基于最佳用途的土地用途有偿管制机制探索

当前基于现状用途的管制存在管制方式偏行政化、管制手段无偿化导致农村集体土地收益偏向国有、非农产业和城市分配,重塑用途管制制度已显示出迫切性。本文探索基于最佳用途,通过"用途差"和"用途差"交易实现土地用途有偿管制的机制,认为通过用途有偿管制机制不仅可以保护农用地,特别是耕地资源,保障土地资源的可持续利用。而且,可激活土地资源价值,特别是有助于农用地资源资产、资本化,缩小农村、农业和农民家庭资产与收入与城镇的差距。     

驻马店极端气温分析

利用驻马店10个站气象资料,分析了极端温度的时间变化特征、高温天气与6-8月降水量之间的关系和极端晴热高温、极端湿热高温天气形成的天气背景及影响因子,确定了高温出现的前期预报指标。     

末次冰盛期-全新世东海陆坡滑塌沉积的地质年代与沉积学证据

基于东海陆坡区OT12-01孔长度为5.35 m沉积物AMS 14C测年、高分辨率粒度分析和XRF岩芯元素扫描数据,识别出了末次冰盛期(LGM)至全新世期间发生的多次滑塌事件。研究发现,OT12-01孔全新世晚期沉积层缺失,LGM至全新世期间呈现AMS 14C年龄模式频繁倒转、沉积物粒度、元素比值垂向上多处突变或"错动"等特征,保存了LGM至全新世非连续的沉积记录。OT12-01孔沉积物主要来源于低海平面时期的长江/黄河物质,OT12-01孔是由中国大陆陆源物质在东海陆架经水动力分选,细颗粒被搬运至东海陆坡后,发生多次滑塌形成。LGM时期物源供给是OT12-01孔形成滑塌沉积的重要因素,末次冰消期海平面快速上升可能是高频滑塌沉积的触发原因,而低海平面时期甲烷水合物溢出、频繁的地震和火山喷发可能是海底滑坡作用发生的诱因。     

反射波成像与纵波径向速度成像在华北油田裂缝型碳酸盐岩储层勘探开发中的联合应用

碳酸盐岩地层因成藏复杂,缝洞储层非均质性强、常规测井响应特征不明显,给勘探和有效开发带来较大难度。缝洞型储层有效性评价是深层油气勘探开发中面临的主要难题。对于储层中尺度较小的裂缝,由于地震的分辨率较低,常规测井方法探测深度较浅,难以对数十米地质构造进行准确评价。近年来发展起来的单井偶极横波反射成像技术能够有效利用低频横波的传播特点,对井旁20～30 m范围内的声反射体进行成像。纵波径向速度成像技术利用多接收阵列反演井壁1 m以内的纵波速度变化,能较好地指示储层的可改造性。偶极横波反射成像较好地发现井壁裂缝延伸以及井旁裂缝,纵波径向速度成像可反映井壁附近储层纵波速度变化,综合认为裂缝较发育,延伸较远或存在井旁隐蔽裂缝储层且井壁纵波径向速度变化较大的层段,具有较好的储层改造潜力。应用该方法对华北油田河西务潜山几口井进行处理分析,分析结果与储层改造后产液有较好的对应性,值得进一步推广应用。     

Size and spatial distribution of loess slides on the Chinese Loess Plateau

ABSTRACT

The size and spatial distribution of loess slides are important for estimating the yield of eroded materials and determining the landslide risk. While previous studies have investigated landslide size distributions, the spatial distribution pattern of landslides at different spatial scales is poorly understood. The results indicate that the loess slide distribution exhibits a power-law scaling across a range of the size distribution. The mean landslide size and size distribution in the different geomorphic types are different. The double Pareto and inverse gamma functions can coincide well with the empirical probability distribution of the loess slide areas and can quantitatively reveal the rollover location, maximum probability, and scaling exponents. The frequency of loess slides increases with mean monthly precipitation. Moreover, point distance analysis showed that > 80% of landslides are located < 3 km from other loess slides. We found that the loess slides at the two study sites (Zhidan and Luochuan County) in northern Shaanxi Province, China show a significant clustered distribution. Furthermore, analysis results of the correlated fractal dimension show that the landslides exhibit a dispersed distribution at smaller spatial scales and a clustered distribution at larger spatial scales.     

Geoarchaeological Investigations in Mesoamerica Move into the 21st Century: A Review

Over the past thirty years, geoarchaeology has moved from the fringe to mainstream status within Mesoamerican archaeological investigations. This review focuses on works published since the year 2000. Five themes are identified as central to recent studies: (1) the correlation of environmental change and cultural history; (2) anthropogenic environmental impacts; (3) ancient land cover, land use, and diet; (4) archaeological prospection; and (5) provenance studies. These themes are often interwoven in the application of complex systems approaches that allow scientists to more accurately model the intricacies of ancient human–environment interactions.     

Grid pattern recognition in road networks using the C4.5 algorithm

Pattern recognition in road networks can be used for different applications, including spatiotemporal data mining, automated map generalization, data matching of different levels of detail, and other important research topics. Grid patterns are a common pattern type. This paper proposes and implements a method for grid pattern recognition based on the idea of mesh classification through a supervised learning process. To train the classifier, training datasets are selected from worldwide city samples with different cultural, historical, and geographical environments. Meshes are subsequently labeled as composing or noncomposing grids by participants in an experiment, and the mesh measures are defined while accounting for the mesh’s individual characteristics and spatial context. The classifier is generated using the C4.5 algorithm. The accuracy of the classifier is evaluated using Kappa statistics and the overall rate of correctness. The average Kappa value is approximately 0.74, which corresponds to a total accuracy of 87.5%. Additionally, the rationality of the classifier is evaluated in an interpretation step. Two other existing grid pattern recognition methods were also tested on the datasets, and comparison results indicate that our approach is effective in identifying grid patterns in road networks.