Zhao X.-M.,Binzhou University |
Zhao X.-M.,Shandong Agricultural University |
Lu C.-Y.,China Land Surveying and Planning Institute |
Liu Q.,Qingdao Agricultural University |
Zhu X.-C.,Shandong Agricultural University
Guang Pu Xue Yu Guang Pu Fen Xi/Spectroscopy and Spectral Analysis | Year: 2014
Aqua regia digestion, double channels-atomic fluorescence spectrometry method was used to determine the concentrations of As and Hg in orchard soils of Qixia City - the main apple production area of Shandong province. Validate the detection limitation, accuracy and precision of the method were validated, the spatial distribution was analyzed, and the characteristics of As and Hg pollution in Qixia orchard soils were assessed. The results showed that the range of As concentration in Qixia soils is between 2.79 and 20.93 mg·kg-1, the average concentration is 10.59 mg·kg-1, the range of Hg concentration in Qixia soil is between 0.01 and 0.79 mg·kg-1, the average concentration is 0.12 mg·kg-1. The variation of As concentration in soils is small, whereas that of Hg concentration is large. Frequency distribution graphics of As and Hg showed that the concentration of As in soils is according with the normal distribution approximately and the concentrations are mostly between 7 and 15 mg·kg-1, the concentration of Hg in soil isn't according with the normal distribution and the concentrations are mostly between 0.03 and 0.21 mg·kg-1. The correlations between the concentrations of As or Hg in soils and the nutrient are not significant and there is no significant correlation even between As and Hg. Based on the environmental technical terms for green food production area, the As concentration in orchard soil of Qixia City is at clean level, but there are 4.76% of sample points with Hg pollution index exceeding 1, and this should be attracted the attention of the administrators.
Jin X.,Nanjing University |
Ding N.,Nanjing University |
Zhang Z.,Nanjing University |
Zhang Z.,China Land Surveying and Planning Institute |
And 2 more authors.
Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering | Year: 2012
In order to research the effect of inter-provincial distribution scheme of new construction land compensation fee by the central government (CGNCOCF) on land consolidation under different goals of fund allocation, based on analysis of the allocation and using objective of new construction land compensation fee (NCOCF), the inter-provincial distribution scheme of new construction land compensation fee by the central government was optimized. A BP neural network model was built to reflect the relationship between the distribution amount of CGNCOCF and dynamic change of land consolidation efficiency, and land consolidation expected efficiency under the different allocation scheme of CGNCOCF was simulated. The results showed that the related factors had significant effect on the allocation efficiency of CGNCOCF at different allocation goals, and selection of the factors and determination of weights should be set up flexibly according to the different allocation targets. The main conclusions of this paper were that at the same distribution target of CPNCOCF, the social benefit was the highest among the land consolidation efficiencies that the CGNCOCF generated, economic benefit was the higher, and the ecological benefit was the lowest. The excepted benefits of allocation scheme of CGNCOCF arranged from high to low as: the comprehensive efficiency goals, land use efficiency targets, and cultivated land protection objective, resource allocation and fair target. The distribution of the fee under comprehensive efficiency targets was the optimal scheme. The land consolidation benefits of each province were different according to different distribution target of CGNCOCF and benefits of land consolidation target, but overall the growth ratio of benefit value was higher compared to reality after optimizing, which showed that the land consolidation benefits increased after the optimization of CGNCOCF.
Chen Y.,Hohai University |
He X.,Hohai University |
Wang J.,China Land Surveying and Planning Institute |
Xiao R.,Hohai University
Remote Sensing | Year: 2014
The purpose of this study was to examine how different polarimetric parameters and an object-based approach influence the classification results of various land use/land cover types using fully polarimetric ALOS PALSAR data over coastal wetlands in Yancheng, China. To verify the efficiency of the proposed method, five other classifications (the Wishart supervised classification, the proposed method without polarimetric parameters, the proposed method without an object-based analysis, the proposed method without textural and geometric information and the proposed method using the nearest-neighbor classifier) were applied for comparison. The results indicated that some polarimetric parameters, such as Shannon entropy, Krogager_Kd, Alpha, HAAlpha_T11, VanZyl3_Vol, Derd, Barnes2_T33, polarization fraction, Barnes1_T33, Neuman_delta_mod and entropy, greatly improved the classification results. The shape index was a useful feature in distinguishing fish ponds and rivers. The distance to the sea can be regarded as an important factor in reducing the confusion between herbaceous wetland vegetation and grasslands. Furthermore, the decision tree algorithm increased the overall accuracy by 6.8% compared with the nearest neighbor classifier. This research demonstrated that different polarimetric parameters and the object-based approach significantly improved the performance of land cover classification in coastal wetlands using ALOS PALSAR data. © 2014 by the authors.
Chen Y.,Hohai University |
He X.,Hohai University |
Wang J.,China Land Surveying and Planning Institute
Arabian Journal of Geosciences | Year: 2015
This study was initiated to classify Jiangsu coastal wetlands, which are situated on the north bank of the Yangtze River in eastern China, using fully polarimetric synthetic aperture radar (PolSAR) data with an improved classification scheme. First, Cloude-Pottier decomposition was completed to obtain polarimetric parameters. Then, the data were classified into 24 clusters using the decomposed parameters. Third, the agglomerative hierarchical-clustering algorithm was applied to merge the clusters into seven classes; the outcomes were regarded as initial values in the subsequent processing. Finally, the improved fuzzy C-means (FCM) algorithm, in which a fuzzy factor was introduced and the traditional Euclidean distance was replaced by the Wishart distance, was used to adjust the land cover boundaries. The experiment results revealed that for similar scattering mechanisms with different scattering intensities, the proposed method presented a satisfactory performance, with an overall accuracy of 86.93 %. The accuracies of seven land cover types were much higher and the boundaries were more clear when using the proposed method compared with two other methods. The study demonstrated the potential of using L-band fully polarimetric SAR data in coastal wetland classification. © 2015 Saudi Society for Geosciences
Wang Z.,China Land Surveying and Planning Institute |
Liu S.,China Land Surveying and Planning Institute |
You S.,China Land Surveying and Planning Institute |
Huang X.,Wuhan University
IEEE Geoscience and Remote Sensing Letters | Year: 2010
The extraction of spatial details is crucial for fusion quality. An efficient way is to exploit the difference between high-resolution panchromatic (Pan) images and low-resolution Pan (LRP), which is to be simulated by weighted average value from low-resolution multispectral images. To obtain the weighting coefficients with multivariate linear regression, three issues were discussed, and corresponding solutions were proposed in this letter. The proposed method consists of separating high-frequency pixels from low-frequency pixels using support vector machine and selecting observations that are evenly distributed by a bucketing technique and forcing coefficients to be sound physically by constrained least squares. Validation experiments are undertaken using three IKONOS data sets, and fusion results are compared against four popular methods. The results show that the proposed method can simulate LRP soundly and therefore achieve a better fusion quality. © 2010 IEEE.