干旱区内陆河流域农户生态补偿支付意愿的空间异质性分析

深入开展支付意愿的空间差异和空间效应分析, 对于分区定策、 精准实施生态治理工程、 提高生态补偿实践绩效、 提升治理与保护效果等方面, 有着重要的现实指导意义。在确定影响流域农户支付意愿的主要因素的基础上, 借助多分类Logistic模型分析各因素对农户支付意愿的影响作用, 并通过引入通达距离、 距河道距离分别比较流域农户支付意愿的空间效应, 得到的主要结论包括： 在不考虑距离因素的情况下, 教育程度、 农户类型对于农户支付意愿的影响显著; 在考虑距离因素的情况下, 受教育程度对支付意愿的影响存在“脱钩”现象, 模型3模拟结果显示, 高中群体处于更高支付意愿的发生比为1.044, 而大专群体处于更高支付意愿水平的发生比仅为0.363, 即支付意愿并不会伴随受教育程度的提高而增强; 通达距离与支付意愿表现为先负相关（“距离衰减”现象）、 之后呈正相关（“距离递增”现象）的关系; 距河道距离远近对流域农户的支付意愿呈现明显的“距离衰减”规律。     

基于流动单元的多油层储层参数计算和评价方法研究

针对英东地区含油储层井段长、非均质性严重、传统渗透率模型无法满足储层评价精度要求这一矛盾,在综合试油、MDT资料,深入分析油、气、水、干层测井响应特征的基础上,利用传统的流动带指数按照“单元化分类评价”的思路分地层对储层渗透率进行表征计算,并在此基础上建立电性参数下渗透率流动带指数计算模型。工区实际生产资料评价结果表明,利用流动带指数渗透率模型计算出的渗透率相对误差低于25%,绝对误差也能控制在半个数量级以内,其结果有效地提高了非均质储层渗透率预测精度,符合储层实际情况,能够满足油藏描述及生产的需要,对该地区后续长井段复杂储层非均质性研究和后期层间吸水矛盾治理具有一定的指导意义。     

Leaf to canopy upscaling approach affects the estimation of canopy traits

In remote sensing applications, leaf traits are often upscaled to canopy level using sunlit leaf samples collected from the upper canopy. The implicit assumption is that the top of canopy foliage material dominates canopy reflectance and the variability in leaf traits across the canopy is very small. However, the effect of different approaches of upscaling leaf traits to canopy level on model performance and estimation accuracy remains poorly understood. This is especially important in short or sparse canopies where foliage material from the lower canopy potentially contributes to the canopy reflectance. The principal aim of this study is to examine the effect of different approaches when upscaling leaf traits to canopy level on model performance and estimation accuracy using spectral measurements (in-situ canopy hyperspectral and simulated Sentinel-2 data) in short woody vegetation. To achieve this, we measured foliar nitrogen (N), leaf mass per area (LMA), foliar chlorophyll and carbon together with leaf area index (LAI) at three vertical canopy layers (lower, middle and upper) along the plant stem in a controlled laboratory environment. We then upscaled the leaf traits to canopy level by multiplying leaf traits by LAI based on different combinations of the three canopy layers. Concurrently, in-situ canopy reflectance was measured using an ASD FieldSpec-3 Pro FR spectrometer, and the canopy traits were related to in-situ spectral measurements using partial least square regression (PLSR). The PLSR models were cross-validated based on repeated k-fold, and the normalized root mean square errors (nRMSE_cv) obtained from each upscaling approach were compared using one-way analysis of variance (ANOVA) followed by Tukey’s post hoc test. Results of the study showed that leaf-to-canopy upscaling approaches that consider the contribution of leaf traits from the exposed upper canopy layer together with the shaded middle canopy layer yield significantly (p < 0.05) lower error (nRMSE_cv < 0.2 for canopy N, LMA and carbon) as well as high explained variance (R² > 0.71) for both in-situ hyperspectral and simulated Sentinel-2 data. The widely-used upscaling approach that considers only leaf traits from the upper illuminated canopy layer yielded a relatively high error (nRMSE_cv>0.2) and lower explained variance (R² < 0.71) for canopy N, LMA and carbon. In contrast, canopy chlorophyll upscaled based on leaf samples collected from the upper canopy and total canopy LAI exhibited a more accurate relationship with spectral measurements compared with other upscaling approaches. Results of this study demonstrate that leaf to canopy upscaling approaches have a profound effect on canopy traits estimation for both in-situ hyperspectral measurements and simulated Sentinel-2 data in short woody vegetation. These findings have implications for field sampling protocols of leaf traits measurement as well as upscaling leaf traits to canopy level especially in short and less foliated vegetation where leaves from the lower canopy contribute to the canopy reflectance.     

Charging of oil fields surrounding the Shaleitian uplift from multiple source rock intervals and generative kitchens,Bohai Bay basin,China

This paper discusses origin and charging directions of oil fields on the Shaleitian Uplift, Bohai Bay basin. The Shaleitian Uplift is a footwall uplift surrounded by three sags containing mature source rocks. The origins of the four oil fields on the Shaleitian Uplift, both in terms of source rock intervals and in terms of generative kitchens, were studied using biomarker distributions for 61 source rock samples and 27 oil samples. Hierarchical cluster analysis using 12 parameters known to be effective indicators of organic matter input and/or depositional conditions allowed the identification of six oil types or classes. These six oil classes could then be linked to three distinct source rock intervals ranging in age from 43.0 Ma to 30.3 Ma. The third member (43.0–38.0 Ma in age) and first member (35.8–32.8 Ma) of the Eocene Shahejie Formation, and the third member of the Oligocene Dongying Formation (32.8–30.3 Ma) each sourced one class of oil. The other three classes represent mixtures of oil generated from multiple source rock intervals. Traps on the Shaleitian Uplift were charged in the east by oil generated from the Eocene Shahejie Formation in the Bozhong Sag, in the southeast by oil generated from the Eocene Shahejie and then Oligocene Dongying formations in the southwestern part of the Bozhong Sag and/or in the eastern part of the Shanan Sag, and in the southwest by oil generated from the Eocene Shahejie Formation in the western part of the Shanan Sag. The estimated migration distances range from less than 5 km to about 20 km. The compositional heterogeneity within fields and multiple-parameter comparisons between oils from nearby wells in different fields have proven to be a powerful tool to determine the in-filling histories of oil fields in cases where multiple source rock intervals and multiple generative kitchens exist.     

基于个体移动轨迹的多中心城市引力模型验证

长期以来由于规模变量、距离衰减系数取值缺乏依据,引力模型在城市研究中的应用容易受到质疑,加之中国城市的多中心化使得模型应用的外部条件发生改变,模型验证工作的必要性再次显现。本文使用2015年移动通信用户的个体移动轨迹数据,使用Huff当年的验证方法,通过变量检验、参数校正两个步骤,验证Huff的引力模型。研究发现：① 城市内部商业中心和就业中心的吸引力与中心的规模呈正比,与距中心的距离呈反比,符合引力模型规律。② 在上海中心城区空间尺度、200 m网格空间单元下,商业中心吸引力的距离衰减系数平均值为2.5,就业中心吸引力的距离衰减系数平均值为3.0,表明居民就业通勤对距离更加敏感,距离衰减比购物出行更加显著。③ 经变量检验、参数校正后的引力模型可用于对商业中心、就业中心优化调整后的势力范围进行预测,预测准确率可分别达到78.5%和71.9%。就业中心势力范围预测准确性略低,这是由于就业中心吸引力衰减除受距离影响外,还受家庭、房价等因素影响,会对预测结果产生扰动。最后,研究还证实了距离衰减系数存在空间分层异质性：距离衰减系数不是唯一值,受道路可达性、至就业（商业）中心距离、至地铁站距离、人口密度影响,不同地区的距离衰减系数存在较显著差异。     

面向转型升级发展的开发区主导产业分布及其空间集聚研究

国际与国内发展环境双重变革下,开发区“二次创业”乃至“三次创业”的呼声不断高涨。为此,有必要重新审视开发区的主导产业分布、集聚及其影响因素,以促进其转型升级发展。以国家级经济产业开发区为例,在系统梳理中国219家国家级经开区主导产业基础上,采用核密度分析法与Ripley's K函数可视化其空间分布格局与空间集聚状态;并面向转型发展与产业升级,采用GWR方法探讨影响技术密集型产业分布与集聚的主要因素及其空间异质性。研究表明：① 国家级经开区主导产业以制造业为主,产业空间集聚存在尺度分异与空间衰减特征。② 从产业组织来看,以单一/双要素密集的主导产业组织模式为主。③ 开发区自身条件对技术密集型产业集聚的促进效果相对有限;城市对开发区产业集聚的支撑作用与城市固定资产投资强度存在一定的反向联系;开发区参与全球化的深度,尤其是利用国际资本的能力与技术密集型产业集聚具有较强关联性。面向转型升级发展,开发区自身应持续改革,主动探索;同时要处理好两个“资本关系”,即开发区与所在城市固定资产投资以及与国际资本的关系。     

2014—2019年中国秸秆焚烧火点的地理特征分析

客观、精细地刻画秸秆火点的地理空间分布特征,对科学引导作物秸秆焚烧和提高行政监管效率具有重要意义。基于2014—2019年中国区域内Satsee-Fire火点数据集和地形、社会经济数据建立的中国秸秆火点数据库和自然-人口-经济数据库,本研究采用GIS分析工具和数理统计方法,剖析了中国秸秆火点在地形、公共交通和人口-经济三方面7个因子之下的空间格局特征,结果表明：① 秸秆焚烧现象集中发生在高程低于250 m、坡度低于8°的区域,而位于北向坡和南向坡的秸秆火点数分别占总数的42.65%、37.36%。② 秸秆焚烧现象在机场和铁路禁燃区内呈不同的空间格局特征。距机场愈远秸秆焚烧行为愈普遍,机场禁燃区的秸秆焚烧有近六成发生在距机场11~15 km处;而铁路禁燃区内的秸秆火点分布较为均衡,总体呈内部圈层较外部区域略微密集态势,空间上火点密度整体随纬度增加而逐步增加,山西、内蒙古、河北及东三省铁路禁燃区火点数占总数的76.88%。③ 近七成的秸秆火点发生在人口密度低于250人/km2的县域,而58.17%的秸秆火点发生在年GDP低于100亿元的县域;秸秆焚烧现象与县域人口密度、GDP水平存在负相关关系,即县域人口密度愈大、县域经济愈发达,发生秸秆焚烧的现象愈为鲜见。     

顾及空间异质性的大范围地面沉降时空预测

大速率、不均匀的地面沉降已经威胁到人类的生产活动,高精度的沉降预测结果对于地质灾害的精准防控具有重要意义。为掌握地面沉降的演化规律,利用现场观测数据或InSAR数据开展了多项预测研究。然而,由于空间异质性的存在,大范围地面沉降的准确预测仍然是一项挑战。在这项研究中,从数据驱动的角度提出了一种顾及空间异质性的大范围地面沉降时空预测方法 STLSTM (Spatio-temporal Long Short-Term Memory)。首先,通过聚类识别地理空间中的均质子区;然后,在每个子区中,一个特别的长短期记忆LSTM (Long ShortTerm Memory)网络被用来捕捉局部位置的非线性特征;最后,利用预训练的网络对未来时刻的地面沉降进行定量预测。在实验部分,哨兵1号影像数据被用来比较STLSTM与其他8种基准方法的性能,利用空间统计指标分析了模型的有效性。结果表明,STLSTM在152 s内达到了最高的预测精度（71.4%）,且能够有效弱化空间异质性对大区域沉降预测任务的影响。总之,这项研究将空间异质性处理策略融合到深度学习模型中,实现了高精度、高时效的大范围地面沉降时空预测。     

大港油田官104断块储层非均质性研究

利用研究区测井二次解释的成果,对储层非均质性特征和在生产中的反映进行了分析,并结合高分辨率层序地层学理论,总结储层非均质性形成的控制因素.针对大港油田官104断块开发过程中层间矛盾突出、单层突进严重的问题,重点分析了研究区储层层间非均质性.通过对研究区的分析可知,地层旋回性、沉积微相和隔层的分布是主要的储层非均质控制因素.并且隔层和沉积相的分布规律受沉积旋回的控制.因此,层间非均质性受控于基准面旋回变化造成的A/S值的变化,A/S值小非均质性弱,A/S值大非均质性强.应用产液、吸水剖面资料验证储层非均质性,并提出下一步挖潜和措施的方向,指导油田的生产.