摘要：Evapotranspiration(ET)is of great significance for the ecological environment and water resource utilization in arid and semi-arid *** Mongolian Plateau,owing to drought,low rainfall,and extremely uneven distribution of water resources,has a typical temperate continental climate.A refined understanding of the spatiotemporal distribution of ET in this region will help in establishing regulatory strategies for climate change responses,regional livestock regulation,and grassland degradation *** this study,meteorological station data,precipitation data,and the Penman-Monteith model were used to study the temporal and spatial distribution characteristics of actual ET over the Mongolian Plateau from 2011 to *** found that:(1)The spatial distribution of ET in the Mongolian Plateau showed a high trend in the north and east and a low trend in the middle and *** was a significant difference in the regional annual ET,with the highest ET reaching over 500 mm and the lowest being only approximately 70 mm.(2)The annual ET values in 2013,2018,and 2019 were relatively large,varying between 80 and 500 mm,and the overall ET of the Mongolian Plateau first decreased,then increased,and then decreased.(3)The temporal distribution exhibits a unimodal trend of increasing and then decreasing,with July being the turning ***-September was a period of high ET,with the highest ET exceeding 100 *** vegetation coverage was high,precipitation was abundant,and the vegetation ET effect was *** was a period of low ET,with a maximum ET of approximately 10 mm in January and December;the ET for the month with the lowest value was approximately *** quantitative inversion method proposed in this study can provide method and data support for north and central Asia,and other large arid and semi-arid areas.

摘要：The permafrost region is one of the most sensitive areas to climate *** global warming,the Mongolian Plateau permafrost is rapidly degrading,and its vegetation ecosystem is seriously *** address this challenge,it is essential to understand the impact of climate change on vegetation at different permafrost degradation stages on the Mongolian *** on the general permafrost distribution,in this study,we divided different permafrost regions and explored the response of vegetation to climate change at different stages of permafrost degradation by the idea of“space instead of time”from 2014 to *** results of the study showed that:(1)Normalized difference vegetation index(NDVI)values showed a decreasing trend,and the proportion of the decreasing region was in the order of sporadic permafrost region>isolated and sparse permafrost region>continuous and discontinuous permafrost regions.(2)The main controlling factors of vegetation growth in permafrost regions are different,air temperature is the main controlling factor of vegetation growth in isolated and sparse permafrost region(r=-0.736)and sporadic permafrost regions(r=-0.522),and precipitation is the main controlling factor of vegetation growth in continuous and discontinuous permafrost region(r=-0.498).(3)The response of NDVI to climate change varies at different stages of permafrost *** the early stages of permafrost degradation,increased land surface temperature(LST)and air temperature favored vegetation growth and increased vegetation cover,whereas increased precipitation impeded vegetation growth;as the permafrost degraded,increased LST and air temperature impeded vegetation growth,whereas increased precipitation promoted vegetation growth.

摘要：在分析了地学数据的Web共享需求及其多学科特点基础上,设计了地学数据的可扩展元数据结构,它包括地学核心元数据、模式核心元数据、模式(专用)扩展元数据等三层体系,并利用W3C推荐的RDF/XML数据模型和方法开发了地学数据共享平台的元数据管理系统(MMS)。该系统的应用验证了地学数据共享元数据构架体系的可靠性和适用性。

摘要：中国是最易受自然灾害影响的国家之一,为提升自然灾害综合防范能力,国务院于2020年启动了第一次全国自然灾害综合风险普查(以下简称灾害普查)。灾害普查数据质量的检查和控制,是保证普查数据共享利用、灾害评估、应急救灾,甚至防灾减灾国际合作的根本。灾害普查任务内容广泛,由多个部门分工完成,其中我国应急管理系统承担着承灾体调查、历史灾害调查、综合减灾能力3项调查任务。本文面向应急管理系统灾害普查数据质检的需要,深刻融入地理大数据的思想,探索自然灾害普查数据质检方法体系。具体包括:①设计了国家、省、市、县4个层级的应急管理体系质检业务流程框架;②建立了完整性、规范性、一致性、合理性四位一体的质检技术规则体系;③构建了由11位编码组成的新型质检规则编码体系,形成计算机软件系统可更新和调用的质检规则库;④提出了标准差、中位数等经典统计与空间相关性分析相结合的属性与空间组合质检方法;⑤探索了基于第三方大数据等异常值交叉检测的新模式;⑥建立了适应我国国情的特殊普查数据处理机制和软件系统响应方式。结合国家试点县质检实践和江西省某县级普查应用实践,对上述方法的可用性进行了实证。实践共发现十类数据异常,其中疑似违反合理性、超出99%可信区间与第三方验证异常等3类异常类型包含的异常数据最多。研究表明该质检方法体系能够使得灾害普查质检端口前移,可以在前端采集时自动发现许多错误,减少后期质量控制的压力,也因此提高质检效率、提升普查数据质量。这一方法预期能够为今后持续开展的灾害普查和相关普查提供质检方法借鉴。

摘要：推荐系统是帮助互联网用户克服信息过剩的有效工具。在地学数据共享领域,较其他物品的内容属性,地学数据具有更加丰富的时空属性,这也给地学数据推荐带来挑战。针对地学数据的特点,为地学数据共享推荐服务开发了一种动态加权的混合过滤方法。该方法分别采用协同过滤和基于内容过滤算法预测用户对数据的兴趣度,再以训练模型计算最优加权权重,计算最终预测评分。在数据获取阶段,通过用户访问日志数据,采用Jenks Natural Break算法分析用户访问记录获取用户的数据兴趣度。在基于内容过滤部分,通过数据的空间、时间及内容属性计算数据相似度,并以用户历史行为为依据计算用户兴趣。在协同过滤和基于内容过滤中分别采用k-NN算法计算用户对未访问数据的预测评分,并进行加权求和。通过训练集,对理想权重值及用户的共同评价度(co-rating level)进行建模,拟合二者的关系。该模型被应用于混合过滤的权重调整,以获得最优的加权方程。测试结果显示,结合数据时空属性的混合过滤方法的准确度和召回率,较单一的协同过滤或基于内容过滤方法有显著提高。

摘要：由于研究主题和应用目的的不同,国内外已经存在和正在产生着越来越多的遥感数据源的土地覆盖分类体系。这不仅使得分类体系缺乏可扩展性与互操作性,而且使得不同分类体系的土地覆盖数据难以对比、交换和集成。本文借鉴ISO 19115地理信息元数据的扩展经验,设计了基于ISO元数据扩展模型的土地覆盖分类体系框架,并研究其动态扩展方法。提出一种包括核心分类、全集分类和专题应用分类的三层土地覆盖可扩展分类体系框架。其中,核心分类是从国内外主要的土地利用/覆盖分类系统中抽取的共性分类元素;全集分类收集全部可能的土地覆盖分类元素;专题应用分类通过对核心分类的继承,和对全集分类的裁剪和扩展生成。该分类框架将为土地利用/覆盖的研究和应用提供一种科学的、可比的动态分类扩展模型和方法。

摘要：蒙古高原地处干旱半干旱地区,河流水系对该区域的资源环境格局及其生态环境影响重大。发源于蒙古国的色楞格河是蒙古高原最主要的水资源来源,准确掌握该流域的水体信息对东北亚地区生态环境问题及资源保护具有重要意义。本文以蒙古高原色楞格河流域为研究对象,基于谷歌地球引擎(Google Earth Engine,GEE)云平台,使用Sentinel-2多光谱卫星遥感影像,利用深度神经网络(Deep Neural Network,DNN)方法对色楞格河流域的水体信息进行提取,并与支持向量机方法进行对比;利用全球30 m SRTM数据生成水系分布矢量图,通过空间分析形成河流提取目标区,结合深度神经网络分类结果,绘制蒙古国色楞格河流域2019年河流分布图。研究结果表明:①该方法能够准确地完成大流域范围内的水体制图,提取结果能够体现色楞格河流域河流的空间分布,且能够减少河流断流、空洞现象;②深度神经网络模型中批量大小设置为8时,在处理数据速度与精度中达到最优,而神经网络结构中隐含层数达到4层时,在精度评价指标测试数据集上达到0.9666,保证了模型特征挖掘能力;③经样本点的验证,结果总体精度达到97.65%,可以满足实际应用需求。本研究预期可以为蒙古高原的水体提取提供方法支持和相关数据支持。

摘要：The Mongolian Plateau,a vital ecological barrier in northern China,is of great importance for studying vegetation dynamics in Mongolia against the background of climate *** studies can enhance our understanding of regional vegetation responses to global warming and contribute to the establishment of a stronger ecological barrier in northern ***,we analyzed the spatial and temporal characteristics of the NDVI(normalized difference vegetation index)in Mongolia using 8 km resolution GIMMS NDVI3g data from 1990 to 2022,along with temperature,precipitation,and elevation *** analysis and correlation methods were used to examine the relationships between the NDVI and temperature,as well as *** results showed four important aspects of these relationships.(1)The NDVI in Mongolia increased significantly from 1990 to 2022 at a rate of 0.0015 yr^(-1)(P<0.05).(2)Mongolia’s NDVI increased from 1990 to 2022 in 60.73%of the *** this total,the area with a significant increase accounted for 31.67%and was concentrated on the eastern and western *** area experiencing a significant decrease accounted for 15.67%and was mainly located on the southwestern edges.(3)The NDVI analysis revealed significant increasing trends in all regions except for those at elevations of 1500-2000 *** greatest rate of increase was observed between 500 and 1000 m,and the increasing trend weakened as elevation continued to increase before gradually becoming significant ***,the NDVI increased significantly across different slopes,and the rate of increase decreased as the slope increased.(4)From 1990 to 2022,Mongolia’s NDVI was mostly negatively correlated with *** occurred over 66.75%of the total land area,with 17.21%of the region exhibiting a significant negative correlation,mainly in the ***,the NDVI demonstrated a positive correlation with precipitation,encompassing 86.71%of the total land *** 4

摘要：蒙古高原广袤的干旱半干旱地区存在大量未经规划的自然道路,也称临时道路或越野公路。此类道路由车辆任意行驶碾压导致,会对地表生态及其稳定性造成影响,加剧干旱半干旱地区土地退化。由于自然道路数量众多、分布不规则且易随着区域发展而改变,因而高效精确获取这些信息是大范围草原地区的一个紧迫需求和难点。该文以蒙古国自然道路为主要提取目标,基于国产高分一号(GF-1)影像采用面向对象的方法进行研究区道路信息提取。首先对覆盖研究区的GF-1影像进行数据预处理,采用多尺度分割方法进行影像对象分割;然后对需要提取的自然道路进行特征分析,通过计算光谱、几何特征参数及随机选取道路样本统计样本特征值,选出能表达自然道路特征的参数构建道路提取规则集;进而结合多种方法的组合应用,最终通过最邻近分类法实现对道路的初步提取,采用阈值分类法等分类算法优化道路信息。结果表明,提取的蒙古国古尔班特斯苏木研究区自然道路长度为3708.745 km,密度为0.129 km/km^(2),总体呈现东南密集,西、北部稀疏的分布特征,与本地区实际的煤矿企业生产和居民城镇生活情况相符。研究表明所提方法可以较完整地提取出研究区自然道路,可为蒙古高原等广大干旱半干旱地区自然道路提取提供方法借鉴。

摘要：产草量是衡量草原生产力和诊断草原健康状况的指标,是草地资源管理的重要依据。近年来,遥感数据结合地面实测数据建模已成为产草量估算的重要手段。充足的实测样点信息是产草量遥感建模估算的基础。受境外采样多重因素的制约,蒙古国产草量估算研究中无法获取足够且分布均匀的实测样点,估产模型的精度受到影响,这一问题目前尚未发现有好的解决方法。本研究选取中蒙铁路沿线(蒙古段)两侧200 km缓冲区作为研究区,针对产草量遥感估算中野外样点稀少且分布不均的问题,引入P-BSHADE方法,基于多年NDVI数据和获取的少量地面实测样点数据,考虑草地分布的非均匀性以及样点之间的相关性,对均匀分布的模拟样点处的产草量数据进行插值实验。结果显示,P-BSHADE法的插值效果优于Kriging法,可得到均匀分布于研究区的样点。基于以上实测样点和插值样点,结合NDVI、EVI、PsnNet 3种植被指数进行遥感建模,最优模型精度达到80%,精度优于已有相关研究。选取其中最优的基于NDVI的指数模型对研究区2000—2019年产草量进行反演,获得的产草量空间格局与年际变化与已有研究结果趋势吻合,进一步印证了结果的可靠性和插值方法的可行性。本研究通过插值的方式改善数据源从而提高估算模型精度是一种全新的思路与尝试,对于"一带一路"等境外区域资源环境监测具有借鉴意义。