Observed trends of climate and land cover changes in Lake Baikal basin

Land cover and vegetation in Lake Baikal basin (LBB) are considered to be highly susceptible to climate change. However, there is less information on the change trends in both climate and land cover in LBB and thus less understanding of the watershed sensitivity and adaptability to climate change. Here we identified the spatial and temporal patterns of changes in climate (from 1979 to 2016), land cover, and vegetation (from 2000 to 2010) in the LBB. During the past 40 years, there was a little increase in precipitation while air temperature has increased by 1.4 °C. During the past 10 years, land cover has changed significantly. Herein grassland, water bodies, permanent snow, and ice decreased by 485.40 km², 161.55 km² and 2.83 km², respectively. However, forest and wetland increased by 111.40 km² and 202.90 km², respectively. About 83.67 km² area of water bodies has been converted into the wetland. Also, there was a significant change in Normalized Difference Vegetation Index (NDVI), the NDVI maximum value was 1 in 2000, decreased to 0.9 in 2010. Evidently, it was in the mountainous areas and in the river basin that the vegetation shifted. Our findings have implications for predicting the safety of water resources and water eco-environment in LBB under global change.     

Spatio-temporal Distribution of Drought in the Belt and Road Area During 1998-2015 Based on TRMM Precipitation Data

Drought is a worldwide natural disaster that has long affected agricultural production as well as social and economic activities. Frequent droughts have been observed in the Belt and Road area, in which much of the agricultural land is concentrated in fragile ecological environment. Based on the Tropical Rainfall Measuring Mission Satellite (TRMM) 3B43 precipitation data, we used the Precipitation Abnormity Percentage drought model to study the monthly spatio-temporal distribution of drought in south region of N50° of the Belt and Road area. It was observed that drought during winter was mainly distributed in Northeast Asia, Southeast Asia, and South Asia, while it was mainly distributed in Central Asia and West Asia during summer. The occurrence of historical droughts indicates an obvious seasonal cycle. The regional variations in drought were analyzed using the Breaks for Additive Season and Trend tool (BFAST) in six sub-regions according to the spatial distribution of six economic corridors in the Belt and Road area. The average drought conditions over the 18 years show a slight decreasing trend in Northeast Asia, West Asia, North Africa, South Asia, Central and Eastern Europe, and a slight increasing trend in Central Asia. However, it was a fluctuating pattern of first increasing and then decreasing in Southeast Asia. The results indicate that the total drought area in the Belt and Road region showed a general decreasing trend at a rate of 40,260 km2 per year from 1998 to 2015.     

Producing Certified Reference Materials at the Central Geological Laboratory of Mongolia

This paper briefly outlines the production and certification of reference materials at the Central Geological Laboratory (CGL) of Mongolia. The marketing of CRMs produced in Mongolia, as well as problems encountered in internationally recognised certification attempts and some proposed solutions, are discussed. The basic elements of the CGL’s strategy for the development of the CRM sector are to produce high quality CRMs according to the requirements of internationally recognised norms, to consider the market needs, to certify the RMs at the international level and to widely advertise them to the geochemical community. The CGL has already established the basis for the further development of this sector by, for instance, accreditation under ISO/IEC 17025, by modernising its preparation technology, by cooperation with international organisations in the field of CRMs and by permanent participation in the International Association of Geoanalysts’ GeoPT™ proficiency testing programme.     

基于深度神经网络的蒙古国色楞格河流域水体信息提取

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。     

基于稀疏样点的蒙古国产草量估算方法研究

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。