 2021. "Modeling Water Quality Parameters Using Landsat Multispectral Images: A Case Study of Erlong Lake, Northeast China." Remote Sensing 13, no. 9: 1603.

Journal article
Published: 05 January 2021 in Sustainability
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An important component in improving the quality of forests is to study the interference intensity of forest fires, in order to describe the intensity of the forest fire and the vegetation recovery, and to improve the monitoring ability of the dynamic change of the forest. Using a forest fire event in Bilahe, Inner Monglia in 2017 as a case study, this study extracted the burned area based on the BAIS2 index of Sentinel-2 data for 2016–2018. The leaf area index (LAI) and fractional vegetation cover (FVC), which are more suitable for monitoring vegetation dynamic changes of a burned area, were calculated by comparing the biophysical and spectral indices. The results showed that patterns of change of LAI and FVC of various land cover types were similar post-fire. The LAI and FVC of forest and grassland were high during the pre-fire and post-fire years. During the fire year, from the fire month (May) through the next 4 months (September), the order of areas of different fire severity in terms of values of LAI and FVC was: low > moderate > high severity. During the post fire year, LAI and FVC increased rapidly in areas of different fire severity, and the ranking of areas of different fire severity in terms of values LAI and FVC was consistent with the trend observed during the pre-fire year. The results of this study can improve the understanding of the mechanisms involved in post-fire vegetation change. By using quantitative inversion, the health trajectory of the ecosystem can be rapidly determined, and therefore this method can play an irreplaceable role in the realization of sustainable development in the study area. Therefore, it is of great scientific significance to quantitatively retrieve vegetation variables by remote sensing.

ACS Style

Aru Han; Song Qing; Yongbin Bao; Li Na; Yuhai Bao; Xingpeng Liu; Jiquan Zhang; Chunyi Wang. Short-Term Effects of Fire Severity on Vegetation Based on Sentinel-2 Satellite Data. Sustainability 2021, 13, 432 .

AMA Style

Aru Han, Song Qing, Yongbin Bao, Li Na, Yuhai Bao, Xingpeng Liu, Jiquan Zhang, Chunyi Wang. Short-Term Effects of Fire Severity on Vegetation Based on Sentinel-2 Satellite Data. Sustainability. 2021; 13 (1):432.

Chicago/Turabian Style

Aru Han; Song Qing; Yongbin Bao; Li Na; Yuhai Bao; Xingpeng Liu; Jiquan Zhang; Chunyi Wang. 2021. "Short-Term Effects of Fire Severity on Vegetation Based on Sentinel-2 Satellite Data." Sustainability 13, no. 1: 432.

Journal article
Published: 13 October 2020 in Sustainability
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: Land use/cover change (LUCC) is one of the causes of global climate and environmental change. Understanding rapid LUCC in urbanized areas is vital for natural resources management for sustainable development. This study primarily considered Vientiane, the capital of Laos, which experienced rapid LUCC due to both natural and anthropogenic factors. The study used geographical information system (GIS) combined with ERDAS and TerrSet technologies to objectively process the ground surveyed and remotely obtained data in order to investigate the historical LUCC as well as predict future LUCC in the study area during the periods of 1995–2018 and 2030–2050, respectively. A comprehensive list of assessment factors comprised of both natural and anthropogenic factors was used for analysis using the cellular automata–Markov (CA–Markov) model. The results show a historical loss of intact forest of 24.36% and of bare land of 1.01%. There were also tremendous increases in degraded forest (11.36%), agricultural land (8.91%), built-up areas (4.49%) and water bodies (1.16%). Finally, the LUCC prediction results indicate the conversion of land use from one type to another, particularly from natural to anthropogenic use, in the near future. These changes demonstrate that the losses associated with ecosystem services will destructively impact human wellbeing in the city and other areas of the country. The study results provide the basic scientific knowledge for LUCC planners, urban designers and natural resources managers. They serve as a decision-making support tool for the establishment of sustainable land resource utilization policies in Vientiane and other cities of similar conditions.

ACS Style

Cheechouyang Faichia; Zhijun Tong; Jiquan Zhang; Xingpeng Liu; Emmanuel Kazuva; Kashif Ullah; Bazel Al-Shaibah. Using RS Data-Based CA–Markov Model for Dynamic Simulation of Historical and Future LUCC in Vientiane, Laos. Sustainability 2020, 12, 8410 .

AMA Style

Cheechouyang Faichia, Zhijun Tong, Jiquan Zhang, Xingpeng Liu, Emmanuel Kazuva, Kashif Ullah, Bazel Al-Shaibah. Using RS Data-Based CA–Markov Model for Dynamic Simulation of Historical and Future LUCC in Vientiane, Laos. Sustainability. 2020; 12 (20):8410.

Chicago/Turabian Style

Cheechouyang Faichia; Zhijun Tong; Jiquan Zhang; Xingpeng Liu; Emmanuel Kazuva; Kashif Ullah; Bazel Al-Shaibah. 2020. "Using RS Data-Based CA–Markov Model for Dynamic Simulation of Historical and Future LUCC in Vientiane, Laos." Sustainability 12, no. 20: 8410.

Journal article
Published: 09 March 2020 in Sustainability
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Residents in industrial cities may be exposed to potentially toxic elements (PTEs) in soil that increase chronic disease risks. In this study, six types of PTEs (Zn, As, Cr, Ni, Cu, and Pb) in 112 surface soil samples from three land use types—industrial land, residential land, and farmland—in Tonghua City, Jilin Province were measured. The geological accumulation index and pollution load index were calculated to assess the pollution level of metal. Meanwhile, the potential ecological risk index, hazard index, and carcinogenic risk were calculated to assess the environmental risks. The spatial distribution map was determined by the ordinary kriging method, and the sources of PTEs were identified by factor analysis and cluster analysis. The average concentrations of Zn, As, Cr, Ni, Cu, and Pb were 266.57, 15.72, 72.41, 15.04, 20.52, and 16.30 mg/kg, respectively. The results of the geological accumulation index demonstrated the following: Zn pollution was present in all three land use types, As pollution in industrial land cannot be neglected, Cr pollution in farmland was higher than that in the other two land use types. The pollution load index decreased in the order of industrial land > farmland > residential land. Multivariate statistical analysis divided the six PTEs into three groups by source: Zn and As both originated from industrial activities; vehicle emissions were the main source of Pb; and Ni and Cu were derived from natural parent materials. Meanwhile, Cr was found to come from a mixture of artificial and natural sources. The soil environment in the study area faced ecological risk from moderate pollution levels mainly contributed by As. PTEs did not pose a non-carcinogenic risk to humans; however, residents of the three land use types all faced estimated carcinogenic risks caused by Cr, and As in industrial land also posed high estimated carcinogenic risk to human health. The conclusion of this article provides corresponding data support to the government’s policy formulation of remediating different types of land and preventing exposure and related environmental risks.

ACS Style

Qing Xia; Jiquan Zhang; Yanan Chen; Qing Ma; Jingyao Peng; Guangzhi Rong; Zhijun Tong; Xingpeng Liu. Pollution, Sources and Human Health Risk Assessment of Potentially Toxic Elements in Different Land Use Types under the Background of Industrial Cities. Sustainability 2020, 12, 2121 .

AMA Style

Qing Xia, Jiquan Zhang, Yanan Chen, Qing Ma, Jingyao Peng, Guangzhi Rong, Zhijun Tong, Xingpeng Liu. Pollution, Sources and Human Health Risk Assessment of Potentially Toxic Elements in Different Land Use Types under the Background of Industrial Cities. Sustainability. 2020; 12 (5):2121.

Chicago/Turabian Style

Qing Xia; Jiquan Zhang; Yanan Chen; Qing Ma; Jingyao Peng; Guangzhi Rong; Zhijun Tong; Xingpeng Liu. 2020. "Pollution, Sources and Human Health Risk Assessment of Potentially Toxic Elements in Different Land Use Types under the Background of Industrial Cities." Sustainability 12, no. 5: 2121.

Journal article
Published: 05 August 2019 in Sustainability
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Drought vulnerability analysis of crops can build a bridge between hazard factors and disasters and become the main tool to mitigate the impact of drought. However, the resulting disagreement about the appropriate definition of vulnerability is a frequent cause for misunderstanding and a challenge for attempts to develop formal models of vulnerability. This paper presents a generally applicable conceptual framework of vulnerability that combines a nomenclature of vulnerable situations and a terminology of vulnerability based on the definition in the intergovernmental panel on climate change (IPCC) report. By selecting 10 indicators, the drought disaster vulnerability assessment model is established from four aspects. In order to verify our model, we present a case study of maize drought vulnerability in the Midwest of the Jilin Province. Our analysis reveals the relationship between each single factor evaluation indicator and drought vulnerability, as well as each indicator to every other indicator. The results show that the drought disturbing degree in different growth periods increases from the central part of the Jilin Province to the western part of the Jilin Province. The sensitivity degree showed an increasing trend from the southeast to the northwest. The places with the strongest self-recovery ability are mainly concentrated in Changchun, Siping, Baicheng, and the other area. The ability to adjust to drought in each growth period is weak and crop yield reduction caused by drought is easy to create. Environmental adaptability is closely related to the social and economic situation every year, so it changes greatly and is flexible. Areas with strong drought vulnerability are mainly concentrated in Baicheng, Tongyu, and Qianguo. The research results can provide a certain basis for risk assessment, early warning, and disaster prevention and mitigation of agricultural drought disaster in the research area.

ACS Style

Ying Guo; Rui Wang; Zhijun Tong; Xingpeng Liu; Jiquan Zhang. Dynamic Evaluation and Regionalization of Maize Drought Vulnerability in the Midwest of Jilin Province. Sustainability 2019, 11, 4234 .

AMA Style

Ying Guo, Rui Wang, Zhijun Tong, Xingpeng Liu, Jiquan Zhang. Dynamic Evaluation and Regionalization of Maize Drought Vulnerability in the Midwest of Jilin Province. Sustainability. 2019; 11 (15):4234.

Chicago/Turabian Style

Ying Guo; Rui Wang; Zhijun Tong; Xingpeng Liu; Jiquan Zhang. 2019. "Dynamic Evaluation and Regionalization of Maize Drought Vulnerability in the Midwest of Jilin Province." Sustainability 11, no. 15: 4234.

Journal article
Published: 10 January 2019 in International Journal of Environmental Research and Public Health
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Climate and weather are important factors that determine winter tourism destinations and snow resources and temperature affect the income of the winter tourism industry. Against the background of climate change, abnormal fluctuations in climate elements bring a series of challenges for winter tourism and cause potential losses to the tourism industry. To effectively assess and plan winter tourism destinations, this study establishes the snow abundance and meteorological suitability indices from snow resource and weather conditions to express winter tourism resources, respectively. The coupling relationship of the two indices was used to analyze the spatial suitability of winter tourism destinations based on the copula function. By case analysis, it was found that the Frank copula one is the best fitting function for winter tourism suitability analysis. The Yushu–Jiutai–Yitong–Dongliao line is the boundary of spatial suitability in the study area. The eastern areas of the boundary have great potential for winter tourism and could strive to develop ice-snow projects, whereas the western regions are relatively weak. This study has guiding significance for winter tourism destination development and resource spatial layout.

ACS Style

Weiying Cai; Hui Di; Xingpeng Liu. Estimation of the Spatial Suitability of Winter Tourism Destinations Based on Copula Functions. International Journal of Environmental Research and Public Health 2019, 16, 186 .

AMA Style

Weiying Cai, Hui Di, Xingpeng Liu. Estimation of the Spatial Suitability of Winter Tourism Destinations Based on Copula Functions. International Journal of Environmental Research and Public Health. 2019; 16 (2):186.

Chicago/Turabian Style

Weiying Cai; Hui Di; Xingpeng Liu. 2019. "Estimation of the Spatial Suitability of Winter Tourism Destinations Based on Copula Functions." International Journal of Environmental Research and Public Health 16, no. 2: 186.

Journal article
Published: 20 July 2018 in Applied Acoustics
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Traffic noise pollution is a widespread public health problem in both developing and developed countries. Quickly and effectively evaluating the quality of an urban acoustic environment is an important challenge for urban planning and management. To solve this problem, this study first classified the urban function area of the study area according to the functional characteristics and environmental quality requirements of the region, and then, the traffic noise propagation model was applied to predict instantaneous sound levels (LA) based on noise attenuation. Finally, a traffic noise evaluation model was proposed to evaluate the quality of the urban acoustic environment. Taking Changchun city as our study area, eighty field samples of equivalent noise levels (Leq) were measured every ten minutes at four types of roads, classified as trunk roads, secondary roads, expressways and rural roads, in different urban function areas. An urban noise map was drawn to reflect the degree of traffic noise pollution. By comparing the measured and predicted values of noise levels, the results show that the traffic noise propagation model can be used to predict instantaneous sound levels. The traffic noise evaluation results show that the quality of the acoustic environment in our study area was at a medium level, which means that long-term exposure to it can affect the normal work and life of people. The traffic noise propagation model and proposed evaluation model are feasible methods for evaluating the quality of the acoustic environment and can provide a reference for the management of noise pollution control of urban traffic.

ACS Style

Hui Di; Xingpeng Liu; Jiquan Zhang; Zhijun Tong; Meichen Ji; Fengxu Li; Tianji Feng; Qing Ma. Estimation of the quality of an urban acoustic environment based on traffic noise evaluation models. Applied Acoustics 2018, 141, 115 -124.

AMA Style

Hui Di, Xingpeng Liu, Jiquan Zhang, Zhijun Tong, Meichen Ji, Fengxu Li, Tianji Feng, Qing Ma. Estimation of the quality of an urban acoustic environment based on traffic noise evaluation models. Applied Acoustics. 2018; 141 ():115-124.

Chicago/Turabian Style

Hui Di; Xingpeng Liu; Jiquan Zhang; Zhijun Tong; Meichen Ji; Fengxu Li; Tianji Feng; Qing Ma. 2018. "Estimation of the quality of an urban acoustic environment based on traffic noise evaluation models." Applied Acoustics 141, no. : 115-124.

Journal article
Published: 26 June 2018 in Sustainability
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As an important component of urban disaster prevention and mitigation systems, the balance and equity of emergency shelter distribution can be measured based on spatial accessibility utilizing the two-step floating catchment area (2SFCA) method. However, there are some issues in previous studies on emergency shelter accessibility evaluated by the 2SFCA method: (1) the high discretization of population distribution data and the travel cost being measured base on Euclidean distance; (2) ignoring the difference between shelter and population catchment sizes. To address these issues, we propose an improved 2SFCA method that computes the shelter and population catchments respectively to evaluate the emergency shelter accessibility in Changchun, China. We compare the proposed improved 2SFCA method to the original 2SFCA method. The results indicate that the catchment size and shelter accessibility calculated by the proposed method are more realistic and objective. The improved 2SFCA method is applicable method for evaluating the shelter accessibility and can provide advice for the planning and management of emergency shelters in the future.

ACS Style

Xiaomeng Zhu; Zhijun Tong; Xingpeng Liu; Xiangqian Li; Pengda Lin; Tong Wang. An Improved Two-Step Floating Catchment Area Method for Evaluating Spatial Accessibility to Urban Emergency Shelters. Sustainability 2018, 10, 2180 .

AMA Style

Xiaomeng Zhu, Zhijun Tong, Xingpeng Liu, Xiangqian Li, Pengda Lin, Tong Wang. An Improved Two-Step Floating Catchment Area Method for Evaluating Spatial Accessibility to Urban Emergency Shelters. Sustainability. 2018; 10 (7):2180.

Chicago/Turabian Style

Xiaomeng Zhu; Zhijun Tong; Xingpeng Liu; Xiangqian Li; Pengda Lin; Tong Wang. 2018. "An Improved Two-Step Floating Catchment Area Method for Evaluating Spatial Accessibility to Urban Emergency Shelters." Sustainability 10, no. 7: 2180.

Article
Published: 15 March 2018 in International Journal of Environmental Research and Public Health
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Water environmental risk is the probability of the occurrence of events caused by human activities or the interaction of human activities and natural processes that will damage a water environment. This study proposed a water environmental risk index (WERI) model to assess the water environmental risk in the Yinma River Basin based on hazards, exposure, vulnerability, and regional management ability indicators in a water environment. The data for each indicator were gathered from 2000, 2005, 2010, and 2015 to assess the spatial and temporal variations in water environmental risk using particle swarm optimization and the analytic hierarchy process (PSO-AHP) method. The results showed that the water environmental risk in the Yinma River Basin decreased from 2000 to 2015. The risk level of the water environment was high in Changchun, while the risk levels in Yitong and Yongji were low. The research methods provide information to support future decision making by the risk managers in the Yinma River Basin, which is in a high-risk water environment. Moreover, water environment managers could reduce the risks by adjusting the indicators that affect water environmental risks.

ACS Style

Hui Di; Xingpeng Liu; Jiquan Zhang; Zhijun Tong; Meichen Ji. The Spatial Distributions and Variations of Water Environmental Risk in Yinma River Basin, China. International Journal of Environmental Research and Public Health 2018, 15, 521 .

AMA Style

Hui Di, Xingpeng Liu, Jiquan Zhang, Zhijun Tong, Meichen Ji. The Spatial Distributions and Variations of Water Environmental Risk in Yinma River Basin, China. International Journal of Environmental Research and Public Health. 2018; 15 (3):521.

Chicago/Turabian Style

Hui Di; Xingpeng Liu; Jiquan Zhang; Zhijun Tong; Meichen Ji. 2018. "The Spatial Distributions and Variations of Water Environmental Risk in Yinma River Basin, China." International Journal of Environmental Research and Public Health 15, no. 3: 521.

Journal article
Published: 03 April 2014 in International Journal of Environmental Research and Public Health
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Floods are a devastating kind of natural disaster. About half of the population in China lives in rural areas. Therefore, it is necessary to assess the flood disaster risk of rural housings. The results are valuable for guiding the rescue and relief goods layout. In this study, we take the severe flood disaster that happened at Kouqian Town in Jilin, China in 2010 as an example to build an risk assessment system for flood disaster on rural housings. Based on the theory of natural disaster risk formation and “3S” technology (remote sensing, geography information systems and global positioning systems), taking the rural housing as the bearing body, we assess the flood disaster risk from three aspects: hazard, exposure and vulnerability. The hazard presented as the flood submerging range and depth. The exposure presented as the values of the housing and the property in it. The vulnerability presented as the relationship between the losses caused by flood and flood depth. We validate the model by the field survey after the flood disaster. The risk assessment results highly coincide with the field survey losses. This model can be used to assess the risk of other flood events in this area.

ACS Style

Qi Zhang; Jiquan Zhang; Liupeng Jiang; Xingpeng Liu; Zhijun Tong. Flood Disaster Risk Assessment of Rural Housings — A Case Study of Kouqian Town in China. International Journal of Environmental Research and Public Health 2014, 11, 3787 -3802.

AMA Style

Qi Zhang, Jiquan Zhang, Liupeng Jiang, Xingpeng Liu, Zhijun Tong. Flood Disaster Risk Assessment of Rural Housings — A Case Study of Kouqian Town in China. International Journal of Environmental Research and Public Health. 2014; 11 (4):3787-3802.

Chicago/Turabian Style

Qi Zhang; Jiquan Zhang; Liupeng Jiang; Xingpeng Liu; Zhijun Tong. 2014. "Flood Disaster Risk Assessment of Rural Housings — A Case Study of Kouqian Town in China." International Journal of Environmental Research and Public Health 11, no. 4: 3787-3802.

Journal article
Published: 16 June 2012 in Natural Hazards
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This study presents a methodology for risk analysis and assessment to manage grassland fire in northern China based on the Geographical Information Systems from the viewpoints of climatology, geography, disaster science, and environmental science and so on. Using natural disaster and risk assessment theory, a multi-dimensional grassland fire risk index (MGFRI) was proposed by integrating weighted comprehensive method, analytic hierarchy process, and fuzzy gamma method into natural disaster risk index. The developed MGFRI will be an easily understandable tool to manage grassland fire by comparing the risk of regions in the northern China and relative contributions of various factors, for example, hazard, exposure, vulnerability, and management ability. A scale of one to five was derived to measure the risk degree. It shows that 4.4 % of grassland falls in the category of ‘very high’ risk, followed by 9.6, 19.1, 60.9, and 5.9 %, respectively, in the categories ‘high’, ‘middle’, ‘low’, and ‘very low’. The assessment results show reliability by test. The results in this study are intended to support local, provincial, and national government agencies to: (1) make resource allocation decisions; (2) make high-level planning decisions; and (3) raise public awareness of grassland fire risk, its causes, and ways to manage it.

ACS Style

Xing-Peng Liu; Ji-Quan Zhang; Zhi-Jun Tong; Yulong Bao. GIS-based multi-dimensional risk assessment of the grassland fire in northern China. Natural Hazards 2012, 64, 381 -395.

AMA Style

Xing-Peng Liu, Ji-Quan Zhang, Zhi-Jun Tong, Yulong Bao. GIS-based multi-dimensional risk assessment of the grassland fire in northern China. Natural Hazards. 2012; 64 (1):381-395.

Chicago/Turabian Style

Xing-Peng Liu; Ji-Quan Zhang; Zhi-Jun Tong; Yulong Bao. 2012. "GIS-based multi-dimensional risk assessment of the grassland fire in northern China." Natural Hazards 64, no. 1: 381-395.

Journal article
Published: 31 May 2012 in International Journal of Environmental Research and Public Health
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In this study, an experiment was performed to assess the trip difficulty for urban residents of different age groups walking in various depths of water, and the data were corroborated with the real urban rainstorm waterlogging scenarios in downtown (Daoli district) Ha-Erbin (China). Mathematical models of urban rainstorm waterlogging were constructed using scenario simulation methods, aided by the GIS spatial analysis technology and hydrodynamic analysis of the waterway systems in the study area. Then these models were used to evaluate the impact of waterlogging on the safety of residents walking in the affected area. Results are summarized as: (1) for an urban rainstorm waterlogging scenario reoccurring once every 10 years, three grid regions would have waterlogging above 0.5 m moving at a velocity of 1.5 m/s. Under this scenario, waterlogging would accumulate on traffic roads only in small areas, affecting the safety and mobility of residents walking in the neighborhood; (2) for an urban rainstorm waterlogging scenario reoccurring once every 20 years, 13 grids experienced the same waterlogging situation affecting a larger area of the city; (3) for an urban rainstorm waterlogging scenario reoccurring once every 50 years, 86 grid regions were affected (waterlogging above 0.5 m moving at 1.5 m/s), and those areas would become impassable for residents.

ACS Style

Peng Chen; Jiquan Zhang; Xinyu Jiang; Xingpeng Liu; Yulong Bao; Yingyue Sun. Scenario Simulation-Based Assessment of Trip Difficulty for Urban Residents under Rainstorm Waterlogging. International Journal of Environmental Research and Public Health 2012, 9, 2057 -2074.

AMA Style

Peng Chen, Jiquan Zhang, Xinyu Jiang, Xingpeng Liu, Yulong Bao, Yingyue Sun. Scenario Simulation-Based Assessment of Trip Difficulty for Urban Residents under Rainstorm Waterlogging. International Journal of Environmental Research and Public Health. 2012; 9 (6):2057-2074.

Chicago/Turabian Style

Peng Chen; Jiquan Zhang; Xinyu Jiang; Xingpeng Liu; Yulong Bao; Yingyue Sun. 2012. "Scenario Simulation-Based Assessment of Trip Difficulty for Urban Residents under Rainstorm Waterlogging." International Journal of Environmental Research and Public Health 9, no. 6: 2057-2074.