黄淮海平原耕地集约利用时空差异及其影响因素研究（英文）

This study developed a comprehensive system to evaluate the intensity of cropland use and evolution of cropland use in the Huang-Huai-Hai Plain.Delphi-entropy methods were adopted to determine the weight of the index,and the Geo Detector model was established to explore the influencing factors.The results are summarized as follows:(1) The intensity of inputs,degree of utilization,and production increased continuously,but the intensity of continuous conditions experienced an overall decline followed by a rebound towards the end of the study period.The number of counties with high and moderately high intensity increased by 56.8% and 14.6%,respectively,from 1996 to 2011.The number of counties with moderately low and low intensity declined by 35.9 % and 11.9 %,respectively.Areas with significant increases in intensity were mainly distributed in northeast Hebei Province,northwest Shandong Province,and north Jiangsu Province.The intensity is high in northern Jiangsu and Anhui;the output effect remained above moderate intensity mainly near Beijing,Tianjin,Tangshan,and counties in the suburbs of Shijiazhuang.(2) Natural disasters,elevation,slope,and road networks were the main factors influencing the intensity of cropland use in this region,with influence values of 0.158,0.143,0.129,and 0.054,respectively.Areas with moderately high and high levels of intensity were distributed in low-lying areas.Uneven distribution of precipitation,seasonal drought,and flood disasters can directly affect the stability index of croplands and reduce the intensity of cropland use.Developed road networks are associated with moderately high intensity.Our results suggest recommendations such as promoting agricultural intensification and large-scale management,promoting the construction of road networks,improving early warning systems for drought and flood disasters,and promoting moderate and intensive use of arable land,and focusing on restoration and sustainable use of cropland.     

顾及最大绝对误差的频率域矢量数据压缩算法

针对传统的基于离散余弦变换（discrete cosine transform,DCT）的矢量数据压缩算法局部误差较大和计算复杂度高的问题,提出了一种顾及矢量数据最大绝对误差的快速近似DCT压缩方法。首先,结合现有矢量数据拓扑关系,构造矢量数据块;其次,根据近似DCT变换正交性的特点,计算约定矩阵的最优化解,将计算复杂度最低的解设为近似DCT变换的转换矩阵;最后,结合矢量数据近似DCT变换和精确DCT变换的总能量差,计算重构数据的最大绝对误差,对超过误差阈值的数据进行三次样条插值,最大限度地保证矢量数据精度。实验结果表明,该方法计算复杂度较低,压缩速度快,在降低压缩率的同时,能较好地保持空间数据的拓扑关系和数据精度。     

一种分层压缩的高精度矢量地图加密方法

传统的矢量数据加密算法主要是直接对数据加密,忽略了矢量数据的结构与冗余。针对此类问题,提出利用分层压缩的矢量数据加密方法。首先,结合矢量数据结构特点,使用最小编码单元对线目标和面目标进行SEC压缩;其次,通过随机置乱MCOs的平均点距离对矢量数据位置加密;最后,使用XOR操作对MCOs顶点方向进行循环加密,达到加密矢量数据几何形状的目的。实验结果表明,该方法明显降低了加密过程计算量,与普通加密算法相比,在保证矢量数据精度和安全性的情况下,提高矢量数据加密效率。