Photogrammetric Engineering & Remote Sensing最新文献_第6页

Quantifying Impacts of Regional Multiple Factors on Spatiotemporal the Mechanisms for Spatio-temporal changes of Net Primary Vegetation Productivity and Net Ecosystem Productivity: An Example in the Jianghuai River Basin, China 量化区域多重因素对净初级植被生产力和净生态系统生产力时空变化机制的影响：以中国江淮流域为例

Photogrammetric Engineering & Remote Sensing Pub Date : 2023-12-01 DOI: 10.14358/pers.23-00017r2

Huimin Chen, Benlin Wang, Liangfeng Zheng, ZhengAmirReza Shahtahmassebi

{"title":"Quantifying Impacts of Regional Multiple Factors on Spatiotemporal the Mechanisms for Spatio-temporal changes of Net Primary Vegetation Productivity and Net Ecosystem Productivity: An Example in the Jianghuai River Basin, China","authors":"Huimin Chen, Benlin Wang, Liangfeng Zheng, ZhengAmirReza Shahtahmassebi","doi":"10.14358/pers.23-00017r2","DOIUrl":"https://doi.org/10.14358/pers.23-00017r2","url":null,"abstract":"Despite much valuable research on the mechanisms for spatio-temporal changesof net primary vegetation productivity (NPP) and net ecosystem productivity (NEP), there is a paucity of information on assessing impacts of regional multiple factors on spatiotemporal researchs of NPP and NEP\u0000 in the complex environment. This study attempts to bridge this information gap using the Jianghuai Basin in China as a case study. Using a field campaign, remotely sensed imagery, socioeconomic data, and meteorological parameters, we developed a framework based on the Carnegie‐Ames‐Stanford\u0000 Approach (CASA) model, correlation technique, trend analysis, and landscape metrics to measure spatiotemporal changes in NPP and NEP from 2001 to 2018. The derived changes were then linked to regional multiple factors including climate, landscape factors, human activity, and land use change.\u0000 The results of the research can provide a scientific basis for vegetation evaluation, ecosystem assessment, and other aspects of the region.","PeriodicalId":211256,"journal":{"name":"Photogrammetric Engineering & Remote Sensing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138618121","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}

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IMU and Bluetooth Data Fusion to Achieve Submeter Position Accuracy in Indoor Positioning IMU 和蓝牙数据融合实现室内定位的亚米级定位精度

Photogrammetric Engineering & Remote Sensing Pub Date : 2023-12-01 DOI: 10.14358/pers.23-00034r2

Ugur Acar

引用次数: 0

GIS Tips & Tricks ‐ Tired of Distributing Multiple “shapefiles”? Try a GeoPackage GIS 使用技巧 - 厌倦了分发多个 "形状文件"？试试 GeoPackage

Photogrammetric Engineering & Remote Sensing Pub Date : 2023-12-01 DOI: 10.14358/pers.89.12.725

Alma M. Karlin

引用次数: 0

Combination of Terrestrial Laser Scanning and Unmanned Aerial Vehicle Photogrammetry for Heritage Building Information Modeling: A Case Study of Tarsus St. Paul Church 地面激光扫描与无人机摄影测量相结合用于遗产建筑信息建模：塔尔苏斯圣保罗教堂案例研究

Photogrammetric Engineering & Remote Sensing Pub Date : 2023-12-01 DOI: 10.14358/pers.23-00031r2

Şafak Fidan, A. Ulvi, Abdurahman Yasin Yiğit, Seda Nur Gamze Hamal, Murat Yakar

{"title":"Combination of Terrestrial Laser Scanning and Unmanned Aerial Vehicle Photogrammetry for Heritage Building Information Modeling: A Case Study of Tarsus St. Paul Church","authors":"Şafak Fidan, A. Ulvi, Abdurahman Yasin Yiğit, Seda Nur Gamze Hamal, Murat Yakar","doi":"10.14358/pers.23-00031r2","DOIUrl":"https://doi.org/10.14358/pers.23-00031r2","url":null,"abstract":"Cultural heritage building information modeling (HBIM) is an emerging process allowing us to reconstruct built heritage virtually. The data of a digitally documented cultural heritage building offers significant advantages as it is accessible and modifiable by all professionals involved\u0000 in the same or different projects. The most important factor affecting the accuracy and precision of the HBIM model is the ability to collect complete and accurate information about the physical structure. Combining terrestrial laser scanning (TLS) and unmanned aerial vehicle (UAV) photogrammetry\u0000 point clouds is one of the most efficient ways to capture accurate digital data on the building. This study provides the foundation for creating an HBIM model for cultural heritage the coupling of spatial data with TLS and UAV. This paper aims to generate synergy between TLS and UAV point\u0000 cloud data and ensure that the spatial database contains sufficient data to model historical objects with HBIM tendencies.","PeriodicalId":211256,"journal":{"name":"Photogrammetric Engineering & Remote Sensing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138616508","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

Leveraging NAIP Imagery for Accurate Large-Area Land Use/land Cover Mapping: A Case Study in Central Texas 利用NAIP图像进行精确的大面积土地利用/土地覆盖制图:德克萨斯州中部的案例研究

Photogrammetric Engineering & Remote Sensing Pub Date : 2023-09-01 DOI: 10.14358/pers.22-00123r2

M. Subedi, Carlos Portillo-Quintero, S. Kahl, N. McIntyre, R. Cox, Gad Perry

{"title":"Leveraging NAIP Imagery for Accurate Large-Area Land Use/land Cover Mapping: A Case Study in Central Texas","authors":"M. Subedi, Carlos Portillo-Quintero, S. Kahl, N. McIntyre, R. Cox, Gad Perry","doi":"10.14358/pers.22-00123r2","DOIUrl":"https://doi.org/10.14358/pers.22-00123r2","url":null,"abstract":"Large-area land use land cover (LULC) mapping using high-resolution imagery remains challenging due to radiometric differences between scenes, the low spectral depth of the imagery, landscape heterogeneity, and computational limitations. Using a random forest (RF)- supervised machine-learning\u0000 algorithm, we present a geographic object-based image analysis approach to classifying a large mosaic of 220 National Agriculture Imagery Program orthoimagery into lulc categories. The approach was applied in central Texas, USA, covering over 6000 km2. We generated 36 variables for each object\u0000 and accounted for spatial structures of sample data to determine the distance at which samples were spatially independent. The final rf model produced 94.8% accuracy on independent stratified random samples. In addition, vegetation and water indices, the mean and standard deviation of principal\u0000 components, and texture features improved classification accuracy. This study demonstrates a cost-effective way of producing an accurate multi-class land use/land cover map using high-spatial/low-spectral resolution orthoimagery.","PeriodicalId":211256,"journal":{"name":"Photogrammetric Engineering & Remote Sensing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121774857","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

Mapping Matters - Your Questions Answered 映射问题-回答您的问题

Photogrammetric Engineering & Remote Sensing Pub Date : 2023-09-01 DOI: 10.14358/pers.89.9.521

Q. Abdullah

引用次数: 0

CFAR Edge Detection Using Hysteresis Thresholding for Polarimetric SAR Imagery 基于滞后阈值的极化SAR图像CFAR边缘检测

Photogrammetric Engineering & Remote Sensing Pub Date : 2023-09-01 DOI: 10.14358/pers.22-00129r2

C. Niu, Wanjie Lu, Wei Liu, T. Hu, Shiju Wang, Yajie Wu

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Effect of Latitude As a Significant Element on the Results of Direct UTM Coordinates Transformation Method 纬度对直接UTM坐标变换结果的影响

Photogrammetric Engineering & Remote Sensing Pub Date : 2023-09-01 DOI: 10.14358/pers.22-00125r2

M. Jassim, Darin Mohammed Tofiq Mohammed

{"title":"Effect of Latitude As a Significant Element on the Results of Direct UTM Coordinates Transformation Method","authors":"M. Jassim, Darin Mohammed Tofiq Mohammed","doi":"10.14358/pers.22-00125r2","DOIUrl":"https://doi.org/10.14358/pers.22-00125r2","url":null,"abstract":"The transformation of global navigation satellite systems coordi- nates between any two datums represents a vital procedure. Although the geocentric coordinates (X, Y, Z) of two datums can be trans- formed using the 7-parameters method, the conversion of Universal Transverse Mercator\u0000 (UTM) projected coordinates (E, N) between two systems cannot be applied with the same procedure. However, see Jassim (2022), which discusses a method that allows the transformation between any two datums using the utm projected coordinates directly regarding the variation of the datum's semi-major\u0000 axis and the eccentricity. The results of the evaluation of this method show that there is a significant shift in the transformed coordinates due to the imperfection of the used algorithm. While this research suggests a modification in the previous algorithm by adding the latitude's variation\u0000 as a third significant factor besides the other two variations (∂a, ∂e2, and Δ), the suggested modification gives a high decline in the uncertainty of the position values. Furthermore, it takes a homogenous fixed limit for different places over Iraqi territory.","PeriodicalId":211256,"journal":{"name":"Photogrammetric Engineering & Remote Sensing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132474767","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

DORSL-FIN: A Self-supervised Neural Network for Recovering Missing Bathymetry from ICESat-2 基于自监督神经网络的ICESat-2测深数据恢复

Photogrammetric Engineering & Remote Sensing Pub Date : 2023-09-01 DOI: 10.14358/pers.23-00011r2

Forrest Corcoran, Christopher E. Parrish

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GIS Tips & Tricks - When Color Matters GIS提示和技巧-当颜色很重要

Photogrammetric Engineering & Remote Sensing Pub Date : 2023-09-01 DOI: 10.14358/pers.89.9.525

Alma M. Karlin

引用次数: 0

Photogrammetric Engineering &amp; Remote Sensing最新文献

Photogrammetric Engineering & Remote Sensing最新文献