Gold Resources Potential Assessment in Eastern Kunlun Mountains of China Combining Weights-of-evidence Model with GIS Spatial Analysis Technique

Resources potential assessment is one of the fields in geosciences,which is able to take great advantage of GIS technology as a substitution of traditional working methods.The gold resources potential in the eastern Kunlun Mountains,Qinghai Province,China was assessed by combining weights-of-evidence model with GIS spatial analysis technique.All the data sets used in this paper were derived from an established multi-source geological spatial database,which contains geological,geophysical,geochemical and remote sensing data.Three multi-class variables,i.e.,structural intersection,Indosinian k-feldspar granite and regional fault,were used in proximity analysis to examine their spatial association with known gold deposits.A prospectivity map was produced by weights-of-evidence model based on seven binary evidential maps,all of which had passed a conditional independence test.The study area was divided into three target zones of high potential,moderate potential and low potential areas,among which high potential areas and moderate potential areas accounted for 20% of the total area and contained 32 of the 43 gold deposits.The results show that the gold resources potential assessment in the eastern Kunlun Mountains has a higher precision.

Modeling visible and near-infrared snow surface reflectance-simulation and validation

Retrieving snow surface reflectance is difficult in optical remote sensing. Hence, this letter evaluates five surface reflectance models, including the Ross-Li, Roujean, Walthall, modified Rahman and Staylor models, in terms of their capacities to capture snow reflectance signatures using ground measurements in Antarctica. The biases of all the models are less than 0.0003 in both visible and near-infrared regions. Moreover, with the exception of the Staylor model, all models have root-mean-square errors of around 0.02, indicating that they can simulate the reflectance magnitude well. The R2 performances of the Ross-Li and Roujean models are higher than those of the others, indicating that these two models can capture the angle distribution of snow surface reflectance better.

Temporal and spatial analysis of changes in snow cover in western Sichuan based on MODIS images

We developed a method for analyzing the change in snow cover using MODIS imagery.The method was applied to images of western Sichuan Province,China taken between 2002 and 2008.The model for extracting data on snow cover from MODIS images was created by spectral analysis.The multi-temporal snow layers were used to evaluate the temporal and spatial change in the area under snow cover between 2002 and 2008 using overlay and statistical analysis in ARCGIS.The majority(60.4%) of western Sichuan was rarely covered by snow and only 0.3% was covered by perennial snow in 2002.Snow cover was pri-marily distributed in Garzê and Aba.The area under snow cover was significantly and negatively correlated with the average monthly temperature and rainfall in 2002.The largest area under snow cover was measured in 2006 and the smallest was in 2007.Similarly,the area of snowmelt was the highest in 2006 and lowest in 2007.In general,the elevation of the snow line in-creased throughout the period 2002-2008;however,the elevation decreased in some years.Our results provide an important insight into the distribution of snow in this region,and may be useful for climate modeling and predicting the availability of water resources and the occurrence of floods and droughts.

A simple data assimilation method for improving the MODIS LAI time-series data products based on the object analysis and gradient inverse weighted filter

A simple data assimilation method for improving estimation of moderate resolution imaging spectroradiometer （MODIS） leaf area index （LAI） time-series data products based on the gradient inverse weighted filter and object analysis is proposed. The properties and quality control （QC） of MODIS LAI data products are introduced. Also, the gradient inverse weighted filter and object analysis are analyzed. An experiment based on the simple data assimilation method is performed using MODIS LAI data sets from 2000 to 2005 of Guizhou Province in China.

A Pan-sharpening method appropriate to vegetation applications

An improved Pan-sharpening algorithm appropriate to vegetation applications is proposed to fuse a set of IKONOS panchromatic （PAN） and multispectral image （MSI） data. The normalized difference vegetation index （NDVI） is introduced to evaluate the quality of fusion products. Compared with other methods such as principal component analysis （PCA）, wavelet transform （WT）, and curvelet transform （CT）, this algorithm has a better trade-off between keeping the spatial and spectral information. The NDVI performances indicate that the fusion product of this method is more suitable for vegetation applications than the other methods.