Arid areas with low precipitation and sparse vegetation typically yield compact urban pattern,and drought directly impacts urban site selection,growth processes,and future scenarios.Spatial simulation and projection b...Arid areas with low precipitation and sparse vegetation typically yield compact urban pattern,and drought directly impacts urban site selection,growth processes,and future scenarios.Spatial simulation and projection based on cellular automata(CA)models is important to achieve sustainable urban development in arid areas.We developed a new CA model using bat algorithm(BA)named bat algorithm-probability-of-occurrence-cellular automata(BA-POO-CA)model by considering drought constraint to accurately delineate urban growth patterns and project future scenarios of Urumqi City and its surrounding areas,located in Xinjiang Uygur Autonomous Region,China.We calibrated the BA-POO-CA model for the drought-prone study area with 2000 and 2010 data and validated the model with 2010 and 2020 data,and finally projected its urban scenarios in 2030.The results showed that BA-POO-CA model yielded overall accuracy of 97.70%and figure-of-merits(FOMs)of 35.50%in 2010,and 97.70%and 26.70%in 2020,respectively.The inclusion of drought intensity factor improved the performance of BA-POO-CA model in terms of FOMs,with increases of 5.50%in 2010 and 7.90%in 2020 than the model excluding drought intensity factor.This suggested that the urban growth of Urumqi City was affected by drought,and therefore taking drought intensity factor into account would contribute to simulation accuracy.The BA-POO-CA model including drought intensity factor was used to project two possible scenarios(i.e.,business-as-usual(BAU)scenario and ecological scenario)in 2030.In the BAU scenario,the urban growth dominated mainly in urban fringe areas,especially in the northern part of Toutunhe District,Xinshi District,and Midong District.Using exceptional and extreme drought areas as a spatial constraint,the urban growth was mainly concentrated in the"main urban areas-Changji-Hutubi"corridor urban pattern in the ecological scenario.The results of this research can help to adjust urban planning and development policies.Our model is readily applicable to simulating urban growth and future scenarios in global arid areas such as Northwest China and Africa.展开更多
针对月球南极光照暗弱、阴影区域众多、月面形貌要素单一弱纹理,给影像立体匹配和三维地形重建带来极大挑战和困难的问题,提出了一种可信度引导的高效立体匹配算法(Efficient Confidence-guided Stereo Matching,ECSM),通过评估非支撑...针对月球南极光照暗弱、阴影区域众多、月面形貌要素单一弱纹理,给影像立体匹配和三维地形重建带来极大挑战和困难的问题,提出了一种可信度引导的高效立体匹配算法(Efficient Confidence-guided Stereo Matching,ECSM),通过评估非支撑点的可信度来更新支撑点点集,构建三角网并利用三角形顶点的可信度重新估算其内部视差,提高匹配精度和效率。在此基础上,构建了月面摄影测量三维地形重建方法,并采用月球勘测轨道器(Lunar Reconnaissance Orbiter,LRO)窄角相机高分辨率影像数据,开展月球南极沙克尔顿(Shackleton)坑缘区域地形重建的验证实验。比较分析不同立体匹配算法生成的视差图和数字高程模型(Digital Elevation Model,DEM),结果表明:所提出的算法在处理月面弱纹理和重复纹理区域影像方面具有可靠性。将生成的DEM与德国宇航中心(Deutsches Zentrum für Luft-und Raumfahrt,DLR)制作的同区域DEM以及美国国家航空航天局(National Aeronautics and Space Administration,NASA)的月球轨道激光高度计DEM(LDEM)进行对比分析,高程和坡度信息方面都表现出较高的一致性,验证了该方法的可行性和有效性,为月球南极探测着陆区选择提供可靠的数据方法基础。展开更多
综合利用火星轨道器多源遥感影像数据,构建了火星表面形貌精细建模与自动分类方法。结合摄影测量法与明暗恢复形状法(Shape From Shading,SFS)研究制作了“天问一号”着陆区域的高分辨率三维地形,并通过深度卷积神经网络对着陆区形貌类...综合利用火星轨道器多源遥感影像数据,构建了火星表面形貌精细建模与自动分类方法。结合摄影测量法与明暗恢复形状法(Shape From Shading,SFS)研究制作了“天问一号”着陆区域的高分辨率三维地形,并通过深度卷积神经网络对着陆区形貌类别及其分布进行分类分析。地形剖面分析结果表明,所提出方法制作的高精度地形数据与中、美两国已发布的火星高分辨率数字高程模型(Digital Elevation Model,DEM)产品相比,高程误差均值分别为1.866 m和1.074 m,均具有较高一致性。此外,通过形貌及制图综合分析可以看出,着陆点附近坡度在3°以下,着陆点附近地表的起伏程度不大于30 cm,以此验证了“天问一号”着陆区整体地势平缓、形貌类别较单一,符合探测器安全着陆的需求。国产“天问一号”高分辨率相机数据制作的地形及分类结果可有效应用于着陆及巡视探测区的形貌特征分析,联合HiRISE等多源火星遥感数据,可为后续“祝融号”巡视器科学探测提供重要的基础数据和参考信息。展开更多
基金supported the National Natural Science Foundation of China(42071371)the National Key R&D Program of China(2018YFB0505400).
文摘Arid areas with low precipitation and sparse vegetation typically yield compact urban pattern,and drought directly impacts urban site selection,growth processes,and future scenarios.Spatial simulation and projection based on cellular automata(CA)models is important to achieve sustainable urban development in arid areas.We developed a new CA model using bat algorithm(BA)named bat algorithm-probability-of-occurrence-cellular automata(BA-POO-CA)model by considering drought constraint to accurately delineate urban growth patterns and project future scenarios of Urumqi City and its surrounding areas,located in Xinjiang Uygur Autonomous Region,China.We calibrated the BA-POO-CA model for the drought-prone study area with 2000 and 2010 data and validated the model with 2010 and 2020 data,and finally projected its urban scenarios in 2030.The results showed that BA-POO-CA model yielded overall accuracy of 97.70%and figure-of-merits(FOMs)of 35.50%in 2010,and 97.70%and 26.70%in 2020,respectively.The inclusion of drought intensity factor improved the performance of BA-POO-CA model in terms of FOMs,with increases of 5.50%in 2010 and 7.90%in 2020 than the model excluding drought intensity factor.This suggested that the urban growth of Urumqi City was affected by drought,and therefore taking drought intensity factor into account would contribute to simulation accuracy.The BA-POO-CA model including drought intensity factor was used to project two possible scenarios(i.e.,business-as-usual(BAU)scenario and ecological scenario)in 2030.In the BAU scenario,the urban growth dominated mainly in urban fringe areas,especially in the northern part of Toutunhe District,Xinshi District,and Midong District.Using exceptional and extreme drought areas as a spatial constraint,the urban growth was mainly concentrated in the"main urban areas-Changji-Hutubi"corridor urban pattern in the ecological scenario.The results of this research can help to adjust urban planning and development policies.Our model is readily applicable to simulating urban growth and future scenarios in global arid areas such as Northwest China and Africa.
文摘深空探测巡视任务中巡视器的高精度定位对于巡视器的自身安全与持续运行至关重要。巡视器定位主要包括相对定位和绝对定位两种方式,其中绝对定位方法主要是利用轨道器/着陆器的数据为基准确定巡视器在全局坐标系下的位置。美国Mars 2020任务携带的机智号无人机在火星环境下完成了飞行验证,它能够获得高分辨率的火星表面影像,从而为火星巡视器绝对定位提供了新思路。据此,本文提出了一种卫星-无人机-巡视器影像协同的多分辨率影像匹配绝对定位框架。首先,利用运动恢复结构(structure from motion, SFM)方法对无人机影像进行三维重建,获取局部高分辨率三维地图;然后,开展巡视器影像与无人机影像的多视角匹配,并基于匹配结果利用后方交会实现巡视器在无人机局部地图中的高精度定位;最后,通过局部无人机影像与卫星影像的配准,实现卫星影像全局坐标系下的巡视器绝对定位。为验证本文方法的可行性,开展了巡视器定位仿真试验,试验结果验证了本文方法的可行性,能够为后续我国开展类似工程任务提供参考。
文摘针对月球南极光照暗弱、阴影区域众多、月面形貌要素单一弱纹理,给影像立体匹配和三维地形重建带来极大挑战和困难的问题,提出了一种可信度引导的高效立体匹配算法(Efficient Confidence-guided Stereo Matching,ECSM),通过评估非支撑点的可信度来更新支撑点点集,构建三角网并利用三角形顶点的可信度重新估算其内部视差,提高匹配精度和效率。在此基础上,构建了月面摄影测量三维地形重建方法,并采用月球勘测轨道器(Lunar Reconnaissance Orbiter,LRO)窄角相机高分辨率影像数据,开展月球南极沙克尔顿(Shackleton)坑缘区域地形重建的验证实验。比较分析不同立体匹配算法生成的视差图和数字高程模型(Digital Elevation Model,DEM),结果表明:所提出的算法在处理月面弱纹理和重复纹理区域影像方面具有可靠性。将生成的DEM与德国宇航中心(Deutsches Zentrum für Luft-und Raumfahrt,DLR)制作的同区域DEM以及美国国家航空航天局(National Aeronautics and Space Administration,NASA)的月球轨道激光高度计DEM(LDEM)进行对比分析,高程和坡度信息方面都表现出较高的一致性,验证了该方法的可行性和有效性,为月球南极探测着陆区选择提供可靠的数据方法基础。
