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Photogrammetric Engineering & Remote Sensing最新文献

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Assessment, Specification, and Validation of a Geolocation System's Accuracy and Predicted Accuracy 地理定位系统准确性和预测准确性的评估、规范和验证
Photogrammetric Engineering & Remote Sensing Pub Date : 2024-03-01 DOI: 10.14358/pers.23-00071r2
J. Dolloff, Henry Theiss, Brian Bollin
{"title":"Assessment, Specification, and Validation of a Geolocation System's Accuracy and Predicted Accuracy","authors":"J. Dolloff, Henry Theiss, Brian Bollin","doi":"10.14358/pers.23-00071r2","DOIUrl":"https://doi.org/10.14358/pers.23-00071r2","url":null,"abstract":"This article presents recommendations and corresponding detailed procedures for the assessment of a geolocation system's accuracy, as well as the specification of accuracy requirements and their subsequent validation when they are available. Applicable metrics and related processing\u0000 are based on samples of corresponding geolocation errors. This article also presents similar recommendations for the predicted accuracy of a geolocation system, based on samples of geolocation error, as well as corresponding predicted error covariance matrices associated with the geolocations.\u0000 Reliable error covariance matrices enable optimal use of a geolocation system's products, such as the optimal fusion of multiple geolocations or multiple products for higher confidence and increased accuracy. The recommendations presented in this article enable reliable estimates of accuracy\u0000 and reliable predicted accuracies, both of which are critical to many geolocation-based applications. The recommendations associated with predicted accuracy are also relatively new and innovative.","PeriodicalId":211256,"journal":{"name":"Photogrammetric Engineering & Remote Sensing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140092693","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 GIS 使用技巧
Photogrammetric Engineering & Remote Sensing Pub Date : 2024-03-01 DOI: 10.14358/pers.90.3.133
Shira A. Ellenson, Alma M. Karlin
{"title":"GIS Tips &Tricks","authors":"Shira A. Ellenson, Alma M. Karlin","doi":"10.14358/pers.90.3.133","DOIUrl":"https://doi.org/10.14358/pers.90.3.133","url":null,"abstract":"","PeriodicalId":211256,"journal":{"name":"Photogrammetric Engineering & Remote Sensing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140087450","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
Introduction to Pointcloudmetry by Mathias Lemmens 马蒂亚斯-莱门斯的《点云测量学导论
Photogrammetric Engineering & Remote Sensing Pub Date : 2024-02-01 DOI: 10.14358/pers.90.2.81
Toby M. Terpstra
{"title":"Introduction to Pointcloudmetry by Mathias Lemmens","authors":"Toby M. Terpstra","doi":"10.14358/pers.90.2.81","DOIUrl":"https://doi.org/10.14358/pers.90.2.81","url":null,"abstract":"","PeriodicalId":211256,"journal":{"name":"Photogrammetric Engineering & Remote Sensing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139812539","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
Crop Monitoring System Using MODIS Time-Series Data for Within-Season Prediction of Yield and Production of US Corn and Soybeans 利用 MODIS 时间序列数据进行美国玉米和大豆产量和生产季内预测的作物监测系统
Photogrammetric Engineering & Remote Sensing Pub Date : 2024-02-01 DOI: 10.14358/pers.23-00052r2
Toshihiro Sakamoto
{"title":"Crop Monitoring System Using MODIS Time-Series Data for Within-Season Prediction of Yield and Production of US Corn and Soybeans","authors":"Toshihiro Sakamoto","doi":"10.14358/pers.23-00052r2","DOIUrl":"https://doi.org/10.14358/pers.23-00052r2","url":null,"abstract":"In terms of contribution to global food security, this study aimed to build a crop monitoring system for within-season yield prediction of US corn and soybeans by using the Moderate Resolution Imaging Spectroradiometer (time-series data, which consists of three essential core algorithms\u0000 (crop phenology detection, early crop classification, and crop yield prediction methods)). Within-season predictions for 2018–2022 were then made to evaluate the perfor- mance of the proposed system by comparing it with the United States Department of Agriculture's (USDA's) monthly forecasts\u0000 and the fixed statistical data. The absolute percentage errors of the proposed system for predicting national-level yield and production were less than 5% for all simulation years as of day of year (DOY) 279. The prediction accuracy as of DOY 247 and DOY 279 were comparable to the USDA's forecasts.\u0000 The proposed system would enable us to make a comprehensive understanding about overview of US corn and soybean crop condition by visualizing detail spatial pattern of good- or poor harvest regions on a within-season basis.","PeriodicalId":211256,"journal":{"name":"Photogrammetric Engineering & Remote Sensing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139684710","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 Few-Shot Semi-Supervised Learning Method for Remote Sensing Image Scene Classification 遥感图像场景分类的少镜头半监督学习方法
Photogrammetric Engineering & Remote Sensing Pub Date : 2024-02-01 DOI: 10.14358/pers.23-00067r2
Yuxuan Zhu, Erzhu Li, Zhigang Su, Wei Liu, A. Samat, Yu Liu
{"title":"A Few-Shot Semi-Supervised Learning Method for Remote Sensing Image Scene Classification","authors":"Yuxuan Zhu, Erzhu Li, Zhigang Su, Wei Liu, A. Samat, Yu Liu","doi":"10.14358/pers.23-00067r2","DOIUrl":"https://doi.org/10.14358/pers.23-00067r2","url":null,"abstract":"Few-shot scene classification methods aim to obtain classification discriminative ability from few labeled samples and has recently seen substantial advancements. However, the current few-shot learning approaches still suffer from overfitting due to the scarcity of labeled samples.\u0000 To this end, a few-shot semi-supervised method is proposed to address this issue. Specifically, semi-supervised learning method is used to increase target domain samples; then we train multiple classification models using the augmented samples. Finally, we perform decision fusion of the results\u0000 obtained from the multiple models to accomplish the image classification task. According to the experiments conducted on two real few-shot remote sensing scene datasets, our proposed method achieves significantly higher accuracy (approximately 1.70% to 4.33%) compared to existing counterparts.","PeriodicalId":211256,"journal":{"name":"Photogrammetric Engineering & Remote Sensing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139817374","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
Remote Sensing Application in Water Quality of Lake Burdur, Türkiye 遥感技术在土耳其布尔杜尔湖水质中的应用
Photogrammetric Engineering & Remote Sensing Pub Date : 2024-02-01 DOI: 10.14358/pers.23-00040r2
Aylin Tuzcu Kokal, Meltem Kaçıkoç, N. Musaoğlu, Aysegul Tanik
{"title":"Remote Sensing Application in Water Quality of Lake Burdur, Türkiye","authors":"Aylin Tuzcu Kokal, Meltem Kaçıkoç, N. Musaoğlu, Aysegul Tanik","doi":"10.14358/pers.23-00040r2","DOIUrl":"https://doi.org/10.14358/pers.23-00040r2","url":null,"abstract":"The advancements in space technology have facilitated water quality (WQ) monitoring of lake conditions at a spatial resolution of 10 m by freely accessible Sentinel-2 images. The main aim of this article was to elucidate the necessity of spatiotemporal WQ monitoring of the shrinking\u0000 Lake Burdur in Türkiye by examining the relation between field and satellite data with a state-of-the-art machine learning- based regression algorithm. This study focuses on detection of algal blooms and WQ parameters, which are chlorophyll-a (Chl-a) and suspended solids (SS). Furthermore,\u0000 this study leverages the advantage of geographic position of Lake Burdur, located at the overlap of two Sentinel-2 frames, which enables the acquisition of satellite images at a temporal resolution of 2–3 days. The findings enrich the understanding of the lake's dynamic structure by\u0000 rapidly monitoring the occurrence of algal blooms. High accuracies were achieved for Chl-a (R-squared: 0.93) and SS (R-squared: 0.94) detection.","PeriodicalId":211256,"journal":{"name":"Photogrammetric Engineering & Remote Sensing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139823892","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
Sector Insight.org– The Value of Membership in the American Society for Photogrammetry and Remote Sensing Sector Insight.org- 美国摄影测量与遥感学会会员资格的价值
Photogrammetric Engineering & Remote Sensing Pub Date : 2024-02-01 DOI: 10.14358/pers.90.2.79
Robert Ryerson, Brian Huberty, Lauren McKinney-Wise, Hamdy Elsayed
{"title":"Sector Insight.org– The Value of Membership in the American Society for Photogrammetry and Remote Sensing","authors":"Robert Ryerson, Brian Huberty, Lauren McKinney-Wise, Hamdy Elsayed","doi":"10.14358/pers.90.2.79","DOIUrl":"https://doi.org/10.14358/pers.90.2.79","url":null,"abstract":"","PeriodicalId":211256,"journal":{"name":"Photogrammetric Engineering & Remote Sensing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139885950","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
Sector Insight.org– The Value of Membership in the American Society for Photogrammetry and Remote Sensing Sector Insight.org- 美国摄影测量与遥感学会会员资格的价值
Photogrammetric Engineering & Remote Sensing Pub Date : 2024-02-01 DOI: 10.14358/pers.90.2.79
Robert Ryerson, Brian Huberty, Lauren McKinney-Wise, Hamdy Elsayed
{"title":"Sector Insight.org– The Value of Membership in the American Society for Photogrammetry and Remote Sensing","authors":"Robert Ryerson, Brian Huberty, Lauren McKinney-Wise, Hamdy Elsayed","doi":"10.14358/pers.90.2.79","DOIUrl":"https://doi.org/10.14358/pers.90.2.79","url":null,"abstract":"","PeriodicalId":211256,"journal":{"name":"Photogrammetric Engineering & Remote Sensing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139826028","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 Few-Shot Semi-Supervised Learning Method for Remote Sensing Image Scene Classification 遥感图像场景分类的少镜头半监督学习方法
Photogrammetric Engineering & Remote Sensing Pub Date : 2024-02-01 DOI: 10.14358/pers.23-00067r2
Yuxuan Zhu, Erzhu Li, Zhigang Su, Wei Liu, A. Samat, Yu Liu
{"title":"A Few-Shot Semi-Supervised Learning Method for Remote Sensing Image Scene Classification","authors":"Yuxuan Zhu, Erzhu Li, Zhigang Su, Wei Liu, A. Samat, Yu Liu","doi":"10.14358/pers.23-00067r2","DOIUrl":"https://doi.org/10.14358/pers.23-00067r2","url":null,"abstract":"Few-shot scene classification methods aim to obtain classification discriminative ability from few labeled samples and has recently seen substantial advancements. However, the current few-shot learning approaches still suffer from overfitting due to the scarcity of labeled samples.\u0000 To this end, a few-shot semi-supervised method is proposed to address this issue. Specifically, semi-supervised learning method is used to increase target domain samples; then we train multiple classification models using the augmented samples. Finally, we perform decision fusion of the results\u0000 obtained from the multiple models to accomplish the image classification task. According to the experiments conducted on two real few-shot remote sensing scene datasets, our proposed method achieves significantly higher accuracy (approximately 1.70% to 4.33%) compared to existing counterparts.","PeriodicalId":211256,"journal":{"name":"Photogrammetric Engineering & Remote Sensing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139876950","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
The Sight-Aesthetic Value of the Underwater Landscapes of Lakes in the Context of Exploration Tourism 探险旅游背景下湖泊水下景观的视觉审美价值
Photogrammetric Engineering & Remote Sensing Pub Date : 2024-02-01 DOI: 10.14358/pers.23-00054r2
P. Dynowski, A. Źróbek-Sokolnik, Marta Czaplicka, Adam Senetra
{"title":"The Sight-Aesthetic Value of the Underwater Landscapes of Lakes in the Context of Exploration Tourism","authors":"P. Dynowski, A. Źróbek-Sokolnik, Marta Czaplicka, Adam Senetra","doi":"10.14358/pers.23-00054r2","DOIUrl":"https://doi.org/10.14358/pers.23-00054r2","url":null,"abstract":"The aim of the study is to identify factors affecting the sight-aesthetic value of the underwater landscapes of lakes for the purposes of exploration tourism. The reason for undertaking this topic is the lack of such studies for inland water bodies. The results will contribute to expanding\u0000 and supplementing the knowledge on the assessment of the sight-aesthetic attractiveness of landscapes and fill gaps in knowledge about the underwater landscapes of lakes. The questionnaire survey implemented the direct comparison method described by Kendall (Kendall, M. G. 1970. Rank Correlation\u0000 Methods. Charles Griffin and Co: Glasgow, Scotland). According to respondents, animals and submerged anthropogenic elements are the most visually attractive in an aquatic environment The results obtained are the reason for conducting further research and developing the methodology for\u0000 the assessment of the sight-aesthetic value of inland bodies of water based on the experience of terrestrial landscape researchers.","PeriodicalId":211256,"journal":{"name":"Photogrammetric Engineering & Remote Sensing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139885148","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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