Topological relationship is one of the basic topics of geographic information systems (GISs), and it has been widely applied to data organization and spatial analysis. Many scholars have studied the models of topological relationship and achieved some progresses, among which the 9-Intersections Model (9IM) is well known. This paper aims at finding a method to solve the prominent issue that current models of spatial topological relationships could not represent complex objects. Taking the line object as an example, according to the concepts of point set topology, the complexity of the line object is redefined and distinguished. A linear sequence model of topological relationships, which is based on 9-Intersections Model (9IM) for complex line objects, is proposed and it is represented by some composite basic 9IM matrices. To calculate and distinguish these topological relationships, we applied different methods according to the different relationships between the lines, e.g. some of the lines intersect, some overlap, and others may disjoint. Our main works are stated as follows: we designed an improved sweep-line algorithm to increase the efficiency of the program; we took rectangular envelope algorithm to reduce the execution times, and used vector cross product to determine whether there are any intersections between lines; and we also used coordinates and slopes to deal with some special situations. The test system is developed to prove the capability and efficiency of the model and the calculation method. The procedure is: firstly, the coordinates of two polylines are input; secondly, the polylines are drawn and displayed on the screen, and then the algorithm is executed; finally, the results of topological expressions are produced and shown. As a result, our model can successfully calculate most special relationships between complex polylines, but without the involvement of arc or self-intersection. Generally, this model is still incomplete at present and needs to be improved in future.
Spatial ordering based on space- filling curves is a linear mapping method from multi- dimensional space to one-dimensional space, which has been widely used in spatial querying, spatial indexing, space partition, image coding, and other related fields. The Hilbert curve is an excellent space-filling curve with remarkable spatial clustering properties. The traditional algorithm for Hilbert ordering code is based on binary circular bit manipulation, which has a complexity of O(n2). In this article, the Hilbert state- transition matrix is generated based on the fractal self- similarity, the spatial quadrants are redefined by the sequence of spatial partition, and the Hilbert state-transition matrix is translated into arrays in C++, all of which effectively reduce the nested loops and the iterations in the process of computing Hilbert code, thus decrease the complexity of algorithm to O(n). Also, the bit field union type is used to avoid the type conversion from number to string in the process of Hilbert code computation, which brings numerical calculation into full play and improves the performance of the Hilbert coding algorithm. Finally, the C++ code for Hilbert code generating algorithm is given, and various tests have been conducted to verify the correctness of the algorithm and to compare the performance with regard to the binary circular bit algorithm as well as the hierarchical space decomposition algorithm. Test results show that the algorithm demonstrates notable merits compared with the other two algorithms.
As a fundamental form of spatial data, Digital Elevation Model (DEM) plays a considerable role in many fields, such as surveying and mapping, territorial planning, and national defense. DEM is usually discrete in data structure and is an approximation of the real terrain. Though the technology of obtaining the elevations of sampling points has been improved, the real surface can only be represented by discrete grids. This means that the slope can only be computed by using the elevations of discrete grids. Therefore, the derived slope will have an unavoidable error. However, it is the slope that determines the transfer of matters and energy on the terrain surface and its accuracy exerts a great influence on the related researches and applications. 5 areas of Shenmu, Suide, Yanchuan, Fuxian and Yijun in Loess Plateau that represent the typical geomorphology are chosen as the sample areas, in which the DEMs with resolutions of 5 m, 15 m, 25 m, 35 m, 45 m, 55 m, 65 m and 75m are established according to the topographic map scaled at 1:10000. The slope is derived by using the algorithm of the third-order finite difference weighted by the reciprocal of squared distance. The slope derived from DEM with a resolution of 5 m is assumed to be the true value, and the slopes derived from other DEMs are taken as the investigated subjects. Each area is divided into 36 subareas. The relationship between the index and the resolutions of DEMs is investigated in 20 subareas selected randomly from the 36 subareas. We proposed an index for the slope information loss based on the single grid, and obtained empirical equations to describe the relationship between the resolutions of DEM and the values of the index. The equations are tested in the other16 subareas and proved to be effective. Using the equations, we can get the most suitable resolution for DEM when the index is known. The users, who want to select proper resolutions for DEM to minimize the amount of data and reduce the cost while ensuring the accuracy of the slope information of DEM, will benefit from the empirical equations.
Human activities and interactions in space and time are essential in people's daily life. The study of space-time accessibility based on group interactions, concerning the freedom of group member behaviors, has attracted considerable research interests in many research fields, including geography, transportation, planning, and behavioral science. However, most existing accessibility evaluation methods are lack of considerations of the opening hours of facilities, for example the open hour from 9:00 am-9:00 pm, and individual preferences such as personal taste of food. In this paper, by extending individual space-time path and individual space-time prism, which are the key concepts of Hägerstrand's time geography, we proposed the group interactive space-time path and the group interactive space-time prism to represent interactions among people in space and time. Then we build a space-time accessibility evaluation model for group interactions by taking into account both the opening hours of facilities and the individual preferences. In particular, this accessibility evaluation model involves four evaluation factors, including group preference, minimum interaction time, facility attractiveness and travel time decay. Finally, we testify this model with a case study of group accessibility regarding to food service facilities in Beijing, China. The evaluated values of accessibility to food service facilities are graded and the top ones can be used for recommendations. For example, when people want to host a party at a restaurant, they may request that the flavor offered by this restaurant should satisfy every group member, the restaurant is open during the preferable time, and its location is not far away from this group of people. The experiment result shows that this model may provide good references to many applications such as group activity location recommendations, mobile social networks and individual travel-activity guide.
When visiting multiple tourist scenic spots, a recommended travel line is usually the most effective route designed for tourists according to the actual road situations. In the field of intelligent tourism navigation, a traditional recommended travel line is mainly generated by path planning algorithm automatically, considering thescenic spots’ positions and road networks based on graph model. Normally, the traditional algorithms firstly map scenic spots (which belong to certain scenic area) into points of interests (POIs),and map the road network that links these POIs into a line collection, then build the corresponding graph model. But when a scenic spot has a limited area and involves multiple entrances or exits(for example buildings with multiple indoor space), the traditional described mechanism for single point coordinates is difficult to reflect these structural features. In reality, scenic area path planning is widely applied in the field of mobile tourism guide recently, especially for pedestrians. There exist significant differences between theoretical optimal paths and actual optimal paths, sincetouristsare inclined to have more choices. In order to solve this problem, this paper analyzed various influences on the process of path planning, caused by scenic spots’ own structural features (such as the size, shape and entrance), and focused on the influences of multiple entrances or exits located within the scenic area. Then,we proposed a Double-Weighted Graph Model considering multiple entrances and exits for tourist scenic area, and the weights of both vertexes and edges of the proposed model can be selected and weighted dynamically. Next, we discussed the building method for the model, and proposed an optimal path planning algorithm based on Dijkstra algorithm and Prim algorithm. Experimental results show that the optimal planned travel line derived from this proposed model and algorithms is considerably reasonable, and the travelling order and travelling distance can be further optimized.
In recent years, with the rapid development of remote sensing technology, the spatial data represented by remote sensing images is widely used in ecosystem modeling, which promoted the development of ecological remote sensing parametric model in the regional scale. Sensitivity analysis is a key step for ecosystem model uncertainty quantification. It can identify the dominant parameters, reduce the model calibration uncertainty, and enhance the model optimization efficiency. Due to the intensive computation of spatial data during the sensitivity analysis, the traditional stand-alone environment cannot meet the requirements of rapid analysis for the regional scale remote sensing parametric model. This study designed and realized a parallel algorithm of Sobol′ spatial sensitivity analysis utilizing Hadoop, which is an open source cloud computing platform, based on VPM (Vegetation Photosynthesis Model). In order to verify the efficiency of the algorithm, we designed a comparison experiment to compare the efficiency differences of the traditional serial algorithm and the parallel algorithm. The parallel programming technology we used in this research was MapReduce, which divided the processes of map sampling and the iterative calculation during the spatial sensitivity analysis into subtasks, and assigned them to multiple computing nodes for parallel computing. The numerical experiment showed that the parallel strategy proposed in this study effectively shortened the time of model iterative calculations and significantly improved the efficiency of spatial sensitivity analysis for ecological remote sensing parametric model. Compared with the serial algorithm, the computing efficiency of the parallel algorithm was enhanced by 14 times.
Knickpoints are fundamental for understanding local erosion basis and the evolution of fluvial landforms. To extract the knickpoints, Digital Elevation Model (DEM) is widely adopted as the basic data in literatures. However, the accuracy of the extraction is greatly influenced by the DEM resolution. In this paper, to explore the influence of DEM resolution on the extraction of knickpoints, we analyzed the gradient of the fluvial longitudinal profiles to extract the knickpoints in Mount Lu area based on DEM and Digital Line Graphic (DLG). Firstly, the longitudinal profiles of the 16 streams with elevations are derived from 5 m DEM, from which the potential knickpoints are extracted from an empirical gradient domain. Secondly, to find a suitable gradient domain, a field investigation of four typical rivers, including Three-Step Spring and Crane Ravine, is carried out to collect the spatial positions of 30 knickpoints with GPS. Thirdly, multiple resolutions of DEM data are generated by wavelet transformation based on the 5 m DEM. The knickpoints in each scale are extracted in the same way from the corresponding DEM. Finally, the influence of the DEM resolution on the accuracy of knickpoints is discussed. The experiment results reveal that the suitable threshold of gradient domain for 5 m DEM is 0.6, by which the knickpoints’ altitude differences are greater than 5 m. The number of knickpoints is subject to a power function of the DEM resolution. As the DEM resolution coarsens, the number of knickpoints decreases. To verify this power function, the ASTER GDEM and SRTM DEM data are used, which reveals the consistency between the extracted knickpoints from the DEMs and the predicted ones from the function.
The analysis of the spatial information in literary works and spatial visualization analysis provide a new perspective for the study of literature, which has important reference value for understanding literary works. This article attempts to analyze the spatial information from ancient poetry texts by using two methods: the specific positioning method based on the relationship between the names of ancient and modern places; and the approximate positioning methods, including the method of inference based on the orientation, the method of replacement based on the approximate location and the method of speculation based on the spatio-temporal data. We have designed a database, which can express the authors of ancient poetry, poetry texts, names of places and geographical spatial information that appears in the poems. Taking the poems of Li Bai of the Tang Dynasty as an example, we have collected 967 pieces of his poems and detected the spatial locations where Li Bai composed his poems, and we collected the geographic names appeared in the poems among 563 pieces. Meanwhile, we have initially set up the geographic database for ancient poetry. Based on GIS technology, we have produced a map using the positional information presented in the poems of Li Bai, including the poetry creation places, the described places and the associated places. We have then carried out an analysis of the characteristics of spatial distribution of the positional information, which clearly shows the distribution pattern of the poetry creation space of Li Bai and the representation space of his poems. The study shows that it is feasible for the analysis of the spatial characteristics to be applied on the literatures by using GIS technology, and it has great reference values in the study of ancient poetry and other literary works from the geographical spatial perspective.
Understanding the mechanism of how road development lays profound impacts on the landscape change is significant for regional sustainable development. This paper takes the YRD section of Beijing-Shanghai Expressway as a case, analyzes the remote sensing images in 1995, 2000, 2005 and 2010,and utilizes buffer zone analysis method to estimate the change rate of the landscape quantity structure and landscape pattern index in different periods and regions. Meanwhile, the correlation analysis and nonlinear regression methods are adopted to investigate the relationship between the change rate of landscape pattern and the buffer zone distance. The results from this study indicated the following points: firstly, the construction of G2 expressway generated an axial impact on landscape pattern change. In rapidly urbanizing areas, there is a negative correlation between the change rate of landscape pattern and the buffer distance, which is different from the case of Qinghai-Tibet Highway. Secondly, there is a significant impact of main roads on the succession rule of landscape pattern along the rapidly urbanizing areas, which has broader and stronger effects than the roads in ecologically fragile areas. Finally, the construction of main roads has different temporal and spatial gradient impacts on the succession rule of landscape pattern. With the development of urbanization, the road's effects on the landscape pattern become more obvious. The influence range of G2 is expanding, which was increased from 6 km during the period of 2000-2005 to 9 km during 2005-2010. In addition, in YRD region, the axial affection is more remarkable in cities with low degree of urbanization than those with high degree of urbanization. By combining buffer zone analysis, correlation analysis and nonlinear regression, as well as calculating the change rate of landscape pattern characteristics indices in different periods and regions, we could effectively assess the influence degree and scope of main roads on the landscape pattern change along the roads.
The adjustment of industrial structure and layout optimization in Guangdong Province is significant,as China is at a critical stage with an impressive acceleration of economic globalization and regional integration process. In order to support the regional economic coordination and the industrial transfer planning, as well as lay out optimization in Guangdong Province, this paper studied and qualified the regional accessibility based on the road networks, and characterized the spatial patterns of regional accessibility with different measurement models. Firstly, cities in Guangdong Province are represented by the nodes in road networks. Secondly, the urban function indices of all cities are introduced to represent their size and economic level, respectively. Then, accessibility measurement models, including daily accessibility model, accessibility measurement model based on matrix analysis, and potential model, are applied to evaluate and qualify the regional accessibility and their spatial patterns. Finally, GIS is used to characterize the spatial patterns and differences of the accessibility derived from difference models. The results show that the spatial patterns of the regional accessibility in Guangdong Province are represented by concentric sphere structures with the center located at the core of Guangzhou and within the Chancheng and Shunde districts in the city of Foshan. The spatial representations of the regional accessibility differences show clear directivity derived from highway networks, and reflect the composite effects of urban geographic locations, transportation conditions and economic levels. Particularly, the cities in the Pearl River Delta at the center of Guangdong Province have the best accessibility and economic ties intensity. But the cities in the north, east and west wings of Guangdong, who are distant from the economic center, i.e. the Pearl River Delta, have the worst accessibility. This reveals the weak associations in the spatial and economic interactions between these cities and the Pearl River Delta. Taking into account of different road networks and economic development scenarios, the study reveals regional accessibility differences in the area of the Guangdong Province. This clearly illustrates the impact of accessibility on the regional economic coordination, the industrial transfer planning and lay out optimization.
Based on MODIS NPP data, terrain data and land cover map, spatio-temporal pattern of the NPP in Wuling mountainous area during 2001-2010 and its relationship with the elevation and the slope were analyzed using regression analysis and classification statistics. Results showed that the average annual NPP of the study area from 2001 to 2010 was 590.72 gC·m-2·yr-1. The mean NPP of forest, shrub/grassland and cropland were 596.79 gC·m-2·yr-1, 586.98 gC·m-2·yr-1 and 563.31 gC·m-2·yr-1 respectively. During 2001-2010, the average annual total NPP of Wuling mountainous area was 98.90 TgC·yr-1, ranging from 92.79 TgC·yr-1 to 106.99 TgC·yr-1. Besides, the spatial pattern of interannual variability of NPP in the north of our study area presented a significant increase trend, while in the south it indicated an opposite tendency. According to the relationships between the mean NPP and the elevation as well as the slope in the case of 30 m and 3° respectively, NPP increased with the altitude and slope first, then decreased slowly. But when the elevation went above 1500 m or the slope was greater than 50°, the mean NPP would present large fluctuations. However, as a whole, the mean NPP increased with the altitude and the slope first, then decreased again. Additionally, the mean NPP within the elevation range of 200~1000 m and the slope range of 5~25° were relatively high, but it decreased gradually from the range of 500 m and above, and had a trend of increase when the slope went greater than 50°, which reflected the erosion intensity was weakened when the slope was greater than a certain threshold.
In this paper, we took the Liaohe watershed as the study area and applied the CLUE-S model for the purpose of landscape pattern simulation, based on the land use data in 2000 and 2010. Eight key driving factors were selected in this study, which include elevation, DEM, slope, distance, soil and others. Firstly, the land use data in 2000 was used to simulate the spatial pattern of land use in 2010 for the Liaohe watershed. Based on the adjusted model parameters, the land use patterns of 2020 were then simulated respectively for the natural increase scenario, economic development scenario, and ecological protection scenario. The results showed that the simulation accuracy for 2010 reached a considerably 90.7%, implying that the CLUE-S model is well fitted for modeling the land use pattern in the Liaohe watershed. In different scenarios, it shows explicitly an increase in urban land and a decrease in cultivated land. Under the economic development scenario, we concluded that: the cultivated land conversion range is the largest; the forest reduction is relatively small; and the construction land surrounding the developing zones of the Liaohe River basin had gradually expanded, which mainly aggregated in Shenyang, Fushun, Anshan and other industrial developed cities. Under the ecological protection scenario, we discovered that the forests and wetlands that located at the mouth of the Liaohe River had gradually increased. This is due to the conversion of farmland into forest in the east region. The conclusions made in this study will provide data reference and basic information for the ecological protection in the Liaohe watershed, the land use planning management, and policy-making in future.
In this paper, we took the Liaohe watershed as the study area and applied the CLUE-S model for the purpose of landscape pattern simulation, based on the land use data in 2000 and 2010. Eight key driving factors were selected in this study, which include elevation, DEM, slope, distance, soil and others. Firstly, the land use data in 2000 was used to simulate the spatial pattern of land use in 2010 for the Liaohe watershed. Based on theadjusted model parameters, the land use patterns of 2020 were then simulated respectively for the natural increase scenario, economic development scenario, and ecological protection scenario. The results showed that the simulation accuracy for 2010 reached a considerably 90.7%, implying that the CLUE-S model is well fitted for modeling the land use pattern in the Liaohe watershed. In different scenarios, it shows explicitly an increase in urban land and a decrease in cultivated land. Under the economic development scenario, we concluded that: the cultivated land conversion range is the largest; the forest reduction is relatively small; and the construction land surrounding the developing zones of the Liaohe River basin had gradually expanded, which mainly aggregated in Shenyang, Fushun, Anshan and other industrial developed cities. Under the ecological protection scenario, we discovered that the forests and wetlands that located at the mouth of the Liaohe River had gradually increased. This is due to the conversion of farmland into forest in the east region. The conclusions made in this study will provide data reference and basic information for the ecological protection in the Liaohe watershed, the land use planning management, and policy-making in future.
In order to study the spatial-temporal changes of land use in coastal city, this paper proposes the concept and meaning of land use change degreebased on the ecological impact,constructs a calculation model, and improves the dynamic degree of single land use type based on the analysis of transfer matrix of land use. Meanwhile, the method of information entropy and gradient buffer zone is introduced. Take the east coast of Nandu River in Haikou City as the study area,the results indicated that: from 1991 to 2010, the construction land had the most significant growth, and the amount of arable land was reducing the most.The increase of information entropyindicated that the equilibrium degreewas gradually increasing, each type of land required for economic industry had been gradually produced under the rapid urbanization process, and regional development was gradually matured. The index of land use change degree can effectively measure the intensity of the land use changes, and its impact on the natural environment. From 1991 to 2010, the region that deviated from the natural environment with stronger variation in land use was 20.60% of the total area, which was in coincidence with the percentage of arable land and forest land that were converted to construction land combined with forest land that was converted to garden area. The region following the natural ecological direction, with stronger variations in land use accounted for only 2.42% of the total area. In addition, the east coastal zone was influenced not only by the radiation of city gradient, the enclave of the development zone and the emerging university town, but also influenced by the agricultural comparative benefits and the regulatory policies of land use. Mangrove areain Dongzhai Harborhad decreased slightly, which was less affected by urbanization effect. The research shows that combining a variety of methods, the characteristics of spatial-temporal changes of land use in the integrated coastal zone and its driving mechanism can be analyzed efficiently.
Hyperspectral imagery generally contains hundreds of contiguous narrow bands, which could provide detailed spectral information for target detection and image classification. Traditional hyperspectral classification fails to generate expected results since it simply considers spectral or textural properties at the pixel scale in the context of natural complexity. In this article, a hybrid classification method was proposed which takes full advantages of spectral and spatial features by fusing object-based segmentation results with traditional per-pixel classification results. Based on this concept, two specific hybrid classification approaches were employed: (1) the mixture of multi-scale segmentation and SVM classification and (2) the mixture of multi-band watershed segmentation and SVM classification. In the first proposed method, spectral variations were attenuated by converting them into homogenous image objects at multiple scales; while, the latter method aggregates spatial information and morphological profiles into the segmented objects to achieve the homogeneous classification. The two classification algorithms were applied to airborne hyperspectral imagery and the results show that the overall accuracy based on traditional pixel-wise classification reaches about 82.49%, relatively lower compared with the hybrid object-based classification methods, which are 92.63% (Method 1) and 96.13% (Method 2) respectively. In addition, Method 2 performs better than Method 1 since it produced a smoother boundary, partly because Method 2 needs less user-defined parameters, and the iterative “trial-and-error” of which may affect the classification results. In conclusion, this study demonstrates that the hybrid of object-based classification is a significantly more robust approach than the traditional per-pixel classifier. The proposed method overcomes the spectral confusion, solves the problem of land fragmentation, and provides a solution to map complex environments accurately.
ZY-3 satellite data, which is a new type of remote sensing imagery, has not yet owned a specific images fusion method. This paper proposed a new fusion algorithm based on the nonsubsampled Contourlet transform and Gram-Schmidt (GS) transform according to the characteristics of CBERS-03 data. Firstly, the linear regression method was used to generate the low-resolution panchromatic image with respect to the low-frequency pixels. Then, the nonsubsampled Contourlet transform was applied respectively on the high-resolution panchromatic image, the low-resolution panchromatic image, and the image generated from their differences, to generate high frequency and low frequency coefficients. With these coefficients, a new panchromatic image was produced by using adaptive fusion strategies. At last, the fused image was obtained through GS orthogonal transformation, by replacing the first component of GS positive transformation with the low-resolution panchromatic image, and replacing the first component of GS inverse transformation with the newly generated panchromatic image. Compared with the traditional image fusion methods, which always have defects of spectral distortion, the proposed method had obvious advantages in terms of spectral fidelity, spatial resolution and classification accuracy. In conclusion, the proposed method is appropriate for images fusion on the ZY-3 multispectral and high resolution data.
The purpose of this study is to evaluate the accuracy of extracting average height of natural secondary forest using airborne LIDAR data and to explore the problems that accompany. The DSMs and DEMs with differentspatial resolutions were simulated, by applying HASM-AD algorithm. DSM minus DEM gives CHM, and the tree heights were extracted from CHM. We applied tree vertex recognition algorithm with different recognition scopes. Using 30 measured plot data for verification, we tried to express how CHM spatial revolutionand recognition scope could affect tree height extraction accuracy. Firstly, we produced the 0.5 m resolution of CHM and gave 3 trials with setting the recognition scope radius as 0.5 m, 1.0 m and 1.5 m consecutively. The contrast between the results showed that the number of tree vertices extracted was the largest when the recognition scope radius was set as 0.5 m. The algorithm's ability to recognize tree vertex decreases as recognition scope radius increases. Then, we set the recognition scope radius as 0.5 m unchanged and gave 3 trials in which we extracted tree vertex from different CHM with 3 different resolutions (0.1 m, 0.25 m, 0.5 m). The results showed that the number of tree vertices extracted in 3 trials were close. In other words, the recognition scope radius could hardly influence tree vertex extraction. Finally, we compared the average value of the extracted tree heights in each plot to the average of the measured values. The result showed that they were highly correlated with each other, and the regression coefficient between them was 0.694. In conclusion, the recognition scope radius has great influence on tree vertex extraction, while resolution of CHM has little influence on tree vertex extraction. Increasing the sampling density of LIDAR data, choosing an appropriate CHM simulation method and improving the tree vertex recognition algorithm can increase the accuracy of tree height extraction.
The chlorophyll-a concentration of waters is one of the main retrieval parameters in the field of water color remote sensing. Based on the coefficients of absorption and backscattering of waters, Colored Dissolved Organic Matter(CDOM), tripton and chlorophyll-a, which are achieved using the Hydrolight software package, the remote sensing reflectance is simulated according to the forward radiation transfer models without the consideration of fluorescence peak. And then, the spectral curves of variable chlorophyll-a concentration are achieved. The spectral characteristics of chlorophyll-a are analyzed according to these remote sensing reflectance curves. Next, the retrieval models of chlorophyll-a are built based on analyzing the spectral characteristics within selected bands or certain band combinations. In this paper, the Normalized Peak Area (NPA) model and three-band model are analyzed and applied to retrieve the chlorophyll-a concentration. As a comparison, other retrieval models are also considered. According to the analysis and results, we find that the chlorophyll-a concentration could be better retrieved by the NPA model, the three-band model, and a few other models, except for the model of reflectance peak position. The least competent retrieval model for chlorophyll-a is the model of reflectance peak position with the R2 of 0.6513. Among all the retrieval models, the NPA model is the best model to retrieve cholorophyll-a concentration with the R2 of 0.9689 and the RMS error of 25.25µg·L-1. The second one is the three-band model with the R2 of 0.9637 and the RMS error of 10.66µg·L-1. The small retrieval error of the three-band model is due to the consideration of the backscattering impacts of tripton, CDOM and waters. The NPA model, in addition, has not only take into consideration of the backscattering impacts, but also the fluorescence efficiency and a variety of environmental factors when applied to retrieve chlorophyll-a concentration. In the end, we could conclude that the NPA could be utilized to retrieve chlorophyll-a concentration for simulated data. This conclusion should be further verified by using it with in situ experiments data.
This paper focuses on the temporal and spatial dynamics of total ozone over China from 1981 to 2010 with multi-resource remote sensing and ground-level monitors. The results indicate that the total ozone over China is continuously decreasing. The speed of the decreasing is slower compared with the whole world and keeps almost the same compared with the northern hemisphere, but it is slightly slower than that of the northern hemisphere. The total ozone declines by 0.11% per year, reaching 0.36 DU. However, the pace of the decreasing slowed down since 2000. The temporal distribution of the total ozone over China is uneven. The total ozone increases with the rise of latitude, and the total ozone of the eastern region is higher than the western region. The total ozone tended to increase from 2005. The seasonal variation of the total ozone in China indicates a sine curve and the maximum and the minimum values appear in March and October respectively, and their corresponding average values are about 333.36 DU and 284.54 DU respectively. The total ozone over China shows an obvious seasonal variation. Overall, the total ozone over China in winter and spring is higher than summer and autumn. In different seasons, the variations of the total ozone over China of the southern area and the northern area are not the same. In winter and spring, the variations of the total ozone over China of the southern area and the northern area are bigger. While in summer and autumn, the variations are not obvious. The seasonal change of the total ozone over China is not evident in the latitudinal direction, but in the longitudinal direction. The seasonal variations of the southern area and the northern area are almost opposite. The amplitude of the seasonal variation increases with respect to the latitude.
Terrestrial evapotranspiration (ET) is a key process in the climate system and a nexus of the water and energy cycles. Understanding the temporal and spatial change of ET is important to analyze the climate impact on water resource. However, large scale ET estimation methods are still in evolution due to the complexity of processing ET. With the aid of MODIS ET products (MOD16), we obtained the 10-year spatial-temporal data sets of terrestrial ET in China from 2001 to 2010.MOD16 ET products were first validated at 8 flux towers and 10 large basins in China. The results show that although some uncertainties are present, the magnitudes and spatial pattern of ET in China are basically reasonable. The MOD16 products withthe best performances were observed at sites with forest and crop land cover, as well as in four basins in the north of China.The average annual terrestrial ET in China from 2001 to 2010 is 532±10 mm.The seasonal change of the ET in Northeast China is most obvious with a coefficient of variation (CV) of 0.87 based onthe average monthly ET, while the Northwest China has little seasonal variations making the CV is only 0.19. Generally, the estimated terrestrial ET in China shows littlesignificant variation during the 2001 to 2010 period. On the regional scale, approximately11.2% of the areas show significant negative ET trends, which occur mainly in the center of Tibetan Plateau, northeast of Inner Mongolia and the north of Xinjiang. Only 2.3% of the areas show significant positive ET trends, which mostly occur in Loess Plateau, Northeast Plain and Huang-Huai-Hai Plain. According to the analysis of the maps of the linear trends of PDSI and NDVI in China during 2001 to 2010, we can see the negative ET mainly occurs in the semi-arid areas which under go increasing drought; while the positive ET occurs in areas where the vegetation is turning better after large-scale ecological restoration projects were implemented.
As key parameters in bio-optical model, the backscattering coefficients of phytoplankton plays an important role in modelling the reflectance spectra and retrieving chlorophyll-a (CHL-a) concentrations from eutrophic water. An exponential model is usually used to simulate the total backscattering coefficients by omitting the phytoplankton backscattering in inland water characterized by lower concentrations of CHL-a. However, the exponential model is not valid for inland water with high CHL-a concentrations, and high relative errors and residues may exist in retrieving the CHL-a concentrations in the algae blooming area, due to the errors made by omitting or introducing inaccurate backscattering coefficients of phytoplankton. Therefore, a precise determination of the phytoplankton backscattering coefficients is of great importance in retrieving chlorophyll-a concentrations. Based on the classical bio-optical model, we proposed a method to partition the phytoplankton backscattering coefficients. The variations of the backscattering coefficients of phytoplankton particles with wavelengths in 400~700 nm and the chlorophyll-a concentrations are illustrated and discussed in details. According to the results mentioned above, following conclusions are drawn: (a) it is appropriate to model the total backscattering coefficients by using exponential function in most Case 2 waters with lower concentrations of Chlorophyll-a, where the non-algal suspended sediments dominated the optical properties. However, it is not applicable in eutrophic waters with higher concentrations of chlorophyll-a, where the algal particles dominated the optical properties; (b) phytoplankton backscattering coefficients vary inversely to their absorption coefficients, and two backscattering peaks emerge in the wavelengths of 560nm and 700nm, which are significantly correlated with CHL-a concentrations; (c) compare to the exponential model, the accuracy of the bio-optical model using the partitioned phytoplankton backscattering coefficients has improved greatly: the correlation coefficient between the retrieved and the measured CHL-a is increased from 0.66 to 0.98, the average relative error decreases from 55% to 38% , and the RMSE decreases from 60.95 to 13.98 in estimating CHL-a concentrations.
Geomorphology of coral reefs is the foundation for understanding the reef-building process and mechanism. It is worthwhile to acquire the geomorphological information of coral reefs in the South China Sea because this information can provide valuable insights for the resources utilization, ecological protection and management as well as sustainable development of coral reefs in China. Based on the development of current remote sensing techniques, an object-oriented geomorphic unit extraction method for coral reefs is proposed in this paper. The satellite images are segmented by the optimal scales, spectral parameters and shape parameters and the segmented objects are combined to different objects to obtain the geomorphic units. Through a large number of experiments, the optimal scales for natural geomorphic units range from 140 to 600. Spectral parameters and shape parameters for sparse reef associations zone, numerous reef associations zone, and reef pits development zone are all 0.9 and 0.1, respectively. Spectral parameters and shape parameters for other natural geomorphic units are 0.8 and 0.2, respectively. On the other hand, optimal scales for man-made geomorphic units range from 25 to 170, while their spectral parameters and shape parameters are all 0.8 and 0.2, respectively. The WorldView-2 high resolution remote sensing image of Boji Reef in Nansha Islands is used as experimental data in this paper and the accuracy of classification results is assessed with the confusion matrix and Kappa coefficient, the overall accuracy of geomorphic unit extraction reaches 85.75% and the Kappa coefficient is 0.8349. The results show that this method can effectively take advantage of the features of spectra, texture and the stacking of different wavebands of satellite images. In addition, this method can grasp the correlation of satellite image and reef geomorphic zonation and make full use of the heterogeneity of reef geomorphology. Therefore, an ideal geomorphic zonation that has a higher accuracy can be obtained to acquire geomorphological information and produce geomorphological digital products of coral reefs in the South China Sea.
