The Natural Resource Management Planning Portal: Perspectives for NRM Planning and Reporting

Natural Resource Management (NRM) is often conducted as a partnership between government and citizens. In Australia, government agencies formulate policy and fund implementation that may be delivered on-ground by community groups (such as Landcare). Since the late 1980s, over AUS$8b of Commonwealth investment has been made in NRM. However, quantitative evidence of environmental improvements is lacking. The NRM Planning Portal has been developed to (1) provide an online spatial information system for sharing Landcare and agency data; and (2) to facilitate NRM priority setting at local and regional planning scales. While the project successfully federates Landcare NRM activity data, challenges included (1) unstructured, non-standardized data, meaning that quantitative reporting against strategic objectives is not currently possible, and (2) a lack of common understanding about the value proposition for adopting the portal approach. Demonstrating the benefit of technology adoption is a key lesson for digital NRM planning.     

Water quality data for Fall Creek,New York,USA: 1972–1995

The 33 086 ha mixed land use Fall Creek watershed in upstate New York is part of the Great Lakes drainage system. Results from more than 3500 water samples are available in a data set that compiles flow data and measurements of various water quality analytes collected between 1972 and 1995 in all seasons and under all flow regimes in Fall Creek and its tributaries. Data is freely accessible at https://ecommons.cornell.edu/handle/1813/8148 and includes measurements of suspended solids, pH, alkalinity, calcium, magnesium, potassium, sodium, chloride, nitrate nitrogen (NO3-N), sulphate sulphur (SO4-S), phosphorus (P) fractions molybdate reactive P (MRP) and total dissolved P (TDP), percent P in sediment, and ammonium nitrogen (NH4-N). Methods, sub-watershed areas, and coordinates for sampling sites are also included. The work represented in this data set has made important scientific contributions to understanding of hydrological and biogeochemical processes that influence loading in mixed use watersheds and that have an impact on algal productivity in receiving water bodies. In addition, the work has been foundational for important regulatory and management decisions in the region.     

“一带一路”背景下的中国与巴基斯坦的贸易关系演进及其影响因素

中巴经济走廊是“一带一路”6大经济走廊之一,而贸易畅通是“一带一路”建设的核心环节。研究中巴贸易关系演变及其影响因素、分析其贸易潜力,对推进“一带一路”建设具有重要的示范作用。论文从中巴贸易发展态势、商品结构、空间格局等方面揭示中巴贸易关系,运用随机前沿引力模型分析中巴贸易关系的主要影响因素、并探析其发展潜力,以期为推进中巴经济走廊建设提供科学支撑。研究发现：① 中巴贸易发展迅速,中对巴贸易顺差持续扩大;中国主要出口机械及电气设备等资本密集型产品,主要进口纺织原料及纺织制品等初级产品和劳动密集型产品。② 中国各省份与巴基斯坦的贸易合作存在明显的空间差异,东部沿海省份与巴贸易联系较紧密,西部各省份除新疆外与巴基斯坦贸易额均较小。③ 中国多数省份对巴贸易商品结构发生显著变动,其中,新疆、山东等进出口商品结构多元的省份的变动相对较小。④ 中国各省份的经济发展水平和市场规模对中巴贸易拉动较强;海运距离对中巴贸易规模有显著的负向影响;领土接壤为中巴组织边境贸易提供了良好条件;铁路和水运口岸的建设对中巴贸易具有积极影响。⑤ 中国各省份与巴基斯坦均有较大贸易潜力,内蒙古、云南、广西、陕西等省份的合作潜力更明显。     

湖南省似大地水准面2017模型及精度分析

利用近7万个湖南及邻近省份重力观测数据、502个GNSS/水准控制点及数字高程模型，以EIGEN-6C4全球重力场模型作参考重力场，采用顾及地球曲率影响的各类地形质量位及引力的第二类Helmert凝集法严密算法，利用高分辨率地形数据恢复甚短波扰动重力场，确定空间分辨率2′×2′的高精度湖南省似大地水准面模型（HNGG2017）。经外部检核，模型整体精度均优于±0.022 m。与历史模型相比，新模型在湖南北部常德汉寿、西南部永州江永等地区精度得到显著改善。     

基于灯光数据的京津冀城市多标度异速分析

城镇体系的时空演化是一个复杂的动力学过程,具有无尺度性,其特征可以采用异速标度指数定量描述。论文以京津冀为例,基于1992—2013年夜间灯光数据的校正结果,提取城镇夜间灯光信息,采用多标度异速分析方法,分析京津冀城镇体系的相对发展特征及其空间分异格局。研究发现：①京津冀大城市的增长空间局限日益显著。虽然大城市如京津唐的绝对发展水平高,但接近环境承载量的极限,22 a间增长快速的是大城市交接地带的小城市(如三河、迁安、廊坊等)。②相对增长速度快的城市从东北到西南呈现带状分布——政府选择发展的“雄安新区”就在这个轴带上。由此可以得出两个结论：其一,京津冀城市演化的趋势相对均衡化,空间结构异质性逐步减弱,整个城镇体系的发展趋于相对平衡状态;其二,大、小城市“两极”贯通或许是增强城镇体系功能的有效途径。京津冀的空间格局优化不能仅仅考虑主要的、规模大的中心城市,而应该基于等级结构协调整个城镇网络体系。     

自然资源一体化政务服务系统及数据融合建设——以南京为例

自然资源部制定的信息化建设总体方案中，要求构建“互联网+自然资源政务服务”应用体系，实现“服务事项标准统一、整体联动、业务协同，自然资源政务服务和共享开放能力全面提高”。一体化政务服务系统作为政务服务应用体系的重点建设内容，也是落实自然资源管理“两统一”职责的重要支撑，如何整合各类数据资源、发挥系统作用，成为亟待研究的问题。本文在分析自然资源业务管理需求后，提出了一体化政务服务系统及数据融合的建设思路。     

大别山及其周边现今垂直形变研究

基于1980年、2005年和2015年3期区域精密水准网观测资料，利用线性动态平差模型计算获取大别山地区水准网长期垂直运动速度场图像。研究发现，淮河平原地表下沉较为严重，大别山呈现弱隆升趋势运动，长江谷地边缘地区较大别山区呈现明显的隆升运动。跨郯庐断裂带水准剖面结果显示，垂直运动与地形呈负相关和弱相关。     

基于云存储技术的海岛信息管理和 展示平台设计与实现

随着海岛遥感影像数据的不断积累,传统数据存储管理方法越来越难以满足需求。针对上述问题,利用云存储技术对海岛影像数据进行分块组织,建立分布式海岛影像数据集,并在优化数据存储的同时,设计了一套海岛信息多形式展示平台。实现了信息检索、数据传输与审核、分析评价、成果展示和共享等功能。     

Developing constitutive models from EPR‐based self‐learning finite element analysis

A constitutive model that captures the material behavior under a wide range of loading conditions is essential for simulating complex boundary value problems. In recent years, some attempts have been made to develop constitutive models for finite element analysis using self‐learning simulation (SelfSim). Self‐learning simulation is an inverse analysis technique that extracts material behavior from some boundary measurements (eg, load and displacement). In the heart of the self‐learning framework is a neural network which is used to train and develop a constitutive model that represents the material behavior. It is generally known that neural networks suffer from a number of drawbacks. This paper utilizes evolutionary polynomial regression (EPR) in the framework of SelfSim within an automation process which is coded in Matlab environment. EPR is a hybrid data mining technique that uses a combination of a genetic algorithm and the least square method to search for mathematical equations to represent the behavior of a system. Two strategies of material modeling have been considered in the SelfSim‐based finite element analysis. These include a total stress‐strain strategy applied to analysis of a truss structure using synthetic measurement data and an incremental stress‐strain strategy applied to simulation of triaxial tests using experimental data. The results show that effective and accurate constitutive models can be developed from the proposed EPR‐based self‐learning finite element method. The EPR‐based self‐learning FEM can provide accurate predictions to engineering problems. The main advantages of using EPR over neural network are highlighted.     

基于MODIS数据的湖北省地级以上城市城区地表温度变化分析

基于MODIS数据,以湖北省地级以上城市城区为研究对象,通过对湖北省13个地级以上城市城区边界矢量数据与地表温度因子进行套合处理,采用叠置分析方法对2000、2015、2017年湖北省地级以上城市城区的地表温度进行统计,并分析城镇化建设对城区地表温度产生的影响。