响应城市内涝机制的减灾型景观地形设计与量化调控方法研究
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项目结题报告(全文)
1.基于时空演变分析的武汉市城市蓝绿系统空间格局及其与城市发展的协同关系研究
- 关键词：
- 蓝绿空间;空间结构演化;协同发展评估模型;时空变化;复合系统;协同度
- 杨柳琪;周燕;罗佳梦;郭诗怡
- 《园林》
- 2022年
- 卷
- 7期
- 期刊
以蓝绿系统为空间基础结构统筹城市生态、经济、社会等多目标的发展策略,是城市应对全球气候变化与城市快速发展挑战的共识。研究蓝绿空间的演化规律及其与城市社会、经济子系统之间的相互作用关系是促进蓝绿系统综合功能充分发挥的前
...2.粤港澳大湾区旅游景点可达性时空格局演变
- 关键词：
- 粤港澳大湾区;时空格局演变;可达性分析;最短时间成本距离模型
- 童娅琼;王树根;李赟鹏;龙晓怡
- 《测绘地理信息》
- 2022年
- 卷
- 02期
- 期刊
粤港澳大湾区以打造成世界级城市群为目标，在大力发展区域经济的同时，也十分重视旅游业的发展。其中旅游景点可达性，是制约旅游经济区域平衡发展和可持续发展的一大难题。为促进粤港澳大湾区旅游交通的便捷程度，推进粤港澳大湾区旅游业一体化发展，本文以粤港澳大湾区为研究区，以研究区内的国家A级景区为研究单元，采用最短时间成本距离模型，对粤港澳大湾区旅游景点的交通可达性进行演化与分析；同时，对旅游景点可达性与景点时空格局演化关系进行了分析。
...3.可拓学辅助景观分析与方案生成的应用方法研究——以咸宁市淦河滨河空间景观优化策略生成过程为例
- 冉玲于；周燕；
- 0年
- 卷
- 期
- 期刊
4.一种面向对象的城市湖泊遥感提取指数
- 关键词：
- 城市湖泊;遥感指数;面向对象;湖泊遥感提取
- 徐兆丰;袁宇欣;彭浩;李岩
- 《地理空间信息》
- 2022年
- 卷
- 1期
- 期刊
城市湖泊是城市水资源环境的核心组成部分,可对城市区域微气候产生积极的调节作用,同时能反映当地的文化底蕴特色。在当今城市化进程的影响下,城市湖泊比自然湖泊更脆弱且更易发生变化。提出了一种面向对象的城市湖泊遥感提取指数方法,
...5.城市蓝绿景观格局对雨洪调蓄功能的影响
- 关键词：
- 蓝绿空间;景观格局;土地利用;城市内涝;雨洪调蓄;logistic回归分析
- 禹佳宁;周燕;王雪原;郭诗怡
- 《风景园林》
- 2021年
- 卷
- 09期
- 期刊
近年来,城市内涝问题频发,引发了社会强烈关注。现有研究多从灾害成因角度聚焦于景观格局变化对洪涝产生的影响,蓝绿景观格局与雨洪调蓄功能的响应关系尚待进一步探讨分析。以武汉市江夏区为研究区域,通过对比连续晴天及雨后情景下的遥感影像结果,建立了淹没转移变化矩阵表征调蓄状况,结合以往研究与斯皮尔曼相关系数分析的结果,选取了面积周长比、形状指数、分形维数、近圆指数、边缘对比度5个景观指数,运用二元Logistic回归分析,探究了景观格局对雨洪调蓄功能的影响。结果表明:1)分维指数对雨洪调蓄能力的发挥有直观的作用,城市存量布局优化中需要着重注意对蓝绿空间自然形态的保护;2)雨洪调蓄功能与蓝绿空间聚集度指标之间没有显著关联,蓝绿空间的复合程度对雨洪调蓄能力的影响有待更精细化的研究。研究结果为蓝绿空间景观格局的调蓄效能理论提供了量化支持,可为今后城市洪涝治理和景观格局优化研究提供一定的思路。
...6.Green space optimization strategy to prevent urban flood risk in the city centre of wuhan
- 关键词：
- Digital storage;Catchments;Land use;Urban planning;Runoff;Rain;Evaluation modeling;Optimization strategy;Prevention and controls;Quantitative data;Storage capacity;Urban flood risks;Urban underlying surfaces;Water permeability
- Liu, Yajing;Zhou, Yan;Yu, Jianing;Li, Pengcheng;Yang, Liuqi
- 《Water 》
- 2021年
- 13卷
- 11期
- 期刊
Changing the water permeability ratio of urban underlying surface helps alleviate urban flood. This paper designs the swale identification experiment to modify the flood-submerging simulation experiment based on the SCS-CN model and proves that the results generated by the modified experiment better reflect the realities. The modified flood-submerging simulation experiment is then applied to downtown Wuhan to obtain the quantitative data. The data are used to quantify the catchment capacities of the lots. Based on the rainfall collection capacities, the maximum surface rainfall runoff volume that would not cause flood is arrived at using the rainfall runoff formula. The maximum runoff volume represents the rainwater storage capacities of the lot based on the proportion of the green space that is identified within the study area. The results suggest that this rainwater storage capacity evaluation model works efficiently to identify the urban areas with flood risks and provides the rainwater runoff thresholds for different areas. Adjustments in the spatial patterns and proportions of the green space help ensure that the rainwater runoff volume is below the thresholds, thus contributing to the prevention and control of the urban flood risks.© 2021 by the authors. Licensee MDPI, Basel, Switzerland....7.Extraction of impervious surface using sentinel-1A time-series coherence images with the aid of a sentinel-2A image
- 关键词：
- Geometrical optics;Image segmentation;Optical remote sensing;Synthetic aperture radar;Artificial targets;Coherence factors;Coherence images;Data-sources;Impervious surface;Interferometric synthetic aperture radars;Optical image;Temporal coherence
- Wu, Wenfu;Teng, Jiahua;Cheng, Qimin;Guo, Songjing
- 《Photogrammetric Engineering and Remote Sensing》
- 2021年
- 87卷
- 3期
- 期刊
The continuous increasing of impervious surface (IS) hinders the sustainable development of cities. Using optical images alone to extract IS is usually limited by weather, which obliges us to develop new data sources. The obvious differences between natural and artificial targets in interferometric synthetic-aperture radar coherence images have attracted the attention of researchers. A few studies have attempted to use coherence images to extract IS—mostly single-temporal coherence images, which are affected by de-coherence factors. And due to speckle, the results are rather fragmented. In this study, we used time-series coherence images and introduced multi-resolution segmentation as a postprocessing step to extract IS. From our experiments, the results from the proposed method were more complete and achieved considerable accuracy, confirming the potential of time-series coherence images for extracting IS.© 2021 American Society for Photogrammetry and Remote Sensing....8.Reconciling the inconsistency of annual temperature cycles modelled from Landsat and MODIS LSTs through a percentile approach
- 关键词：
- Radiometers;Regression analysis;Surface measurement;Land surface temperature;Parameter estimation;Time series analysis;Landsat;Atmospheric temperature;Annual temperatures;Cycle parameters;LANDSAT;Parameters estimated;Physical modelling;Spatial scale;Surface energy fluxes;Surface temperatures;Temperature cycles;Thermal patterns
- Fu, Huyan;Shao, Zhenfeng;Fu, Peng;Zhan, Wenfeng;Xie, Yanhua;Cheng, Tao
- 《International Journal of Remote Sensing》
- 2021年
- 42卷
- 20期
- 期刊
Land surface temperature (LST) is an important variable to understand surface energy fluxes, land–atmosphere interactions, and urban thermal environments. Time series analysis of LSTs through semi-physical models such as the annual temperature cycle (ATC) model has become critical for these understandings. However, studies are lacking in examining and reconciling the inconsistency of time series LST modelling results across spatial scales, weakening the reliability of these semi-physical models to characterize landscape thermal patterns. In this study, a percentile approach was used to reveal and reconcile discrepancies of ATC parameters estimated from Landsat (100 m) and Moderate Resolution Imaging Spectroradiometer (MODIS, 1000 m) LSTs. Results showed substantial differences across spatial scales for each of the ATC parameters, i.e. mean annual surface temperature (MAST), yearly amplitude of surface temperature (YAST), and revised phase shift (RPS), within the same land cover (e.g. 4.0 K difference between MAST estimated from Landsat LSTs and that from MODIS LSTs for grassland). The spatial distribution of ATC parameters estimated from MODIS LSTs across land cover types was quite different from that from Landsat LSTs. The percentile aggregation analysis suggested that the difference between MAST/YAST (and RPS) derived from MODIS LSTs and Landsat-aggregated values at the 25th (and 40th) percentile within a MODIS block was close to zero. Further regression analysis showed that differences in ATC parameters, particularly MAST and YAST, derived from different datasets could be reconciled. Our study offers new insights into understanding inconsistencies in and reconciliations of ATC parameters modelled at different spatial scales for quantifying landscape thermal patterns spatially and temporally.© 2021 Informa UK Limited, trading as Taylor & Francis Group....9.粤港澳大湾区旅游资源与旅游经济发展的空间错位研究
- 关键词：
- 旅游经济;旅游资源;空间错位;粤港澳大湾区
- 王雪菡;贺蔚;李赟鹏
- 《测绘地理信息》
- 2021年
- 卷
- S1期
- 期刊
以粤港澳大湾区（Guangdong-Hong Kong-Macao Greater Bay Area,GBA）为研究区域,通过构建旅游资源指数与旅游经济指数分析区域内旅游资源与旅游经济的发展状况。然后利用重心模型与空间错位指数,对粤港澳大湾区旅游经济与旅游资源空间错位现象进行具体研究。研究表明各个城市空间错位现象类型、程度以及发展趋势不同,随着时间发展粤港澳大湾区整体空间错位程度变小,旅游资源与旅游经济发展愈发协调。
...10.Multi-scale adversarial network for vehicle detection in UAV imagery
- 关键词：
- Image enhancement;Feature extraction;Unmanned aerial vehicles (UAV);Antennas;Aircraft detection;Remote sensing;Adversarial networks;Aerial vehicle;Domain adaptation;Feature extractor;Multi-scale structures;Multi-scales;Remote sensing imagery;Unmanned aerial vehicle imagery;Vehicle images;Vehicles detection
- Zhang, Ruiqian;Newsam, Shawn;Shao, Zhenfeng;Huang, Xiao;Wang, Jiaming;Li, Deren
- 《ISPRS Journal of Photogrammetry and Remote Sensing》
- 2021年
- 180卷
- 期
- 期刊
Vehicle detection in Unmanned Aerial Vehicle (UAV) imagery plays a crucial role in a variety of applications. However, UAVs are usually small, very maneuverable, and can take images from a variety of viewpoints and heights, leading to large differences in vehicle appearance and size. To address the vehicle detection challenge with such diversity in UAV images, we seek to align features between different viewpoints, illumination, weather, and background using remote sensing imagery as an anchor. Following this domain adaptation concept, we propose a multi-scale adversarial network, consisting of a deep convolutional feature extractor, a multi-scale discriminator, and a vehicle detection network. Specifically, the feature extractor is a Siamese network with one path for the UAV imagery and another for the satellite imagery. The shared weights in this sub-network allow us to exploit the large collections of labeled remote sensing imagery for improved vehicle detection in UAV imagery. Experimental results suggest that our proposed algorithm improves the vehicle detection accuracy in the UAVDT dataset and VisDrone dataset. The proposed model achieves great performance in images taken from different perspectives, at different altitudes, and under different imaging situations.© 2021 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS)...