新一代1:50万中国植被图绘制方法探讨

植被图是表示多种植被或植物群落的空间分布规律及其生态环境的地图,它是生物多样性保护、生态研究、自然资源管理和生态恢复的重要依据.目前,中国植被专题资源信息的本底数据《中华人民共和国植被图(1:1000000)》从开始绘制至今已将近40年,中国的植被分布格局已经发生了极大的变化,《中华人民共和国植被图(1:1000000)》已存在植被斑块的类别和边界与现实不符等问题,中国的植被分布本底数据亟待更新.如今卫星遥感技术的发展为实现大面积区域的植被制图提供了一种实用且经济的手段.本文综述了国家尺度植被图的制图方法和卫星遥感技术在植被分类制图上的进展,并以此为基础,探讨中国新一代1:50万植被图的遥感制图方法.新一代1:50万中国植被图的绘制通过众源采集结合专家鉴定的方式获取海量植被类型样本,基于多源遥感数据,以植被斑块为对象,采用深度学习的方式实现遥感植被分类,并基于自主构建的植被在线平台,借助于全国各地的植被生态学家的专业知识实现对制图结果的校订和更新

基于激光雷达的自然资源三维动态监测现状与展望

激光雷达作为一种主动的三维遥感观测技术,在不同尺度的土地、矿产、森林、草原、湿地、水、海洋等自然资源的三维动态监测中发挥着越来越重要的作用。本文将在简要介绍激光雷达技术发展现状的基础上,重点阐述激光雷达技术在各类自然资源三维动态监测中的应用现状,同时对激光雷达在自然资源调查中的应用潜力和局限性进行综合分析,最后探讨以激光雷达技术为基础的自然资源三维动态监测的未来发展趋势和方向。随着激光雷达技术和平台的不断发展以及激光雷达信息的深入挖掘,将不断促进激光雷达技术在自然资源三维动态监测应用中的纵深发展。然而单一激光雷达数据由于其本身存在的局限性,难以满足自然资源全要素、全流程、全覆盖、高精度、高效率的现代化动态监测的要求,如何将多源、多尺度、多平台遥感数据与人工智能相结合,构建"天—空—地"一体化的自然资源调查监测技术体系,是未来自然资源三维动态监测的发展方向

JUNO Sensitivity on Proton Decay p→νˉK+p\to \bar\nu K^+ Searches

The Jiangmen Underground Neutrino Observatory (JUNO) is a large liquid scintillator detector designed to explore many topics in fundamental physics. In this paper, the potential on searching for proton decay in $p\to \bar\nu K^+$ mode with JUNO is investigated.The kaon and its decay particles feature a clear three-fold coincidence signature that results in a high efficiency for identification. Moreover, the excellent energy resolution of JUNO permits to suppress the sizable background caused by other delayed signals. Based on these advantages, the detection efficiency for the proton decay via $p\to \bar\nu K^+$ is 36.9% with a background level of 0.2 events after 10 years of data taking. The estimated sensitivity based on 200 kton-years exposure is $9.6 \times 10^{33}$ years, competitive with the current best limits on the proton lifetime in this channel

JUNO sensitivity on proton decay p → ν K + searches*

The Jiangmen Underground Neutrino Observatory (JUNO) is a large liquid scintillator detector designed to explore many topics in fundamental physics. In this study, the potential of searching for proton decay in the $p\to \bar{\nu} K^+$ mode with JUNO is investigated. The kaon and its decay particles feature a clear three-fold coincidence signature that results in a high efficiency for identification. Moreover, the excellent energy resolution of JUNO permits suppression of the sizable background caused by other delayed signals. Based on these advantages, the detection efficiency for the proton decay via $p\to \bar{\nu} K^+$ is 36.9% ± 4.9% with a background level of $0.2\pm 0.05({\rm syst})\pm$$0.2({\rm stat})$ events after 10 years of data collection. The estimated sensitivity based on 200 kton-years of exposure is $9.6 \times 10^{33}$ years, which is competitive with the current best limits on the proton lifetime in this channel and complements the use of different detection technologies