区域可持续发展能力的能值与(火用)耦合分析模型构建

可持续发展能力评价方法是识别人地协同规律、支撑科学决策的重要工具和热点需求。通过文献回顾与理论分析框架构建,耦合能值及?方法,提出自组织能力指数（SO）、生态压力指数（EP）、可持续发展能力指数（SC）构成的,基于热力学理论的可持续发展能力分析模型,利用文献荟萃法筛选17个典型发达国家1985年状态值计算SO与EP阈值,划分了4个阶段。利用中美两国1985-2015年特征对比验证,结果显示：① 2005年以前中国属“低自组织能力、低生态压力”阶段,之后进入“低自组织能力、高生态压力”阶段,存在低生态效率、规模扩张驱动特征;美国一直属“高自组织能力、高生态压力”阶段,存在高生态效率驱动、经济与生态脱钩特征,与全球生态足迹网络和世界自然基金会等的研究结果一致,模型具有较好适应性和可靠性。② 模型利用“获得?量/输入能值量”表达经济社会生态效率、“经济社会?损耗量/生态系统年产?量”表达生态压力,连接了经济社会对生态基底的熵化路径,可识别区域所处可持续发展阶段、分析水平变化和驱动因素。③ 模型以人类与生态并重的视角,从深度上反映经济社会的生态效率、从广度上评价生态空间被占用比例,具有宏观规模与微观效率分析相结合的优势,是对经典方法的补充。     

西北贫困地区乡村类型识别与振兴途径研究

乡村振兴战略是新时期我国推进城乡融合发展的重要举措。贫困地区既是脱贫攻坚的主战场,又是乡村振兴的重点区域。如何科学识别村落类型,分类推进典型区域乡村振兴发展,对于破解农村发展不平衡不充分问题具有重要的现实意义。本文解析了乡村地域系统发展理论,阐释了城乡融合发展理论,剖析了村域空间结构格局演变和城乡要素结构功能优化重组;构建了西北干旱贫困地区乡村振兴村落类型识别体系,从乡村主体、产业发展、人居环境、资源禀赋4个子系统进行逐级分类判断,识别乡村主导类型,结合专家征询分析与村落特征,将乡村振兴村落类型识别为集聚提升类、三产融合类、城郊融合类、特色保护类、搬迁撤并类,结合不同乡村振兴模式提出了相应地发展路径,以期为乡村振兴提供理论依据与决策参考。     

关于新时期中国西部发展沙产业的思考

沙产业是中国西部开发、生态文明建设和脱贫致富的必然选择。在对新时期沙产业内涵理解的基础上,对中国西部发展沙产业的空间基础、资源基础和科技基础进行了潜力分析,通过案例分析了新时期沙产业发展与生态文明建设和精准扶贫的关系。指出了目前中国西部沙产业发展中存在的主要问题,并提出了中国西部沙产业发展的政策建议。     

张掖盆地地下水硝酸盐污染与人体健康风险评价

地下水是张掖盆地的重要水资源,其硝酸盐污染尚未得到足够重视。对张掖盆地2004、2015年地下水硝酸盐浓度进行了系统分析,并采用美国环境保护署（USEPA）推荐的健康风险评价模型评估了地下水硝酸盐的健康风险。结果表明：自2004年以来张掖盆地地下水硝酸盐污染日趋严重。2015年硝酸盐浓度最高已达到283.32 mg·L^-1,17.61%的采样点硝酸盐氮浓度超过GB5749-2006《生活饮用水卫生标准》中饮用地下水限量值（20 mg·L^-1）。研究区人群经皮肤接触途径摄入硝酸盐的健康风险在可接受水平,而饮水摄入硝酸盐的健康风险较高,总风险中饮水途径引起健康风险的贡献率占99.40%,远大于皮肤接触途径。儿童经饮水摄入和皮肤接触两种途径的健康风险均显著高于成人,分别为成人的1.544倍和1.039倍。32.39%的采样点地下水硝酸盐对儿童的健康风险超出了可接受水平,14.79%的采样点地下水硝酸盐对成人的健康风险不可接受。甘州区城区、临泽县北部边缘及高台县城区周围硝酸盐浓度最高,这些区域内所有人群都面临硝酸盐引发的高健康风险,其余区域硝酸盐引发的健康风险相对较低。     

COSMO-SkyMed颜色变换强度RC法南京建设用地变化检测

基于非局部滤波的SAR强度RC合成变化检测法对小图斑、线型地物等动态监测灵敏,且对数据获取无时空基线要求,在多云多雨城市地表要素变化检测中具备潜力。本文研究以多时相SAR强度RC合成图为数据源,提出一种基于色彩空间变换的变化图斑半自动提取方法,即通过色彩空间转换、训练样本选取、监督分类影像分割、变化区域提取4步骤,可实现基于SAR强度图的城市建设用地动态监测与图斑高效更新。选取南京河西新城与江北新区为示范,以最优参数配置（3特征向量与10样本类别）进行试验,实现了优于88%的建设用地查准率指标。     

深度卷积神经网络支持下的遥感影像飞机检测

针对YOLOv3算法对小目标检测较差及出现较多漏检的问题,本文提出了一种优化的YOLOv3算法.首先使用K-means算法计算出与数据集相适用的锚框;其次将扩张卷积引入到YOLOv3网络,用来增强网络高层的感受野,改善小目标的检测效果;然后使用深度可分离卷积取代YOLOv3网络残差模块中的普通卷积,可减少计算量,从而得到一种新型卷积神经网络结构;最后在数据集上进行对比试验.结果表明,优化的YOLOv3算法能够检测出更多目标,降低漏检率,相比于YOLOv3算法,其召回率提高11.86%,F1-score提高2.99%.     

Spatiotemporal characteristics of Qinghai Lake ice phenology between 2000 and 2016

Journal of Geographical Sciences - Lake ice phenology is considered a sensitive indicator of regional climate change. We utilized time series information of this kind extracted from a series of...     

The spatial local accuracy of land cover datasets over the Qiangtang Plateau,High Asia

We analyzed the spatial local accuracy of land cover (LC) datasets for the Qiangtang Plateau, High Asia, incorporating 923 field sampling points and seven LC compilations including the International Geosphere Biosphere Programme Data and Information System (IGBPDIS), Global Land cover mapping at 30 m resolution (GlobeLand30), MODIS Land Cover Type product (MCD12Q1), Climate Change Initiative Land Cover (CCI-LC), Global Land Cover 2000 (GLC2000), University of Maryland (UMD), and GlobCover 2009 (Glob-Cover). We initially compared resultant similarities and differences in both area and spatial patterns and analyzed inherent relationships with data sources. We then applied a geographically weighted regression (GWR) approach to predict local accuracy variation. The results of this study reveal that distinct differences, even inverse time series trends, in LC data between CCI-LC and MCD12Q1 were present between 2001 and 2015, with the exception of category areal discordance between the seven datasets. We also show a series of evident discrepancies amongst the LC datasets sampled here in terms of spatial patterns, that is, high spatial congruence is mainly seen in the homogeneous southeastern region of the study area while a low degree of spatial congruence is widely distributed across heterogeneous northwestern and northeastern regions. The overall combined spatial accuracy of the seven LC datasets considered here is less than 70%, and the GlobeLand30 and CCI-LC datasets exhibit higher local accuracy than their counterparts, yielding maximum overall accuracy (OA) values of 77.39% and 61.43%, respectively. Finally, 5.63% of this area is characterized by both high assessment and accuracy (HH) values, mainly located in central and eastern regions of the Qiangtang Plateau, while most low accuracy regions are found in northern, northeastern, and western regions.

     

How changes of groundwater level affect the desert riparian forest ecosystem in the Ejina Oasis,Northwest China

Groundwater is a key factor controlling the growth of vegetation in desert riparian systems. It is important to recognise how groundwater changes affect the riparian forest ecosystem. This information will not only help us to understand the ecological and hydrological process of the riparian forest but also provide support for ecological recovery of riparian forests and water-resources management of arid inland river basins. This study aims to estimate the suitability of the Water Vegetation Energy and Solute Modelling(WAVES) model to simulate the Ejina Desert riparian forest ecosystem changes,China, to assess effects of groundwater-depth change on the canopy leaf area index(LAI) and water budgets, and to ascertain the suitable groundwater depth for preserving the stability and structure of desert riparian forest. Results demonstrated that the WAVES model can simulate changes to ecological and hydrological processes. The annual mean water consumption of a Tamarix chinensis riparian forest was less than that of a Populus euphratica riparian forest, and the canopy LAI of the desert riparian forest should increase as groundwater depth decreases. Groundwater changes could significantly influence water budgets for T. chinensis and P. euphratica riparian forests and show the positive and negative effects on vegetation growth and water budgets of riparian forests. Maintaining the annual mean groundwater depth at around 1.7-2.7 m is critical for healthy riparian forest growth. This study highlights the importance of considering groundwater-change impacts on desert riparian vegetation and water-balance applications in ecological restoration and efficient water-resource management in the Heihe River Basin.