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Photogrammetric Engineering & Remote Sensing最新文献

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Edge Detection Method for High-Resolution Remote Sensing Imagery by Combining Superpixels with Dual-Threshold Edge Tracking 基于超像素和双阈值边缘跟踪的高分辨率遥感图像边缘检测方法
Photogrammetric Engineering & Remote Sensing Pub Date : 2023-08-01 DOI: 10.14358/pers.23-00003r2
Yanxiong Liu, Zhipeng Dong, Yikai Feng, Yilan Chen, Long Yang
{"title":"Edge Detection Method for High-Resolution Remote Sensing Imagery by Combining Superpixels with Dual-Threshold Edge Tracking","authors":"Yanxiong Liu, Zhipeng Dong, Yikai Feng, Yilan Chen, Long Yang","doi":"10.14358/pers.23-00003r2","DOIUrl":"https://doi.org/10.14358/pers.23-00003r2","url":null,"abstract":"Edge detection in high-spatial-resolution remote sensing images (HSRIs ) is a key technology for automatic extraction, analysis, and understanding of image information. With respect to the problem of fake edges in image edge detection caused by image noise and the phenomenon of the\u0000 same class objects reflecting different spectra, this article proposes a novel edge detection method for HSRIs by combin- ing superpixels with dual-threshold edge tracking. First, the image is smoothed using the simple linear iterative clustering algorithm to eliminate the influence of image\u0000 noise and the phenomenon of the same class objects reflecting different spectra on image edge detec - tion. Second, initial edge detection results of the image are obtained using the dual-threshold edge tracking algorithm. Finally, the initial image edge detection results are post-processed\u0000 by removing the burrs and extracting skeleton lines to obtain accurate edge detection results. The experimental results confirm that the proposed method outperforms the others and can obtain smooth, continuous, and single-pixel response edge detection results for HSRIs .","PeriodicalId":211256,"journal":{"name":"Photogrammetric Engineering & Remote Sensing","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128147827","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
GIS Automated Delineation of Hospital Service Areas by Fahui Wang and Changzhen Wang GIS对医院服务区域的自动圈定
Photogrammetric Engineering & Remote Sensing Pub Date : 2023-08-01 DOI: 10.14358/pers.89.8.465
D. Zourarakis
{"title":"GIS Automated Delineation of Hospital Service Areas by Fahui Wang and Changzhen Wang","authors":"D. Zourarakis","doi":"10.14358/pers.89.8.465","DOIUrl":"https://doi.org/10.14358/pers.89.8.465","url":null,"abstract":"","PeriodicalId":211256,"journal":{"name":"Photogrammetric Engineering & Remote Sensing","volume":"124 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128061186","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
Expansion of Urban Impervious Surfaces in Lahore (1993–2022) Based on Gee and Remote Sensing Data 基于Gee和遥感数据的拉合尔城市不透水面扩展研究
Photogrammetric Engineering & Remote Sensing Pub Date : 2023-08-01 DOI: 10.14358/pers.23-00001r2
Z. Shao, Muhammad Nasar Ahmad, Akib Javed, F. Islam, Zahid Jahangir, Israr Ahmad
{"title":"Expansion of Urban Impervious Surfaces in Lahore (1993–2022) Based on Gee and Remote Sensing Data","authors":"Z. Shao, Muhammad Nasar Ahmad, Akib Javed, F. Islam, Zahid Jahangir, Israr Ahmad","doi":"10.14358/pers.23-00001r2","DOIUrl":"https://doi.org/10.14358/pers.23-00001r2","url":null,"abstract":"Impervious surfaces are an essential component of our environment and are mainly triggered by human developments. Rapid urbanization and population expansion have increased Lahore's urban impervious surface area. This research is based on estimating the urban imper- vious surface area\u0000 ( uisa ) growth from 1993 to 2022. Therefore, we aimed to generate an accurate urban impervious surfaces area map based on Landsat time series data on Google Earth Engine ( gee ). We have used a novel global impervious surface area index ( gisai ) for impervious surface area ( uisa ) extraction.\u0000 The gisai accomplished significant results, with an average overall accuracy of 90.93% and an average kappa coefficient of 0.78. We also compared the results of gisai with Global Human Settlement Layer-Built and harmonized nighttime light ( ntl ) isa data products. The accuracy assessment\u0000 and cross-validation of uisa results were performed using ground truth data on ArcGIS and gee. Our research findings revealed that the spatial extent of uisa increased by 198.69 km2 from 1993 to 2022 in Lahore. Additionally, the uisa has increased at an average growth rate of 39.74\u0000 km2. The gisai index was highly accurate at extract- ing uisa and can be used for other cities to map impervious surface area growth. This research can help urban planners and policymak- ers to delineate urban development boundaries. Also, there should be controlled urban expansion\u0000 policies for sustainable metropolis and should use less impermeable materials for future city developments.","PeriodicalId":211256,"journal":{"name":"Photogrammetric Engineering & Remote Sensing","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122660441","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: 0
Small Object Detection in Remote Sensing Images Based on Window Self-Attention Mechanism 基于窗口自关注机制的遥感图像小目标检测
Photogrammetric Engineering & Remote Sensing Pub Date : 2023-08-01 DOI: 10.14358/pers.23-00004r3
Jiaxin Xu, Qiao Zhang, Yu Liu, Mengting Zheng
{"title":"Small Object Detection in Remote Sensing Images Based on Window Self-Attention Mechanism","authors":"Jiaxin Xu, Qiao Zhang, Yu Liu, Mengting Zheng","doi":"10.14358/pers.23-00004r3","DOIUrl":"https://doi.org/10.14358/pers.23-00004r3","url":null,"abstract":"For remorte sensing image object detection tasks in the small object feature, extraction ability is insufficient and difficult to locate, and other problems. This paper proposes an improved algorithm for small object detection in remote sensing images based on a window self-attention\u0000 mechanism. On the basis of You Only Look Once (YOLO)v5s, a shallow feature extraction layer with four times downsampling is added to the feature fusion pyramid and the window self-attention mechanism is added to the Path Aggregation Network. Experiments show that the improved model obtained\u0000 the Mean Average Precision (mAP) of 78.3% and 91.8% on the DIOR and Remote Sensing Object Detection public data sets with frames per second of 65 and 51, respectively. Compared with the basal YOLOv5s network, the mAP has improved by 5.8% and 3.3%, respectively. Compared with other object detection\u0000 methods, the detection accuracy and real-time performance have been improved.","PeriodicalId":211256,"journal":{"name":"Photogrammetric Engineering & Remote Sensing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129896549","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: 0
SectorInsight.com —The Journey from a Ph.D. to a Successful Company SectorInsight.com -从博士到成功公司的旅程
Photogrammetric Engineering & Remote Sensing Pub Date : 2023-07-01 DOI: 10.14358/pers.89.7.401
K. Lim
{"title":"SectorInsight.com —The Journey from a Ph.D. to a Successful Company","authors":"K. Lim","doi":"10.14358/pers.89.7.401","DOIUrl":"https://doi.org/10.14358/pers.89.7.401","url":null,"abstract":"","PeriodicalId":211256,"journal":{"name":"Photogrammetric Engineering & Remote Sensing","volume":"89 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115442653","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: 0
Classifying Building Roof Damage Using High Resolution Imagery for Disaster Recovery 基于高分辨率图像的建筑屋顶损伤分类
Photogrammetric Engineering & Remote Sensing Pub Date : 2023-07-01 DOI: 10.14358/pers.22-00106r2
E. Gonsoroski, Y. Ahn, E. Harville, Nathaniel Countess, M. Lichtveld, K. Pan, L. Beitsch, S. Sherchan, C. Uejio
{"title":"Classifying Building Roof Damage Using High Resolution Imagery for Disaster Recovery","authors":"E. Gonsoroski, Y. Ahn, E. Harville, Nathaniel Countess, M. Lichtveld, K. Pan, L. Beitsch, S. Sherchan, C. Uejio","doi":"10.14358/pers.22-00106r2","DOIUrl":"https://doi.org/10.14358/pers.22-00106r2","url":null,"abstract":"Post-hurricane damage assessments are often costly and time-consuming. Remotely sensed data provides a complementary method of data collection that can be completed comparatively quickly and at relatively low cost. This study focuses on 15 Florida counties impacted by Hurricane Michael\u0000 (2018), which had category 5 strength winds at landfall. The present study evaluates the ability of aerial imagery collected to cost-effectively measure blue tarps on buildings for disaster impact and recovery. A support vector machine model classified blue tarp, and parcels received a damage\u0000 indicator based on the model's prediction. The model had an overall accuracy of 85.3% with a sensitivity of 74% and a specificity of 96.7%. The model results indicated approximately 7% of all parcels (27 926 residential and 4431 commercial parcels) in the study area as having blue tarp present.\u0000 The study results may benefit jurisdictions that lacked financial resources to conduct on-the-ground damage assessments.","PeriodicalId":211256,"journal":{"name":"Photogrammetric Engineering & Remote Sensing","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114807598","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: 0
GIS Tips & Tricks — File Navigation is Easier than You Think GIS提示和技巧-文件导航比你想象的更容易
Photogrammetric Engineering & Remote Sensing Pub Date : 2023-07-01 DOI: 10.14358/pers.89.7.407
Alma M. Karlin
{"title":"GIS Tips & Tricks — File Navigation is Easier than You Think","authors":"Alma M. Karlin","doi":"10.14358/pers.89.7.407","DOIUrl":"https://doi.org/10.14358/pers.89.7.407","url":null,"abstract":"","PeriodicalId":211256,"journal":{"name":"Photogrammetric Engineering & Remote Sensing","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124590612","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: 0
Estimation of the Forest Stand Biomass and Greenhouse Gas Emissions Using Lidar Surveys 利用激光雷达测量估算林分生物量和温室气体排放
Photogrammetric Engineering & Remote Sensing Pub Date : 2023-07-01 DOI: 10.14358/pers.23-00006r2
R. Sultanova, R. Mustafin
{"title":"Estimation of the Forest Stand Biomass and Greenhouse Gas Emissions Using Lidar Surveys","authors":"R. Sultanova, R. Mustafin","doi":"10.14358/pers.23-00006r2","DOIUrl":"https://doi.org/10.14358/pers.23-00006r2","url":null,"abstract":"At the research points, the relationship between the Normalized Difference Vegetation and Normalized Green Red Difference indices is characterized by a determination coefficient equal to 0.52. The estimation of the emission of carbon dioxide and nitrogen oxide in the forest air at an\u0000 altitude of 40 m above the level of the soil cover during the growing season showed differences in their values during the daytime and at night. The results helped determine promising methods of inventory of the carbon landfill forest area for aboveground woody biomass assessment based on\u0000 data obtained from several sources and land forest estimation research. The research involved: 1) integration of an unmanned aerial vehicle -based digital camera and lidar sensors in order to optimize the efficiency and cost of data collection; 2) taking advantage of high-resolution aerial\u0000 photographs and sparse lidar point clouds using an information fusion approach and the ability to compensate for their shortcomings.","PeriodicalId":211256,"journal":{"name":"Photogrammetric Engineering & Remote Sensing","volume":"293 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115282180","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: 0
A Lightweight Conditional Convolutional Neural Network for Hyperspectral Image Classification 一种用于高光谱图像分类的轻量级条件卷积神经网络
Photogrammetric Engineering & Remote Sensing Pub Date : 2023-07-01 DOI: 10.14358/pers.22-00130r2
Linfeng Wu, Huajun Wang, Huiqing Wang
{"title":"A Lightweight Conditional Convolutional Neural Network for Hyperspectral Image Classification","authors":"Linfeng Wu, Huajun Wang, Huiqing Wang","doi":"10.14358/pers.22-00130r2","DOIUrl":"https://doi.org/10.14358/pers.22-00130r2","url":null,"abstract":"Deep learning (dl), especially convolutional neural networks (cnns), has been proven to be an excellent feature extractor and widely applied to hyperspectral image (hsi) classification. However, dl is a computationally demanding algorithm with many parameters and a high computational\u0000 burden, which seriously restricts the deployment of dl-based hsi classification algorithms on mobile and embedded systems. In this paper, we propose an extremely lightweight conditional three-dimensional (3D) hsi with a double-branch structure to solve these problems. Specifically,\u0000 we introduce a lightweight conditional 3D convolution to replace the conventional 3D convolution to reduce the computational and memory cost of the network and achieve flexible hsi feature extraction. Then, based on lightweight conditional 3D convolution, we build two parallel paths\u0000 to independently exploit and optimize the diverse spatial and spectral features. Furthermore, to precisely locate the key information, which is conducive to classification, a lightweight attention mechanism is carefully designed to refine extracted spatial and spectral features, and improve\u0000 the classification accuracy with less computation and memory costs. Experiments on three public hsi data sets show that the proposed model can effectively reduce the cost of computation and memory, achieve high execution speed, and better classification performance compared with several\u0000 recent dl-based models.","PeriodicalId":211256,"journal":{"name":"Photogrammetric Engineering & Remote Sensing","volume":"119 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123478031","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: 0
Book Review: Fundamentals of Capturing and Processing Drone Imagery and Data. Edited by Amy E. Frazier and Kunwar K. Singh 书评:捕捉和处理无人机图像和数据的基本原理。Amy E. Frazier和Kunwar K. Singh编辑
Photogrammetric Engineering & Remote Sensing Pub Date : 2023-07-01 DOI: 10.14358/pers.89.7.405
Kathryn M. Rocheford
{"title":"Book Review: Fundamentals of Capturing and Processing Drone Imagery and Data. Edited by Amy E. Frazier and Kunwar K. Singh","authors":"Kathryn M. Rocheford","doi":"10.14358/pers.89.7.405","DOIUrl":"https://doi.org/10.14358/pers.89.7.405","url":null,"abstract":"","PeriodicalId":211256,"journal":{"name":"Photogrammetric Engineering & Remote Sensing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129434754","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: 0
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