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verified SJR 0,442 · Q2 • database Scopus / SJR & Web of Science indexed
Photogrammetric Engineering and Remote Sensing
United States · American Society for Photogr...
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Photogrammetric Engineering and Remote Sensing

Photogrammetric Engineering and Remote Sensing is a journal indexed in SJR in Computers in Earth Sciences with an H index of 146. It has an SJR impact factor of 0,442 and it has a best quartile of Q2. It is published in English. It has an SJR impact factor of 0,442.

ISSN: 0099-1112
Editorial: American Society for Photogrammetry and Remote Sensing
Category: Computers in Earth Sciences
Indexation: verifiedScopus / SJR verifiedWeb of Science

Unclaimed profile — some fields may be incomplete.

open_in_new Portal NPD menu_book Guidelines NPD
schedule Datos CoP · solo campos en BD
SJR Impact Factor trending_up
0,442 Q2
H-index 146
Tasa de Aceptación pie_chart
22% Selectiva
Fuente Acceptance_Rate
Tiempo a publicación hourglass_top
NPD
Campo Sin dato
Coste de Publicación (APC) payments
NPD Subscription
Ruta Non-OA NPD

Metrics

Campos Scimago / CoP — sin series inventadas

Scopus / SJR Web of Science

SJR Impact

0,442

H-index

146

Docs (year)

72

Docs 3y

263

Total refs

2394

Cites 3y

336

Citable 3y

209

Cites/Doc 2y

1.44

Ref/Doc

33.25

Immediate OA

—

Embargoed OA

NPD

Non OA / Submission

—

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Bioenergy Crop Identification at Field Scale Using VHR Airborne CIR Imagery

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Basic Products of the ZiYuan-3 Satellite and Accuracy Evaluation

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Band Grouping versus Band Clustering in SVM Ensemble Classification of Hyperspectral Imagery

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AVHRR-Based Spectral Vegetation Index for Quantitative Assessment of Vegetation State and Productivity

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Automatic Building Extraction Using a Fuzzy Active Contour Model

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Automatic Building Detection Using the Dempster-Shafer Algorithm

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Automated Water Classification in the Tibetan Plateau Using Chinese GF-1 WFV Data

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Automated Crater Detection, A New Tool for Mars Cartography and Chronology

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Applying ASPRS Accuracy Standards to Surveys from Small Unmanned Aircraft Systems (UAS)

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Applications Paper: Lidar Detection of the Ten Tallest Trees in the Tennessee Portion of the Great Smoky Mountains National Park

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