荟萃期刊|Photogrammetric Engineering & Remote Sensing

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※Introduction

Photogrammetric Engineering & Remote Sensing, commonly referred to as PE&RS, is the official journal for imaging and geospatial information science and technology.Included in the journal on a regular basis are a Highlight Article, the popular columns “Grids & Datums” and “Mapping Matters”, and peer reviewed scientific papers.

Included in the journal on a regular basis are a Highlight Article, the popular columns“Grids & Datums” and “Mapping Matters”, and peer reviewed scientific papers.

※CALL FOR PAPERS

Special Issue: Computer Vision and Big Data Analytics for Remote Sensing

Topics of Interest

The potential topics includes, but not limited to:

•Precision Agriculture

•Aerial phenotyping

•Automatic crop monitoring using unmanned aerial systems

•Sensors and field robots

•Vegetation stress detection

•Machine Learning

•Computer vision based data fusion for remote sensing

•Object detection and classification using remotely sensed data

•Change detection using multi-temporal data

•Super-resolution image reconstruction

•Image contrast enhancement

•Image registration

•3D surface modeling and reconstruction

•High-performance computing paradigm for remote sensing applications

•Dimensionality reduction for remote sensing data

•Spatial and spectral feature extraction methods

•Noise modelling and estimation

•Big Data analytics

•Data visualization

•Augmented and Virtual Reality with remote sensing data

※CALL FOR PAPERS

Special Issue: Remote Sensing of Urban Environment

Submissions may address, but are not limited to the following topics:

•Urban heatisland

•Urban airquality

•Urban information retrieval (e.g., buildings, roads, impervious layer, vegetation species)

•Urban landcover/use mapping and updating

•Urban climate change

•Urban landscape and development pattern

•Urbanization

•Multisource(e.g. multi-angular, multi-temporal, multi-sensor) remote sensing data fusion

•New data and sensors for urban remote sensing (e.g. volunteered geographic information)

•Algorithms and techniques for interpreting urban remote sensing data (e.g. machine learning)

•Urban scene understanding and monitoring

※Metrics

ISSN：0099-1112

Impact Factor：2.493

3-year Impact Factor：1.796

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