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1.
Forest fire is known as an important natural hazard in many countries which causes financial damages and human losses; thus, it is necessary to investigate different aspects of this phenomenon. In this study, performance of four models of linear and quadratic discriminant analysis (LDA and QDA), frequency ratio (FR), and weights-of-evidence (WofE) was investigated to model forest fire susceptibility in the Yihuang area, China. For this purpose, firstly, a forest fire locations map was prepared implementing MODIS satellite images and field surveys. Then, it was classified into two groups including training (70%) and validation (30%) by a random algorithm. In addition, 13 forest fire effective factors were prepared and used such as slope degree, slope aspect, altitude, Topographic Wetness Index (TWI), plan curvature, land use, Normalized Difference Vegetation Index (NDVI), annual rainfall, distance from roads and rivers, wind effect, annual temperature, and soil texture. Using the training dataset and effective factors, LDA, QDA, FR, and WofE models were applied and forest fire susceptibility maps were prepared. Finally, area under the curve (AUC) of receiver operating characteristics (ROC) was implemented for investigating the performance of the models. The results depicted that WofE had the best performance (AUC = 82.2%), followed by FR (AUC = 80.9%), QDA (AUC = 78.3%), and LDA (AUC = 78%), respectively. The results of this study showed the high contribution of altitude, slope degree, and temperature. On the other hand, it was seen that slope aspect and soil had the lowest importance in forest fire susceptibility mapping. From the AUC results, it can be concluded that FR, WofE, LDA, and QDA had acceptable performance and could be used for forest fire susceptibility mapping at the regional scale.  相似文献   

2.
A. Golara 《Natural Hazards》2014,73(2):567-577
Seismic hazard maps are widely used for engineering design, land-use planning, and disaster mitigation. The development of the new seismic hazard map of Iran with regard to the specification of Iranian high-pressure gas network is based on probabilistic seismic hazard analysis using the historical and new earthquakes data, geology, tectonics, fault activity, and seismic zone models in Iran. The map displays the probabilistic estimates of peak ground acceleration for the return period of 2,475 year (2 % probability in 50 years). The results presented in this study will provide the basis for the preparation of risk map, the estimation of insurance premiums, finding best paths for future pipelines, planning, and relocating lifeline facilities especially for interconnected infrastructures.  相似文献   

3.
The presented research was performed in order to model the fire risk in a part of Hyrcanian forests of Iran. The fuzzy sets integrated with analytic hierarchy process (AHP) in a decision-making algorithm using geographic information system (GIS) was used to model the fire risk in the study area. The used factors included four major criteria (topographic, biologic, climatic, and human factors) and their 17 sub-criteria. Fuzzy AHP method was used for estimating the importance (weight) of the effective factors in forest fire. Based on this modeling method, the expert ideas were used to express the relative importance and priority of the major criteria and sub-criteria in forest fire risk in the study area. The expert ideas mean was analyzed based on fuzzy extent analysis. Then, the fuzzy weights of criteria and sub-criteria were obtained. The major criteria models and fire risk model were presented based on these fuzzy weights. On the other hand, the spatial data of 17 sub-criteria were provided and organized in GIS to obtain the sub-criteria maps. Each sub-criterion map was converted to raster format and it was reclassified based on risk of its classes to fire occurrence. Then, all sub-criteria maps were converted to fuzzy format using fuzzy membership function in GIS. The fuzzy map of each major criterion (topographic, biologic, climatic, and human criteria) was obtained by weighted overlay of its sub-criteria fuzzy maps considering to major criterion model in GIS. Finally, the fuzzy map of fire risk was obtained by weighted overlay of major criteria fuzzy maps considering to fire risk model in GIS. The actual fire map was used for validation of fire risk model and map. The results showed that the fuzzy estimated weights of human, biologic, climatic, and topographic criteria in fire risk were 0.301, 0.2595, 0.2315, and 0.208, respectively. The results obtained from the fire risk map showed that 38.74% of the study area has very high and high risk for fire occurrence. Results of validation of the fire risk map showed that 80% of the actual fires were located in the very high and high risk areas in fire risk map. It can show the acceptable accuracy of the fire risk model and map obtained from fuzzy AHP in this study. The obtained fire risk map can be used as a decision support system for predicting of the future fires in the study area.  相似文献   

4.
Tiwari  Anuj  Shoab  Mohammad  Dixit  Abhilasha 《Natural Hazards》2021,105(2):1189-1230

This study performs a comparative evaluation of Frequency Ratio (FR), Analytic Hierarchy Process (AHP), and Fuzzy AHP (FAHP) modeling techniques for forest fire susceptibility mapping in Pauri Garhwal, Uttarakhand, India. Locations of past forest fire events reported from November 2002 to July 2019 were collected from the Uttarakhand Forest Department and Forest Survey of India and combined with the ground observations obtained from the manual survey. Then, the locations were categorized into two groups of 70% (10,500 locations) and 30% (4500 locations), randomly, for training and validation purposes, respectively. Forest fire susceptibility mapping was performed on the basis of fourteen different topographic, biological, human-induced and climatic criteria such as Digital Elevation Model, Slope, Aspect, Curvature, Normalized Difference Vegetation Index, Normalized Difference Moisture Index, Topographic Wetness Index, Soil, Distance to Settlement, Distance to Road, Distance to Drainage, Rainfall, Temperature, and Wind Speed. The Receiver Operating Characteristic curve and the Area Under the Curve (AUC) were implemented for validation of the three achieved Forest Fire Susceptibility Maps. The AUC plot evaluation revealed that FAHP has a maximum prediction accuracy of 83.47%, followed by AHP (81.75%) and FR (77.21%). Thus, the map produced by FAHP exhibits the most satisfactory properties. Results and findings of this study will help in developing more efficient fire management strategies in both the open and the protected forest areas (Rajaji and Jim Corbett National Park) of the district.

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5.
Construction of forest roads can cause short-term and long-term negative effects on forest ecosystems in different ways if they are not well planned and appropriately maintained. In this research, environmental damages caused by an excavator during road construction were examined in steep terrain covered by beech (Fagus orientalis L.) stands. The study was conducted along a 1.5 km road in western Blacksea Region of Turkey. All of the road construction operations were monitored during a construction period, and measurements of cross sections sizes and stand damages were measured during and after the construction activities. The road construction was evaluated according to the appropriate method and standards. The average widths of roadway, fill slope and construction zone were 4.82, 6.91, and 16.61 m, respectively. Along the 1,500 m road, forested area impacted was 24,915 m2 while the number of trees cut was 1,495 and rate of the damaged trees below the fill slope was found to be 24.7 %. In the study, based on the appropriate method and standards, less forested area might have been impacted (23 %). As a result of regression analysis, it was found that the rate of damaged trees increased as the values of the proportion of rocks, the width of the road surface and the width of the cut-slope increased. To reduce the negative effects of forest road construction on the environment, new forest road construction by excavators should be performed using appropriate methods within mountainous terrains.  相似文献   

6.
Deadwood is an indicator that addresses many parameters of naturalness and is becoming a general reference for natural forests. If there are enough of the different kinds of deadwood in a forest, then it is likely to be properly natural. Also, it is a practical indicator, representing the health and biodiversity of forests. The aim of this research was to find out how much deadwood should be present in different developmental stages in a natural forest as a reference. For this purpose, a natural forest ecosystem in Mazandaran province, north of Iran, which is located in Noshahr, was selected. Species, diameter and height of all (living and dead) trees in each area were assessed. Then, developmental stages were determined, and their map was produced. The amount of deadwood was determined in different stages. Results showed that all three stages (initial, optimal and decay stage) could be recognized in the studied beech stands. Deadwood rate varied and greatest volume and number of it occurred in decay and initial stages, respectively. The frequency and volume of deadwood depend on the pattern of natural disturbance, developmental stages and stand structure. The amount of deadwood within managed forests is open to debate and requires detailed knowledge about beech stands in local conditions. So, based on these results in natural forests of beech in north of Iran, deadwood volume between 4.9 and 54.3 m3 ha?1 or 1.1–9.6 % of total volume of wood could be considered as a reasonable amount and each developmental stage must be different.  相似文献   

7.
Natural Hazards - The Canadian Fire Weather Index (FWI) is one of the most used tools to forecast forest fire hazard. In this paper, we propose an adaptation of the FWI to take into account the...  相似文献   

8.
Assessing the groundwater recharge potential zone and differentiation of the spring catchment area are extremely important to effective management of groundwater systems and protection of water quality. The study area is located in the Saldoran karstic region, western Iran. It is characterized by a high rate of precipitation and recharge via highly permeable fractured karstic formations. Pire-Ghar, Sarabe-Babaheydar and Baghe-rostam are three major karstic springs which drain the Saldoran anticline. The mean discharge rate and electrical conductivity values for these springs were 3, 1.9 and 0.98 m3/s, and 475, 438 and 347 μS/cm, respectively. Geology, hydrogeology and geographical information system (GIS) methods were used to define the catchment areas of the major karstic springs and to map recharge zones in the Saldoran anticline. Seven major influencing factors on groundwater recharge rates (lithology, slope value and aspect, drainage, precipitation, fracture density and karstic domains) were integrated using GIS. Geology maps and field verification were used to determine the weights of factors. The final map was produced to reveal major zones of recharge potential. More than 80 % of the study area is terrain that has a recharge rate of 55–70 % (average 63 %). Evaluating the water budget of Saldoran Mountain showed that the total volume of karst water emerging from the Saldoran karst springs is equal to the total annual recharge on the anticline. Therefore, based on the geological and hydrogeological investigations, the catchment area of the mentioned karst springs includes the whole Saldoran anticline.  相似文献   

9.
Forest fire can modify and accelerate the hydrological response of Mediterranean basins submitted to intense rainfall: during the years following a fire, the effects on the hydrological response may be similar to those produced by the growth of impervious areas. Moreover, climate change and global warming in Mediterranean areas can imply consequences on both flash flood and fire hazards, by amplifying these phenomena. Based on historical events and post-fire experience, a methodology to interpret the impacts of forest fire in terms of rainfall-runoff model parameters has been proposed. It allows to estimate the consequences of forest fire at the watershed scale depending on the considered burned area. In a second stage, the combined effect of forest fire and climate change has been analysed to map the future risk of forest fire and their consequence on flood occurrence. This study has been conducted on the Llobregat river basin (Spain), a catchment of approximately 5,000 km2 frequently affected by flash floods and forest fires. The results show that forest fire can modify the hydrological response at the watershed scale when the burned area is significant. Moreover, it has been shown that climate change may increase the occurrence of both hazards, and hence, more frequent severe flash floods may appear.  相似文献   

10.
Forest conversion due to illegal logging and agricultural expansion is a major problem that is hampering biodiversity conservation efforts in the Zagros region. Yet, areas vulnerable to forest conversion are unknown. This study aims to predict the spatial distribution of deforestation in western Iran. Landsat images dated 1988, 2001, and 2007 are classified in order to generate digital deforestation maps which locate deforestation and forest persistence areas. Meanwhile, in order to examine deforestation factors’ investigation, deforestation maps with physiographic and human spatial variables are entered into the model. Areas vulnerable to forest changes in the Zagros forest region are predicted by a multilayer perceptron neural network (MLPNN) with a Markov chain model. The results show that about 19,294 ha forest areas are deforested in the last 19 years. The predictive performance of the model appears successful, which is validated using the actual land cover map of the same year from Landsat data. The validated map is found to be 94 % accurate. The validation is also tested using the relative operating characteristic approach which yielded a value of 0.96. The model is then further extended to predict forest cover losses for 2020. The MLPNN approach was found to have a great potential to predict land use/land cover changes because it permits developing complex, nonlinear models.  相似文献   

11.
The present work attempts to interpret the groundwater vulnerability of the Melaka State in peninsular Malaysia. The state of groundwater pollution in Melaka is a critical issue particularly in respect of the increasing population, and tourism industry as well as the agricultural, industrial and commercial development. Focusing on this issue, the study illustrates the groundwater vulnerability map for the Melaka State using the DRASTIC model together with remote sensing and geographic information system (GIS). The data which correspond to the seven parameters of the model were collected and converted into thematic maps by GIS. Seven thematic maps defining the depth to water level, net recharge, aquifer media, soil media, topography, impact of vadose zone and hydraulic conductivity were generated to develop the DRASTIC map. In addition, this map was integrated with a land use map for generating the risk map to assess the effect of land use activities on the groundwater vulnerability. Three types of vulnerability zones were assigned for both DRASTIC map and risk map, namely, high, moderate and low. The DRASTIC map illustrates that an area of 11.02 % is low vulnerability, 61.53 % moderate vulnerability and 23.45 % high vulnerability, whereas the risk map indicates that 14.40 % of the area is low vulnerability, 47.34 % moderate vulnerability and 38.26 % high vulnerability in the study area. The most vulnerability area exists around Melaka, Jasin and Alor Gajah cities of the Melaka State.  相似文献   

12.
The weights-of-evidence is a data-driven method that provides a simple approach to integration of diverse geo-data set information. In this study, we will use weights-of-evidence to build a model for predicting tracts in the Ahar–Arasbaran zone of Urumieh-Dokhtar orogenic belt (northwestern Iran) that are favorable for porphyry copper deposits. Weights of evidence are a data-driven method requiring known deposits and occurrences that are used as training points in the evaluated area. This zone hosts two major porphyry Cu deposits (The Sarcheshmeh deposit contains 450 million tonnes of sulfide ore with an average grade of 1.13 % Cu and 0.03 % Mo and Sungun deposit, which has 500 million tonnes of sulfide reserves grading 0.76 % Cu and 0.01 % Mo), and a number of subeconomic porphyry copper deposits are all associated with Mid- to Late Miocene diorite/granodiorite to quartz-monzonite stocks. Five evidential layers including geology, alteration, geochemistry, geophysics, and faulting are chosen for potential mapping. Weight factors were determined based on the applied method to generate last mineral prospectivity map. The studied area reduces to less than 11.78 %, while large zones are excluded for further studies. This result represents a significant area reduction and may help to better focus on mineral exploration targeting porphyry copper deposits in the Ahar–Arasbaran zone.  相似文献   

13.
The Sonajil intrusive is located about 60 km southeast of Ahar, in Azarbaijan province in northwestern Iran, and is intruded into by andesitic trachytic Eocene pyroclastics and agglomerate. To the center, the stock is hydrothermally altered, that contains sub-economic copper mineralization. The 1,248 cells with 100?×?100 m grid were sampled, and measurement of elements by ICP-MS method and major oxides included by X-ray fluorescence method was performed. After statistical interpretations, geochemical anomalies and indices alteration (sericitization, alkali, Spitz–Darling, chloritization, Hashimoto, Hashiguchi) were calculated, and their map distribution was prepared. Based on these maps and other interpretations of data, our study indicated that despite the anomaly of copper and other elements such as gold, molybdenum, lead, arsenic and antimony of not being quite consistent, almost all of them are within the alteration zones.  相似文献   

14.
The aim of the present research is to monitor changes in herbage production during the grazing season in the Semirom and Brojen regions, Iran, using multitemporal Moderate Resolution Imaging Spectroradiometer (MODIS) data. At first, various preprocessing steps were applied to a topography map. The atmospheric and topographic corrections were applied using subtraction of the dark object method and the Lambert method. Image processing, including false-color composite, principal component analysis, and vegetation indices were employed to produce land use and pasture production maps. Vegetation sampling was carried out over a period of 4 months during June–September 2008, using a stratified random sampling method. Twenty random sampling points were selected, and herbage production was estimated and verified with the double-checking method. Four MODIS data sets were used in this study. The models for image processing and integrating ground data with satellite images were processed, and the resulting images were categorized into seven classes. Finally, the land covers were verified for accuracy. A postclassification analysis was carried out to verify the seven class change detections. The results confirmed that Normalized Difference Vegetation Index (NDVI) and Soil-Adjusted Vegetation Index (SAVI) maps had a close relationship with the field data. The indices produced with shortwave infrared bands had a close relationship with field data where the ground cover and yields were high. The R 2 value observed was 0.85. The changes in the pasture vegetation were high during the growing season in more than 90 % of the pastures. During the growing season, most changes in the pastures belonged to class 5 and 2 in the NDVI and SAVI index maps, respectively.  相似文献   

15.
This paper describes the application of a well-known multi-criteria decision-making technique, called preference ranking organization method for enrichment evaluation (PROMETHEE II), in combination with fuzzy analytical hierarchy process (FAHP), as a weighting technique to explore landslide susceptibility mapping (LSM). To this end, eight landslide-related geodata layers of the Minoo Dasht located in the Gorgan province of Iran, involving slope, aspect, distance to river, drainage density, distance to fault, mean annual rainfall, distance to road and lithology have been integrated using the PROMETHEE II enhanced by FAHP technique. Afterward, the receiver operating characteristics (ROC) curves for the proposed LSM were drawn using an inventory of landslides containing 83 recent and historic landslide points, and the area under curve = 0.752 value was calculated accordingly. Additionally, to further verify the practicality of such susceptibility map, it was also evaluated against the landslide inventory using simple overlay. The outcome was that about 11 % of the occurred landslide points fall into the very high susceptibility class of the LSM, but approximately 52 % of them indeed fall into the high and very high susceptibility zones together. Also, it resulted that no recorded landslide occurred in the zone of very low susceptibility. According to the results of the ROC curves analysis and simple overlay evaluation, the produced map has exhibited good performance.  相似文献   

16.
Holocene fire disturbance and vegetation history were reconstructed using macroscopic charcoal and pollen accumulation rates from two lake sediment records (Holtjärnen and Klotjärnen) collected in the boreal forest of central Sweden. The records were used to examine the potential drivers associated with changes in fire regime. Climate, vegetation and human activity were all identified as factors variously influencing the fire regime. In the early Holocene, near bicentennial fire return intervals were regionally widespread, suggesting that fire disturbance was largely regulated by climate at that time. In the mid‐ and late Holocene, vegetation exerted an important control on the fire regime. During the mid‐Holocene, the expansion of thermophilous broadleaf vegetation offset the influence of warmer climate by altering the local microclimate and by changing the structure and flammability of the available fuels. During the transition to the late Holocene, thermophilous vegetation decreased in abundance and Pinus increased, resulting in a more flammable forest even though the climate was cooling and moistening. Fire disturbance correspondingly increased. The modern boreal forest was established in the late Holocene as Picea expanded regionally as the climate cooled, moistened, and became increasingly continental. Although no change in the frequency of fire was apparent at this time, increased stand densities likely facilitated greater fuel consumption in subsequent fires. Within the last millennium, human action markedly modified the forested landscape, altering the fire regime.  相似文献   

17.
《地学前缘(英文版)》2020,11(4):1203-1217
Natural hazards are often studied in isolation.However,there is a great need to examine hazards holistically to better manage the complex of threats found in any region.Many regions of the world have complex hazard landscapes wherein risk from individual and/or multiple extreme events is omnipresent.Extensive parts of Iran experience a complex array of natural hazards-floods,earthquakes,landslides,forest fires,subsidence,and drought.The effectiveness of risk mitigation is in part a function of whether the complex of hazards can be collectively considered,visualized,and evaluated.This study develops and tests individual and collective multihazard risk maps for floods,landslides,and forest fires to visualize the spatial distribution of risk in Fars Province,southern Iran.To do this,two well-known machine-learning algorithms-SVM and MARS-are used to predict the distribution of these events.Past floods,landslides,and forest fires were surveyed and mapped.The locations of occurrence of these events(individually and collectively) were randomly separated into training(70%) and testing(30%) data sets.The conditioning factors(for floods,landslides,and forest fires) employed to model the risk distributions are aspect,elevation,drainage density,distance from faults,geology,LULC,profile curvature,annual mean rainfall,plan curvature,distance from man-made residential structures,distance from nearest river,distance from nearest road,slope gradient,soil types,mean annual temperature,and TWI.The outputs of the two models were assessed using receiver-operating-characteristic(ROC) curves,true-skill statistics(TSS),and the correlation and deviance values from each models for each hazard.The areas-under-the-curves(AUC) for the MARS model prediction were 76.0%,91.2%,and 90.1% for floods,landslides,and forest fires,respectively.Similarly,the AUCs for the SVM model were 75.5%,89.0%,and 91.5%.The TSS reveals that the MARS model was better able to predict landslide risk,but was less able to predict flood-risk patterns and forest-fire risk.Finally,the combination of flood,forest fire,and landslide risk maps yielded a multi-hazard susceptibility map for the province.The better predictive model indicated that 52.3% of the province was at-risk for at least one of these hazards.This multi-hazard map may yield valuable insight for land-use planning,sustainable development of infrastructure,and also integrated watershed management in Fars Province.  相似文献   

18.
Artificial neural networks (ANNs) show a significant ability to discover patterns in data that are too obscure to go through standard statistical methods. Data of natural phenomena usually exhibit significantly unpredictable non-linearity, but the robust behavior of a neural network makes it perfectly adaptable to environmental models such as a wildland fire danger rating system. These systems have been adopted by many developed countries that have invested in wildland fire prevention, and thus civil protection agencies are able to identify areas with high probabilities of fire ignition and resort to necessary actions. Since one of the drawbacks of ANNs is the interpretation of the final model in terms of the importance of variables, this article presents the results of sensitivity analysis performed in a back-propagation neural network (BPN) to distinguish the influence of each variable in a fire ignition risk scheme developed for Lesvos Island in Greece. Four different methods were utilized to evaluate the three fire danger indices developed within the above scheme; three of the methods are based on network’s weights after the training procedure (i.e., the percentage of influence—PI, the weight product—WP, and the partial derivatives—PD methods), and one is based on the logistic regression (LR) model between BPN inputs and observed outputs. Results showed that the occurrence of rainfall, the 10-h fuel moisture content, and the month of the year parameter are the most significant variables of the Fire Weather, Fire Hazard, and Fire Risk Indices, respectively. Relative humidity, elevation, and day of the week have a small contribution to fire ignitions in the study area. The PD method showed the best performance in ranking variables’ importance, while performance of the rest of the methods was influenced by the number of input parameters and the magnitude of their importance. The results can be used by local forest managers and other decision makers dealing with wildland fires to take the appropriate preventive measures by emphasizing on the important factors of fire occurrence.  相似文献   

19.
This research aims at uncovering the stand-scale Holocene fire history of balsam fir forest stands from two bioclimatic zones of the boreal forest and assessing the existence of a sub-continental shift in past fire activity that could have triggered a change in the Holocene zonal pattern. In eastern Canada, the extant closed-crown boreal forest corresponds to two ecological regions separated along 49°N, the northern black spruce zone and the southern balsam fir zone. We sampled balsam fir stands from the southern fir zone (n = 7) and among the northernmost patches of fir forest located far beyond the fir zone boundary, into the spruce zone (n = 6). Macrofossil analysis of charcoal in mineral soils was used to reconstruct both the stand-scale and regional Holocene fire histories. Data were interpreted in the context of published palaeoecological evidence. Stands of the balsam fir zone were submitted to recurrent fire disturbances between c. 9000 and 5000 cal. yr B.P. Local fire histories suggested that four sites within the fir zone escaped fire during the Holocene. Such fire protected sites allowed the continuous maintenance of the balsam fir forest in the southern boreal landscape. Stands of the spruce zone have been affected by recurrent fires from 5000 cal. yr B.P. to present. Local fire histories indicated that no site escaped fire in this zone. Published palaeoecological data suggested that balsam fir migrated to its current northern limit sometime between 7300 and 6200 cal. yr B.P. A change of the fire regime 5000 years ago caused the regional decline of an historical northern balsam fir forest and its replacement by black spruce forest. The consequence was a sub-continental reshuffling of the fir and spruce zones within the closed-crown boreal forest. The macrofossil analysis of charcoal in mineral soils was instrumental to the reconstruction of stand-scale Holocene fire history at sites where no other in situ fire proxies were available.  相似文献   

20.
The assessment of drought hazard impacts on wheat cultivation as a strategic crop in Iran is essential for making mitigation plans to reduce the impact of drought. Standardized precipitation index has gained importance in recent years as a potential drought indicator and is being used more frequently for assessment of drought hazard in many countries. In the present study, the calculated standardized precipitation index for 48 stations dataset in the 30-year time scale fulfilled 30 statistical matrices. The drought hazard index map was produced by sum overlaying the spatial representations of 30 statistical matrices and categorized into four levels of low, moderate, high, and very high, which demonstrated probability of drought occurrences of 10–20 %, 20–30 %, 30–40 %, and 40–50 %, respectively. Finally, after the general division of zonal statistics in drought hazard index map of Iran, major drought hazard zones were geographically classified into five zones. The statistical analysis showed a significant correlation (R 2?=?0.701 to 0.648) between drought occurrences and wheat cultivation including surface area and total production for these drought hazard zones.  相似文献   

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