Search

Fast urbanization in developing countries contributes to heavier pollution in urban water environments, as urbanization enhances land development and even requires lake filling to meet urban land needs, which produces significant water runoff pollution. Centralized construction brings heavier non-point source pollution, which is one of the most crucial types of pollution in urban areas. However, the pollution caused by urbanization in infilled lake areas is lack of attention. To reduce the negative impact of pollution brought on by urbanization, it is important to monitor the characteristics of runoff water qualities and their relationship with rainfall features. In this study, runoff water quality was monitored from 10 rainfall events, totaling 157 samples in the Wuhan Shahu area, an infilled lake area, to characterize the pollutant event mean concentrations (EMCs) and to explore the different effects of land-use types. COD (chemical oxygen demand), TN (total nitrogen), and TP (total phosphorus) were selected as water quality indicators. The results show that the pollutants have a significant spatial variation. Residential runoff had the largest COD (averaged EMC = 54.02 (mg/L)) and TN (averaged EMC = 2.69 (mg/L)) pollution, while road runoff had the second largest COD (averaged EMC = 48.05 (mg/L)) and TN (2.572 (mg/L)) pollution. The TP pollution level is opposite to COD and TN, as commercial and green spaces have heavier pollution, while the differences in TP pollution levels between the four types of land are not significant. The release of organic matter and nitrogen is closely related to human activities on land types, while phosphorus emission is relatively stable, indicating that it is not easily affected or controlled. In addition, the variation in pollutants between land types is also related to a certain extent. The correlation analysis shows that parameters like antecedent dry days (ADDs), rainfall intensity, and rainfall duration most significantly affect the EMCs of commercial and green spaces. Phosphorus pollutants on roads are harder to reduce. These results may help researchers to identify the specific pollutant source and find an effective method to reduce pollution in infilled lake areas and other areas. [ABSTRACT FROM AUTHOR]

The non-grain production rate (NGPR) of cropland is a grave threat to global grain and food supply, and has been a hot issue across the world. However, few scholars explored the impacts of the NGPRs of different cropland types, such as those of paddy land and irrigated land in the same region. Thus, according to the third land survey data, this research first estimated the NGPRs of cropland, paddy land, irrigated land, and dry land at different scales in Shandong Province, China in 2019. Then, their spatial characteristics at a county scale were identified by combining the standard deviation ellipse model and spatial autocorrelation analysis. Finally, the potential driving factors of the NGPR of cropland were explored with the geographical weight regression model. Results are as follows: (1) The NGPR of cropland is at relatively lower level in Shandong Province and is dominated by that of irrigated land, and the NGPR of dry land is higher than those of other cropland types; (2) Significant regional differences exist in the NGPR of cropland, with profound severity in the southeast and much lower in the northwest; (3) At the provincial scale, the total power of agricultural machinery per capita and utilization degree of cropland factors can relieve the NGPR of cropland in nearly the entire research area. The proportion of GDP of the primary industry in GDP, urban population rate, and DEM are the main obstacles for NGPR decrease. At the county scale, the influences of driving factors varied across regions. This research can provide targeted and regional differentiated references for policy improvement and NGPR management. [ABSTRACT FROM AUTHOR]

With the sustainable and coordinated development of cities, the formulation of urban street policies requires multiangle analysis. In regard to the existing street research, a large number of studies have focused on specific landscapes or accessibility of streets, and there is a lack of research on the multiple functions of streets. Recent advances in sensor technology and digitization have produced a wealth of data and methods. Thus, we may comprehensively understand streets in a less labor-intensive way, not just single street functions. This paper defines an index system of the multiple functions of urban streets and proposes a framework for multifunctional street measurement. Via the application of deep learning to Baidu Street View (BSV) imagery, we generate three functions, namely, landscape, traffic, and economic functions. The results indicate that street facilities and features are suitably identified. According to the multifunctional perspective, this paper further classifies urban streets into multifunctional categories and provides targeted policy recommendations for urban street planning. There exist correlations among the various street functions, and the correlation between the street landscape and economic functions is highly significant. This framework can be widely applied in other countries and cities to better understand street differences in various cities. [ABSTRACT FROM AUTHOR]

Construction and protection of ecological networks (ENs) is considered to be an effective means to curb habitat fragmentation and strengthen landscape connectivity. In this study, a complete evaluation framework of ENs based on "quality–function–structure" was proposed to support the formulation of protection strategies for ENs. First, we built the ENs of Wuhan urban agglomeration (WUA) from 2000 to 2020 based on the advantages of circuit theory and remote sensing data of land use monitoring. The results showed that land development activities are an important driving force for the temporal and spatial evolution of global ENs. Forest fragmentation, transitional urban expansion, and agricultural reclamation were important inducements for the shrinkage of ecological sources. They may also increase the resistance of species migration, which will lead to qualitative change and even fracture of ecological corridors. Second, circuit theory, centrality index, and complex network theory were applied to evaluate the quality defects, functional connectivity, and topology characteristics of ENs in WUA, respectively, from 2000 to 2020. The results showed that the antagonism between ecological corridors and land development activities led to ecological quality defects (ecological barriers and pinchpoints). Different land development models had differential effects on centrality indexes. Moreover, the main trunk in the northern Dabie Mountains and the southern Mufu mountains was developed, while the secondary trunks were abundant in the middle of WUA. Finally, we proposed protection strategies for ENs based on the coupling of the "quality–function–structure" of WUA in 2020. It is suggested that all ecological sources must be included in nature reserves to prevent natural or manmade erosion. The key areas to be repaired were determined through the quality evaluation of ecological corridors. The priority of construction and protection of ecological corridors was determined by coupling two topological structures and functions. We argue that specific protection strategies and directions can be determined according to the construction objectives of local ENs. [ABSTRACT FROM AUTHOR]

As the key tool for land use management in China, land use planning (LUP) is characterized by the advantage of being state-led, quota-oriented, and easily monitored. Nevertheless, increasing research has doubted its effectiveness, particularly in controlling urban expansion, while few studies have empirically confirmed it. To this end, we construct a planning constraint index (PCI), supported by land use quota, for evaluating the pressure from LUP on urban expansion, and then analyze the spatial equilibrium of PCI. We also explore the spatial effects of PCI on urban expansion via the geographically weighted regression model (GWR) by collecting the spatial data of 280 prefecture-level cities in China from 2009 to 2016. The results show that: (1) most cities present a shortage of urban land quotas, and spatial disequilibrium exist among regions; (2) PCI has significant negative effects on urban expansion for all of the 280 cities, and spatial disparity of these effects occurs as well; (3) PCI has a stronger influence in southwest China where the economy is relatively backward. This study aims to provide a reference for land use planners and policymakers to help improve the effectiveness of LUP. [ABSTRACT FROM AUTHOR]

Visible and near-infrared (VIS-NIR) spectroscopy has been extensively applied to estimate soil organic matter (SOM) in the laboratory. However, if field/moist VIS-NIR spectra can be directly applied to estimate SOM, then much of the time and labor would be avoided. Spectral derivative plays an important role in eliminating unwanted interference and optimizing the estimation model. Nonetheless, the conventional integer order derivatives (i.e., the first and second derivatives) may neglect some detailed information related to SOM. Besides, the full-spectrum generally contains redundant spectral variables, which would affect the model accuracy. This study aimed to investigate different combinations of fractional order derivative (FOD) and spectral variable selection techniques (i.e., competitive adaptive reweighted sampling (CARS), elastic net (ENET) and genetic algorithm (GA)) to optimize the VIS-NIR spectral model of moist soil. Ninety-one soil samples were collected from Central China, with their SOM contents and reflectance spectra measured. Support vector machine (SVM) was applied to estimate SOM. Results indicated that moist spectra differed greatly from dried ground spectra. With increasing order of derivative, the spectral resolution improved gradually, but the spectral strength decreased simultaneously. FOD could provide a better tool to counterbalance the contradiction between spectral resolution and spectral strength. In full-spectrum SVM models, the most accurate estimation was achieved by SVM model based on 1.5-order derivative spectra, with validation R2 = 0.79 and ratio of the performance to deviation (RPD) = 2.20. Of all models studied (different combinations of FOD and variable selection techniques), the highest validation model accuracy for SOM was achieved when applying 1.5 derivative spectra and GA method (validation R2 = 0.88 and RPD = 2.89). Among the three variable selection techniques, overall, the GA method yielded the optimal predictability. However, due to its long computation time, one alternative was to use CARS method. The results of this study confirm that a suitable combination of FOD and variable selection can effectively improve the model performance of SOM in moist soil. [ABSTRACT FROM AUTHOR]

Rapid urbanization in China has caused a large number of rural-to-urban migrants (RUMs) and rapid urban land expansion (ULE). Understanding the relationship between RUMs and ULE has important implications for urban sustainable development. This study explored the spatial patterns of RUMs and ULE in Hubei Province from 2009 to 2014, and analyzed the relationship between the two using a decoupling model. The results show that: (1) a large proportion of the rural population migrated to urban areas in Hubei Province from 2009 to 2014, and the distribution of RUMs was uneven: developed areas attracted more RUMs than undeveloped regions; (2) the urban land in Hubei Province increased rapidly from 2009 to 2014, and the urban land use in Hubei Province was extensive and inefficient; (3) the decoupling types between RUMs and ULE in Hubei Province were dominated by expansive negative and weak decoupling; (4) according to the changes in per capita urban land area and decoupling types, the coordination relationship between RUMs and ULE in Hubei Province was divided into eight types, and while the relationship between RUMs and ULE in most areas were coordinated and beneficial to urban land intensive use, the rest were uncoordinated. Finally, reasonable implications for urban sustainable development and new land use policy were put forward. [ABSTRACT FROM AUTHOR]

Soil organic matter (SOM) is an important parameter of soil fertility, and visible and near-infrared (VIS-NIR) spectroscopy combined with multivariate modeling techniques have provided new possibilities to estimate SOM. However, the spectral signal is strongly influenced by soil moisture (SM) in the field. Interest in using spectral classification to predict soils in the moist conditions tominimize the influence of SMis growing. The objective of this study was to investigate the transferability of two approaches, SM-based cluster method with known SM(classifying the VIS-NIR spectra into different SM clusters to develop models separately), the normalized soil moisture index (NSMI)-based cluster method with unknown SM(utilizing NSMI to indicate the SM and establish models separately), to predict SOM directly in moist soil spectra. One hundred and twenty one soil samples were collected from Central China, and eight SM levels were obtained for each sample through rewetting experiments. Their reflectance spectra and SOMconcentrations were measured in the laboratory. Partial least square-support vector machine (PLS-SVM) was employed to construct SOMprediction models. Specifically, prediction models were developed for NSMI-based clusters with unknown SMdata. The models were assessed through three statistics in the processes of calibration and validation: the coefficient of determination (R2), root mean square error (RMSE) and the ratio of the performance to deviation (RPD). Results showed that the variable SMled to reduced VIS-NIR reflectance nonlinearly across the entire spectral range. NSMI was an effective spectral index to indicate the SM. Classifying the VIS-NIR spectra into different SMclusters in known SMstates could improve the performance of PLS-SVMmodels to acceptable prediction accuracies (R2cv = 0.69-0.77, RPD = 1.79-2.08). The estimation of SOM, when using the NSMI-based cluster method with unknown SM(RPD = 1.95-2.04), was similar to the use of the SM-based cluster method with known SM (RPD = 1.79-2.08). The predictive results (RPD = 1.87-2.06) demonstrated that the NSMI-based cluster method has potential for application outside the laboratory for SOMprediction without knowing the SMexplicitly, and this method is also easy to carry out and only requires spectral information. [ABSTRACT FROM AUTHOR]

Ecological-living-production land (ELPL) is gaining an increasing attention of governors, planners and scholars to alleviate ecological deterioration on the premise of ensuring regional sustainable development in China. This paper has built an ecological-living-production land classification system (ELCS) by the reclassification method, and further analyzed the spatio-temporal characteristics and evolution mechanism of ELPL from 2009 to 2014 with a case study of Hubei Province of Central China. The results show that (1) land with an ecological function held a dominant role in Hubei Province. Ecological land (EL) and production-eco land (PEL) covered the largest areas. The area of EL was the largest in Western Hubei Eco-cultural Tourism Circle (WHETC), and the area of PEL accounted for the largest proportion in Wuhan Urban Circle (WUC). (2) Land with an ecological function was decreasing continuously, while the land with living function expanded rapidly. Additionally, the intensity of ELPL changes in the WUC was higher than that in the WHETC. (3) The changes of ELPL threatened the food and ecological security and adversely affected the sustainable development. The factors of population growth and GDP increase were the main driving forces of ELPL change. The results of this study provide valuable information for planning decision makings (e.g., the ELPL spatial pattern optimization). [ABSTRACT FROM AUTHOR]

Farmland is one of the most important and active components of the soil carbon pool. Exploring the controlling factors of farmland soil organic carbon density (SOCD) and its sequestration rate (SOCDSR) is vital for improving carbon sequestration and addressing climate change. Present studies provide considerable attention to the impacts of natural factors and agricultural management on SOCD and SOCDSR. However, few of them focus on the interaction effects of environmental variables on SOCD and SOCDSR. Therefore, using 64 samples collected from 19 agricultural stations in China, this study explored the effects of natural factors, human activities, and their interactions on farmland SOCD and SOCDSR by using geographical detector methods. Results of geographical detectors showed that SOCD was associated with natural factors, including groundwater depth, soil type, clay content, mean annual temperature (MAT), and mean annual precipitation. SOCDSR was related to natural factors and agricultural management, including MAT, groundwater depth, fertilization, and their interactions. Interaction effects existed in all environmental variable pairs, and the explanatory power of interaction effects was often greater than that of the sum of two single variables. Specifically, the interaction effect of soil type and MAT explained 74.8% of the variation in SOCD, and further investigation revealed that SOCD was highest in Luvisols and was under a low MAT (<6 °C). The interaction effect of groundwater depth and fertilization explained 40.4% of the variation in SOCDSR, and fertilization was conducive to SOCD increase at a high groundwater depth (<3 m). These findings suggest that low soil temperature, high soil moisture, and fertilization are conducive to soil carbon accumulation. These findings also highlight the importance of agricultural management and interaction effects in explaining SOCD and SOCDSR, which promote our knowledge to better understand the variation of SOCD and its dynamics. [ABSTRACT FROM AUTHOR]

Land subsidence has become an increasing global concern over the past few decades due to natural and anthropogenic factors. However, although several studies have examined factors affecting land subsidence in recent years, few have focused on the spatial heterogeneity of relationships between land subsidence and urbanization. In this paper, we adopted the small baseline subset-synthetic aperture radar interferometry (SBAS-InSAR) method using Sentinel-1 radar satellite images to map land subsidence from 2015 to 2018 and characterized its spatial pattern in Wuhan. The bivariate Moran's I index was used to test and visualize the spatial correlations between land subsidence and urbanization. A geographically weighted regression (GWR) model was employed to explore the strengths and directions of impacts of urbanization on land subsidence. Our findings showed that land subsidence was obvious and unevenly distributed in the study area, the annual deformation rate varied from −42.85 mm/year to +29.98 mm/year, and its average value was −1.0 mm/year. A clear spatial pattern for land subsidence in Wuhan was mapped, and several apparent subsidence funnels were primarily located in central urban areas. All urbanization indicators were found to be significantly spatially correlated with land subsidence at different scales. In addition, the GWR model results showed that all urbanization indicators were significantly associated with land subsidence across the whole study area in Wuhan. The results of bivariate Moran's I and GWR results confirmed that the relationships between land subsidence and urbanization spatially varied in Wuhan at multiple spatial scales. Although scale dependence existed in both the bivariate Moran's I and GWR models for land subsidence and urbanization indicators, a "best" spatial scale could not be confirmed because the disturbance of factors varied over different sampling scales. The results can advance the understanding of the relationships between land subsidence and urbanization, and they will provide guidance for subsidence control and sustainable urban planning. [ABSTRACT FROM AUTHOR]

Although many publications have noted the impact of urban planning on urban development and land-use change, the incorporation of planning constraints into urban growth simulation has not been adequately addressed so far. This study aims to develop a planning-constrained cellular automata (CA) model by combining cell-based trade-off between urban growth and natural conservation with a zoning-based planning implementation mechanism. By adjusting the preference parameters of different planning zones, multiple planning-constrained scenarios can be generated. Taking the Wuhan Urban Development Area (WUDA), China as a case study, the planning-constrained CA model was applied to simulate current and future urban scenarios. The results show a higher simulation accuracy compared to the model without planning constraints. With the weakening of planning constraints, urban growth tends to occupy more ecological and agricultural land with high conservation priority. With the increase in preference on urban growth or natural conservation, the future urban land pattern will become more fragmented. Furthermore, new urban land beyond the planned urban development area can be captured in future urban scenarios, which will provide certain early warning. The simulation of the current urban spatial pattern should help planners and decisionmakers to evaluate the past implementation of urban planning, and scenarios simulation can provide effective support for future urban planning by evaluating the consequences. [ABSTRACT FROM AUTHOR]

Limited studies focus on educational equity from the spatial accessibility perspective. This study combines survey data and big data and proposes a multi-mode Huff two-step floating catchment area (MMH2SFCA) method to calculate accessibility while considering multiple travel modes and school attractiveness. This method can also calculate education quality by extending the accessibility in each community. Results show that our proposed method can reliably identify the accessibility differences of schools across communities. The case study indicates an inequitable distribution of educational accessibility and quality. The communities with high accessibility are concentrated in the urban center and exurban zones surrounding schools, whereas high-quality areas are mainly concentrated in the urban center. Correlation analysis suggests that the educational quality of communities with high accessibility is not always high. The findings of this study can provide improvement for accessibility measurements and help explore a new research perspective for educational equity research. [ABSTRACT FROM AUTHOR]

Visible and near-infrared reflectance (VIS-NIR) spectroscopy is widely applied to estimate soil organic carbon (SOC). Intense and diverse human activities increase the heterogeneity in the relationships between SOC and VIS-NIR spectra in anthropogenic soil. This fact results in poor performance of SOC estimation models. To improve model accuracy and parsimony, we investigated the performance of two variable selection algorithms, namely competitive adaptive reweighted sampling (CARS) and random frog (RF), coupled with five spectral pretreatments. A total of 108 samples were collected from Jianghan Plain, China, with the SOC content and VIS-NIR spectra measured in the laboratory. Results showed that both CARS and RF coupled with partial least squares regression (PLSR) outperformed PLSR alone in terms of higher model accuracy and less spectral variables. It revealed that spectral variable selection could identify important spectral variables that account for the relationships between SOC and VIS-NIR spectra, thereby improving the accuracy and parsimony of PLSR models in anthropogenic soil. Our findings are of significant practical value to the SOC estimation in anthropogenic soil by VIS-NIR spectroscopy. [ABSTRACT FROM AUTHOR]

Jobs–housing imbalance is a hot topic in urban study and has obtained many results. However, little research has overcome the limits of administrative boundaries in job accessibility measurement and considered differences in job accessibility within multiple commuting circles. Using Baidu location data, this research proposes a new method to measure job accessibility within multiple commuting circles at the grids' level. Taking the Wuhan metropolitan area as a case study, the results are as follows: (1) Housing and service jobs are concentrated in the central urban areas along the Yangtze River, whereas industrial jobs are scattered throughout suburbs with double centers. The potential competition for job opportunities is fiercer in the city center than in the suburbs. (2) Job accessibility with different levels shows significant circle-like distribution. People with long- or short-distance potential commutes demand to live close to the groups with the same demand. Residents with long-distance commutes demand to live outside of where those with short-distance commutes demand to reside, regardless of whether their commuting demand is for service or industrial jobs. (3) There are three optimization patterns for transit services to increase job accessibility in various areas. These patterns involve areas with inadequate job opportunities, poor transit services to service jobs, and poor transit services to industrial jobs. Developing current transit facilities or new transit alternatives as well as adding extra jobs near housing could improve jobs–housing imbalance in these areas. Findings from this study could guide the allocation of jobs and housing as well as the development of transport to reduce residents' commuting burdens and promote transportation equity. The method used in this study can be applied to evaluate jobs–housing imbalance from the perspective of the supply in other metropolises. [ABSTRACT FROM AUTHOR]

Public transport accessibility (PTA) is an essential index for evaluating the efficiency of urban public transport resource and public service. Improving public transport accessibility is considered as the most effective way of alleviating urban congestion and promoting urban sustainability. PTA can be divided into three types, which are access to stations, accessibility of networks and access to activities. This paper focuses on evaluating access to public transport service at stations, considering walking time to stations and waiting time for services at stations. Numerous studies have been carried out on evaluating the accessibility of public transport stations. When building accessibility evaluation model, rare has seen different public transport modes as an integrated system. Hence the topological structure and geometrical layout of the system are not considered. In this paper, factors like the configuration of the public transport system and the surrounding environment of stations are included for the evaluation. The centrality of station index (COS) is presented to describe the importance of stations in the integrated public transport system. The COS index is an improved combination of the gravity model and degree centrality index of the complex network. This index improves the degree centrality index by replacing the number of nodes with weighted connections between stations. By modeling public transport operation, configuration and surroundings of stations, a comprehensive public transport service accessibility index (CPTAI) is formulated to quantify accessibility at the community level. To compute this index, a network analysis model is firstly applied to find the nearest station for each point of interest (POI) by using ArcGIS desktop 10.2, and the transport service frequency at the nearest station is measured. Then Baidu Map API is employed to measure the impedance indexes between stations in the integrated public transport network. Activities covered by stations within a given distance are seen as the generation and attraction of trips in between the stations. Then a weighted gravity model and COS is presented to calculate the integrated service frequency (ISF) for each POI afterward. In the end, the index is converted to the community level, which is CPTAI. The experiment is carried out in Wuhan metropolitan area, Hubei, China. Smart card data (SCD) is utilized to evaluate CPTAI and examine the association between commuting trips by public transport and accessibility level within Wuhan metropolitan area. Experimental results show that CPTAI has a significant statistical association with trips by public transport. [ABSTRACT FROM AUTHOR]

In constructing models for predicting soil organic matter (SOM) by using visible and near-infrared (vis–NIR) spectroscopy, the selection of representative calibration samples is decisive. Few researchers have studied the inclusion of spectral pretreatments in the sample selection strategy. We collected 108 soil samples and applied six commonly used spectral pretreatments to preprocess soil spectra, namely, Savitzky–Golay (SG) smoothing, first derivative (FD), logarithmic function log(1/R), mean centering (MC), standard normal variate (SNV), and multiplicative scatter correction (MSC). Then, the Kennard–Stone (KS) strategy was used to select calibration samples based on the pretreated spectra, and the size of the calibration set varied from 10 samples to 86 samples (80% of the total samples). These calibration sets were employed to construct partial least squares regression models (PLSR) to predict SOM, and the built models were validated by a set of 21 samples (20% of the total samples). The results showed that 64−78% of the calibration sets selected by the inclusion of pretreatment demonstrated significantly better performance of SOM estimation. The average improved residual predictive deviations (ΔRPD) were 0.06, 0.13, 0.19, and 0.13 for FD, log(1/R), MSC, and SNV, respectively. Thus, we concluded that spectral pretreatment improves the sample selection strategy, and the degree of its influence varies with the size of the calibration set and the type of pretreatment. [ABSTRACT FROM AUTHOR]

Wuhan city is the biggest city in central China and has suffered subsidence problems in recent years because of its rapid urban construction. However, longtime and wide range monitoring of land subsidence is lacking. The causes of subsidence also require further study, such as natural conditions and human activities. We use small baseline subset (SBAS) interferometric synthetic aperture radar (InSAR) method and high-resolution RADARSAT-2 images acquired between 2015 and 2018 to derive subsidence. The SBAS-InSAR results are validated by 56 leveling benchmarks where two readings of elevation were recorded. Two natural factors (carbonate rock and soft soils) and three human factors (groundwater exploitation, subway excavation and urban construction) are investigated for their relationships with land subsidence. Results show that four major areas of subsidence are detected and the subsidence rate varies from −51.56 to 27.80 millimeters per year (mm/yr) with an average of −0.03 mm/yr. More than 83.81% of persistent scattered (PS) points obtain a standard deviation of less than −6 mm/yr, and the difference between SBAS-InSAR method and leveling data is less than 5 mm/yr. Thus, we conclude that SBAS-InSAR method with Radarsat-2 data is reliable for longtime monitoring of land subsidence covering a large area in Wuhan city. In addition, land subsidence is caused by a combination of natural conditions and human activities. Natural conditions provide a basis for subsidence and make subsidence possible. Human activities are driving factors and make subsidence happen. Moreover, subsidence information could be used in disaster prevention, urban planning, and hydrological modeling. [ABSTRACT FROM AUTHOR]

Mapping land surface water bodies from satellite images is superior to conventional in situ measurements. With the mission of long-term and high-frequency water quality monitoring, the launch of the Ocean and Land Colour Instrument (OLCI) onboard Sentinel-3A and Sentinel-3B provides the best possible approach for near real-time land surface water body mapping. Sentinel-3 OLCI contains 21 bands ranging from visible to near-infrared, but the spatial resolution is limited to 300 m, which may include lots of mixed pixels around the boundaries. Sub-pixel mapping (SPM) provides a good solution for the mixed pixel problem in water body mapping. In this paper, an unsupervised sub-pixel water body mapping (USWBM) method was proposed particularly for the Sentinel-3 OLCI image, and it aims to produce a finer spatial resolution (e.g., 30 m) water body map from the multispectral image. Instead of using the fraction maps of water/non-water or multispectral images combined with endmembers of water/non-water classes as input, USWBM directly uses the spectral water index images of the Normalized Difference Water Index (NDWI) extracted from the Sentinel-3 OLCI image as input and produces a water body map at the target finer spatial resolution. Without the collection of endmembers, USWBM accomplished the unsupervised process by developing a multi-scale spatial dependence based on an unsupervised sub-pixel Fuzzy C-means (FCM) clustering algorithm. In both validations in the Tibet Plate lake and Poyang lake, USWBM produced more accurate water body maps than the other pixel and sub-pixel based water body mapping methods. The proposed USWBM, therefore, has great potential to support near real-time sub-pixel water body mapping with the Sentinel-3 OLCI image. [ABSTRACT FROM AUTHOR]

Ancillary data, such as soil type, may improve the visible and near-infrared (vis-NIR) estimation of soil organic carbon (SOC); however, they require data collection or expert knowledge. The application of a national soil spectral library to local SOC estimations usually requires soil type information, because the relationships between vis-NIR spectra and SOC from different populations may vary. Using 515 samples of five soil types (genetic soil classification of China, GSCC) from the Chinese soil spectral library (CSSL), we compared three strategies in the vis-NIR estimation of SOC. Different regression models were calibrated using the entire dataset (Strategy I, without using soil type as ancillary data) and the subsets stratified by soil type from CSSL as ancillary data (strategies II and III). In Strategy II, the subsets were stratified by soil type from the CSSL for validation. In Strategy III, the subsets were stratified by spectrally derived soil type for validation. The results showed that 86.72% of the samples were successfully discriminated for the soil types by using the vis-NIR spectra. The coefficients of determination in the prediction ( R p 2 ) of SOC estimation by strategies I, II, and III were 0.74, 0.83, and 0.82, respectively. The stratified calibration strategies (strategies II and III) improved the vis-NIR estimation of SOC. The misclassification of the soil type in the application of Strategy III slightly affected the SOC estimations. Nevertheless, this strategy is inexpensive and beneficial when expert knowledge on soil classification is lacking. We concluded that vis-NIR spectroscopy could be applied to distinguish some soil types in terms of GSCC, which further provided essential and easily accessible ancillary data for the application of stratified calibration strategies in the vis-NIR estimation of SOC. [ABSTRACT FROM AUTHOR]

Existing spatial community detection algorithms are usually modularity based. Motivated by different applications, these algorithms build appropriate spatial null models to describe spatial effects on the connection of nodes. Then, by choosing certain modularity maximizing strategies, they try to find interesting community structures hidden behind the null models. In this paper, a novel structural similarity-based spatial network community is defined, which is based on the shared neighbors of nodes. In addition, there are two other special node roles defined: the spatial hub and outlier. Then, a density and adjacency expansion-based spatial structural community detection algorithm for networks (DASSCAN) is proposed for mining these communities, hubs and outliers. DASSCAN uses structural similarity to measure the relationship between nodes, and then, structurally similar and spatially adjacent nodes are merged into communities using a density-based clustering method and spatial adjacency expansion strategy. Comparative experiments on two kinds of Chinese train line networks clarified the accuracy and efficiency of DASSCAN in finding the spatial structural communities, spatial hubs and outliers. The communities found can be used to uncover more interesting spatial structural patterns, and the hubs and outliers are more accurate and have more valuable meanings. [ABSTRACT FROM AUTHOR]

Ecological security is an important research topic, especially urban ecological security. As highly populated eco-systems, cities always have more fragile ecological environments. However, most of the research on urban ecological security in literature has focused on evaluating current or past status of the ecological environment. Very little literature has carried out simulation or prediction of future ecological security. In addition, there is even less literature exploring the urban ecological environment at a fine scale. To fill-in the literature gap, in this study we simulated and predicted urban ecological security at a fine scale (district level) using an improved Cellular Automata (CA) approach. First we used the pressure-state-response (PSR) method based on grid-scale data to evaluate urban ecological security. Then, based on the evaluation results, we imported the geographically weighted regression (GWR) concept into the CA model to simulate and predict urban ecological security. We applied the improved CA approach in a case study-simulating and predicting urban ecological security for the city of Wuhan in Central China. By comparing the simulated ecological security values from 2010 using the improved CA model to the actual ecological security values of 2010, we got a relatively high value of the kappa coefficient, which indicates that this CA model can simulate or predict well future development of ecological security in Wuhan. Based on the prediction results for 2020, we made some policy recommendations for each district in Wuhan., Competing Interests: The authors declare no conflict of interest. The founding sponsors had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, and in the decision to publish the results.

Alternative land use zoning scenarios provide guidance for sustainable land use controls. This study focused on an ecologically vulnerable catchment on the Loess Plateau in China, proposed a novel land use zoning model, and generated alternative zoning solutions to satisfy the various requirements of land use stakeholders and managers. This model combined multiple zoning objectives, i.e., maximum zoning suitability, maximum planning compatibility and maximum spatial compactness, with land use constraints by using goal programming technique, and employed a modified simulated annealing algorithm to search for the optimal zoning solutions. The land use zoning knowledge was incorporated into the initialisation operator and neighbourhood selection strategy of the simulated annealing algorithm to improve its efficiency. The case study indicates that the model is both effective and robust. Five optimal zoning scenarios of the study area were helpful for satisfying the requirements of land use controls in loess hilly regions, e.g., land use intensification, agricultural protection and environmental conservation.

Comprehensive land-use planning (CLUP) at the county level in China must include land-use zoning. This is specifically stipulated by the China Land Management Law and aims to achieve strict control on the usages of land. The land-use zoning problem is treated as a multi-objective optimization problem (MOOP) in this article, which is different from the traditional treatment. A particle swarm optimization (PSO) based model is applied to the problem and is developed to maximize the attribute differences between land-use zones, the spatial compactness, the degree of spatial harmony and the ecological benefits of the land-use zones. This is subject to some constraints such as: the quantity limitations for varying land-use zones, regulations assigning land units to a certain land-use zone, and the stipulation of a minimum parcel area in a land-use zoning map. In addition, a crossover and mutation operator from a genetic algorithm is adopted to avoid the prematurity of PSO. The results obtained for Yicheng, a county in central China, using different objective weighting schemes, are compared and suggest that: (1) the fundamental demand for attribute difference between land-use zones leads to a mass of fragmentary land-use zones; (2) the spatial pattern of land-use zones is remarkably optimized when a weight is given to the sub-objectives of spatial compactness and the degree of spatial harmony, simultaneously, with a reduction of attribute difference between land-use zones; (3) when a weight is given to the sub-objective of ecological benefits of the land-use zones, the ecological benefits get a slight increase also at the expense of a reduction in attribute difference between land-use zones; (4) the pursuit of spatial harmony or spatial compactness may have a negative effect on each other; (5) an increase in the ecological benefits may improve the spatial compactness and spatial harmony of the land-use zones; (6) adjusting the weights assigned to each sub-objective can generate a corresponding optimal solution, with a different quantity structure and spatial pattern to satisfy the preference of the different decision makers; (7) the model proposed in this paper is capable of handling the land-use zoning problem, and the crossover and mutation operator can improve the performance of the model, but, nevertheless, leads to increased time consumption.

Heavy metal pollution in soil is becoming a widely concerning environmental problem in China. The aim of this study is to integrate multiple sources of data, namely total Cu and Pb contents, digital elevation model (DEM) data, remote sensing image and interpreted land-use data, for mapping the spatial distribution of total Cu and Pb contamination in top soil along the Le'an River and its branches. Combined with geographical analyses and watershed delineation, the source and transportation route of pollutants are identified. Regions at high risk of Cu or Pb pollution are suggested. Results reveal that topography is the major factor that controls the spatial distribution of Cu and Pb. Watershed delineation shows evidence that the streamflow resulting from rainfall is the major carrier of metal pollutants.

Aquatic ecological carrying capacity is an effective method for analyzing sustainable development in regional water management. In this paper, an integrated approach is employed for assessing the aquatic ecological carrying capacity of Wujin District in the Tai Lake Basin, China. An indicator system is established considering social and economic development as well as ecological resilience perspectives. While calculating the ecological index, the normalized difference vegetation index (NDVI) is extracted from Moderate Resolution Imaging Spectroradiometer (MODIS) time-series images, followed by spatial and temporal analysis of vegetation cover. Finally, multi-index assessment of aquatic ecological carrying capacity is carried out for the period 2000 to 2008, including both static and dynamic variables. The results reveal that aquatic ecological carrying capacity presents a slight upward trend in the past decade and the intensity of human activities still exceeded the aquatic ecological carrying capacity in 2008. In terms of human activities, population has decreased, GDP has quadrupled, and fertilizer application and industrial wastewater discharge have declined greatly in the past decade. The indicators representing aquatic ecosystem conditions have the lowest scores, which are primarily attributed to the water eutrophication problem. Yet the terrestrial ecosystem is assessed to be in better condition since topographic backgrounds and landscape diversity are at higher levels. Based on the work carried out, it is suggested that pollutant emission be controlled to improve water quality and agricultural development around Ge Lake (the largest lake in Wujin District) be reduced.