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.     

Modelling the effect of changing precipitation inputs on deep soil water utilization

Forests in the Southeastern United States are predicted to experience future changes in seasonal patterns of precipitation inputs as well as more variable precipitation events. These climate change‐induced alterations could increase drought and lower soil water availability. Drought could alter rooting patterns and increase the importance of deep roots that access subsurface water resources. To address plant response to drought in both deep rooting and soil water utilization as well as soil drainage, we utilize a throughfall reduction experiment in a loblolly pine plantation of the Southeastern United States to calibrate and validate a hydrological model. The model was accurately calibrated against field measured soil moisture data under ambient rainfall and validated using 30% throughfall reduction data. Using this model, we then tested these scenarios: (a) evenly reduced precipitation; (b) less precipitation in summer, more in winter; (c) same total amount of precipitation with less frequent but heavier storms; and (d) shallower rooting depth under the above 3 scenarios. When less precipitation was received, drainage decreased proportionally much faster than evapotranspiration implying plants will acquire water first to the detriment of drainage. When precipitation was reduced by more than 30%, plants relied on stored soil water to satisfy evapotranspiration suggesting 30% may be a threshold that if sustained over the long term would deplete plant available soil water. Under the third scenario, evapotranspiration and drainage decreased, whereas surface run‐off increased. Changes in root biomass measured before and 4 years after the throughfall reduction experiment were not detected among treatments. Model simulations, however, indicated gains in evapotranspiration with deeper roots under evenly reduced precipitation and seasonal precipitation redistribution scenarios but not when precipitation frequency was adjusted. Deep soil and deep rooting can provide an important buffer capacity when precipitation alone cannot satisfy the evapotranspirational demand of forests. How this buffering capacity will persist in the face of changing precipitation inputs, however, will depend less on seasonal redistribution than on the magnitude of reductions and changes in rainfall frequency.     

A-FPN算法及其在遥感图像船舶检测中的应用

光学遥感图像船舶检测主要面临两个挑战:光学遥感图像背景复杂,船舶检测易受海浪、云雾及陆地建筑等多方面干扰;遥感图像分辨率低,船舶目标小,对于其分类与定位带来很大困难;针对上述问题,在FPN的基础上,提出一种融入显著性特征的卷积神经网络模型A-FPN (Attention-Based Feature Pyramid Networks)。首先,利用卷积提取图像特征金字塔;然后,利用顶层金字塔逐级构建显著特征层,抑制背景信息,通过金字塔顶层的细粒度特征提高浅层特征的表达能力,构建自上而下的多级显著特征映射结构;最后利用Softmax分类器进行多层级船舶检测。A-FPN模型利用显著性机制引导不同感受下的特征进行融合,提高了模型的分辨能力,对遥感图像处理领域具有重要应用价值。实验阶段,利用公开的遥感目标检测数据集NWPU VHR-10中的船舶样本进行测试,准确率为92.8%,表明A-FPN模型适用于遥感图像船舶检测。     

非等间距GM(1,1)模型的总体最小二乘算法及其病态问题

在非等间距GM(1,1)模型中，系数矩阵中有无误差的常数项和有误差的随机项，并且系数矩阵与观测向量误差同源，即系数矩阵与观测向量中有相同的元素存在，这些相同元素应该有相同的改正数，为此本文推导了一种适合非等间距GM(1,1)模型求解的总体最小二乘算法。同时，考虑到非等间距GM(1,1)模型中存在病态问题时影响总体最小二乘计算结果的稳定性，提出对系数矩阵常数列乘以某一常数的方法，以改善病态问题。     

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。     

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.     

资源三号和天绘一号卫星影像无控联合平差精度分析

近年来国产卫星传感器类型日益丰富，使用自主可控的国产卫星影像进行生产和研究的需求越来越大，多源国产卫星影像联合平差的精度分析显得尤为重要。本文针对在立体测图生产中，资源三号卫星影像在时相较旧、噪声较大、云覆盖和摄影漏洞等特殊困难的条件下，利用天绘一号卫星影像进行补漏生产的情况，最终分析并验证了两者无控联合平差的可行性和成果精度。