Under the environment of cluster, OGC simple feature specification and MPI parallel programming model-based parallel polygon union algorithm should address the “many-to-many” mapping relationships between features of overlapping layers. However, spatially adjacent features are not necessarily continuous in the storage sequence. It cannot assign parallel tasks to computational nodes of cluster according to feature sequences, which lead to an implementation dilemma on the task mapping procedure of parallel union algorithm. This research is focused on the design and implementation of parallel polygon union algorithm in the cluster parallel environment. We believe that to determine the “one-to-many” or “many-to-many” relationships between polygons of the two overlapping layers is the primary prerequisite to the implementation of parallel polygon overlay algorithms at the feature layer level. Therefore, firstly we analyzed the differences on parallelizing algorithms by comparing impacts brought by the two kinds of feature mapping relationships. Secondly, we proposed six different parallel task mapping strategies based on the R-tree spatial index data structure, the exactly spatial searching functionalities of MySQL and the MPI communication mechanism. Finally, we implemented six parallel polygon union algorithms based on the six task-mapping approaches and conducted experiments to compare the pros and cons of each strategy. The experimental results show that the parallel polygon union algorithm based on R-tree-based feature pre-screening strategy is the most efficient one in serial, which also demonstrates better parallel accelerating effects than others. Furthermore, the strategy of exactly spatial searching based on MySQL shows higher time costs on feature pre-screening, but it can filter out all polygons which do not intersected with geometries which can thereby reduce redundant union operations and improve the computational efficiency. Therefore, the R-tree-based and MySQL exactly spatial searching-based feature pre-screening strategies are effective approaches to solving the parallel task mapping problem and implementing the parallel polygon union algorithm using the MPI programming model under the cluster environment.
At present, slopes are usually derived from discrete DEMs. When deriving slope from DEM, the variation of DEM resolution will cause changes in the slope values which are extracted from the local grids. The variation will be significant in understating the general rule of the variation of average slope with respect to DEM resolution. 8 areas representing the typical geomorphology in Loess Plateau were chosen as the sample areas, and the DEMs with a 5m resolution were established according to the topographic map scaled at 1:10 000. In every sample area, 22 500 sampling points were selected, and the slopes which were derived according to the algorithm of third-order finite difference weighted by reciprocal of squared distance on the sampling points were taken as the research object. The regression analysis, single-factor variance analysis, contrast analysis were adopted to analyze the rule of the influence of DEM resolution on grid slopes. The following conclusions were obtained: (1) the average slope may increase as the resolution of DEM becomes coarser; (2) in all the sample areas, with the resolution becoming coarser, the number of the grids with negative slope error is at least 1.13 times of the grids with positive slope error. The amplitude of average slope of the grids with negative slope error is greater than 3.1 times of the latter. The number of grids with decreasing slopes is 1.81-4.04 times of the grids with increasing slopes; (3) the change of average slope can be explained in this research by combining the author proposed index with the previously mentioned conclusion (2); (4) the number of grids with varied slope values is not sensitive to the resolution of DEM. The slopes of the grids which have positive slope error or negative slope error are intensively distributed in certain intervals of slopes that derived from the DEMs with 5m resolution. The intervals are not sensitive to the resolutions of DEM; (5) the total slope error can be computed, according to the empirical formula proposed in this research and calculated from the DEM resolution and the average slope of DEM with a 5m resolution.
Nowadays, people are more likely to participate in outdoor activities which results in the increase of people’s missing. In the process of search and rescue, the application of geographic information technology is able to help the search team to narrow the search area and allocate the search resources. As a result, GIS’ application improves the efficiency and saves time and cost. This paper firstly discussed the role of GIS in determining the search area and allocating the search resources in the search and rescue process. Then, based on time-geography tools, this paper optimized the search process on considering that time is a continuous variable. Space-time prism, which is one of the most important tools in time-geography theory, was used to express the spatio-temporal constraints of missing person as well as the search teams. The missing person can only be found in places where both the rescue team and missing person can reach at the same time. The aim of an optimization for the research and rescue process is to find the right place where both the missing person and the search team can arrive at the same time. In the spatio-temporal environment, this kind of place is the intersection of both sides’ space-time prisms. So, the search team only needs to search people in the intersection time and space of the prisms. In this way, the search area was narrowed and the time period was identified more precisely. When other search teams joins in the search process, the final search area is obtained after the intersection of every resource’s search area is calculated. At the same time, the search boundary for each resource is also obtained. Each resource can take actions according to its search boundary. This paper used ArcGIS software platform to achieve the optimization process. A search and rescue process using simulated data was presented afterwards. Compared with traditional buffer analysis method, the search area calculated from this method is smaller and the search time is more precise. This method can be used in combination with other methods to improve the efficiency, save cost, as well as allocate the research resources in a search and rescue process.
In recent years, the number of bus pickpocketing is on the rise, which has caused great danger to the public. In order to prevent and combat bus pickpocketing, we need to effectively identify the crime patterns. However, since bus pickpocketing may occur when the bus is moving, it is difficult to define a location and a crime time for it, and the traditional methods of crime analysis often focus on spatial or temporal properties of crimes separately. Therefore, this paper introduced the weighted spatio-temporal association rules mining to find out the spatio-temporal crime patterns of bus pickpocketing. It can be carried out through four steps. Firstly, conduct the temporal and spatial granularity division: divide the main bus running time into equal units of 2h and encode these units, which are entitled by “bus time”. Then, divide the bus routes into sections according to the bus stops, and entitle these sections by “bus section”. Secondly, conduct the spatial analysis and time merge process: extract and gather bus sections and crime time information for pickpocketing cases, and merge the crime time with “bus time”. Thirdly, as the crime rate of each “bus section” varies, their contributions to the result will also be different. Therefore, this paper assigned each “bus section” a weight according to their crime rates, based on the assumption that every “bus section” of a crime case has the same crime rate. Finally, conduct the weighted spatio-temporal association rules mining: use Apriori algorithm to find out the spatio-temporal crime patterns of bus pickpocketing. The results prove that the proposed mining model has the following characteristics: (1) it is innovative to extract bus sections according to the bus stops; (2) It is more realistic to assign a weight to each “bus section” to distinguish the importance of spatial location; (3) The crime patterns show the correspondence between the bus sections and “bus time” of high crime rates. Further work would focus on the efficiency of Apriori algorithm, the evaluation of association rules, the weight settings (consolidating other factors) and the result visualization.
The detection of anomalous human behaviors has received tremendous attention in the research of intelligent video analysis. However, most of existing methods for anomaly analysis are based on image space, and abundant information in the geographical space goes unused. In fact, human activities are closely related to geographical spaces, and different scenario types may correspond to different classes of human behaviors. So, in this paper we chose interrogation room as a representative of the micro-spatial environment and conducted a study on the anomaly detection of extorting confessions by torture, considering the spatial constraints. Firstly, the concept of behavioral variables has been stated, and then behavioral variables and their classes of extorting confessions by torture have been deeply analyzed. Secondly, the video characters of behavioral variables of extorting confessions by torture have been discussed and their corresponding detection models have further been designed. Plus, a bi-directional mapping model between the geographical space and the image space has been constructed according to vanishing points. This proposed mapping method can effectively avoid the calculation of intrinsic and extrinsic camera parameters. Based on above, a hierarchical and classified strategy for anomaly detection of extorting confessions by torture has been developed, considering the spatial constraints to human behaviors without learning and training processes. At last, the presented method in this paper is tested and verified by a series of simulated experiments.
：Geographic information technologies are playing increasingly significant roles in supplementing the blind with spatial cognition, enhancing their mobility of outdoor activities and their quality of life in urban area. Increasing researches have appeared in the fields of electronics and computer science. Technologies related to RFID, infrared, Bluetooth, WiFi, ultrasonic and image recognition have been employed to develop tools for urban barriers detection. Barricade detection with electronic tools; however, cannot well satisfy the needs of the blind’s outdoor activities. As a matter of fact, researchers become increasingly aware of the importance of geographic information (including semantic information), with which the more familiar and convenient paths can be chosen, and the risks of outdoor activities can be reduced. With the development of geographic information technology, the abroad correlated researches have focused on the exploration of the requirements of spatial perception for the blind, and these researchers set geographic information to be the foundation of assisting outdoor blind guidance. Accordingly, geographic information technologies are integrated with other technologies to serve the blind guidance. However, this kind of research is quite rare in China. From the perspective of geographic information, this article gives a summary of relevant researchillustrates current issues, and point out the development tendency. It also aims at providing essential theoretical support for the development of related hardware and software, and further promoting the application of geographic information technologies in the field of blind service.
With the rapid regional integration and phenomenal development, the South Fujian Golden Delta (SFGD) has become one of the important growth poles in Southeast China. However, some problems, such as urban spatial reorganization and regional coordination, emerge with the accelerating urbanization and integration. Extensive studies on SFGD focus on qualitative description of the developmental dynamics and industrial strategies, which is inadequate to explain the characteristics of the uneven development within this region. Especially, it is unable to reveal the evolution of the spatial and temporal dimensions of the regional development. In order to analyze the effects of different industries to SFGD and its uneven spatial pattern, the Nich value of different industries and the method of gravity center model are introduced to explore the temporal and spatial characteristics and the dynamic evolvement of the gravity center of economic growth and the tertiary industry in SFGD, in the years between 2000 and 2012. The results show that: Firstly, there is a significant polarization in SFGD. The gravity centers of economic growth, the secondary and the tertiary industries were concentrating on the northeastern Xiamen since 2000, and the trend of a East-West polarization was obvious; secondly, the relationship and interaction between Xiamen and Quanzhou was intensive while the tertiary industry had a leading effect on the center of economic growth, and the tertiary industry moved back since 2008 while the uneven development of the secondary industry was weakened; thirdly, with the linear movement trend of the gravity center of the primary industry towards the southwestern region of SFGD, the growth of the secondary and the tertiary industries of Zhangzhou fell behind, compared with the coast area of the northeast SFGD.
Geomorphic indices have been widely used in relative tectonic activity studies. Most studies provide semi-quantitative information to depict relative degree of tectonic activity in mountain fronts or small basins. Here we introduced an additional fractal dimension index (FD) which is found to improve the analysis of tectonic geomorphology. Based on ASTER-GDEM data and the technique of GIS, the other tectonic geomorphic indices are extracted in Minjiang River drainage basin including hypsometric integral, stream-gradient index, drainage basin asymmetry, drainage basin shape, ratio of valley floor width-to-height, and drainage elongation ratio. This drainage is located in the transitional region between Eastern Tibetan Plateau and Sichuan Basin with an area of 23 000 km2. The results obtained from these indices are combined to yield an index of relative active tectonics (IAT) that is obtained by the average of the different classes of geomorphic indices. Based on IAT value, four classes are defined: Class 1: very high relative tectonic activity with 1≤IAT<1.5; Class 2: high with 1.5≤IAT<2.0; Class 3: moderate with 2.0≤IAT<2.5 and Class 4: low with 2.5≤IAT. Through the analysis of the geomorphic results in Minjiang River drainage basin, we conclude that the value of hypsometric index is moderate, the shape of hypsometric curve is convex-concave, Minjiang River basin tilt from right to left facing downstream, the shape of this basin is elongate, the stream length gradient index is high and the fractal dimension value is low, and this drainage have relatively higher tectonic activity (IAT=1.33). The indicative value of IAT is consistent with the areas of known relative uplift rates, landforms and geology. This method provides a new insight for exploring diversities of relative tectonic activities on an areal basis.
The spatio-temporal distributions of water vapor transport and precipitation are important factors for hydrologic modeling and water resources planning. The precipitation in Hanjiang River Basin is an important factor to South-to-North Water Diversion Project. At the same time, the water resources utilization of Hanjiang River Basin has significant impact on the downstream ecologic environment of Hangjiang River. The research of spatio-temporal distribution of water vapor transport and precipitation is a foundation for hydrologic modeling, water resources utilization and environment management for Hanjiang River Basin. First, a work flowhart was designed based on climate reanalysis data, station precipitation data and GIS. Based on GIS tools, by using NCEP/ NCAR monthly reanalysis data and precipitation data of 19 meteorological stations in Hanjiang River Basin, the paper has provided methods for calculating water vapor transport, precipitable water, measured precipitation and the conversion rate from precipitable water to actual precipitation. Using the climate reanalysis data and precipitation data in the July of 1998 as the experiment data, the spatial distribution of precipitable water, measured precipitation and the conversion rate from precipitable water to actual precipitation were calculated and visualized based on GIS. The spatial changing trends of the distributions are analyzed. The paper has explored the spatio-temporal distribution and relationships among water vapor transport, precipitable water, measured precipitation and the conversion rate. The temporal distribution of precipitable water and measured precipitation during 1981-2010 were analyzed, and the results indicated that the changing trends of precipitable water and measured precipitation are similar, and the conversion rate from precipitable water to actual precipitation has increased in recent years in Hanjiang River Basin.
In the past few decades, a series of ecological restoration and protection projects had been implemented in the Inner Mongolia region. However, which extent these projects met the satisfaction?In this paper, from the perspective of land use/land cover data and DPSIR conceptual framework, we systematically describe spatial and temporal changes of ecosystem services values and analyze driving factors of these changes from both the regional and the prefecture-level scale, adopting the parameters of the stock value, intensity of the stock value and the incremental value. The results show that:(1) Since 2000, the whole region's stock value had increased by only 0.24%, but the decreasing rate of the cumulative positive and negative incremental values had promoted by 32.9%. There are more changes occurred in the eastern area than in the western area; (2) Since 2000, after the "Grain for Green" policy was carried out, the stock values of ecosystem services in the plain cultivation areas and forests conservation areas had increased by 4.52% and 4.23% respectively, yet the incremental values had increased by 0.59 billion and 0.89 billion respectively. All the changes was constrained by climate change, population growth and a series of political and economic macro-policies; (3) Since 2000, the stock value had increased by 3.51%, while the incremental value still decreased by 0.42 billion in the highland steppe areas, which was constrained by the precipitation fluctuations and population growth factors; (4) Since 2000, the positive influences of human activities in central and eastern areas gradually increased from 45.8% to 76%; however, under the traditional way of economic development, the ecological protection in the midwest areas still faced great difficulties and pressures. The result of our study provides a scientific reference for dividing eco-zone and constructing eco-restoration, and it could be further utilized in establishing a suitable ecological compensation mechanism.
Urban thermal environment is an important part of urban ecosystem, and urban heat island (UHI) effect directly reflects the climate characteristics of the city. It has an important practical significance to analyze comprehensively the urban heat island for studying urban air temperature change resulting from urbanization and environment change, and protecting urban eco-environment .Taking the valley city of Xining as a case study area, six Landsat 5 TM scenes were adopted from USGS website, and meteorological station data were obtained from China Meteorological Data Sharing Service System respectively. Firstly, the six Landsat 5 TM scenes were preprocessed by using ArcGIS 10.0 and ENVI 5.0 and the meteorological station data was processed using EXCEL software. Secondly, based on mono-window algorithm, the land surface temperature (LST) of the study area was retrieved. Then, all LST retrieval results obtained from the six Landsat 5 TM scenes were normalized to 0-1 for comparing the temporal differences of varied urban heat island. Thirdly, all normalized results were divided into five equal interval levels based on density separation technology of ENVI 5.0 software. Finally, the correlations between LST and NDVI as well as LST and NDBI were analyzed respectively. The results show that an obvious urban heat island effect exists in Xining city from 1996 to 2011. In addition, the spatial distribution pattern and extension of the urban heat island is consistent with urban sprawl. The urban heat island area is respectively 54.2 km2 in August 1996, 85.9 km2 in July 2001, 147.1 km2 in July 2007, 166.7 km2 in March 2009, 148.9 km2 in July 2010, and 158.7 km2 in September 2011, showing an expanding trend from 1996 to 2011 in general. Specifically, the heat island area has reduced substantially in the low and medium LST sub-region, whereas the heat island area has increased significantly in the high LST sub-region. The heat island effect is the strongest in winter, and it decreases evidently in the summer, then the autumn. In the spatial pattern of valley city, the land surface temperature is negatively correlated with NDVI, and positively correlated with NDBI. According to the spatio-temporal evolution of urban heat island, with the adoption of analysis of causes and strategic thinking, the constructive strategies and measures to alleviate urban heat island effect are proposed from different aspects, thus providing a scientific reference for decision making to improve the thermal environment of Xining City in the future.
：Forest understory contributes significantly to cycles and accumulation of carbon, water and nutritional elements in the ecosystem. Remote sensing with multi-angular, hyperspectral or Lidar systems is very sensitive to the stratification of forest, which allows us to quantify understory. In this paper, the progress of forest understory retrieval from remote sensing is reviewed. The definition of understory is firstly discussed. Then, a systematical analysis is presented. The review focuses on forest background reflectivity, understory leaf area index, and understory height and coverage that are retrieved respectively from multi-angular, hyperspectral and Lidar data. Based on the different contributions of forest canopy and background with respect to different observation angles, multi-angle observations make it possible to retrieve forest background reflectivity. The retrieved forest background reflectivity could further be used to estimate understory leaf area index through various retrieval algorithms. In addition, as Lidar systems are capable of directly observing understory through forest canopy, understory height and coverage could be retrieved from Lidar cloud points and waveform information. Finally, the shortcoming of current research and possible improvements in future research are discussed. There are mainly three facets where future understory retrieval could emphasize, including the using of spectral, phonological and angular differences between understory and overstory, the simulation of multi-angular observations by bidirectional reflectance function, and the fusion of multi-source data from radar, Lidar and hyperspectral remote sensing systems.
Urban impervious surface pattern causes changes of surface albedo, emissivity and surface roughness by changing the structure of urban surface, and thereforeinfluences the balance of surface radiation and energy directly. Impervious surfaces will increase the surface sensible heat flux, resulting in a rise of surface Bowen ratio, which provides a physical basis forpredicting the distribution of urban artificial impervious surfaces through spatial differences of Bowen ratio. In this study, we selected Beijing as the experimental areaand appliedthe PCACA model and theoretical positioning algorithm to calculate the Bowen ratio of urban surfaces with Landsat TM satellite thermal infrared remote sensing data. Furthermore, based on the correlation between the spatial distribution of surface Bowen ratio and the proportion of urban impervious surfaces, a regression equation was built to estimatethe percentage of Beijing urban artificial impervious surfaces distribution. The result was tested and verifiedwith the artificial impervious surface ratio of the city extracted from high-resolution remote sensing data. The result shows that in the method which inverts urban surface Bowen ratio data using the PCACA model, and then estimates the ratio of urban artificial impervious surface percentage distribution based on the correlation between the surface Bowen ratio data and the proportion data of urban impervious surfaces, Bowen ratio can be used not only to qualitatively determine if a remote sensing pixel is the impermeable at a pixel level, but also to calculate with high accuracy the proportion of the impermeable part of a mixed pixel, and the correlation coefficient R² value between the estimated impervious surface ratio based on Bowen ratio and the real proportion was 0.731. This method reveals the mechanism of the impact of the urban impervious land surfaceson heat flux and their spatial quantitative relationship.
Mean solar exoatmospheric irradiances over band b (ESUNb) is an important parameter for computing apparent reflectance. In recent years, ZY-1 02C, ZY-3 and GF-1 were launched and they have played an important role in land and resources survey as well as urban planning and construction. However, ESUNb values of these domestic remote sensing satellites have not been released publicly, and till now it causes difficulties in processing their DN values to the physical quantities. In order to calculate ESUNb values, Extraterrestrial Solar Spectral Irradiance and Spectral Response Function (SRF) are necessary. This paper aimed to calculate the unknown ESUNb based on a selection of optimal solar spectrum from nine released solar spectra, including ASTM-E490, WRC, Wehrli, etc. A number of medium spatial resolution and high spatial resolution sensors whose ESUNb had been officially released were chosen, such as EO1/ALI, Terra/ASTER, QuickBird, etc. Through calculating the mean absolute error (MAE) and the standard deviation of absolute error (SDAE) between the calculated ESUNb values and the officially released values for these sensors, WRC solar spectrum and Wehrli solar spectrum were selected as the optimal solar spectra for sensors with medium spatial resolution and high spatial resolution respectively. This is because WRC solar spectrum showed the least MAE (3.208 W·m2·μm-1) and Wehrli solar spectrum showed the least MAE (0.701 W·m2·μm-1) and SDAE (1.034 W·m2·μm-1). Based on WRC solar spectrum and Wehrli solar spectrum, ESUNb values of ZY-1 02C/PMS, ZY-3/Multispectral camera and Three-line array camera, GF-1/WFV and PMS were calculated and given accordingly. The resultant values were between the maximum and minimum ESUNb values for all the nine solar spectra. In addition, the uncertainty analysis was conducted and their relative biases due to the selection of different solar spectra were between -1.938% and 1.477%. Calculating ESUNb values in this way is simple and easy, because it can ensure the comparability of data between different remote sensors. This method can be applied to the other new remote sensing sensors so as to fully utilize their data.
Snow depth is an important parameter to characterize snow features, and it is also one of the most sensitive factors of regional response to climate change. Based on the daily dataset of snow depth from 1979 to 2010, the spatial and temporal variations and distribution anomaly of snow depth over the Qinghai-Tibetan Plateau in China were analyzed with the use of spatial and statistics analysis function of GIS. The results showed that, during the period from 1979 to 2010, snow depth increased obviously and significantly with the rate of 0.26 cm/(10a) in the Qinghai-Tibetan Plateau, and especially the snow depth in the alpine desert zone in Kunlun Mountains increased most obviously with the rate of 0.73 cm/(10a), and it decreased most clearly with the rate of -0.34 cm/(10a) in the montane evergreen broad-leaved forest in south side of eastern Himalayas. Snow depth gradually increased from the 1980s to the 1990s, while it changed stably in the early 21th century. The results indicated that monthly average snow depth started to rise from September, reached a maximum in January, and then declined to the minimum in August. From the perspective of seasons, snow depth rose, particularly in winter with the rate of 0.57 cm/(10a), and increased most obviously in Ali, north of Kunlun Mountains and the alpine desert zone in Kunlun Mountains. Among the four seasons, spring mean snow depth contributed most significantly to the annual situation, with the correlation coefficient between them up to 0.885. As far as the spatial distribution is concerned, the deeper snow depth lied in the southeast, the western and southern areas of the Qinghai-Tibetan Plateau; the area with an annual upward trend accounted for 67.1%, of which 91.3% is the mild and moderate increase which mainly occurred in the north and west of Qinghai-Tibetan Plateau; moreover, the maximum snow depth varied between -0.1 and 0.1 cm/a, which was on the rise in the north wing of the Kunlun Mountain, the mountainous region of the Qaidam Basin, and south of Qiangtang Plateau where the snow depth mildly increased; the sensitive areas of distribution anomaly of snow depth were in the alpine shrub of Guoluo-Naqu region, south Qinghai and the Qiangtang Plateau.
Due to its close relation with the physical state of ground surface, vegetation status and the change of precipitation, latent heat flux in the Three Gorges Reservoir Region is an important expression of water circulation and energy exchange of ground-air and an important parameter for assessment of climatic effect on regional scale. Taking a part of the Three Gorges Reservoir Region as a typical transect, making use of the timeliness and regional advantages of remote sensing data, and combining with the conventional meteorological data, the quantitative inversion of surface latent heat flux was completed. The contrast verification between the result of remote sensing inversion and FAO Penman-Monteith formula calculated proved the feasibility and reliability of inversion methods based on the relative error. There is a realistic significance for the reservoir area climate scene simulation on the regional scale. Considering the influence of terrain factor fully is conducive to the inversion results closing to the actual values. Further analysis on the spatial distribution of surface latent heat flux in the sample region provided scientific evidence for the climate effect under a changing surface cover. The results show that different surface cover condition appears different latent heat flux, and the spatial distribution of latent heat flux is changing obviously with the change in surface cover, namely, the spatial heterogeneity. For example, the latent heat flux values range from 20 to 80W/m2 in urban residential area and non-vegetation coverage area, 180 to 280 W/m2 in artificial forest, mountain forest, grass, shrub and piedmont farming area, and 420 to 470 W/m2 in water body. In addition, because the surface cover is more complex as well as influenced by undulating landform, the spatial distribution of latent heat flux presents obviously terrain differentiation characteristics.
With Acacia Rachii (Acacia confusa) grown in coastal region in Fuzhou as research object, and based on HJ-1A CCD1 imagery which was acquired from China Center for Resource Satellite Data and Applications, the Acacia Rachii LAI was monitored in field using LAI-2000 canopy analysis system, and two kinds of universal LAI inversion methods through regression analysis method and radiative transfer model PROSAIL model separately were introduced and used in this study. The simulation precisions for different models were analyzed and evaluated through comparing the simulated LAI and measured LAI. Further, we compared the research output with those of previous researchers. The results showed that: (1) Compared with the three vegetation indices (NDVI, EVI and OSAVI), HJVI vegetation index performed best in Acacia Rachii LAI inversion among all of the vegetation indices with R2=0.7344 and RMSE=0.1421, which introduced blue band and green band in order to weaken the effects of atmosphere and soil; (2) The optimal inversion models of the above four vegetation indices all were non-linear models, and the optimal regression model for Acacia Rachii LAI inversion based on vegetation indices was the power regression model of HJVI, indicating that there existed non-linear relationships between Acacia Rachii LAI and vegetation indices; (3) There had obvious improvement in the precision of LAI inversion through PROSAIL model compared with regression analysis method based on vegetation indices with R2=0.7903 and RMSE=0.1303, which indicated that PROSAIL model could better estimate Acacia Rachii LAI than regression analysis method to some extent. Therefore, radiative transfer model such as PROSAIL used to construct the inversion model is feasible. It could reflect ground condition better and possesses higher application value and broad application prospect.
Wetlands are ecosystems interlaced between water and land that are highly affected by drought. Analysis of the differing degree of drought from different wetlands can provide scientific bases for disaster mitigation and wetland conservation. Based on HJ-CCD images in two periods (May 2010 and May 2011), we extracted the wetland water areas of Honghu Lake and Liangzi Lake, and then combining with statistical and questionnaire data we analyzed the differences of drought degree between the two lakes from three aspects: (1) the wetland water area change and its spatial distribution; (2) wetland ecosystem functional degeneration and (3) the influences of wetland ecosystem to human well-being. Subsequently, the differences of drought degree between the two lakes were analyzed from meteorological factors, wetland forming reasons and wetland types, regional geographical environment, regional hydrological condition and the wetland conservation degree. The three main meteorological factors, i.e. monthly average precipitation, temperature and wind speed, were selected because precipitation mainly affects the inflow of the lakes, while temperature and wind speed are the main factors in outflow of the lakes. Moreover, we also used the questionnaire data to analyze the differences of the wetland conservation measures and the understanding of local people to wetland protection. The results show that, the drought degree of Honghu Lake is more serious than Liangzi Lake. During the drought, water area of Honghu Lake has reduced 83.93 km2, with the proportion of 26%, while the water area reduction of Liangzi Lake is 13.02 km2 with the proportion of only 4%. Many functions of the two lakes are damaged such as water conservation, biological diversity conservation, material production and water purification function. Since the damage degree of these functions of Honghu Lake is more serious than Liangzi Lake, Honghu Lake brings more negative impacts on human well-being than Liangzi Lake. The results also indicate that the lake forming reason and the regional geographical environment are the main factors in the differences of drought degree between the two lakes, as well as some meteorological factors such as wind speed. In addition, the differences and effects of wetland conservation measures also influence the drought degree between the two lakes.
