2021 28th International Conference on Geoinformatics最新文献_第3页

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2021 28th International Conference on Geoinformatics Pub Date : 2021-11-03 DOI: 10.1109/ieeeconf54055.2021.9687636

引用次数: 0

The Construction And Precision Analysis Of The Three - Dimensional Oblique Photogrammetry Model 三维倾斜摄影测量模型的构建与精度分析

2021 28th International Conference on Geoinformatics Pub Date : 2021-11-03 DOI: 10.1109/ieeeconf54055.2021.9687641

Wenfei Xi, Xiao-qing Zuo, Bo Xiao, Jiang Zhu, Di Zhou

引用次数: 0

Research of Forest Fire Points Detection Method Based on MODIS Active Fire Product 基于MODIS活火产品的森林火点探测方法研究

2021 28th International Conference on Geoinformatics Pub Date : 2021-11-03 DOI: 10.1109/ieeeconf54055.2021.9687646

Jie Wang, Guanghui Wang, Jianwei Qi, Yu Liu, Wei Zhang

{"title":"Research of Forest Fire Points Detection Method Based on MODIS Active Fire Product","authors":"Jie Wang, Guanghui Wang, Jianwei Qi, Yu Liu, Wei Zhang","doi":"10.1109/ieeeconf54055.2021.9687646","DOIUrl":"https://doi.org/10.1109/ieeeconf54055.2021.9687646","url":null,"abstract":"Forest fire is a common natural disaster, which has a great threat to ecological and human life safety. Compared with the traditional monitoring method, Satellite remote sensing can provide more timely and large-area monitoring in the process of early detection, dynamic tracking, and disaster assessment of forest fires. This paper proposed a forest fire detection method based on MODIS active fire products, by adding Normalized vegetation index (NDVI), slope, elevation, and other factors as identification conditions. To verify the reliability of the proposed method, this paper used the MODIS active fire products data in China in July 2018, the identification accuracy was up to 88.94%, and the missing detection rates were only 4.25%, the error was mainly due to the low spatial resolution of MODIS data. The validation results showed that the overall accuracy of the proposed method was very satisfactory, which can meet the real-time early warning of a forest fire. Moreover, taking a forest fire that occurred in Qinyuan County, Shanxi Province as an example, the paper analyzed how to use the identified forest fire points to monitor the fire and make fire-fighting plans, which proved that using the fire points data can provide scientific bases for forest fire monitoring and extinguishing.","PeriodicalId":171165,"journal":{"name":"2021 28th International Conference on Geoinformatics","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126035510","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

A Risk Assessment Approach of World Heritage Sites Based on RS and GIS: —the cases studies of Mount Emei 基于RS和GIS的世界遗产地风险评估方法——以峨眉山为例

2021 28th International Conference on Geoinformatics Pub Date : 2021-11-03 DOI: 10.1109/ieeeconf54055.2021.9687651

Shiman Huang, Qingwu Hu, Shaohua Wang

引用次数: 0

SMART-IMPALA: Efficient Querying of hyper Massive Spatiotemporal Trajectory Data SMART-IMPALA:超大海量时空轨迹数据的高效查询

2021 28th International Conference on Geoinformatics Pub Date : 2021-11-03 DOI: 10.1109/ieeeconf54055.2021.9687505

Lianjie Zhou, Wei Tu, Qingquan Li

{"title":"SMART-IMPALA: Efficient Querying of hyper Massive Spatiotemporal Trajectory Data","authors":"Lianjie Zhou, Wei Tu, Qingquan Li","doi":"10.1109/ieeeconf54055.2021.9687505","DOIUrl":"https://doi.org/10.1109/ieeeconf54055.2021.9687505","url":null,"abstract":"Efficient sharing of hyper massive spatiotemporal trajectory data (HMSTD) is the foundation for establishing large-scale perception infrastructure, such as vehicle monitoring network in a smart city containing New York, Tokyo, Beijing, and Shanghai these megacities. Consequently, the daily trajectory data scale of vehicle monitoring networks in the smart city is growing rapidly, reaching daily volumes of 1 billion. Accessing HMSTD in transport, the Internet of Things, or other fields is hard and limited under the present spatiotemporal data indexing methods. Therefore, we propose a path-divided Hadoop Distributed File System (HDFS) data blocking (SMART) based on the Apache Impala (SMART -Impala) method to optimize the efficient access method of HMSTD to improve the efficiency of hyperdata sharing. Apache Impala, as a practical and powerful distributed data access means for massive data stored in memory, is widely applied in massive data sharing. In Smart-Impala, the spatiotemporal trajectory data retrieve capability of Impala is extended. Besides, a self-adaption parquet data partitioning strategy or pattern is proposed. In experiments, the Shenzhen BeiDou (BD) bus network is selected as the experimental scenario, consisting of 35809 buses equipped with BD positioning sensors, creating 1.03 billion data records each day. The buses distribution in Shenzhen city is achieved from 7:00 a.m. to 9:00 a.m. and 11:00 a.m. to 01:00 p.m. Moreover, SMART-Impala achieves approximately 8 times, 9 times, 29 times, 110 times higher performance than that in MongoDB or HBase in data scales of 10 million, 100 million, 500 million, 1 billion, whose results outperform that of the average division in Impala, MongoDB, and HBase methods.","PeriodicalId":171165,"journal":{"name":"2021 28th International Conference on Geoinformatics","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130106272","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Evaluation of Habitat Quality in Lanzhou Region Based on InVEST Model 基于InVEST模型的兰州地区生境质量评价

2021 28th International Conference on Geoinformatics Pub Date : 2021-11-03 DOI: 10.1109/ieeeconf54055.2021.9687658

Yichuan Liu, Baorong Xu, Qingwu Hu, Jiansong Li

{"title":"Evaluation of Habitat Quality in Lanzhou Region Based on InVEST Model","authors":"Yichuan Liu, Baorong Xu, Qingwu Hu, Jiansong Li","doi":"10.1109/ieeeconf54055.2021.9687658","DOIUrl":"https://doi.org/10.1109/ieeeconf54055.2021.9687658","url":null,"abstract":"Properly handling the relationship between land use patterns and habitat quality in arid and semi-arid ecologically fragile cities is of vital importance to the formulation of sustainable development strategies. Based on the land use data in 2000 and 2015 of Lanzhou, the InVEST model is used to measure its habitat quality and scarcity, and the land transfer matrix is used to analyze the spatial agglomeration and distribution of habitat quality. The results show that the value of habitat degradation has gradually changed from the low value in a wide range at the center to a scattered high value at the boundary. And the highest value at the boundary decreased significantly from 151 to 132. The overall habitat quality is poor but not much change. The spatial distribution of habitat quality is related to the urban pattern under the “Fourth Edition of the General Regulations”, it tends to increase in agglomeration because the distribution of habitat types are “High-High” and “Low-Low”. and the colder and hotter spots transform to the coldest and hottest spots. The overall quality of the habitat is stable. The scarce habitat types are mainly concentrated in the grassland. So the Lanzhou region must coordinate social and ecological construction.","PeriodicalId":171165,"journal":{"name":"2021 28th International Conference on Geoinformatics","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126817632","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

Evaluating Road Network Capacity in the Semantic Geospatial Sensor Web 基于语义地理空间传感器网络的道路网络容量评估

2021 28th International Conference on Geoinformatics Pub Date : 2021-11-03 DOI: 10.1109/ieeeconf54055.2021.9687506

Rou Jiang, Sirui Yan, Jiangwei Chen, Shuohong Xie, Yiming Yang, Xiaoliang Meng, Yuchun Huang

引用次数: 1

Wetland degradation monitoring using time series of multi-sensor data: A case study of Yangtze River 基于多传感器时间序列的湿地退化监测——以长江湿地为例

2021 28th International Conference on Geoinformatics Pub Date : 2021-11-03 DOI: 10.1109/ieeeconf54055.2021.9687637

Jinquan Ai, Chunmei Niu, Jiangtao Zhu, Huangjing Li, Lijuan Chen

{"title":"Wetland degradation monitoring using time series of multi-sensor data: A case study of Yangtze River","authors":"Jinquan Ai, Chunmei Niu, Jiangtao Zhu, Huangjing Li, Lijuan Chen","doi":"10.1109/ieeeconf54055.2021.9687637","DOIUrl":"https://doi.org/10.1109/ieeeconf54055.2021.9687637","url":null,"abstract":"Effective monitoring and assessment of land degradation are essential for the land manager and decision-makers to make optimal land management decisions. This work aims to present a methodology to monitor land degradation in the Chongming Dongtan wetland, where wetland degradation and plant invasions have been observed in the past few decades. Time series of multi-sensor imagery from 2013 to 2016 were selected to identify the rate and status of land degradation due to reclamation based on land cover classification and change detection techniques. Results showed that the overall accuracy of each image classification was higher than 80% and Kappa statistics of agreement more than 0.74. The distribution maps of land degradation in each period were generated respectively based on the classification and change detection results. Coastal wetlands decline, biodiversity loss and wetland hydrological regime change are the main degraded types. Although climate change plays an important role, human activities especially via large-scale reclamations are more directly impacted by land degradation in the study area.","PeriodicalId":171165,"journal":{"name":"2021 28th International Conference on Geoinformatics","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116598115","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Image enhancement and image matching of UAV based on histogram equalization 基于直方图均衡化的无人机图像增强与图像匹配

2021 28th International Conference on Geoinformatics Pub Date : 2021-11-03 DOI: 10.1109/ieeeconf54055.2021.9687650

Jingchun Zhou, Wenfei Xi, Dongsheng Li, Hongzhi Huang

引用次数: 0

Discussion on the Practice of Data Processing of GNSS Precision Point Positioning GNSS精密点定位数据处理实践探讨

2021 28th International Conference on Geoinformatics Pub Date : 2021-11-03 DOI: 10.1109/ieeeconf54055.2021.9687661

Xiliu Yang, Jiudong Yang

引用次数: 1