A decline in snow cover area of Passu and Ghulkin valleys between 1995 and 2022

The global cryosphere is experiencing accelerated melting due to climate change.Currently,the Karakoram anomaly is under discussion with a debate about the possibility that the anomaly may have recently ended.This study aims to evaluate the up-to-date changes in snow cover in the western Karakoram region.We observed the snow cover changes in Passu and Ghulkin valleys in the Hunza River basin(HRB)of the Karakoram through multitemporal Landsat satellite data between 1995 and 2022.We found a significant reduction in snow cover in these valleys,with an average reduction rate of 0.42 km~2/yr,resulting in a total reduction of~11.46 km~2 between 1995 and 2022.This reduction in snow cover is consistent with the mass loss of glaciers in the Karakoram region in recent years.The decline in snow cover in these valleys is also consistent with the meteorological data.The temperature in summer(June)has significantly increased whereas the precipitation in the accumulation season(March)has decreased.These rapid changes suggest that it is crucially important to monitor the snow cover on a regular basis to support downstream management of snowmelt runoff.In addition,there is a need of planning for mitigation and adaptation strategies for snow-related hazards.

Temporal and Spatial Variation Characteristics of Snow Cover Area in the Pamirs from 2010 to 2020

Scientific and comprehensive monitoring of snow cover changes in the Pamirs is of great significance to the prevention of snow disasters around the Pamirs and the full utilization of water resources. Utilize the 2010-2020 snow cover product MOD10A2, Synthesis by maximum, The temporal and spatial variation characteristics of snow cover area in the Pamirs in the past 11 years have been obtained. Research indicates: In terms of interannual changes, the snow cover area of the Pamir Plateau from 2010 to 2020 generally showed a slight decrease trend. The average snow cover area in 2012 was the largest, reaching 54.167% of the total area. In 2014, the average snow cover area was the smallest, accounting for only 44.863% of the total area. In terms of annual changes, there are obvious changes with the change of seasons. The largest snow area is in March, and the smallest snow area is in August. In the past 11 years, the average snow cover area in spring and summer showed a slow decreasing trend, and there was almost no change in autumn and winter. In terms of space, the snow cover area of the Pamirs is significantly affected by altitude, and the high snow cover areas are mainly distributed in the Karakoram Mountains and other areas with an altitude greater than 5000 meters.

Support Vector Machines for Cloud Detection over Ice-Snow Areas

In polar regions, cloud and underlying ice-snow areas are difficult to distinguish in satellite images because of their high albedo in the visible band and low surface temperature of ice-snow areas in the infrared band. A cloud detection method over ice-snow covered areas in Antarctica is presented. On account of different texture features of cloud and ice-snow areas, five texture features are extracted based on GLCM. Nonlinear SVM is then used to obtain the optimal classification hyperplane from training data. The experiment results indicate that this algorithm performs well in cloud detection in Antarctica, especially for thin cirrus detection. Furthermore, when images are resampled to a quarter or 1/16 of the full size, cloud percentages are still at the same level, while the processing time decreases exponentially.

Soil and Vegetation Spectral Coupling Difference (SVSCD) for Minerals Extraction from Hyperion Data in Vegetation Covered Area

Remote sensing data have been widely applied to extract minerals in geologic exploration, however, in areas covered by vegetation, extracted mineral information has mostly been small targets bearing little information. In this paper, we present a new method for mineral extraction aimed at solving the difficulty of mineral identification in vegetation covered areas. The method selected six sets of spectral difference coupling between soil and plant(SVSCD). These sets have the same vegetation spectra reflectance and a maximum different reflectance of soil and mineral spectra from Hyperion image based on spectral reflectance characteristics of measured spectra. The central wavelengths of the six, selected band pairs were 2314 and 701 nm, 1699 and 721 nm, 1336 and 742 nm, 2203 and 681 nm, 2183 and 671 nm, and 2072 and 548 nm. Each data set's reflectance was used to calculate the difference value. After band difference calculation, vegetation information was suppressed and mineral abnormal information was enhanced compared to the scatter plot of original band. Six spectral difference couplings, after vegetation inhibition, were arranged in a new data set that requires two components that have the largest eigenvalue difference from principal component analysis(PCA). The spatial geometric structure features of PC1 and PC2 was used to identify altered minerals by spectral feature fitting(SFF). The collecting rocks from the 10 points that were selected in the concentration of mineral extraction were analyzed under a high-resolution microscope to identify metal minerals and nonmetallic minerals. Results indicated that the extracted minerals were well matched with the verified samples, especially with the sample 2, 4, 5 and 8. It demonstrated that the method can effectively detect altered minerals in vegetation covered area in Hyperion image.

Preliminary Study on Dynamic Changes of Insect Communities in Airport Ground Cover Areas in Different Weather Conditions

[Objectives]This study was conducted to investigate insect activity rhythms in airport ground cover areas,and provide guidance for insect control and bird strike prevention.[Methods]The daily rhythm of insects in the northern area of the airport was studied,and their activity rhythms and characteristics under different weather conditions were analyzed.[Results]In rainy days,the insect number in the three sample areas was low.In cloudy days,insect activity was relatively stable,and insect number was consistent in the morning and evening,and maintained in a stable range,while in sunny weather,insect activity was increased,and the number changed greatly with time.For a single tussock plant growth area,the number of insects was at a relatively low level under rainy weather.In fine weather,the peak period of insect activity was between 10:00-11:00 and 14:00-15:00.[Conclusions]This study can provide a reference for the formulation of safe flight departure time.

Effect of Vachellia tortilis on understory vegetation,herbaceous biomass and soil nutrients along a grazing gradient in a semi-arid African savanna

The spatial pattern and abundance of herbaceous vegetation in semi-arid savannas are dictated by a complex and dynamic interaction between trees and grasses. Scattered trees alter the composition and spatial distribution of herbaceous vegetation under their canopies. Therefore, we studied the effect of Vachellia tortilis on herbaceous vegetation composition, biomass and basal area, and soil nutrients on sites with varying grazing intensities in the central rift valley of Ethiopia. Data were collected on species composition, cover and biomass of herbs and grasses, and soil moisture and nutrient contents under light,medium, and heavy grazing pressures, both under the inside and outside of V. tortilis canopies. Species richness was similar in both locations but decreased with increased grazing. Only the overall biomass and herb cover were significantly greater under the canopy than outside, and overall biomass showed significant unchanging decline with increased grazing. However, vegetation cover was significantly greater on moderately grazed sites compared to low and heavily grazed sites. All soil variables were significantly higher under V. tortilis canopies than outside.Our findings suggest that V. tortilis has more effect on composition and diversity of herbaceous vegetation than on species richness, and that V. tortilis promotes the herbaceous layer biomass by reducing soil moisture loss and increasing soil fertility under the inside than outside the canopies. Therefore, we suggest that management practices should be directed on reducing pressure on V. tortilis by regulating grazing. Low to moderate grazing levels(i.e., a stocking rate less than 39.6 TLU ha-1yr-1) seems to be tolerable to ensure sustainable conservation of the species in the study area in particular and in semi-arid savannas in general.

Application of snowmelt runoff model(SRM) in mountainous watersheds:A review

The snowmelt runoff model （SRM） has been widely used in simulation and forecast of streamflow in snow-dominated mountainous basins around the world. This paper presents an overall review of worldwide applications of SRM in mountainous watersheds, particularly jn data-sparse watersheds of northwestern China. Issues related to proper selection of input climate variables and parameters, and determination of the snow cover area （SCA）using remote sensing data in snowmelt runoff modeling are discussed through extensive review of literature. Preliminary applications of SRM in northwestern China have shown that the model accuracies are relatively acceptable although most of the watersheds lack measured hydro-meteorological data. Future research could explore the feasibility of modeling snowmelt runoff in data-sparse mountainous watersheds in northwestern China by utilizing snow and glacier cover remote sensing data, geographic information system （GIS） tools, field measurements, and innovative ways of model parameterization.

SNOW COVER MONITORING BY REMOTE SENSING AND SNOWMELT RUNOFF CALCULATION IN THE UPPER HUANGHE RIVER BASIN

The upper Huanghe(Yellow) River basin is situated in the northeast of the Qinghai Xizang(Tibet)Plateau of China. The melt water from the snow cover is main water supply for the rivers in the region during springtime and other arid regions of the northwestern China, and the hydrological conditions of the rivers are directly controlled by the snowmelt water in spring. So snowmelt runoff forecast has importance for hydropower, flood prevention and water resources utilization. The application of remote sensing and Geographic Information System (GIS) techniques in snow cover monitoring and snowmelt runoff calculation in the upper Huanghe River basin are introduced amply in this paper. The key parameter-snow cover area can be computed by satellite images from multi platform, multi temporal and multi spectral. A cluster of snow cover data can be yielded by means of the classification filter method. Meanwhile GIS will provide relevant information for obtaining the parameters and also for zoning. According to the typical samples extracting snow covered mountainous region, the snowmelt runoff calculation models in the upper Huanghe River basin are presented and they are mentioned in detail also. The runoff snowmelt models based on the snow cover data from NOAA images and observation data of runoff, precipitation and air temperature have been satisfactorily used for predicting the inflow to the Longyangxia Reservoir , which is located at lower end of snow cover region and is one of the largest reservoirs on the upper Huanghe River, during late March to early June. The result shows that remote sensing techniques combined with the ground meteorological and hydrological observation is of great potential in snowmelt runoff forecasting for a large river basin. With the development of remote sensing technique and the progress of the interpretation method, the forecast accuracy of snowmelt runoff will be improved in the near future. Large scale extent and few stations are two objective reality situations in China, so they should be considered in simulation and forecast. Apart from dividing, the derivation of snow cover area from satellite images would decide the results of calculating runoff. Field investigation for selection of the learning samples of different snow patterns is basis for the classification.

Assessment of Agricultural Drought Risk in the Sichuan Basin Based on Information Diffusion Theory

Based on data of agricultural drought situation and sown area of main crops in each county or district of the Sichuan Basin, the spatial distribution and probability of agricultural drought risk at different risk levels were studied using normal information diffusion method, and the risk zoning was carried out. The results showed that normal information diffusion method could fit the distribution of agricultural drought risk in the Sichuan Basin. By comparison with the end of the 20^th century, agricultural drought risk in Meishan, Chongqing City and so on increased at the beginning of the 21^st century when x1≥ 10% or x1≥40%. Agricultural drought risk was low in the west of the Sichuan Basin, which was related to rich precipitation here, but it was high in Bazhong, Zhongjiang, Luxian and so forth. The risk zoning results can provide scientific references for disaster prevention and emergency management of government.

Parametric analyses of evapotranspiration landfill covers in humid regions

Natural soils are more durable than almost all man-made materials. Evapotranspiration （ET） covers use vegetated soil layers to store water until it is either evaporated from the soil surface or transpired through vegetation. ETcovers rely on the water storage capacity of soil layer, rather than low permeability materials, to minimize percolation. While the use of ET covers in landfills increased over the last decade, they were mainly used in arid or semi-arid regions. At present, the use of ET covers has not been thoroughly investigated in humid areas. The purpose of this paper is to investigate the use of ETcovers in humid areas where there is an annual precipitation of more than 800 mm. Numerical analyses were carried out to investigate the influences of cover thickness, soil type, vegetation level and distribution of precipitation on performance of ET covers. Performance and applicability of capillary barriers and a new-type cover were analyzed. The results show that percolation decreases with an increasing cover thickness and an increasing vegetation level, but the increasing trend becomes unclear when certain thickness or LAI （leaf area index） is reached. Cover soil with a large capability of water storage is recommended to minimize percolation. ET covers are significantly influenced by distribution of precipitation and are more effective in areas where rainy season coincides with hot season. Capillary barriers are more efficient than monolithic covers. The new cover is better than the monolithic cover in performance and the final percolation is only 0.5% of the annual precipitation.

Application of Snow Melt Runoff Model in a Mountainous Basin of Iran

Simulation and modeling the stream flow provide major data while it is a challenge in mountainous basins with regard to the important role of snowmelt runoff as well as the data scarcity in these places. The main purpose of this paper is to examine the capability of an integrated application of remote sensing data and Snowmelt Runoff Model (SRM) to simulate scheme of daily stream flow in the snow-dominated catchment, located in the North-East region of Iran. The main parameters of the model are Snow Cover Area (SCA), temperature and participation. Regarding to the lack of measured data, the input variable and parameters of the model are extracted or estimated based on accessible maps, satellite data and available meteorological and hydrological stations. The changes of snow-cover, as spatial-temporal data, which are the most effective variable in performance of SRM, are obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS) eight-day composite snow cover images. The evaluation of the model application efficiency was tested by the coefficient of determination and the volume difference, which are 0.85% and -4.6% respectively. The result depicts the relative capability of SRM though it is evident that the more accurate the estimation of model parameters, the more efficient simulation results can be obtained.

Relationship between PM_(10) and PM_(2.5) levels in high-traffic area determined using path analysis and linear regression

The objective of this study was to determine the relationship between PM10 and PM2.5 levels as related to meteorological conditions and traffic flow using both a linear regression analysis and a path analysis. The Particulate matter（PM） samples were collected from Sukhumvit road, Bangkok, Thailand, at both open（104 samples） and covered（92 samples）areas along the road. Fifteen percent of all samples were separated before the statistical models were run and used for model validation. The results from the path analysis were more elaborate than those from the linear regression, thus indicating that meteorological conditions had a direct effect on the particulate levels and that the effects of traffic flow were more variable in open areas. The model also indicated that meteorological conditions had an indirect effect and that traffic flow had a direct effect on particulate levels in covered areas. The model validation results indicated that for open areas, the R^2 values were not very different between the path analysis and the linear regression model, but that the path analysis was more accurate than the linear regression model at very low PM concentrations. At high PM concentrations, the path analysis model also had a better fit than did the linear regression, so the predictions from the path analysis model were more accurate than those from the linear regression.

Reconstruction of Lu-level cropland areas in the Northern Song Dynasty （AD976-1078）

Based on data on taxed-cropland area and on the number of households in historical documents, a probabilistic model of cropland distribution and a cropland area allocation model were designed and validated. Cropland areas for the years AD976, 997, 1066, and 1078 were estimated at the level of Lu（an administrative region of the Northern Song Dynasty）. The results indicated that（1） the cropland area of the whole study region for AD976, 997, 1066, and 1078 was about 468.27 million mu（a Chinese unit of area, with1 mu=666.7m2）, 495.53 million mu, 697.65 million mu, and 731.94 million mu, respectively. The fractional cropland area（FCA） increased from 10.7% to 16.8%, and the per capita cropland area decreased from 15.7 mu to 8.4 mu.（2） With regard to the cropland spatial pattern, the FCA of the southeast, north, and southwest regions of the Northern Song territory increased by 12.0%, 5.2%, and 1.2%, respectively. The FCA of some regions in the Yangtze River Plain increased to greater than 40%, and the FCA of the North China Plain increased to greater than 20%. However, the FCA of the southwest region（except for the Chengdu Plain） in the Northern Song territory was less than 6%.（3） There were 84.2% Lus whose absolute relative error was smaller than 20% in the mid Northern Song Dynasty. The validation results indicate that our models are reasonable and that the results of reconstruction are credible.

New method for estimating strike and dip based on structural expansion orientation for 3D geological modeling

Strike and dip are essential to the description of geological features and therefore play important roles in 3D geological modeling.Unevenly and sparsely measured orientations from geological field mapping pose problems for the geological modeling,especially for covered and deep areas.This study developed a new method for estimating strike and dip based on structural expansion orientation,which can be automatically extracted from both geological and geophysical maps or profiles.Specifically,strike and dip can be estimated by minimizing an objective function composed of the included angle between the strike and dip and the leave-one-out cross-validation strike and dip.We used angle parameterization to reduce dimensionality and proposed a quasi-gradient descent(QGD)method to rapidly obtain a near-optimal solution,improving the time-efficiency and accuracy of objective function optimization with the particle swarm method.A synthetic basin fold model was subsequently used to test the proposed method,and the results showed that the strike and dip estimates were close to the true values.Finally,the proposed method was applied to a real fold structure largely covered by Cainozoic sediments in Australia.The strikes and dips estimated by the proposed method conformed to the actual geological structures more than those of the vector interpolation method did.As expected,the results of 3D geological implicit interface modeling and the strike and dip vector field were much improved by the addition of estimated strikes and dips.

Assessment of multifunctional landscapes dynamics in the mountainous basin of the Mo River （Togo, West Africa）

In this study, historical landscape dynamics were investigated to（i） map the land use/cover types for the years 1972, 1987, 2000 and 2014;（ii） determine the types and processes of landscape dynamics; and（iii） assess the landscape fragmentation and habitat loss over time. Supervised classification of multi-temporal Landsat images was used through a pixel-based approach. Post–classification methods included systematic and random change detection, trajectories analysis and landscape fragmentation assessment. The overall accuracies（and Kappa statistics） were of 68.86%（0.63）, 91.32%（0.79）, 90.66%（0.88） and 91.88%（0.89） for 1972, 1987, 2000 and 2014, respectively. The spatio-temporal analyses indicated that forests, woodlands and savannahs dominated the landscapes during the four dates, though constant areal decreases were observed. The most important dynamic process was the decline of woodlands with an average annual net loss rate of –2%. Meanwhile, the most important land transformation occurred during the transition 2000–2014, due to anthropogenic pressures. Though the most important loss of vegetation greenness occurred in the unprotected areas, the overall analyses of change indicated a declining trend of land cover quality and an increasing landscape fragmentation. Sustainable conservation strategies should be promoted while focusing restoration attention on degraded lands and fragmented ecosystems in order to support rural livelihood and biodiversity conservation.