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During the outbreak of the COVID-19, China implemented an urban lockdown in the first period. These measures not only effectively curbed the spread of the virus but also brought a positive impact on the ecological environment. The water quality of urban inland river has a significant impact on urban ecology and public health. This study uses Sentinel-2 visible and near-infrared band reflectance and the Normalized Difference Turbidity Index (NDTI) to analyze the water quality of the Haihe River Basin during the control period of COVID-19. It is found that during the lockdown period, the river water quality was significantly improved compared to the same period in 2019. The average NDTI of the Haihe River Basin in March decreased by 0.27, a decrease of 219.06%; in April, it increased by 0.07, that is 38.38%. Further exploration using VIIRS lights found that the brightness of the lights in the main urban area was significantly lower in February, the beginning of the lockdown. However, as the city was unblocked, the lights rose sharply in March and then recovered to normal. There is obvious asynchrony in changes between river turbidity and light. The results can help understand the impact of human activities on the natural environment.
Xu Chen; Wei Chen; Yanbing Bai; Xiaole Wen. Changes in turbidity and human activities along Haihe River Basin during lockdown of COVID-19 using satellite data. Environmental Science and Pollution Research 2021, 1 -16.
AMA StyleXu Chen, Wei Chen, Yanbing Bai, Xiaole Wen. Changes in turbidity and human activities along Haihe River Basin during lockdown of COVID-19 using satellite data. Environmental Science and Pollution Research. 2021; ():1-16.
Chicago/Turabian StyleXu Chen; Wei Chen; Yanbing Bai; Xiaole Wen. 2021. "Changes in turbidity and human activities along Haihe River Basin during lockdown of COVID-19 using satellite data." Environmental Science and Pollution Research , no. : 1-16.
Tianjin is the largest open city along the coastline in Northern China, which has several important wetland ecosystems. However, no systematic study has assessed the water body changes over the past few decades for Tianjin, not to mention their response to human activities and climate change. Here, based on the water change tracking (WCT) algorithm, we proposed an improved water change tracking (IWCT) algorithm, which could remove built-up shade noise (account for 0.4%~6.0% of the final water area) and correct omitted water pixels (account for 1.1%~5.1% of the final water area) by taking the time-series data into consideration. The seasonal water product of the Global Surface Water Data (GSWD) was used to provide a comparison with the IWCT results. Significant changes in water bodies of the selected area in Tianjin were revealed from the time-series water maps. The permanent water area of Tianjin decreased 282.5 km2 from 1984 to 2019. Each time after the dried-up period, due to government policies, the land reclamation happened in Tuanbo Birds Nature Reserve (TBNR), and, finally, 12.6 km2 of the lake has been reclaimed. Meanwhile, 488.6 km2 of land has been reclaimed from the sea along the coastal zone in the past 16 years at a speed of 28.74 km2 yr−1 in the Binhai New Area (BHNA). The method developed in this study could be extended to other sensors which have similar band settings with Landsat; the products acquired in this study could provide fundamental reference for the wetland management in Tianjin.
Xingxing Han; Wei Chen; Bo Ping; Yong Hu. Implementation of an Improved Water Change Tracking (IWCT) Algorithm: Monitoring the Water Changes in Tianjin over 1984–2019 Using Landsat Time-Series Data. Remote Sensing 2021, 13, 493 .
AMA StyleXingxing Han, Wei Chen, Bo Ping, Yong Hu. Implementation of an Improved Water Change Tracking (IWCT) Algorithm: Monitoring the Water Changes in Tianjin over 1984–2019 Using Landsat Time-Series Data. Remote Sensing. 2021; 13 (3):493.
Chicago/Turabian StyleXingxing Han; Wei Chen; Bo Ping; Yong Hu. 2021. "Implementation of an Improved Water Change Tracking (IWCT) Algorithm: Monitoring the Water Changes in Tianjin over 1984–2019 Using Landsat Time-Series Data." Remote Sensing 13, no. 3: 493.
Wei Chen; Qihui Zheng; Haibing Xiang; Xu Chen; Tetsuro Sakai. Forest Canopy Height Estimation Using Polarimetric Interferometric Synthetic Aperture Radar (PolInSAR) Technology Based on Full-Polarized ALOS/PALSAR Data. Remote Sensing 2021, 13, 1 .
AMA StyleWei Chen, Qihui Zheng, Haibing Xiang, Xu Chen, Tetsuro Sakai. Forest Canopy Height Estimation Using Polarimetric Interferometric Synthetic Aperture Radar (PolInSAR) Technology Based on Full-Polarized ALOS/PALSAR Data. Remote Sensing. 2021; 13 (2):1.
Chicago/Turabian StyleWei Chen; Qihui Zheng; Haibing Xiang; Xu Chen; Tetsuro Sakai. 2021. "Forest Canopy Height Estimation Using Polarimetric Interferometric Synthetic Aperture Radar (PolInSAR) Technology Based on Full-Polarized ALOS/PALSAR Data." Remote Sensing 13, no. 2: 1.
Coastal wetlands provide essential ecosystem services and are closely related to human welfare. However, they can experience substantial degradation, especially in regions in which there is intense human activity. To control these increasingly severe problems and to develop corresponding management policies in coastal wetlands, it is critical to accurately map coastal wetlands. Although remote sensing is the most efficient way to monitor coastal wetlands at a regional scale, it traditionally involves a large amount of work, high cost, and low spatial resolution when mapping coastal wetlands at a large scale. In this study, we developed a workflow for rapidly mapping coastal wetlands at a 10 m spatial resolution, based on the recently emergent Google Earth Engine platform, using a machine learning algorithm, open-access Synthetic Aperture Radar (SAR) and optical images from the Sentinel satellites, and two terrain indices. We then generated a coastal wetland map of the Bohai Rim (BRCW10) based on the workflow. It has a producer accuracy of 82.7%, according to validation using 150 wetland samples. The BRCW10 data reflected finer information when compared to wetland maps derived from two sets of global high-spatial-resolution land cover data, due to the fusion of multiple data sources. The study highlights the benefits of simultaneously merging SAR and optical remote sensing images when mapping coastal wetlands.
Shaobo Sun; Yonggen Zhang; Zhaoliang Song; Baozhang Chen; Yangjian Zhang; Wenping Yuan; Chu Chen; Wei Chen; Xiangbin Ran; Yidong Wang. Mapping Coastal Wetlands of the Bohai Rim at a Spatial Resolution of 10 m Using Multiple Open-Access Satellite Data and Terrain Indices. Remote Sensing 2020, 12, 4114 .
AMA StyleShaobo Sun, Yonggen Zhang, Zhaoliang Song, Baozhang Chen, Yangjian Zhang, Wenping Yuan, Chu Chen, Wei Chen, Xiangbin Ran, Yidong Wang. Mapping Coastal Wetlands of the Bohai Rim at a Spatial Resolution of 10 m Using Multiple Open-Access Satellite Data and Terrain Indices. Remote Sensing. 2020; 12 (24):4114.
Chicago/Turabian StyleShaobo Sun; Yonggen Zhang; Zhaoliang Song; Baozhang Chen; Yangjian Zhang; Wenping Yuan; Chu Chen; Wei Chen; Xiangbin Ran; Yidong Wang. 2020. "Mapping Coastal Wetlands of the Bohai Rim at a Spatial Resolution of 10 m Using Multiple Open-Access Satellite Data and Terrain Indices." Remote Sensing 12, no. 24: 4114.
Eucalyptus trees are a major fast-growing species in southern China. The ecological problems associated with constantly developing new Eucalyptus plantations have been the focus of extensive debate. In this study, we used spatial analysis and geostatistical methods along with four continuous national forest resource inventories and meteorological data to analyze dynamic changes in the distribution of Eucalyptus plantations in China. The productivity levels of Eucalyptus plantations were compared at different time periods by measuring annual mean productivity in permanent sample plots to provide baseline data related to the scientific management of Eucalyptus plantations. Results showed that the area of Eucalyptus plantations increased constantly in China from 1998 to 2013, expanding from 60.7 × 104 hm2 in 1998 to more than 445.5 × 104 hm2 in 2013. The productivity of Eucalyptus plantations was positively correlated with temperature and rainfall, but negatively correlated with elevation. However, these changes did not necessarily indicate an improvement in the management quality of Eucalyptus plantations, because they were mainly caused by an increased in the proportion of newly reclaimed areas for Eucalyptus afforestation and the constantly decreasing area of original Eucalyptus plantations, to which sufficient attention must be given.
Wei Chen; Qihui Zheng; Yongfeng Dang; Tetsuro Sakai. Eucalyptus Productivity Increase in China Comes From Newly Afforested Plantations. 2020, 1 .
AMA StyleWei Chen, Qihui Zheng, Yongfeng Dang, Tetsuro Sakai. Eucalyptus Productivity Increase in China Comes From Newly Afforested Plantations. . 2020; ():1.
Chicago/Turabian StyleWei Chen; Qihui Zheng; Yongfeng Dang; Tetsuro Sakai. 2020. "Eucalyptus Productivity Increase in China Comes From Newly Afforested Plantations." , no. : 1.
Wetlands are threatened by the global warming and the human exploitation pressure, and have been shrinking quickly in recent years. Timely and accurate wetland area change detection is the primary task for wetland conservation and restoration. The objective of this study is to develop an integrated change detection approach which integrates the advantages of spectral mixture analysis (SMA) and change vector analysis (CVA) for the change identification of wetland dynamics. In the proposed approach, water, vegetation and soil fractions of wetlands were derived by SMA; then, the detailed change information (including change magnitude and 12 change direction categories) were calculated through CVA. The proposed approach was applied for the wetlands change in Erdos Larus Relictus National Nature Reserve (ELRNNR), China, using time-series Landsat images during 1977–2017. We found that the wetland faced serious degradation, with water fraction changed to soil (5.79 km2), to vegetation (1.35 km2) and to both soil and vegetation (3.53 km2). From 1977 to 2000, a slight degradation occurred in the northeast edge of Bojiang Lake and a marginal degradation in Bojiang and Houjia Lakes inside the ELRNNR, with water fraction changed to soil and vegetation. During 2000–2010, severe degradation occurred in ELRNNR, and from 2010 to 2017, the wetland was more susceptible to the precipitation change and human activities. Analysis of the result indicated that the long-term drought and effects of mismanagement as well as misuse by human beings were the driving factors of wetland degradation. The proposed approach in this study achieves a higher accuracy than the classification approach to detect wetland change, with the ability to obtain more detailed change information.
Di Liu; Wei Chen; Gunter Menz; Olena Dubovyk. Development of integrated wetland change detection approach: In case of Erdos Larus Relictus National Nature Reserve, China. Science of The Total Environment 2020, 731, 139166 .
AMA StyleDi Liu, Wei Chen, Gunter Menz, Olena Dubovyk. Development of integrated wetland change detection approach: In case of Erdos Larus Relictus National Nature Reserve, China. Science of The Total Environment. 2020; 731 ():139166.
Chicago/Turabian StyleDi Liu; Wei Chen; Gunter Menz; Olena Dubovyk. 2020. "Development of integrated wetland change detection approach: In case of Erdos Larus Relictus National Nature Reserve, China." Science of The Total Environment 731, no. : 139166.
Information for individual trees (e.g., position, treetop, height, crown width, and crown edge) is beneficial for forest monitoring and management. Light Detection and Ranging (LiDAR) data have been widely used to retrieve these individual tree parameters from different algorithms, with varying successes. In this study, we used an iterative Triangulated Irregular Network (TIN) algorithm to separate ground and canopy points in airborne LiDAR data, and generated Digital Elevation Models (DEM) by Inverse Distance Weighted (IDW) interpolation, thin spline interpolation, and trend surface interpolation, as well as by using the Kriging algorithm. The height of the point cloud was assigned to a Digital Surface Model (DSM), and a Canopy Height Model (CHM) was acquired. Then, four algorithms (point-cloud-based local maximum algorithm, CHM-based local maximum algorithm, watershed algorithm, and template-matching algorithm) were comparatively used to extract the structural parameters of individual trees. The results indicated that the two local maximum algorithms can effectively detect the treetop; the watershed algorithm can accurately extract individual tree height and determine the tree crown edge; and the template-matching algorithm works well to extract accurate crown width. This study provides a reference for the selection of algorithms in individual tree parameter inversion based on airborne LiDAR data and is of great significance for LiDAR-based forest monitoring and management.
Wei Chen; Haibing Xiang; Kazuyuki Moriya. Individual Tree Position Extraction and Structural Parameter Retrieval Based on Airborne LiDAR Data: Performance Evaluation and Comparison of Four Algorithms. Remote Sensing 2020, 12, 571 .
AMA StyleWei Chen, Haibing Xiang, Kazuyuki Moriya. Individual Tree Position Extraction and Structural Parameter Retrieval Based on Airborne LiDAR Data: Performance Evaluation and Comparison of Four Algorithms. Remote Sensing. 2020; 12 (3):571.
Chicago/Turabian StyleWei Chen; Haibing Xiang; Kazuyuki Moriya. 2020. "Individual Tree Position Extraction and Structural Parameter Retrieval Based on Airborne LiDAR Data: Performance Evaluation and Comparison of Four Algorithms." Remote Sensing 12, no. 3: 571.
Wetland is one of the most productive ecosystems in the world, a unique habitat for creatures. However, nearly half of the world's wetlands have deteriorated and disappeared in the past 100 years due to human disturbance, and the wetlands are still in a situation of continuous degradation. Current wetland evaluation cannot reveal spatial heterogeneity and its changes within the wetland. Therefore, based on remote sensing technology and landscape index, this study constructed a wetland health indicator system consisting of 12 indicators and used analytic hierarchy process (AHP) to calculate their weights. Using remote sensing data, experimental data and auxiliary data, this indicator system was applied to the Hongze Lake wetland in Jiangsu Province, China and the spatial pattern of health status was mapped. The health index of the edge of Hongze Lake is relatively lower, and the interior is healthier. The whole health index is 5.63. This study indicated that the wetland health assessment methodology proposed can effectively evaluate the spatial pattern of wetland ecosystem health and provide technical support for the protection and restoration of wetlands.
Chunying Wu; Wei Chen. Indicator system construction and health assessment of wetland ecosystem——Taking Hongze Lake Wetland, China as an example. Ecological Indicators 2020, 112, 106164 .
AMA StyleChunying Wu, Wei Chen. Indicator system construction and health assessment of wetland ecosystem——Taking Hongze Lake Wetland, China as an example. Ecological Indicators. 2020; 112 ():106164.
Chicago/Turabian StyleChunying Wu; Wei Chen. 2020. "Indicator system construction and health assessment of wetland ecosystem——Taking Hongze Lake Wetland, China as an example." Ecological Indicators 112, no. : 106164.
Fires are frequent in boreal forests affecting forest areas. The detection of forest disturbances and the monitoring of forest restoration are critical for forest management. Vegetation phenology information in remote sensing images may interfere with the monitoring of vegetation restoration, but little research has been done on this issue. Remote sensing and the geographic information system (GIS) have emerged as important tools in providing valuable information about vegetation phenology. Based on the MODIS and Landsat time-series images acquired from 2000 to 2018, this study uses the spatio-temporal data fusion method to construct reflectance images of vegetation with a relatively consistent growth period to study the vegetation restoration after the Greater Hinggan Mountain forest fire in the year 1987. The influence of phenology on vegetation monitoring was analyzed through three aspects: band characteristics, normalized difference vegetation index (NDVI) and disturbance index (DI) values. The comparison of the band characteristics shows that in the blue band and the red band, the average reflectance values of the study area after eliminating phenological influence is lower than that without eliminating the phenological influence in each year. In the infrared band, the average reflectance value after eliminating the influence of phenology is greater than the value with phenological influence in almost every year. In the second shortwave infrared band, the average reflectance value without phenological influence is lower than that with phenological influence in almost every year. The analysis results of NDVI and DI values in the study area of each year show that the NDVI and DI curves vary considerably without eliminating the phenological influence, and there is no obvious trend. After eliminating the phenological influence, the changing trend of the NDVI and DI values in each year is more stable and shows that the forest in the region was impacted by other factors in some years and also the recovery trend. The results show that the spatio-temporal data fusion approach used in this study can eliminate vegetation phenology effectively and the elimination of the phenology impact provides more reliable information about changes in vegetation regions affected by the forest fires. The results will be useful as a reference for future monitoring and management of forest resources.
Zhibin Huang; Chunxiang Cao; Wei Chen; Min Xu; Yongfeng Dang; Ramesh P. Singh; Barjeece Bashir; Bo Xie; Xiaojuan Lin. Remote Sensing Monitoring of Vegetation Dynamic Changes after Fire in the Greater Hinggan Mountain Area: The Algorithm and Application for Eliminating Phenological Impacts. Remote Sensing 2020, 12, 156 .
AMA StyleZhibin Huang, Chunxiang Cao, Wei Chen, Min Xu, Yongfeng Dang, Ramesh P. Singh, Barjeece Bashir, Bo Xie, Xiaojuan Lin. Remote Sensing Monitoring of Vegetation Dynamic Changes after Fire in the Greater Hinggan Mountain Area: The Algorithm and Application for Eliminating Phenological Impacts. Remote Sensing. 2020; 12 (1):156.
Chicago/Turabian StyleZhibin Huang; Chunxiang Cao; Wei Chen; Min Xu; Yongfeng Dang; Ramesh P. Singh; Barjeece Bashir; Bo Xie; Xiaojuan Lin. 2020. "Remote Sensing Monitoring of Vegetation Dynamic Changes after Fire in the Greater Hinggan Mountain Area: The Algorithm and Application for Eliminating Phenological Impacts." Remote Sensing 12, no. 1: 156.
Being a globally emerging mite-borne zoonotic disease, scrub typhus is a serious public health concern in Nepal. Mapping environmental suitability and quantifying the human population under risk of the disease is important for prevention and control efforts. In this study, we model and map the environmental suitability of scrub typhus using the ecological niche approach, machine learning modeling techniques, and report locations of scrub typhus along with several climatic, topographic, Normalized Difference Vegetation Index (NDVI), and proximity explanatory variables and estimated population under the risk of disease at a national level. Both MaxEnt and RF technique results reveal robust predictive power with test The area under curve (AUC) and true skill statistics (TSS) of above 0.8 and 0.6, respectively. Spatial prediction reveals that environmentally suitable areas of scrub typhus are widely distributed across the country particularly in the low-land Tarai and less elevated river valleys. We found that areas close to agricultural land with gentle slopes have higher suitability of scrub typhus occurrence. Despite several speculations on the association between scrub typhus and proximity to earthquake epicenters, we did not find a significant role of proximity to earthquake epicenters in the distribution of scrub typhus in Nepal. About 43% of the population living in highly suitable areas for scrub typhus are at higher risk of infection, followed by 29% living in suitable areas of moderate-risk, and about 22% living in moderately suitable areas of lower risk. These findings could be useful in selecting priority areas for surveillance and control strategies effectively.
Bipin Kumar Acharya; Wei Chen; Zengliang Ruan; Gobind Prasad Pant; Yin Yang; Lalan Prasad Shah; Chunxiang Cao; Zhiwei Xu; Meghnath Dhimal; Hualiang Lin. Mapping Environmental Suitability of Scrub Typhus in Nepal Using MaxEnt and Random Forest Models. International Journal of Environmental Research and Public Health 2019, 16, 4845 .
AMA StyleBipin Kumar Acharya, Wei Chen, Zengliang Ruan, Gobind Prasad Pant, Yin Yang, Lalan Prasad Shah, Chunxiang Cao, Zhiwei Xu, Meghnath Dhimal, Hualiang Lin. Mapping Environmental Suitability of Scrub Typhus in Nepal Using MaxEnt and Random Forest Models. International Journal of Environmental Research and Public Health. 2019; 16 (23):4845.
Chicago/Turabian StyleBipin Kumar Acharya; Wei Chen; Zengliang Ruan; Gobind Prasad Pant; Yin Yang; Lalan Prasad Shah; Chunxiang Cao; Zhiwei Xu; Meghnath Dhimal; Hualiang Lin. 2019. "Mapping Environmental Suitability of Scrub Typhus in Nepal Using MaxEnt and Random Forest Models." International Journal of Environmental Research and Public Health 16, no. 23: 4845.
A forest spectral library would be helpful for tree species monitoring and management. To meet the demand of standard spectral information for the subtropical forest, a three-level spectral library including leaf spectra of 67 typical subtropical tree species was built using two spectrometers in this study. Towards the spectra measured by different spectrometers, the spectra consistency was tested using one-way Analysis of Variance (ANOVA) and Jeffries-Matusita distance (J-M distance). To find the optimal band range for subtropical tree species discrimination, the spectral separability of these 67 species were assessed using J-M distance based on original spectra, first order and second order derivative spectra on visible-near infrared band (VNIR, 350-1000 nm), shortwave infrared band (SWIR, 1000-2500 nm) and full band (350-2500 nm). Two kinds of dimension-reduced spectra in these three spectral band range were also analyzed for the tree species separability. It was found that: 1) the spectra measured by the two spectrometers with the same spectral resolution were significantly different, but the derivative spectra were not; 2) the SWIR spectral band was optimal for separating these subtropical tree species; 3) the selection method outperformed transform method for reducing spectra dimension and separating subtropical tree species. This study was expected to provide a reference for spectral library development and subtropical tree species discrimination.
Shanning Bao; Chunxiang Cao; Wei Chen; Tianyu Yang; Chunying Wu. Towards a subtropical forest spectral library: spectra consistency and spectral separability. Geocarto International 2019, 36, 226 -240.
AMA StyleShanning Bao, Chunxiang Cao, Wei Chen, Tianyu Yang, Chunying Wu. Towards a subtropical forest spectral library: spectra consistency and spectral separability. Geocarto International. 2019; 36 (2):226-240.
Chicago/Turabian StyleShanning Bao; Chunxiang Cao; Wei Chen; Tianyu Yang; Chunying Wu. 2019. "Towards a subtropical forest spectral library: spectra consistency and spectral separability." Geocarto International 36, no. 2: 226-240.
Forest canopy height plays an important role in forest management and ecosystem modeling. There are a variety of techniques employed to map forest height using remote sensing data but it is still necessary to explore the use of new data and methods. In this study, we demonstrate an approach for mapping canopy heights of poplar plantations in plain areas through a combination of stereo and multispectral data from China’s latest civilian stereo mapping satellite ZY3-02. First, a digital surface model (DSM) was extracted using photogrammetry methods. Then, canopy samples and ground samples were selected through manual interpretation. Canopy height samples were obtained by calculating the DSM elevation differences between the canopy samples and ground samples. A regression model was used to correlate the reflectance of a ZY3-02 multispectral image with the canopy height samples, in which the red band and green band reflectance were selected as predictors. Finally, the model was extrapolated to the entire study area and a wall-to-wall forest canopy height map was obtained. The validation of the predicted canopy height map reported a coefficient of determination (R2) of 0.72 and a root mean square error (RMSE) of 1.58 m. This study demonstrates the capacity of ZY3-02 data for mapping the canopy height of pure plantations in plain areas.
Mingbo Liu; Chunxiang Cao; Wei Chen; Xuejun Wang. Mapping Canopy Heights of Poplar Plantations in Plain Areas Using ZY3-02 Stereo and Multispectral Data. ISPRS International Journal of Geo-Information 2019, 8, 106 .
AMA StyleMingbo Liu, Chunxiang Cao, Wei Chen, Xuejun Wang. Mapping Canopy Heights of Poplar Plantations in Plain Areas Using ZY3-02 Stereo and Multispectral Data. ISPRS International Journal of Geo-Information. 2019; 8 (3):106.
Chicago/Turabian StyleMingbo Liu; Chunxiang Cao; Wei Chen; Xuejun Wang. 2019. "Mapping Canopy Heights of Poplar Plantations in Plain Areas Using ZY3-02 Stereo and Multispectral Data." ISPRS International Journal of Geo-Information 8, no. 3: 106.
Wetland is one of the three major ecosystems on the earth and has fundamental ecological functions and plays an irreplaceable role in serving biological survival and human development. Considering the characteristics of five types of wetlands, this study constructed a wetland ecological health evaluation indicator system using a wide variety of data from statistical report, field sampling, remote sensing, and questionnaire survey. In this study, we have selected 13 indicators (related to water, soil, biological, landscape and social factors) for ecological health evaluation of 19 wetlands in Beijing-Tianjin-Hebei region of China which have national importance. The detailed analysis shows a comprehensive health index of 5.53. There was significant spatial heterogeneity in the health status of the 19 wetlands in this region. The evaluation results and analysis provides scientific services for developing reasonable and targeted wetland protection and utilization policies of wetlands.
Wei Chen; Chunxiang Cao; Di Liu; Rong Tian; Chunying Wu; Yiqun Wang; Yifan Qian; Guoqiang Ma; Daming Bao. An evaluating system for wetland ecological health: Case study on nineteen major wetlands in Beijing-Tianjin-Hebei region, China. Science of The Total Environment 2019, 666, 1080 -1088.
AMA StyleWei Chen, Chunxiang Cao, Di Liu, Rong Tian, Chunying Wu, Yiqun Wang, Yifan Qian, Guoqiang Ma, Daming Bao. An evaluating system for wetland ecological health: Case study on nineteen major wetlands in Beijing-Tianjin-Hebei region, China. Science of The Total Environment. 2019; 666 ():1080-1088.
Chicago/Turabian StyleWei Chen; Chunxiang Cao; Di Liu; Rong Tian; Chunying Wu; Yiqun Wang; Yifan Qian; Guoqiang Ma; Daming Bao. 2019. "An evaluating system for wetland ecological health: Case study on nineteen major wetlands in Beijing-Tianjin-Hebei region, China." Science of The Total Environment 666, no. : 1080-1088.
Using Landsat remote-sensing data combined with geological information extracted from ALOS and Sentinel-1A radar data, the ecological environment was evaluated in the years 2007, 2008, 2013, and 2017 through gray correlation analysis on the basis of the construction of the pressure-state-response model. The main objective of this research was to assess the ecological environment changes in Wenchuan County before and after the earthquake, and to provide reference for future social development and policy implementation. The grading map of the ecological environment was obtained for every year, and the ecological restoration status of Wenchuan County after the earthquake was evaluated. The results showed that the maximum area cover at a “safe” ecological level was over 46.4% in 2007. After the 2008 earthquake, the proportion of “unsafe” and “very unsafe” ecological levels was 40.0%, especially around the Lancang River and the western mountain area in Wenchuan County. After five years of restoration, ecological conditions were improved, up to 48.0% in the region. The areas at “critically safe” and above recovered to 85.5% in 2017 within nine years after the deadly Wenchuan earthquake of May 12, 2008. In this paper, we discuss the results of detailed analysis of ecological improvements and correlation with the degrees of pressure, state, and response layers of the Pressure-State-Response (PSR) model.
Zhibin Huang; Min Xu; Wei Chen; Xiaojuan Lin; Chunxiang Cao; Ramesh P. Singh. Postseismic Restoration of the Ecological Environment in the Wenchuan Region Using Satellite Data. Sustainability 2018, 10, 3990 .
AMA StyleZhibin Huang, Min Xu, Wei Chen, Xiaojuan Lin, Chunxiang Cao, Ramesh P. Singh. Postseismic Restoration of the Ecological Environment in the Wenchuan Region Using Satellite Data. Sustainability. 2018; 10 (11):3990.
Chicago/Turabian StyleZhibin Huang; Min Xu; Wei Chen; Xiaojuan Lin; Chunxiang Cao; Ramesh P. Singh. 2018. "Postseismic Restoration of the Ecological Environment in the Wenchuan Region Using Satellite Data." Sustainability 10, no. 11: 3990.
Due to urban expansion, economic development, and rapid population growth, land use/land cover (LULC) is changing in major cities around the globe. Quantitative analysis of LULC change is important for studying the corresponding impact on the ecosystem service value (ESV) that helps in decision-making and ecosystem conservation. Based on LULC data retrieved from remote-sensing interpretation, we computed the changes of ESV associated with the LULC dynamics using the benefits transfer method and geographic information system (GIS) technologies during the period of 1992–2018 following self-modified coefficients which were corrected by net primary productivity (NPP). This improved approach aimed to establish a regional value coefficients table for facilitating the reliable evaluation of ESV. The main objective of this research was to clarify the trend and spatial patterns of LULC changes and their influence on ecosystem service values and functions. Our results show a continuous reduction in total ESV from United States (US) $1476.25 million in 1992, to US $1410.17, $1335.10, and $1190.56 million in 2001, 2009, and 2018, respectively; such changes are attributed to a notable loss of farmland and forest land from 1992–2018. The elasticity of ESV in response to changes in LULC shows that 1% of land transition may have caused average changes of 0.28%, 0.34%, and 0.50% during the periods of 1992–2001, 2001–2009, and 2009–2018, respectively. This study provides important information useful for land resource management and for developing strategies to address the reduction of ESV.
Xiaojuan Lin; Min Xu; Chunxiang Cao; Ramesh P. Singh; Wei Chen; Hongrun Ju. Land-Use/Land-Cover Changes and Their Influence on the Ecosystem in Chengdu City, China during the Period of 1992–2018. Sustainability 2018, 10, 3580 .
AMA StyleXiaojuan Lin, Min Xu, Chunxiang Cao, Ramesh P. Singh, Wei Chen, Hongrun Ju. Land-Use/Land-Cover Changes and Their Influence on the Ecosystem in Chengdu City, China during the Period of 1992–2018. Sustainability. 2018; 10 (10):3580.
Chicago/Turabian StyleXiaojuan Lin; Min Xu; Chunxiang Cao; Ramesh P. Singh; Wei Chen; Hongrun Ju. 2018. "Land-Use/Land-Cover Changes and Their Influence on the Ecosystem in Chengdu City, China during the Period of 1992–2018." Sustainability 10, no. 10: 3580.
Global land degradation and sustainable development has become a serious challenge for the terrestrial ecosystems. Shrub plays a crucial role in global ecosystem protection, ecological reconstruction, which is especially important in arid and semi-arid sandland ecosystem. Shrub above ground biomass (AGB) is a proxy of carbon sequestration capacity. Shrub AGB in Mu Us Sandland was estimated using different methods based on Landsat Thematic Mapper (TM) data, topography data, combined with in situ survey data. Linear regression model, multiple stepwise regression model, machine learning model and geometric optical model were used to estimate shrub biomass in combination with in situ data, respectively and their effects were validated and compared. Results showed that shrub AGB predicted from one multiple stepwise regression model with Ratio Vegetation Index (RVI) and Brightness from K-T transformation as input variables reached highest accuracy. For both high and low shrub coverage regions, shrub AGB distribution maps derived by this multiple stepwise regression model achieved higher precision. All these findings will provide a scientific support for ecological sustainable development in eco-vulnerable ecosystems.
Wei Chen; Jian Zhao; Chunxiang Cao; Haijing Tian. Shrub biomass estimation in semi-arid sandland ecosystem based on remote sensing technology. Global Ecology and Conservation 2018, 16, e00479 .
AMA StyleWei Chen, Jian Zhao, Chunxiang Cao, Haijing Tian. Shrub biomass estimation in semi-arid sandland ecosystem based on remote sensing technology. Global Ecology and Conservation. 2018; 16 ():e00479.
Chicago/Turabian StyleWei Chen; Jian Zhao; Chunxiang Cao; Haijing Tian. 2018. "Shrub biomass estimation in semi-arid sandland ecosystem based on remote sensing technology." Global Ecology and Conservation 16, no. : e00479.
Sudden oak death (SOD) is one of the most rapid and destructive forest pathogens, which has caused the death of many host plants in Europe and America. There are currently no cases in China where there are more host plants and a more suitable climate for this pathogen to survive. Therefore, it is vital to discern the potential suitable habitat, quantify the risk levels, and monitor the potential high-risk areas. In this study, we modelled the potential invasion range and risk level of this pathogen at present and in future scenarios in China, using the least correlated components of all the environmental factors based on the Genetic Algorithm for Ruleset Production niche model and GIS analysis. The results indicate that most areas in China are free from a potential SOD risk, and the majority of potential occurrence areas are concentrated in Southern China (Yunnan, Sichuan, Guizhou, Chongqing, Hunan, Fujian). The area of high and extremely high risk in 2050 (RCP26, RCP45, RCP60, and RCP85) is larger than that at present. The most susceptible area is Yunnan province with 80% of the area prone to SOD at extremely high risk in present and future scenarios. The results will be important for monitoring potential high-risk areas in the currently uninfected parts of China.
Bo Xie; Chunxiang Cao; Wei Chen; Bing Yu. Prediction and analysis of the potential risk of sudden oak death in China. Journal of Forestry Research 2018, 30, 2357 -2366.
AMA StyleBo Xie, Chunxiang Cao, Wei Chen, Bing Yu. Prediction and analysis of the potential risk of sudden oak death in China. Journal of Forestry Research. 2018; 30 (6):2357-2366.
Chicago/Turabian StyleBo Xie; Chunxiang Cao; Wei Chen; Bing Yu. 2018. "Prediction and analysis of the potential risk of sudden oak death in China." Journal of Forestry Research 30, no. 6: 2357-2366.
Remotely sensed data are often adversely affected by many types of noise, which influences the classification result. Supervised machine-learning (ML) classifiers such as random forest (RF), support vector machine (SVM), and back-propagation neural network (BPNN) are broadly reported to improve robustness against noise. However, only a few comparative studies that may help investigate this robustness have been reported. An important contribution, going beyond previous studies, is that we perform the analyses by employing the most well-known and broadly implemented packages of the three classifiers and control their settings to represent users’ actual applications. This facilitates an understanding of the extent to which the noise types and levels in remotely sensed data impact classification accuracy using ML classifiers. By using those implementations, we classified the land cover data from a satellite image that was separately afflicted by seven-level zero-mean Gaussian, salt–pepper, and speckle noise. The modeling data and features were strictly controlled. Finally, we discussed how each noise type affects the accuracy obtained from each classifier and the robustness of the classifiers to noise in the data. This may enhance our understanding of the relationship between noises, the supervised ML classifiers, and remotely sensed data.
Sornkitja Boonprong; Chunxiang Cao; Wei Chen; Xiliang Ni; Min Xu; Bipin Kumar Acharya. The Classification of Noise-Afflicted Remotely Sensed Data Using Three Machine-Learning Techniques: Effect of Different Levels and Types of Noise on Accuracy. ISPRS International Journal of Geo-Information 2018, 7, 274 .
AMA StyleSornkitja Boonprong, Chunxiang Cao, Wei Chen, Xiliang Ni, Min Xu, Bipin Kumar Acharya. The Classification of Noise-Afflicted Remotely Sensed Data Using Three Machine-Learning Techniques: Effect of Different Levels and Types of Noise on Accuracy. ISPRS International Journal of Geo-Information. 2018; 7 (7):274.
Chicago/Turabian StyleSornkitja Boonprong; Chunxiang Cao; Wei Chen; Xiliang Ni; Min Xu; Bipin Kumar Acharya. 2018. "The Classification of Noise-Afflicted Remotely Sensed Data Using Three Machine-Learning Techniques: Effect of Different Levels and Types of Noise on Accuracy." ISPRS International Journal of Geo-Information 7, no. 7: 274.
Burnt forest recovery is normally monitored with a time-series analysis of satellite data because of its proficiency for large observation areas. Traditional methods, such as linear correlation plotting, have been proven to be effective, as forest recovery naturally increases with time. However, these methods are complicated and time consuming when increasing the number of observed parameters. In this work, we present a random forest variable importance (RF-VIMP) scheme called multilevel RF-VIMP to compare and assess the relationship between 36 spectral indices (parameters) of burnt boreal forest recovery in the Great Xing’an Mountain, China. Six Landsat images were acquired in the same month 0, 1, 4, 14, 16, and 20 years after a fire, and 39,380 fixed-location samples were then extracted to calculate the effectiveness of the 36 parameters. Consequently, the proposed method was applied to find correlations between the forest recovery indices. The experiment showed that the proposed method is suitable for explaining the efficacy of those spectral indices in terms of discrimination and trend analysis, and for showing the satellite data and forest succession dynamics when applied in a time series. The results suggest that the tasseled cap transformation wetness, brightness, and the shortwave infrared bands (both 1 and 2) perform better than other indices for both classification and monitoring.
Sornkitja Boonprong; Chunxiang Cao; Wei Chen; Shanning Bao. Random Forest Variable Importance Spectral Indices Scheme for Burnt Forest Recovery Monitoring—Multilevel RF-VIMP. Remote Sensing 2018, 10, 807 .
AMA StyleSornkitja Boonprong, Chunxiang Cao, Wei Chen, Shanning Bao. Random Forest Variable Importance Spectral Indices Scheme for Burnt Forest Recovery Monitoring—Multilevel RF-VIMP. Remote Sensing. 2018; 10 (6):807.
Chicago/Turabian StyleSornkitja Boonprong; Chunxiang Cao; Wei Chen; Shanning Bao. 2018. "Random Forest Variable Importance Spectral Indices Scheme for Burnt Forest Recovery Monitoring—Multilevel RF-VIMP." Remote Sensing 10, no. 6: 807.
Increasing trends of urbanization lead to vegetation degradation in big cities and affect the urban thermal environment. This study investigated (1) the cooling effect of urban green space spatial patterns on Land Surface Temperature (LST); (2) how the surrounding environment influences the green space cool islands (GCI), and vice versa. The study was conducted in two Asian capitals: Beijing, China and Islamabad, Pakistan by utilizing Gaofen-1 (GF-1) and Landsat-8 satellite imagery. Pearson’s correlation and normalized mutual information (NMI) were applied to investigate the relationship between green space characteristics and LST. Landscape metrics of green spaces including Percentage of Landscape (PLAND), Patch Density (PD), Edge Density (ED), and Landscape Shape Index (LSI) were selected to calculate the spatial patterns of green spaces, whereas GCI indicators were defined by Green Space Range (GR), Temperature Difference (TD), and Temperature Gradient (TG). The results indicate that both vegetation composition and configuration influence LST distributions; however, vegetation composition appeared to have a slightly greater effect. The cooling effect can be produced more effectively by increasing green space percentage, planting trees in large patches with equal distribution, and avoiding complex-shaped green spaces. The GCI principle indicates that LST can be decreased by increasing the green space area, increasing the water body fraction, or by decreasing the fraction of impervious surfaces. GCI can also be strengthened by decreasing the fraction of impervious surfaces and increasing the fraction of water body or vegetation in the surrounding environment. The cooling effect of vegetation and water could be explained based on their thermal properties. Beijing has already enacted the green-wedge initiative to increase the vegetation canopy. While designing the future urban layout of Islamabad, the construction of artificial lakes within the urban green spaces would also be beneficial, as is the case with Beijing.
Shahid Naeem; Chunxiang Cao; Waqas Ahmed Qazi; Mehdi Zamani; Chen Wei; Bipin Kumar Acharya; Asid Ur Rehman. Studying the Association between Green Space Characteristics and Land Surface Temperature for Sustainable Urban Environments: An Analysis of Beijing and Islamabad. ISPRS International Journal of Geo-Information 2018, 7, 38 .
AMA StyleShahid Naeem, Chunxiang Cao, Waqas Ahmed Qazi, Mehdi Zamani, Chen Wei, Bipin Kumar Acharya, Asid Ur Rehman. Studying the Association between Green Space Characteristics and Land Surface Temperature for Sustainable Urban Environments: An Analysis of Beijing and Islamabad. ISPRS International Journal of Geo-Information. 2018; 7 (2):38.
Chicago/Turabian StyleShahid Naeem; Chunxiang Cao; Waqas Ahmed Qazi; Mehdi Zamani; Chen Wei; Bipin Kumar Acharya; Asid Ur Rehman. 2018. "Studying the Association between Green Space Characteristics and Land Surface Temperature for Sustainable Urban Environments: An Analysis of Beijing and Islamabad." ISPRS International Journal of Geo-Information 7, no. 2: 38.