Spatial process analysis and simulation is one of the hot research areas. However, spatio-optimization is usually based on static patterns which ignore the dynamic process. This paper discusses the concept of collaborative space simulation and optimization and then provides the examples on how simulation and optimization can be integrated. The examples include optimal site selection for public facilities, path coverage optimization, nature reserve planning and scenarios simulation for urban energy consumption. Results show that this proposed method can be successfully applied especially for the fast growing regions.
In recent years, along with the rapid development of location technologies such as GPS, RFID and wireless sensor networks as well as the widespread use of location-aware devices such as mobile phones and GPS receivers, large amounts of trajectories of moving objects can be easily acquired. By using moving objects databases, massive trajectories of moving objects can be manipulated and handled for various applications, which makes the study of moving objects databases more and more important. Among the most recent researches, the study space where moving objects travel can be mainly divided into two types, the Euclidean space and the geographic road networks. In Euclidean space, moving objects can move freely. However, under geographic network environment, moving objects are limited to geographic networks and must follow the road regulation. For the latter research branch is much more practical than the former one, this paper concerns the latter branch and focuses on modeling moving objects in geographic networks, which is the foundation of the study of moving objects databases. It has been a hot research topic in the field of moving objects database management and also provides key technology for many other areas such as transportation, location-based services, urban mobility and social computing. Although it is of great theoretical significance and application value, modeling moving object in geographic networks challenges the research community a lot due to network constraints. In this paper, firstly, most existent geographic network-constrained moving object data models over recent decades has been systematically reviewed and classified. The related literatures show that most geographic network-constrained models can be divided into four categories including edge-based network-constrained model, route-based network-constrained model, partition-based network-constrained model and spatial-temporal network-constrained model. Then model characteristics, advantages as well as limitations have been elaborately analyzed, based on which, finally some crucial points on modeling moving objects in geographic networks has been proposed and discussed.
One feature discovered in the study of complex networks is community structure, it means that vertices are gathered into several groups that the edges within groups are more than those between them. Detecting the community structure hidden in the networks has extensive application prospects. Recently, many approaches have been developed for finding communities, such as Gievan-Newman algorithm, Newman fast algorithm and so on. Also, there are some approaches consider both the network topology and the attributes of vertices, such as SA-cluster algorithm. However, a few studies focused on considering geographic distance between vertices. Tobler's first low says that near things are more related than distant things. Based on this proposition, we think that the strength of interaction between vertices is concerned with geographic distance. By defining the weights of the edges in the network as the function of distance between two directly connected nodes, we modified the fast modularity maximization algorithm (CNM algorithm). The weight is defined in such a way that the closer the distance, the greater the weight. The algorithm is tested on the flight network of China. We consider the strength of interaction between two cities is related with both the connection of flights and distance. We find 10 communities in the air transport network, and the distribution of communities displays regionally.
Hemispherical photography method was widely used in the measurement of structural parameters and photosynthetically active radiation of vegatation canopies. The simulation of hemispherical photography method under high-reality virtual forest environment can be used to evaluate the measurement precision of hemispherical photography method quantitatively and used as a useful tool for ground based validation. But there are some difficulties faced for the analogy of hemispherical photography method under high-reality virtual forest environment, such as the highly complex of scene, huge number of triangles, the distribution model of trees, and the low efficiency of simulation etc. In this study, a library of virtual forest scenes with characteristics of different stand density, the distribution mode of tree, size, species etc. was build first based on the principle of the establishment of high-reality virtual forest environment, and then, a comparative analysis between four different splitting plane search methods (such as spatial median algorithm, object median algorithm, heuristic ordering algorithm and heuristic BIN zoning algorithm) was carried out based on the ray tracing and hemispherical photography analogy methods. Results show that the heuristic ordering algorithm is the best choice for the analog of hemispherical photography method as compared to the other three splitting plane search methods. At last, the efficiency of the organization of data sets at two scales of isolated tree model and virtual forest scene for four data structures was comparative analyzed based on the library of high reality of virtual forest environment. A list of parameters was used as the indicator to evaluate the performance of the four data structures, such as the number of the ergodic nodes of scene, the number of the ergodic nodes of isolated tree model, the ergodic number of isolated trees, the number of ergodic triangles and the average compute time etc. Results show that the data structure of Kdtree was superior to the other three data structures. In the end, we can draw conclusion that the unity of heuristic ordering algorithm and Kdtree data structure is the best choice for the analog of hemispherical photography method under high reality virtual forest environments.
The source of data used in the process of building geological section is drillhole data, and the way of modeling deals with the problem of depositional termination or section smoothing is more complex, stability and robustness is not satisfactory. So it is difficult to apply to the actual production process. To solve this problem, this article proposes a geological section construction algorithm based on virtual drilling controlling. First of all, according to processing strategy of depositional termination we build the virtual drilling on the thinning out treatment; second, in accordance with segments smooth strategy, we use four-point interpolation subdivision algorithm to build subdivision smoothing virtual drilling; third, we rebuild the polygon topology on formation line feature, that can build strata polygon entity; and the last, we integrate various of geological section's mapping elements to finish the output. The example shows that using the algorithm proposed in this paper to build the geological section can accurately reflect the geological structure of the study area, and increased segmentation times can significantly improve the plots moothing effect. This algorithm puts the virtual drilling into all aspects of geological section building and takes it as the middle unit in the algorithm. It can effectively simplify the implementation process, and ensure the stability and efficiency of the algorithm.
Geographic information standardization is confronted with the urgent challenges of the rapid growth of geographic information industry in China. Although the past years witnessed great achievements in standardization of applications in this field, we still have no breakthrough work for some essential problems. In order to accelerate the standardization development,“12th Five-Year Planning for surveying, mapping and geographic information standardization”took the construction of geographic information standard system and sub-systems as the top priority task. In this paper, we reviewed the progress in geographic information standardization system, and elaborated the importance of geographic information software standard system construction for geographic information industry. Based on the analysis of existing national geographic information standard system, we found three typical problems which greatly hindered development of geographic information software standardization, and discouraged participation from enterprises and institutions in further. The solution is building an independent geographic information software standard sub-system compatible with existing standard system. In pursuit of this objective, we first chose the geographic information software classification system as the base of standard system discreetly, then declared the objectives and principles of system construction, at last made the recommended draft of geographic information software standard system framework diagram and class table, which consists of six main classes, as (1) Basic Platform Software; (2) Data Acquisition and Production Software; (3) Data Management Software; (4) Data Analysis and Mining Software; (5) Application and Service Software; and (6) Application System. Finally, we made the conclusion of project status and prospected the future developments.
In statistic geographic information system, census data, stored as polygon attribute, is a kind of polygon- based statistical data. Moreover, in the studies of geography and social science, polygon-based statistical data is a main data source for uncovering spatial patterns of social phenomena by spatial analysis. However, due to the limitation of data and restriction of computer processing power, uncertainty of polygon-based statistical data spatial analysis is always ignored, and there is no well methodology for analyzing such uncertainty. To address this question, we developed a method concerning modifiable areal unit problem (MAUP) to evaluate uncertainty of polygon-based statistical data spatial analysis. The population data collected from each buiding in Beijing makes the mehtod applicable. For MAUP, we considered it as scale and aggregation separately. For polygon- based statistical data, we applied census data of Haidian District (Beijing) with polygons of buildings as its georeference. With this method, we introduced scale and shape indices and applied visual analysis and data fitting to detect the uncertainty of five analysis methods: Sum, Mean, Standard deviation, Global Moran's I and Anselin Local Moran's I (LISA). In addition, the relationships between scale, shape indices and the five analysis methods are also revealed in order to demonstrate the way that MAUP affects polygon-based statistical data spatial analysis. The result of the research shows as follows: (1) the results derived from census data spatial analysis with normal census tracts as zone system are arbitrary and have great uncertainty. (2) The results derived from census data spatial analysis with regular nets as zone system well describe the spatial patterns of original data, but still depend on the scale and zoning of the net system. (3) The results derived from census data spatial analysis with regular grid as zone system, are functionally related to the scale of the grid system, and the uncertainty of the results represents multi-scale spatial patterns of original data. And (4) aggregation together with scale affects census data spatial analysis. With regard to regular net system with fixed scale, the number of the neighbors of each polygon affects the results of the analysis. According to the above, it is better to re-aggregate the census data by regular grid system with proper scale and apply multi-scale methods in polygon-based statistical data analysis.
As one type of CA, logistic-CA now has been successfully adopted in urban studies. But logistic-CA model can only be applied to simulation according to historical evolution trend. Besides, the quantity of prediction in a certain year cannot be correctly obtained. In this study, we have carried out two modifications on the lo-gistic-CA model, one is to insert grey prediction; the other is making the model capable of simulating urban morphology evolution under multi-scenarios. Then we applied this model to simulate and predict urban morphology evolution of the coastal area in Tianjin Municipality, in order to investigate the regularity and characteristics under three scenarios, e.g. historical extrapolation, endogenous development and exogenous development, so as to better grasp urban morphology evolution regularities. The simulation of three scenarios shows that urban morphology inevitably grows followed a cross form,but the characteristic of three scenarios are a lots of differences. Modified logistic-CA model gives full play to the advantage of CA, that is, bottom-up simulation of urban spatial process under multi-scenarios. Through examination, the modified model has a high accuracy in simulation and prediction, which achieves the goal of quantitative simulation and prediction of urban morphology evolution under multi-scenarios. It is necessary for urban planning to master the expansion of the inevitability of urban form, in order to grasp the possibility of a specific area to achieve effective control of the urban development process.
With the implementation of development strategy of bay-type city, Xiamen City has been one of the most dynamic regions of the Western Taiwan Straits Economic Zone. However, it confronts the conflicts between the rapidly spatial expansion and the limited resources and environment. Based on the characteristic of natural ecology and social ecology of Xiamen City, taking example by related researched, elevation, slope, NDVI, rivers and reservoirs, land cover and protected area were selected to form the ecological sensitivity assessment indicator system. With the help of spatial analysis function of geographic information system, the ecological sensitivity degrees and their spatial distribution of the study area were quantitatively analyzed by single-factor evaluation method and multifactor weighted integrated assessment method. According to the level of ecological sensitivity, the study region was subdivided into four grades: insensitive, low sensitive, moderate sensitive, and highly sensitive. The integrated evaluation result showed that, significant differences were found in special distribution of Xiamen's ecological sensitivity. The high sensitive regions, accounting for 28.1% of total area, mainly concentrated in the northern part of Xiamen City, which displayed a half annular distribution. The moderate sensitive regions, which shared only 10.4% of total area, are presented as irregular spots or branches. The low sensitivity area, with 27.9% of total area, was distributed around the peripheral buffer zone of high sensitive regions and moderate sensitive regions. The insensitive areas, which accounted for 33.6% of total area, were mainly located in artificial business landscape. It was also found that the appropriate development area was Huli and Xiang'an District, while inappropriate development area was Tong'an District. This study could provide scientific references for land use optimization and regional eco-environment protection countermeasures in the process of urban development.
With the extensive application of geographic information systems and the deeply development of geography disciplines, the spatial and temporal structure and process analysis are receiving more attention. The analysis of spatio-temporal variability of precipitation is the basis for the understanding of formation and development of regional water resources. It not only reveals the change of time-series, but finds the spatial structure and changing pattern. Thus, it provides the basis for predicting the drought and waterlogging. Based on the rainy season precipitation data of the past 51 years in Henan Province, combined with a digital elevation model (DEM), using regression analysis, spatial autocorrelation, simulation of spatial interpolation, and cross-validation, we conducted an analysis of spatial and temporal variability of precipitation in Henan Province. The result reveals that: (1) the trend is clear, and the rainy season precipitation in Henan Province overall has shown an increasing trend and in recent years it is particularly evident; (2) The differences of monthly precipitation are obvious, the maximum value is in July, and the average reaches 178.3 mm. (3) The spatial variance exists. There is a clear pattern that the precipitation in the south and east are more than that of north and west in spatial. There is a strong clustering characteristic that in the south, Luoshan and Huangchuan counties as the center formed the rainfall abundant areas, while in the north, Hui County as the center formed the rainfall scarce areas. Lin, Luanchuan and Xixia counties as spatial outliers, are significantly higher than the adjacent regional precipitation. After the spatial autocorrelation analysis, the spatial and temporal anisotropy can be acquired. Therefore, according to the spatio-temporal analysis, we get the interpolation map with Cokriging method, and it tallies with the prior conclusion.
Considering both various hydro-meteorological factors and different underlying surfaces in watersheds, a physically based and distributed hydrological model called SWAT (Soil and Water Assessment Tool) was developed to predict the runoff, sediment, and agricultural chemical yields in watersheds and large river basins over long periods of time. Lizixi Watershed is a typical representative with moderate erosion in Sichuan purple hilly area. Based on the serious purple soil erosion and water loss of slope farmlands in central Sichuan hilly areas, Lizixi Watershed is chosen as the study area to analyze the law and degree of soil and water losses in pur-ple hilly areas. Firstly, the SWAT model databases of Lizixi Watershed are constructed including the database of topography, soil, weather and land use. Then the Zhaojiaci Hydrometric Station's actual runoff and sediment data from 1970 to 1979 are used to calibrate the hydrological parameters of SWAT model, while the observed data from 1980 to 1986 are used to validate the model. The effects of simulation are evaluated by the relative error Re and Nash determinacy coefficient Ens. The results show that the relative errors of runoff and sediment simulation are within the scope of ±15% and their values of Nash determinacy coefficient are equal to or greater than 0.70. The values indicate that the simulation of annual and monthly runoff and annual sediment load is of high accuracy. And the tendency of the simulation value is consistent with the corresponding measured value and changes of rainfall. So it is feasible to make use of the SWAT model to simulate and predict the runoff and sediment yields in the purple hills with abundant rainfall and serious soil erosion. The use of the model can provide a reference for preventing soil erosion and making the control measures of water and soil conservation.
By the support of remote sensing (RS) and geographic information system (GIS) technology, Dawenliu Nature Reserve of Yellow River Delta (YRD) was picked as the study objective, which is located at Dongying City of Shandong Province. The multi-temporal Landsat images were used as the data source, which were registered to the high precision GIS database, matched each other and with the database, and all the images have the same coordinate system. Four corrected images (1996/2000/2005/2009) were used for land use interpretation, and seven images (1976/1981/1986/1996/2000/2005/2009) were extracted for the information shoreline change, regarding mean low tide level as the analysis baseline. The results show that the land area increased 13.35km2 from 1996-2009. Tidal flat made up the largest proportion in all the land use types and culture ponds were the smallest, which significantly increased. The reed area rapidly increased during the late period, which indicated that eco-environment trended to get better. Coast was divided into siltation coast, erosion coast and steady coast. From 1976 to 2009, 373.92km2 was silted, 156.78 km2 eroded, and net accretion area was 217.14km2. Both the natural factors, such as Yellow River zero flow, and human activities, such as Yellow River water and sediment regulation project, wetland restoration projects, tidal flat development and the construction of a large number of farms, had rendered big influence on the distribution of land use types in the study area. Meanwhile, runoff and sediment of Yellow River and ocean dynamic worked together to change shoreline. Therefore, combing the data of runoff and sediment of Yellow River, tide and ocean dynamic, comprehensive analysis on shoreline evolution will be an important focus in future. Temporal and spatial variation of land use and shoreline evolution interacted each other, so linkage mechanism between healthy assess of land use and shoreline change will be a basic monitoring content of the nature reserve in future.
As the important part of infrastructure in high density urban area, spatial distribution of parking lot relies on population, roads and buildings. Under the influence of various factors, parking lot in high density urban areas owns a specific distribution rule. Combining GIS with Voronoi diagram, we discussed the spatial distribution characteristics and co-agglomeration of parking lot in high density urban areas, and analyzed the spatial autocorrelation between parking lot and various factors. Taking Haizhu District in Guangzhou City as a case, we calculated CV value and clustering index by building Voronoi diagram in the researched area and streets. Through the analysis, we know that the parking lots agglomerated markedly in the whole district and every street. In high density urban areas, parking lots tend to gather in commercial circle and economic center such as Jiangnan Road commercial circle and center section of Guangzhou new axis which run through Haizhu District which are the cluster center of parking lots. It showed that population density, building density and road density affect the spatial distribution of parking lots obviously with two variable regional spatial autocorrelation analysis, which population density perform more significantly. Higher the development level of the high density city, more obvious the effect of various factors on density and the degree of agglomeration of parking lots.
Land surface temperature (LST) is one of the key parameters in the physics of land surface processes, and satellite observation is the major way to derive regional LST distribution. However, the pixel observed by satellite is usually a mixture of different land cover types and the temperature of each type seems more meaningful land useful than the mixed pixel temperature. Therefore, component temperature estimation is an important research field. To take use of the rich temporal information imbedded in the geostationary satellite data, a practical approach was proposed to derive the component temperature based on MAP criterion and Markov models in this study. The approach was on the basis of mixed pixel temperature theory and under the assumption that there were only two components in the mixed pixel (vegetation and soil) and the nearby pixels had the same temperature for each component. The method was applied to simulated geostationary satellite data, and the component temperature estimation results showed good agreement with the true values. The RMSEs of vegetation and soil temperature were within 2K for most cases. In addition, the sensitivity analysis of the method to the mixed pixel temperature estimation error, the vegetation fraction cover (FVC) estimation error and its range of the pixels considered in the estimation were conducted. The results indicated that the pixel temperature error and the FVC error showed little effect on the estimation results while the FVC range played an important role in the estimation because of its determinant function on the first guess of the component temperature.
On the basis of the atmospheric radiative transfer theory, land surface temperature (LST) was retrieved from NOAA-18 (N) AVHRR/3 cloud-free data using a general split-window (GSW) algorithm. A simulated database including the thermal infra-red channels (Channel 4 with spectral range 10.3-11.3μm and Channel 5with spectral range11.5-12.5μm) radiance observed at the satellite level was established with the atmospheric radiative transfer model MODTRAN 4. It covers various land surface types and atmospheric conditions. Then the coefficients of the GSW were determined by grouping the LST, the atmospheric water vapor content (WVC), the land surface emissivity (LSE), and the viewing zenith angle (VZA) by several sub-ranges. Results showed that the root mean square error (RMSE) between the estimated and actual LST is less than 1.0K when the VZA is less than 30° or the WVC is less than 3.5 g/cm2. The RMSE is less than 1.5K when the VZA is less than 45° and the WVC is less than 5.5 g/cm2. In addition, the proposed algorithm was applied to the NOAA-18 (N) AVHRR/3 data to retrieve LSTs. The LSE was determined by using the NDVI thresholds method, and the WVC was estimated with the transmittance ratio method proposed by Li et al. (2003). Finally, the field measured data of the US-Flux stations were used to validate the retrieved LST. The results showed that the RMSE is less than 1.8K.
Success rate, correct rate and precision of SAR image matching are usually low, so it indirectly affects the subsequent application of SAR images. SIFT feature is the local feature of the image, and it remains invariance of the rotation, scale and luminance variation; it also maintains a certain degree of stability of the viewing angle variation, the affine transformation and the noise. The stable features are extracted by using SIFT algorithm which is applied to airborne SAR image matching. AS 2D homography transform is the model of the RANSAC algorithm, four pairs of points at least are used to calculate 2D homography transform model parameters. RANSAC algorithm is a kind of robust parameter estimation method to obtain the effective sample data. The mismatching points are eliminated by using the RANSAC algorithm based on 2D homograpy transform. Based on VC++ and OpenCV programming, three sets of different kinds of airborne SAR image data are selected to complete matching experiment of airborne SAR image in which SIFT algorithm combined with error eliminated algorithm is used. The result shows that for airborne SAR images of artificial buildings and natural vegetation, SIFT algorithm can be used to effectively extract numerous stable matching points and the correct rate is high; for airborne SAR images of lack of texture information, SIFT algorithm can be used to extract a small amount of stable matching points and the correct rate is obviously lower than the former. In a word, SIFT algorithm can be used to extract the stable matching points in the airborne SAR image matching, and the mismatching points are effectively eliminated by using RANSAC algorithm based on 2D homograpy transform, so the correct rate and precision of matching is greatly improved.
Remote sensing images have been widely used in extracting and studying paddy rice information and its spatial distribution, which is highly important in land cover analysis, grain structural adjustment and prices making. But studies using multi-temporal TM images to extract small-scale rice information were few. Based on that rice favors growing on wet land, this paper selected three bands of TM images, the short-wave infrared band (1.55-1.75um) which can reflect plant water content and soil moisture, the red band (0.62-0.69um) and the near infrared band (0.76-0.96um), both of which can reflect vegetation coverage and growing condition, to compute the NDVI and LSWI of rice paddles in the three different periods: transplanting stage, heading stage, and maturing stage. Given the two indices demonstrate different characteristics during rice's different growing stages, the paper developed a corresponding time-series-based decision tree model for rice information extraction. A case study using this model was performed in the southern Luannan County, Tangshan City. Been field validated, the experiment results showed the effectiveness of the decision model in distinguishing rice paddles from water area, corn land, farm land and other similar land features, and the producer accuracy and the user accuracy are 95.18% and 98.84%, which outperform the single-temporal results by 6.78% and 7.54% respectively.
Soil salinization is an important worldwide environmental problem, especially in arid and semi-arid regions. Quantitative remote sensing provides accurate and up-to-date information of spatio-temporal dynamics of salinity. Studies at both home and overseas showed that it is hard to acquire reliable information of salinity by using a single wavelength in visible, near infrared (NIR), thermal or microwave domain, especially in a sophisticat-ed surface conditions such as agricultural fields, while the reported methods inherited many limitations in practical applications including time-lag effect, being too complex to calculate, being excessively dependent on meteorological observations and field measurements etc. Therefore, developing of simple, effective and operational methods for the satellite estimation of surface salinity, especially vegetation cover is of great interest for both researchers in remote sensing community and policy makers for the sustainable development of eco-environments. Mixed pixels as an important aspects in remote sensing information uncertainty, it always been one of the core areas of quantitative remote sensing science research. With the congenital features, i.e., a homogeneous underlying surface and simple meteorological conditions and so on, arid area has become an ideal place for quantitative remote sensing products testing. In this article we took the Kuqa River, in north of Tarim Basin oasis as the study field. At first we selected spectral mixture analysis models, according to different feature types we extracted the endmembers in different ways. Depending on EAR (Endmember Average RMSE) and MASA (Minimum Average Spectral Angle) we chose the optimal endmembers. At last we carried out pixel unmixing by using the MESMA (Multiple End-member Spectral Mixture Analysis) model, then we finished the accuracy evaluation and comparative analysis. The results showed that MESMA model can effectively improve the information accuracy of a pixel. Therefore, it provided a scientific basis for the high-precision information extraction for typical oasis surface features.
Yellow River Delta is the mainly distribution region of land reserve resources in China. The reclamation at the estuary of the Yellow River beach is becoming the key point of maintaining cultivated land dynamic balance in Shandong Province, even the whole nation. Taking Dongying City, Kenli County, Hekou District and Lijin County as a study area, this paper monitored the dynamic change and retrieved the cultivation age of cultivated land in Yellow River Delta, using TM images of 6 different periods ( 1984, 1995, 2000, 2004, 2008 and 2010 ). Based on cultivation age data, an assessment model of cultivated land productivity was built up by entropy weight method. This model used vegetation index (EVI and MSAVI), vegetation coverage (Fv) and temperature- vegetation dryness index (TVDI) as factors indicating land productivity. Results show that: significant dynamic changes of cultivated land had been occurred from 1984 to 2010 in the study area. During 26 years, 77362.33 ha newly-reclaimed cultivated land, most of which came from grassland, had been reclaimed. In the newly-reclaimed cultivated land, the land at cultivation age during 8 to 12 years had most area, which accounted for 34.47%. The newly-reclaimed cultivated land productivity in the study area presented that productivity increased with the cultivation time increased. Average productivity of newly-reclaimed cultivated land at age during 2 to 4 years had lowest productivity, which was only 67.66% of traditional cultivated land. The traditional cultivated land productivity in the study area also presented that productivity increased with the cultivation time increased. Average productivity of traditional cultivated land in 2010 had increased 76.51% than in 1984.
critical to monitor its long-term change to understand the condition and variation of Poyang Lake and to evaluate its response to climate change and human activities.In this paper,an algorithm for extracting water area of Poyang Lake using MODIS land surface reflectance data is presented.Firstly,the maximum water area is acquired based on composition of the minimum land surface reflectance in red band for each year.Then,only those pixels in the maximum water coverage region are identified as the water or land status with MODIS land surface reflec- tance in green,near-infrared and shortwave channels.Lastly,the water coverage fraction is calculated during certain periods and used to analyze the seasonal and annual variations of Poyang Lake.This algorithm could eliminate the impacts of cloud contamination and rapid seasonal change of lake water area on this analysis.The water area were extracted and analyzed from MODIS 8-day land surface reflectance observations(MOD09A1)during 2000 to 2010.The results show that the water area of Poyang Lake based on our algorithm is of high consistency to the hydrological observations at local sites.The algorithm could represent the significant seasonal variations of the water area of Poyang Lake.From April to September,the lake is vast due to the abundant water from Poyang Lake basin and Yangtze River.From October to March in the next year,the lake shrinks significantly.The minimum water area occurs in January,while it is in July for the maximum water area.During 2000 to 2010,no significant change of the water area of Poyang Lake is found during the flood season.After 2003,the lake shows a noticeable decrease in its water area during the dry season.
Eurasian boreal forest possesses rich forest resources and accounts for 25% of global forest cover. Changes in forest cover and structure caused by human-induced or natural forest disturbances, such as forest fires,have significant impact on the forest carbon cycle. The considerable progress on earth observation technology makes it entirely possible to provide dynamic monitoring of forest resources. This paper discusses the spatial and temporal changes of forest fire disturbance in European Russia. MODIS Thermal Anomalies/Fire product contains information such as fire location, credibility, fire point radiation energy and other attribute information, which can be used for the monitoring of fire frequency, level, and changes. In this study we use MODIS Thermal Anomalies/Fire daily product from 2005 to 2010, combined with RS image processing and GIS spatial analysis methods, to identify burned pixels in European Russia. Spatial and temporal distribution of forest fire has been analyzed. At last we estimate the amount of loss caused by forest fires. The result shows that forest fires are mainly distributed in central and southern regions of European Russia and the fire number is showing an upward trend, fire coverage of 2010 is 1.5 times greater than that of 2005. The fire data reveals apparent changes within a year, and the fire season is generally from April to October. Large fire events occurred in 2010 can be well reflected in the results of this study.
