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Many efforts have been devoted to extracting impervious surfaces based on different methods from multiple spatial resolution images. Differences in extraction methods and spatial resolutions are significant and have led to discrepant performances in terms of the impervious surface extraction accuracy. However, which extraction method is more suitable for which kind of spatial resolution image in practice is poorly understood. This study systematically compared the performances of 12 methods of impervious surface extraction for four spatial resolution images (i.e. Landsat 8 [30 m], Sentinel-2A [20 m], Sentinel-2A [10 m], and Gaofen-2 [4 m]) in three testing areas. The results indicated that for the medium-spatial resolutions of 30 and 20 m, the support vector machine (SVM) method was considered as the optimal classification method with the highest accuracy of impervious surface extraction. For the high-spatial resolutions of 10 and 4 m, the object based image analysis (OBIA) method obtained the highest accuracy of the impervious surface distribution. Furthermore, the perpendicular impervious surface index (PISI) outperformed the other indices in obtaining the impervious surface distribution, with the highest accuracy for four spatial resolution images. These comprehensive assessments can provide a valuable guidance for future impervious surface extraction from different spatial resolutions.
Shanshan Feng; Fenglei Fan. Impervious surface extraction based on different methods from multiple spatial resolution images: a comprehensive comparison. International Journal of Digital Earth 2021, 1 -27.
AMA StyleShanshan Feng, Fenglei Fan. Impervious surface extraction based on different methods from multiple spatial resolution images: a comprehensive comparison. International Journal of Digital Earth. 2021; ():1-27.
Chicago/Turabian StyleShanshan Feng; Fenglei Fan. 2021. "Impervious surface extraction based on different methods from multiple spatial resolution images: a comprehensive comparison." International Journal of Digital Earth , no. : 1-27.
The dynamic change and spatial–temporal distribution of vegetation coverage are of great significance for regional ecological evolution, especially in the subtropics and tropics. Identifying the heterogeneity in vegetation activities and its response to climate factors is crucial for projecting ecosystem dynamics. We used long-term (2001–2018) satellite-derived enhanced vegetation index (EVI) datasets and climatic factors to analyze the spatiotemporal patterns of vegetation activities in an experimental area in Guangdong Province (China), as well as their links to changes in temperature (TEM), relative humidity (HUM), precipitation (PRE), sunshine duration (SUN), and surface runoff. The pruned exact linear time change point detection method (PELT) and the disturbance lag model (DLM) were used to understand the detailed ecological coverage status and time lag relationships between the EVI and climatic factors. The results indicate the following. (1) At the whole regional scale, a significant overall upward trend in the EVI variation was observed in 2001–2018. More specifically, there were two distinct periods with different trends, which were split by a turning point in 2005. PRE was the main climate-related driver of the rising EVI pre-2005, and the increase in TEM was the main climate factor influencing the forest EVI variation post-2006. (2) A three-month time lag effect was observed in the EVI response to relative humidity. The same phenomenon was found in the sunshine duration factor. (3) The EVI of farmlands (one type of land use) exhibited the largest lags between relative humidity and the sunshine duration factor, followed by grasslands and forests. (4) The comprehensive index of surface runoff could explain the time lags of vegetation activities, and the surface runoff value showed an apparently negative relationship with the vegetation coverage change.
Sai Wang; Fenglei Fan. Analysis of the Response of Long-Term Vegetation Dynamics to Climate Variability Using the Pruned Exact Linear Time (PELT) Method and Disturbance Lag Model (DLM) Based on Remote Sensing Data: A Case Study in Guangdong Province (China). Remote Sensing 2021, 13, 1873 .
AMA StyleSai Wang, Fenglei Fan. Analysis of the Response of Long-Term Vegetation Dynamics to Climate Variability Using the Pruned Exact Linear Time (PELT) Method and Disturbance Lag Model (DLM) Based on Remote Sensing Data: A Case Study in Guangdong Province (China). Remote Sensing. 2021; 13 (10):1873.
Chicago/Turabian StyleSai Wang; Fenglei Fan. 2021. "Analysis of the Response of Long-Term Vegetation Dynamics to Climate Variability Using the Pruned Exact Linear Time (PELT) Method and Disturbance Lag Model (DLM) Based on Remote Sensing Data: A Case Study in Guangdong Province (China)." Remote Sensing 13, no. 10: 1873.
The urban heat island effect caused by the rapid increase in urban anthropogenic heat has gradually become an important factor affecting the living environment of urban residents. Studying the temporal and spatial variation characteristics of urban anthropogenic heat is of great significance for urban planning and urban ecological service systems. In this study, the urban anthropogenic heat flux (AHF) in 2004, 2009, 2014, and 2020 in the central urban area of Guangzhou was retrieved based on Landsat data and the surface energy balance equation, and the temporal and spatial characteristics of different types of anthropogenic heat were explored by combining the transfer matrix and the migration of the gravity center. The results showed that: (1) The overall change trend of anthropogenic heat in the central urban area of Guangzhou was enhanced, and the degree of enhancement was related to the type of urban functional land. (2) Different types of anthropogenic heat had different characteristics in terms of area expansion and spatial changes. Low-value anthropogenic heat (zero-AHF zone, low-AHF zone, medium-AHF zone) changed drastically in terms of area expansion. High-value anthropogenic heat (medium-AHF zone, high-AHF zone) changed more drastically in space. The increase in urban population, rapid economic development, and increased industrial production activities have stimulated the emission of anthropogenic heat, which has a positive impact on the intensity of anthropogenic heat.
Ting Peng; Caige Sun; Shanshan Feng; Yongdong Zhang; Fenglei Fan. Temporal and Spatial Variation of Anthropogenic Heat in the Central Urban Area: A Case Study of Guangzhou, China. ISPRS International Journal of Geo-Information 2021, 10, 160 .
AMA StyleTing Peng, Caige Sun, Shanshan Feng, Yongdong Zhang, Fenglei Fan. Temporal and Spatial Variation of Anthropogenic Heat in the Central Urban Area: A Case Study of Guangzhou, China. ISPRS International Journal of Geo-Information. 2021; 10 (3):160.
Chicago/Turabian StyleTing Peng; Caige Sun; Shanshan Feng; Yongdong Zhang; Fenglei Fan. 2021. "Temporal and Spatial Variation of Anthropogenic Heat in the Central Urban Area: A Case Study of Guangzhou, China." ISPRS International Journal of Geo-Information 10, no. 3: 160.
The intensity of human activity, habitat loss and habitat degradation have significant impacts on biodiversity. Habitat quality plays an important role in spatial dynamics when evaluating fragmented landscapes and the effectiveness of biodiversity conservation. This study aimed to evaluate the status and characteristic variation in habitat quality to analyze the underlying factors affecting habitat quality in the Guangdong–Hong Kong–Macao Greater Bay Area (GBA). Here, we applied Kendall’s rank correlation method to calculate the sensitivity of habitat types to threat factors for the Integrated Valuation of Ecosystem Services and Tradeoffs habitat quality (InVEST-HQ) model. The spatiotemporal variation in habitat quality of the GBA in the period 1995–2015 was estimated based on the InVEST-HQ model. We analyzed the characteristic habitat quality using different ecosystem classifications and at different elevation gradients. Fractional vegetation cover, the proportion of impervious surface, population distribution and gross domestic product were included as the effect factors for habitat quality. The correlation between the effect factors and habitat quality was analyzed using Pearson’s correlation tests. The results showed that the spatial pattern of habitat quality decreased from fringe areas to central areas in the GBA, that the forest ecosystem had the highest value of habitat quality, and that habitat quality increased with elevation. In the period from 1995 to 2015, habitat quality declined markedly and this could be related to vegetation loss, land use change and intensity of human activity. Built-up land expansion and forest land fragmentation were clear markers of land use change. This study has great significance as an operational approach to mitigating the tradeoff between natural environment conservation and rapid economic development.
Linlin Wu; Caige Sun; Fenglei Fan. Estimating the Characteristic Spatiotemporal Variation in Habitat Quality Using the InVEST Model—A Case Study from Guangdong–Hong Kong–Macao Greater Bay Area. Remote Sensing 2021, 13, 1008 .
AMA StyleLinlin Wu, Caige Sun, Fenglei Fan. Estimating the Characteristic Spatiotemporal Variation in Habitat Quality Using the InVEST Model—A Case Study from Guangdong–Hong Kong–Macao Greater Bay Area. Remote Sensing. 2021; 13 (5):1008.
Chicago/Turabian StyleLinlin Wu; Caige Sun; Fenglei Fan. 2021. "Estimating the Characteristic Spatiotemporal Variation in Habitat Quality Using the InVEST Model—A Case Study from Guangdong–Hong Kong–Macao Greater Bay Area." Remote Sensing 13, no. 5: 1008.
Rainfall and freeze-thaw landslides are common occurrences on southeastern Tibet Plateau; however, it can be difficult to categorize them via field surveys. Landslide classification can be determined using image processing methods, such as deep learning. However, the performance of classification is restricted by limited datasets resulting from small numbers of landslides. A new deep learning method is proposed herein for classifying landslides by remote sensing images using the VGG-19 and transfer learning to compensate for an insufficient number of labelled samples. Transfer learning was used to fine tune the classification model. The results of ablation experiments show that the classification model combined with transfer learning can obtain a near zero total loss value in the training process. The proposed method can achieve a lower loss value than direct learning and has a superior generalization ability. The prediction accuracies, Kappa index and F1-score of VGG-19 when using transfer learning and 30 training samples reached 98%, 0.979 and 0.982 respectively. The experiments indicate that the proposed method can be applied to landslide classification on plateaus.
Liu Defang; Junjie Li; Fenglei Fan. Classification of landslides on the southeastern Tibet Plateau based on transfer learning and limited labelled datasets. Remote Sensing Letters 2021, 12, 286 -295.
AMA StyleLiu Defang, Junjie Li, Fenglei Fan. Classification of landslides on the southeastern Tibet Plateau based on transfer learning and limited labelled datasets. Remote Sensing Letters. 2021; 12 (3):286-295.
Chicago/Turabian StyleLiu Defang; Junjie Li; Fenglei Fan. 2021. "Classification of landslides on the southeastern Tibet Plateau based on transfer learning and limited labelled datasets." Remote Sensing Letters 12, no. 3: 286-295.
The interaction between urbanization and the eco-environment is usually viewed as an effect–feedback framework. Its coupling system is composed of urbanization and eco-environment subsystems. In this paper, the coupling degree (CD) and the coupling coordinated degree (CCD) are used to reflect the coupling interaction and coupling coordination between the urbanization subsystem and the eco-environment subsystem. Based on the dynamic relative quantities of urbanization and eco-environment data in the Pearl River Delta, CD and CCD values were calculated, and the spatiotemporal evolution trend of coordination was analyzed. The results show that (1) from 2000 to 2015, the nine cities in the Pearl River Delta had high CD values and CCD values. Though they had different performances in different periods, they were all in a coordinated class, including good coordination (GC), moderate coordination (MC), and bare coordination (BC). (2) In terms of temporal evolution, the coupling coordination between urbanization and the eco-environment in the entire Pearl River Delta greatly improved. (3) From the perspective of spatial distribution, the coupling coordination of the central region was higher than that of the peripheral regions, and that of the west bank of the Pearl River was higher than that of the east bank of the Pearl River. These results can help local policy makers enact appropriate measures for sustainable development.
Caige Sun; Shengyong Zhang; Chuncheng Song; Jianhui Xu; Fenglei Fan. Investigation of Dynamic Coupling Coordination between Urbanization and the Eco-Environment—A Case Study in the Pearl River Delta Area. Land 2021, 10, 190 .
AMA StyleCaige Sun, Shengyong Zhang, Chuncheng Song, Jianhui Xu, Fenglei Fan. Investigation of Dynamic Coupling Coordination between Urbanization and the Eco-Environment—A Case Study in the Pearl River Delta Area. Land. 2021; 10 (2):190.
Chicago/Turabian StyleCaige Sun; Shengyong Zhang; Chuncheng Song; Jianhui Xu; Fenglei Fan. 2021. "Investigation of Dynamic Coupling Coordination between Urbanization and the Eco-Environment—A Case Study in the Pearl River Delta Area." Land 10, no. 2: 190.
The widespread presence of mixed pixels in remotely sensed images is a pressing challenge for accurate target detection and classification. Linear spectral mixture analysis (LSMA) is commonly used to address this problem by deriving remotely sensed information at the subpixel level. In the implementation of LSMA, the effects of mixed-pixel spectral interference need to be taken into account; mixed spectra would exhibit as a pure spectral characteristic when the abundance of one endmember in a mixed pixel exceeds a specific threshold. However, the thresholds of endmember abundance resulting in mixed-pixel spectral interference remain unclear. Thus, this study designed an experiment to analyze the effect of the spectral interference of mixed pixels and to identify the thresholds causing such interference by spectral similarity measures (spectral angle and spectral distance). Four types of pure endmember spectra (vegetation, high-albedo impervious surface (HIS), low-albedo impervious surface (LIS), soil) and corresponding representative mixed spectra with endmember abundances of 95%–5% at intervals of 5% were collected from Earth Observing-1 Hyperion imagery. Spectral similarity measures among the pure endmember spectra and representative mixed spectra were used to determine the thresholds of endmember abundance that cause spectral interference. The results verified the effect of the spectral interference of mixed pixels. The thresholds of abundance causing mixed-pixel spectral interference in vegetation, HIS, LIS, and soil endmembers were 70%, 75%, 80%, and 70%, respectively. Therefore, when the endmember abundance within mixed pixels exceeds the abovementioned thresholds, these mixed spectra are interfered and would exhibit as a pure spectral characteristic. Accordingly, interfered mixed pixels have to be removed before applying LSMA or other unmixing methods to avoid the effect of spectral interference.
Shanshan Feng; Fenglei Fan. Analyzing the Effect of the Spectral Interference of Mixed Pixels Using Hyperspectral Imagery. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2020, 14, 1434 -1446.
AMA StyleShanshan Feng, Fenglei Fan. Analyzing the Effect of the Spectral Interference of Mixed Pixels Using Hyperspectral Imagery. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 2020; 14 ():1434-1446.
Chicago/Turabian StyleShanshan Feng; Fenglei Fan. 2020. "Analyzing the Effect of the Spectral Interference of Mixed Pixels Using Hyperspectral Imagery." IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 14, no. : 1434-1446.
Impervious surface area (ISA) is an important representation of urban area. It is very popular to extract ISA by using linear spectral mixture analysis (LSMA). However, there are still some defects in this method: underestimated in areas with a large amount of ISA. Hence, we designed a threshold hierarchical method (THM) to test this underestimation and understand which scale is the best to mixture. The capacity of the THM and the optimal threshold in the impervious surface extraction are the focus in this work. In THM model, the medium-resolution image (Landsat 8 OLI) and the high-resolution image (Gaofen-2, GF-2) were used, the LSMA and the object-oriented method (OOM) were applied for the area with a larger amount of impervious surfaces, which was extracted from the Landsat 8 OLI image after finishing the LSMA procedure by a threshold of the ISA abundance data, the GF-2 image was employed to extract the ISA by OOM. The results show that the THM had the capacity to achieve higher ISA extraction accuracy and ameliorate the ISA underestimate problem.
Caige Sun; Hao Chen; Fenglei Fan; Caige Sun. Improving Accuracy of Impervious Surface Extraction Based on a Threshold Hierarchical Method (THM). Applied Sciences 2020, 10, 8409 .
AMA StyleCaige Sun, Hao Chen, Fenglei Fan, Caige Sun. Improving Accuracy of Impervious Surface Extraction Based on a Threshold Hierarchical Method (THM). Applied Sciences. 2020; 10 (23):8409.
Chicago/Turabian StyleCaige Sun; Hao Chen; Fenglei Fan; Caige Sun. 2020. "Improving Accuracy of Impervious Surface Extraction Based on a Threshold Hierarchical Method (THM)." Applied Sciences 10, no. 23: 8409.
This article attempts to detail time series characteristics of PM2.5 concentration in Guangzhou (China) from 1 June 2012 to 31 May 2013 based on wavelet analysis tools, and discuss its spatial distribution using geographic information system software and a modified land use regression model. In this modified model, an important variable (land use data) is substituted for impervious surface area, which can be obtained conveniently from remote sensing imagery through the linear spectral mixture analysis method. Impervious surface has higher precision than land use data because of its sub-pixel level. Seasonal concentration pattern and day-by-day change feature of PM2.5 in Guangzhou with a micro-perspective are discussed and understood. Results include: (1) the highest concentration of PM2.5 occurs in October and the lowest in July, respectively; (2) average concentration of PM2.5 in winter is higher than in other seasons; and (3) there are two high concentration zones in winter and one zone in spring.
Fenglei Fan; Runping Liu. Exploration of spatial and temporal characteristics of PM2.5 concentration in Guangzhou, China using wavelet analysis and modified land use regression model. Geo-spatial Information Science 2018, 21, 311 -321.
AMA StyleFenglei Fan, Runping Liu. Exploration of spatial and temporal characteristics of PM2.5 concentration in Guangzhou, China using wavelet analysis and modified land use regression model. Geo-spatial Information Science. 2018; 21 (4):311-321.
Chicago/Turabian StyleFenglei Fan; Runping Liu. 2018. "Exploration of spatial and temporal characteristics of PM2.5 concentration in Guangzhou, China using wavelet analysis and modified land use regression model." Geo-spatial Information Science 21, no. 4: 311-321.
This paper presents a method of mapping and monitoring ecological quality and environmental change using an ecological evaluation model (EEM), which is based on remote sensing data of the Pearl River Delta region in Guangdong, China. Five geographical indices were selected: Impervious Surface, Normalized Difference Vegetation Index, Land Surface Temperature, and Greenness and Brightness generated from the Tasseled Cap Transformation. These geographical indices are of ecological significance and they were used as variables to build the EEM through factor analysis. In addition, land use maps derived from remote sensing data were overlaid on these five index maps to analyze the effects of land use change on ecological status. Based on the EEM values, five levels of ecological zones were identified using a standard-deviation segmenting method. The results showed that the areas of the first and second levels decreased significantly, those of the third and fourth levels increased, and the area of the fifth level remained unchanged. It was established that the remote sensing method is practical for the analysis of ecological change, thus this work could be considered a case study for other ecological monitoring research.
Jinqu Zhang; Yunqiang Zhu; Fenglei Fan. Mapping and evaluation of landscape ecological status using geographic indices extracted from remote sensing imagery of the Pearl River Delta, China, between 1998 and 2008. Environmental Earth Sciences 2016, 75, 1 -16.
AMA StyleJinqu Zhang, Yunqiang Zhu, Fenglei Fan. Mapping and evaluation of landscape ecological status using geographic indices extracted from remote sensing imagery of the Pearl River Delta, China, between 1998 and 2008. Environmental Earth Sciences. 2016; 75 (4):1-16.
Chicago/Turabian StyleJinqu Zhang; Yunqiang Zhu; Fenglei Fan. 2016. "Mapping and evaluation of landscape ecological status using geographic indices extracted from remote sensing imagery of the Pearl River Delta, China, between 1998 and 2008." Environmental Earth Sciences 75, no. 4: 1-16.
Fenglei Fan; Wei Fan; Qihao Weng. Improving Urban Impervious Surface Mapping by Linear Spectral Mixture Analysis and Using Spectral Indices. Canadian Journal of Remote Sensing 2015, 41, 577 -586.
AMA StyleFenglei Fan, Wei Fan, Qihao Weng. Improving Urban Impervious Surface Mapping by Linear Spectral Mixture Analysis and Using Spectral Indices. Canadian Journal of Remote Sensing. 2015; 41 (6):577-586.
Chicago/Turabian StyleFenglei Fan; Wei Fan; Qihao Weng. 2015. "Improving Urban Impervious Surface Mapping by Linear Spectral Mixture Analysis and Using Spectral Indices." Canadian Journal of Remote Sensing 41, no. 6: 577-586.
Fenglei Fan; Yingbin Deng. Corrigendum to “Enhancing endmember selection in multiple endmember spectral mixture analysis (MESMA) for urban impervious surface area mapping using spectral angle and spectral distance parameters” [Int. J. Appl. Earth Observ. Geoinf. 33 (2014) 290–301]. International Journal of Applied Earth Observation and Geoinformation 2015, 36, 103 -105.
AMA StyleFenglei Fan, Yingbin Deng. Corrigendum to “Enhancing endmember selection in multiple endmember spectral mixture analysis (MESMA) for urban impervious surface area mapping using spectral angle and spectral distance parameters” [Int. J. Appl. Earth Observ. Geoinf. 33 (2014) 290–301]. International Journal of Applied Earth Observation and Geoinformation. 2015; 36 ():103-105.
Chicago/Turabian StyleFenglei Fan; Yingbin Deng. 2015. "Corrigendum to “Enhancing endmember selection in multiple endmember spectral mixture analysis (MESMA) for urban impervious surface area mapping using spectral angle and spectral distance parameters” [Int. J. Appl. Earth Observ. Geoinf. 33 (2014) 290–301]." International Journal of Applied Earth Observation and Geoinformation 36, no. : 103-105.
As the main pollutants in the atmosphere, PM 10 and PM 2.5 get much attention and become primary focus recently due to their significant effect on human health. In this paper, the paralleled 24-hour average concentrations of PM 10 and PM 2.5 during June 2012 to May 2013 are obtained from 13 monitoring stations which spread all over the Guangzhou (China). The characteristics variations of PM 10 and PM 2.5 are analyzed using SPSS software. According to the curves of PM 10 and PM 2.5 , it can be found that these two curves (PM 10 and PM 2.5 ) are considerable volatility but quite similar trend with high correlation. The regression analysis between PM 10 and PM 2.5 are finished, the equation is PM 10 =1.26*PM 2.5 +3.28(R 2 =0.94). Meanwhile, the ratio (PM 2.5 /PM 10 ) is analyzed to explore which one is the main pollution type in Guangzhou. Based on our work, we find that:(i) the ratio is range from 0.42 to 0.98 with the average value of 0.76, which suggests that PM 2.5 is the main pollution type and greater than PM 2.5-10 in Guangzhou; (ii) seasonal variation of the ratios are shown as followed: Winter (0.80) = Autumn (0.80) > Spring (0.76) > Summer (0.62). (iii) Spatially, the maximum value of the ratio (0.85) occurs in South (Panyu) of Guangzhou, followed by Center (0.76), North (Conghua, 0.75) and Northwest (Huadu, 0.72) of Guangzhou orderly. Lastly, the spatial concentration map of PM 10 and PM 2.5 is drawn using GIS.
Runping Liu; Fenglei Fan. Mass concentration variations characteristics of PM10 and PM2.5 in Guangzhou (China). 2014 Third International Workshop on Earth Observation and Remote Sensing Applications (EORSA) 2014, 111 -115.
AMA StyleRunping Liu, Fenglei Fan. Mass concentration variations characteristics of PM10 and PM2.5 in Guangzhou (China). 2014 Third International Workshop on Earth Observation and Remote Sensing Applications (EORSA). 2014; ():111-115.
Chicago/Turabian StyleRunping Liu; Fenglei Fan. 2014. "Mass concentration variations characteristics of PM10 and PM2.5 in Guangzhou (China)." 2014 Third International Workshop on Earth Observation and Remote Sensing Applications (EORSA) , no. : 111-115.
The components of urban surface are diversified and mainly included building area, vegetation, water body and so on. To give urbanization a quantitative analysis in order to describe and forecast some problems, which occurred in the process of urbanization, the analysis of urban land surface components is important and necessary. One of the recent major advances in urban land surface components analysis is V-I-S (vegetation, impervious surface and soil) model, which is presented for urban land surface components change and deemed the urban as the combo of three components: Vegetation, Impervious surface and Soil. Ignoring water surfaces, the V-I-S model included the most fundamental components of urban land surface cover and may reflect the connotation of urban expansion. Remote sensing have developed a variety of approaches to distinguish surface cover through multi-spectral data and has became the most convenient and popular means to map the V-I-S components in urban area for its wide area coverage and regular orbiting period. As the third biggest city in China, Guangzhou has been in a rapid urbanization process during the past two decades. The V-I-S model is implied in the study to quantify the composition of urban land surface with multi-temporal Landsat images between 1990 and 2009 to explore a spatiotemporal change of urban land surface components. The linear spectral mixture analysis method was used to extract three components in V-I-S model at sub-pixel level. The results show that: temporally, V-I-S proportional changes in the time series reveal different patterns of urban development in different period. Spatially, spatial variation analysis in different districts can highlight regional differences in urban sprawl process. The significant difference of urban expansion pattern is analyzed in the study by assessing the changing abundance and area of vegetation, impervious surface and soil from 1990 to 2009.
Wei Fan; Runping Liu; Fenglei Fan. Spatiotemporal change analysis of urban land surface component based on V-I-S Model A case study in Guangzhou. 2014 Third International Workshop on Earth Observation and Remote Sensing Applications (EORSA) 2014, 126 -130.
AMA StyleWei Fan, Runping Liu, Fenglei Fan. Spatiotemporal change analysis of urban land surface component based on V-I-S Model A case study in Guangzhou. 2014 Third International Workshop on Earth Observation and Remote Sensing Applications (EORSA). 2014; ():126-130.
Chicago/Turabian StyleWei Fan; Runping Liu; Fenglei Fan. 2014. "Spatiotemporal change analysis of urban land surface component based on V-I-S Model A case study in Guangzhou." 2014 Third International Workshop on Earth Observation and Remote Sensing Applications (EORSA) , no. : 126-130.
Cities represent one of Earth’s fastest growing land-use types on a per-area basis, and over half of the planet’s 7 billion humans now reside in cities.1 It is very important to give a quantitative analysis in order to describe and forecast some problems that have occurred in the process of urbanization. Generally, remote sensing provided the most convenient means to monitor and quantify urban expansion by taking advantage of its wide area coverage and regular orbiting period and it had proven useful for mapping urban areas and obtaining data for the analysis of urban land cover change.2–3 In China, urbanization (urban expansion) has been experienced during different periods during the last two decades and many projects or researches on urban expansion have been launched.45.6.–7 These researchers mostly placed their attention on land use/land cover classification at the pixel level by using supervised or unsupervised classifications. These methods were limited by their precision of classification and image quality, such as spatial resolution, and they could not properly discriminate land cover classes in a heterogeneous context.8
Fenglei Fan; Wei Fan. Understanding spatial-temporal urban expansion pattern (1990–2009) using impervious surface data and landscape indexes: a case study in Guangzhou (China). Journal of Applied Remote Sensing 2014, 8, 083609 .
AMA StyleFenglei Fan, Wei Fan. Understanding spatial-temporal urban expansion pattern (1990–2009) using impervious surface data and landscape indexes: a case study in Guangzhou (China). Journal of Applied Remote Sensing. 2014; 8 (1):083609.
Chicago/Turabian StyleFenglei Fan; Wei Fan. 2014. "Understanding spatial-temporal urban expansion pattern (1990–2009) using impervious surface data and landscape indexes: a case study in Guangzhou (China)." Journal of Applied Remote Sensing 8, no. 1: 083609.
The rainfall and runoff relationship becomes an intriguing issue as urbanization continues to evolve worldwide. In this paper, we developed a simulation model based on the soil conservation service curve number (SCS-CN) method to analyze the rainfall-runoff relationship in Guangzhou, a rapid growing metropolitan area in southern China. The SCS-CN method was initially developed by the Natural Resources Conservation Service (NRCS) of the United States Department of Agriculture (USDA), and is one of the most enduring methods for estimating direct runoff volume in ungauged catchments. In this model, the curve number (CN) is a key variable which is usually obtained by the look-up table of TR-55. Due to the limitations of TR-55 in characterizing complex urban environments and in classifying land use/cover types, the SCS-CN model cannot provide more detailed runoff information. Thus, this paper develops a method to calculate CN by using remote sensing variables, including vegetation, impervious surface, and soil (V-I-S). The specific objectives of this paper are: (1) To extract the V-I-S fraction images using Linear Spectral Mixture Analysis; (2) To obtain composite CN by incorporating vegetation types, soil types, and V-I-S fraction images; and (3) To simulate direct runoff under the scenarios with precipitation of 57mm (occurred once every five years by average) and 81mm (occurred once every ten years). Our experiment shows that the proposed method is easy to use and can derive composite CN effectively.
Fenglei Fan; Yingbin Deng; Xuefei Hu; Qihao Weng. Estimating Composite Curve Number Using an Improved SCS-CN Method with Remotely Sensed Variables in Guangzhou, China. Remote Sensing 2013, 5, 1425 -1438.
AMA StyleFenglei Fan, Yingbin Deng, Xuefei Hu, Qihao Weng. Estimating Composite Curve Number Using an Improved SCS-CN Method with Remotely Sensed Variables in Guangzhou, China. Remote Sensing. 2013; 5 (3):1425-1438.
Chicago/Turabian StyleFenglei Fan; Yingbin Deng; Xuefei Hu; Qihao Weng. 2013. "Estimating Composite Curve Number Using an Improved SCS-CN Method with Remotely Sensed Variables in Guangzhou, China." Remote Sensing 5, no. 3: 1425-1438.
Based on three TM/ETM+ images of Guangzhou acquired in the winters of 1995, 2000 and 2009, land use/land cover (LULC) changes and the corresponding changes of ecosystem service value (ESV) in Guangzhou were estimated by using the artificial neural network (ANN) classifier and ESV coefficients of Xie et al. Results show that the annual total ESVs of Guangzhou were $1248.53, 1255.20, 1287.58 million in 1995, 2000 and 2009, with increases of $6.67 million from 1995 to 2000, $32.38 million from 2000 to 2009, and $39.25 million from 1995 to 2009, respectively. The annual average increasing rate was on average 0.24% during the study period. The combined ESV of woods land and water body together was more than 82.5% of the annual total values of Guangzhou in the three dates. The ESVs of gas regulation, climate regulation, water conservation, waste treatment, biodiversity protection, raw material and recreational culture functions increased while the ESVs of soil formation and conservation and food production functions decreased from 1995 to 2009. It is suggested that the LULC changes were mainly responsible for the ESV changes in Guangzhou and a sound land use planning should be taken effectively for sustainable urban development in Guangzhou.
YongZhu Xiong; Changbai Zhu; Fenglei Fan. Estimation of changes in urban ecosystem service values from remote sensing data in Guangzhou, China. 2012 Second International Workshop on Earth Observation and Remote Sensing Applications 2012, 86 -90.
AMA StyleYongZhu Xiong, Changbai Zhu, Fenglei Fan. Estimation of changes in urban ecosystem service values from remote sensing data in Guangzhou, China. 2012 Second International Workshop on Earth Observation and Remote Sensing Applications. 2012; ():86-90.
Chicago/Turabian StyleYongZhu Xiong; Changbai Zhu; Fenglei Fan. 2012. "Estimation of changes in urban ecosystem service values from remote sensing data in Guangzhou, China." 2012 Second International Workshop on Earth Observation and Remote Sensing Applications , no. : 86-90.
Fenglei Fan -; Maohui Qiu -; Yueliang Ma -; Wei Fan -. Monitoring and Analyzing Water Pollution of the Pearl River in Guangzhou Section by Using Remote Sensing Images and Field Acquisition Data. INTERNATIONAL JOURNAL ON Advances in Information Sciences and Service Sciences 2012, 4, 67 -75.
AMA StyleFenglei Fan -, Maohui Qiu -, Yueliang Ma -, Wei Fan -. Monitoring and Analyzing Water Pollution of the Pearl River in Guangzhou Section by Using Remote Sensing Images and Field Acquisition Data. INTERNATIONAL JOURNAL ON Advances in Information Sciences and Service Sciences. 2012; 4 (8):67-75.
Chicago/Turabian StyleFenglei Fan -; Maohui Qiu -; Yueliang Ma -; Wei Fan -. 2012. "Monitoring and Analyzing Water Pollution of the Pearl River in Guangzhou Section by Using Remote Sensing Images and Field Acquisition Data." INTERNATIONAL JOURNAL ON Advances in Information Sciences and Service Sciences 4, no. 8: 67-75.
Impervious surface area (ISA) is considered as an indicator of environment change and is regarded as an important input parameter for hydrological cycle simulation, water management and area pollution assessment. The Pearl River Delta (PRD), the 3rd most important economic district of China, is chosen in this paper to extract the ISA information based on Landsat images of 1998, 2003 and 2008 by using a linear spectral un-mixing method and to monitor impervious surface change by analyzing the multi-temporal Landsat-derived fractional impervious surface. Results of this study were as follows: (1) the area of ISA in the PRD increased 79.09% from 1998 to 2003 and 26.88% from 2003 to 2008 separately; (2) the spatial distribution of ISA was described according to the 1998/2003 percentage respectively. Most of middle and high percentage ISA was located in northwestern and southeastern of the whole delta, and middle percentage ISA was mainly located in the city interior, high percentage ISA was mainly located in the suburban around the city accordingly; (3) the expanding direction and trend of high percentage ISA was discussed in order to understand the change of urban in this delta; High percentage ISA moved from inner city to edge of urban area during 1998–2003 and moved to the suburban area that far from the urban area mixed with jumpily and gradually during 2003–2008. According to the discussion of high percentage ISA spatial expanded direction, it could be found out that high percentage ISA moved outward from the centre line of Pearl River of the whole delta while a high ISA percentage in both shores of the Pearl River Estuary moved toward the Pearl River; (4) combining the change of ISA with social conditions, the driving relationship was analyzed in detail. It was evident that ISA percentage change had a deep relationship with the economic development of this region in the past ten years. Contemporaneous major sport events (16th Asia Games of Guangzhou, 26th Summer Universidad of Shenzhen) and the government policies also promoted the development of the ISA. Meanwhile, topographical features like the National Nature Reserve of China restricted and affected the expansion of the ISA. Above all, this paper attempted to extract ISA in a major region of the PRD; the temporal and spatial analyses to PRD ISA demonstrated the drastic changes in developed areas of China. These results were important and valuable for land use management, ecological protection and policy establishment.
Yingbin Deng; Fenglei Fan; Renrong Chen. Extraction and Analysis of Impervious Surfaces Based on a Spectral Un-Mixing Method Using Pearl River Delta of China Landsat TM/ETM+ Imagery from 1998 to 2008. Sensors 2012, 12, 1846 -1862.
AMA StyleYingbin Deng, Fenglei Fan, Renrong Chen. Extraction and Analysis of Impervious Surfaces Based on a Spectral Un-Mixing Method Using Pearl River Delta of China Landsat TM/ETM+ Imagery from 1998 to 2008. Sensors. 2012; 12 (2):1846-1862.
Chicago/Turabian StyleYingbin Deng; Fenglei Fan; Renrong Chen. 2012. "Extraction and Analysis of Impervious Surfaces Based on a Spectral Un-Mixing Method Using Pearl River Delta of China Landsat TM/ETM+ Imagery from 1998 to 2008." Sensors 12, no. 2: 1846-1862.
Fenglei Fan -; Caige Sun -; Zhongnuan Chen -; Kaiwen Zhong -; Yunpeng Wang -. Monitoring the Land Use Change and its�� Conversion Mechanism of Economic Core Corridor of Pearl River Delta Based on Remote Sensing Data in Recent Years. International Journal of Digital Content Technology and its Applications 2011, 5, 160 -165.
AMA StyleFenglei Fan -, Caige Sun -, Zhongnuan Chen -, Kaiwen Zhong -, Yunpeng Wang -. Monitoring the Land Use Change and its�� Conversion Mechanism of Economic Core Corridor of Pearl River Delta Based on Remote Sensing Data in Recent Years. International Journal of Digital Content Technology and its Applications. 2011; 5 (10):160-165.
Chicago/Turabian StyleFenglei Fan -; Caige Sun -; Zhongnuan Chen -; Kaiwen Zhong -; Yunpeng Wang -. 2011. "Monitoring the Land Use Change and its�� Conversion Mechanism of Economic Core Corridor of Pearl River Delta Based on Remote Sensing Data in Recent Years." International Journal of Digital Content Technology and its Applications 5, no. 10: 160-165.