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IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Volume 13 -2020
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[Front cover]
Year: 2020 | Volume: 13
IEEE Geoscience and Remote Sensing Society
Year: 2020 | Volume: 13
Table of Contents
Year: 2020 | Volume: 13
This volume of the IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (J-STARS) marks a new milestone as J-STARS has become a gold fully open-access (OA) journal since January 1, 2020. The IEEE Geoscience and Remote Sensing Society made the decision of this OA flip following the requirement of IEEE that each society should have at least one fully OA journal. J-STARS i...Show More
Rationale of GNSS Reflected Delay–Doppler Map (DDM) Distortions Induced by Specular Point Inaccuracies
Publication Year: 2020,Page(s):3 - 13
Cited by: Papers (3)
Global navigation satellite system reflectometry (GNSS-R)-derived winds from the cyclone GNSS (CYGNSS) satellite constellation are expected to significantly improve weather forecasts in the tropical region. Delay-Doppler maps (DDMs) acquired by the TechDemosat-1 (TDS-1) GNSS-R satellite mission suffer from distortions that are highly correlated to on-board specular point estimation inaccuracies. S...Show More
Sea Ice Transition Detection Using Incoherent Integration and Deconvolution
Publication Year: 2020,Page(s):14 - 20
Cited by: Papers (5)
Currently, reflectometry-based sea ice detection methods rely on observables extracted from delay-Doppler maps (DDM)s, which are sensitive to ice in the specular zone. Due to the size of the glistening zone, the transition from open seas to sea ice in the specular zone can take up to 10 s for satellite platforms and no methods exist that can process this. In this article, using DDMs collected by T...Show More
Track-Based Cyclone Maximum Wind Retrievals Using the Cyclone Global Navigation Satellite System (CYGNSS) Mission Full DDMs
Mohammad M. Al-Khaldi;Joel T. Johnson;Younghun Kang;Steven J. Katzberg;Alexandra Bringer;Ethan Kubatko;Dylan Wood
Publication Year: 2020,Page(s):21 - 29
Cited by: Papers (12)
Cyclone maximum wind retrievals are demonstrated using tracks of full delay-Doppler map (DDM) measurements of the Cyclone Global Navigation Satellite System (CYGNSS) constellation. The method is based on the production of a library of simulated DDMs for a synthetic storm model, as the parameters of the synthetic storm are varied. A matched filter approach between normalized simulated and measured ...Show More
Daphne: A Virtual Assistant for Designing Earth Observation Distributed Spacecraft Missions
Publication Year: 2020,Page(s):30 - 48
Cited by: Papers (12)
This article describes Daphne, a virtual assistant for designing Earth observation distributed spacecraft missions. It is, to the best of our knowledge, the first virtual assistant for such application. The article provides a thorough description of Daphne, including its question answering system and the main features we have implemented to help system engineers design distributed spacecraft missi...Show More
Mapping Plastic Greenhouses Using Spectral Metrics Derived From GaoFen-2 Satellite Data
Publication Year: 2020,Page(s):49 - 59
Cited by: Papers (37)
Plastic greenhouses are an important hallmark of agricultural progress. To meet the growing demand for vegetable and food, the amount of plastic greenhouses has increased significantly over the past few decades. Remote sensing is considered as a promising data source for taking inventory and monitoring plastic greenhouses for managing modern agriculture. However, a systematic catalog of number and...Show More
Automatic Weighted Splines Filter (AWSF): A New Algorithm for Extracting Terrain Measurements From Raw LiDAR Point Clouds
Publication Year: 2020,Page(s):60 - 71
Cited by: Papers (4)
Airborne raw light detection and ranging (LiDAR) measurements are georeferenced three-dimensional coordinates of ground surface, including all natural and man-made features. Extracting terrain surface measurements from raw LiDAR data is referred to as “filtering.” Many filtering algorithms have been published, indicating the difficulty of the task; however, none performs equally well on all kinds ...Show More
Classification of LiDAR Point Clouds Using Supervoxel-Based Detrended Feature and Perception-Weighted Graphical Model
Yusheng Xu;Zhen Ye;Wei Yao;Rong Huang;Xiaohua Tong;Ludwig Hoegner;Uwe Stilla
Publication Year: 2020,Page(s):72 - 88
Cited by: Papers (27)
Interpretation of 3-D scene through LiDAR point clouds has been a hot research topic for decades. To utilize measured points in the scene, assigning unique tags to the points of the scene with labels linking to individual objects plays a crucial role in the analysis process. In this article, we present a supervised classification approach for the semantic labeling of laser scanning points. A novel...Show More
Fast Methods of Coverage Evaluation for Tradespace Analysis of Constellations
Publication Year: 2020,Page(s):89 - 101
Cited by: Papers (8)
Simulation of distributed space missions (DSMs) for the purpose of phase-A mission design studies and general tradespace analysis is computationally challenging owing to the necessity of evaluating thousands of architecture options. Machine learning and evolutionary optimization methods have enabled intelligent search of the architectural tradespace of DSMs, including spacecraft and instrument des...Show More
First Precise Spaceborne Sea Surface Altimetry With GNSS Reflected Signals
Estel Cardellach;Weiqiang Li;Antonio Rius;Maximilian Semmling;Jens Wickert;Florian Zus;Christopher S. Ruf;Carlo Buontempo
Publication Year: 2020,Page(s):102 - 112
Cited by: Papers (78)
The precision of sea surface altimetry using bistatically reflected signals of the Global Navigation Satellite System (GNSS) is typically one to two orders of magnitude worse than dedicated radar altimeters. However, when the scattering is coherent, the electromagnetic phase of the carrier signal can be tracked, providing precise ranging measurements. Under grazing angle (GA) geometries, the condi...Show More
Very High Resolution Remote Sensing Imagery Classification Using a Fusion of Random Forest and Deep Learning Technique—Subtropical Area for Example
Luofan Dong;Huaqiang Du;Fangjie Mao;Ning Han;Xuejian Li;Guomo Zhou;Di'en Zhu;Junlong Zheng;Meng Zhang;Luqi Xing;Tengyan Liu
Publication Year: 2020,Page(s):113 - 128
Cited by: Papers (86)
Recently, convolutional neural networks (CNNs) showed excellent performance in many tasks, such as computer vision and remote sensing semantic segmentation. Especially, the ability to learn high-representation features of CNN draws much attention. And random forest (RF) algorithm, on the other hand, is widely applied for variables selection, classification, and regression. Based on the previous fu...Show More
Drought Monitoring Using the Sentinel-3-Based Multiyear Vegetation Temperature Condition Index in the Guanzhong Plain, China
Xijia Zhou;Pengxin Wang;Kevin Tansey;Darren Ghent;Shuyu Zhang;Hongmei Li;Lei Wang
Publication Year: 2020,Page(s):129 - 142
Cited by: Papers (9)
The vegetation temperature condition index (VTCI) has been shown to perform well for drought monitoring using multiyear advanced very high-resolution radiometer (AVHRR) and moderate resolution imaging spectroradiometer (MODIS) data. Compared to single-year VTCI, the VTCI calculated by multiyear data can quantitatively reflect the degree of drought and precipitation in a region. Sentinel-3 is a rec...Show More
Thick Clouds Removal From Multitemporal ZY-3 Satellite Images Using Deep Learning
Yang Chen;Luliang Tang;Xue Yang;Rongshuang Fan;Muhammad Bilal;Qingquan Li
Publication Year: 2020,Page(s):143 - 153
Cited by: Papers (42)
The presence of clouds greatly reduces the ground information of high-resolution satellite data. In order to improve the utilization of high-resolution satellite data, this article presents a cloud removal method based on deep learning. This is the first end-to-end architecture that has great potential to detect and remove clouds from high-resolution satellite data. For cloud detection, a convolut...Show More
A Novel Statistical Texture Feature for SAR Building Damage Assessment in Different Polarization Modes
Publication Year: 2020,Page(s):154 - 165
Cited by: Papers (19)
Texture features are important characteristics in distinguishing collapsed buildings and intact buildings. However, texture features currently used in synthetic aperture radar (SAR) building damage assessment are extracted following the methods of optical images directly, which do not consider the statistical feature of speckles and limit the accuracy improving. Therefore, a statistical texture fe...Show More
Mapping Urban Slum Settlements Using Very High-Resolution Imagery and Land Boundary Data
Publication Year: 2020,Page(s):166 - 177
Cited by: Papers (12)
Accurate mapping of slums is crucial for urban planning and management. This article proposes a machine learning, hierarchical object-based method to map slum settlements using very high-resolution (VHR) imagery and land boundary data to support slum upgrading. The proposed method is tested in Kingston Metropolitan Area, Jamaica. First, the VHR imagery is classified into major land cover classes (...Show More
Estimation of Grassland Height Based on the Random Forest Algorithm and Remote Sensing in the Tibetan Plateau
Jianpeng Yin;Qisheng Feng;Tiangang Liang;Baoping Meng;Shuxia Yang;Jinlong Gao;Jing Ge;Mengjing Hou;Jie Liu;Wei Wang;Hui Yu;Baokang Liu
Publication Year: 2020,Page(s):178 - 186
Cited by: Papers (18)
Grassland height is one of the main factors used to evaluate grassland conditions. However, the retrieval of natural grassland height at the regional scale by remote sensing data and conventional statistical models will result in large errors, especially in the heterogeneous alpine grassland of the Tibetan Plateau (TP). In this article, we aimed to construct a model based on multiple variables (bi...Show More
OpenSARUrban: A Sentinel-1 SAR Image Dataset for Urban Interpretation
Juanping Zhao;Zenghui Zhang;Wei Yao;Mihai Datcu;Huilin Xiong;Wenxian Yu
Publication Year: 2020,Page(s):187 - 203
Cited by: Papers (40)
The Sentinel-1 mission provides a freely accessible opportunity for urban image interpretation based on synthetic aperture radar (SAR) data with a specific resolution, which is of paramount importance for Earth observation. In parallel, with the rapid development of advanced technologies, especially deep learning, we urgently need a large-scale SAR dataset supporting urban image interpretation. Th...Show More
Detailed Variations in Urban Surface Temperatures Exploration Based on Unmanned Aerial Vehicle Thermography
Publication Year: 2020,Page(s):204 - 216
Cited by: Papers (37)
Determining the land surface temperature (LST) variations in urban surfaces using high spatiotemporal resolution thermal infrared data is necessary for urban microthermal environmental modeling. An unmanned aerial vehicle (UAV) equipped with a thermal infrared imager was used to monitor the high-precision spatiotemporal variation of LSTs for six typical urban surfaces, including water, tree canopy...Show More
Sensing Sea Ice Based on Doppler Spread Analysis of Spaceborne GNSS-R Data
Yongchao Zhu;Tingye Tao;Kegen Yu;Zhenxuan Li;Xiaochuan Qu;Zhourun Ye;Jun Geng;Jingui Zou;Maximilian Semmling;Jens Wickert
Publication Year: 2020,Page(s):217 - 226
Cited by: Papers (29)
The spaceborne Global Navigation Satellite System-Reflectometry (GNSS-R) delay-Doppler map (DDM) data collected over ocean carry typical feature information about the ocean surface, which may be covered by open water, mixed water/ice, complete ice, etc. A new method based on Doppler spread analysis is proposed to remotely sense sea ice using the spaceborne GNSS-R data collected over the Northern a...Show More
Road Extraction From High-Resolution Satellite Images Based on Multiple Descriptors
Publication Year: 2020,Page(s):227 - 240
Cited by: Papers (22)
Geometry and texture noise make it difficult to accurately describe road image rules, which leads to the low degree of automation of traditional template matching algorithms based on internal texture homogenization. We propose a semi-automatic road extraction method based on multiple descriptors to improve the degree of automation while ensuring the accuracy of road extraction. This method aims to...Show More
Analysis of Low-Oversampled Staggered SAR Data
Muriel Pinheiro;Pau Prats-Iraola;Marc Rodriguez-Cassola;Michelangelo Villano
Publication Year: 2020,Page(s):241 - 255
Cited by: Papers (21)
The combination of SCan-On-REceive with continuous variation of the pulse repetition interval during transmission (staggered operation) is a viable option for the acquisition of high-resolution synthetic aperture radar (SAR) data over wide areas. Since the acquired data are not uniformly sampled and contain gaps within the synthetic aperture mainly due to the interruption of reception during trans...Show More
Retrieval Topic Recurrent Memory Network for Remote Sensing Image Captioning
Publication Year: 2020,Page(s):256 - 270
Cited by: Papers (51)
Remote sensing image (RSI) captioning aims to generate sentences to describe the content of RSIs. Generally, five sentences are used to describe the RSI in caption datasets. Every sentence can just focus on part of images' contents due to the different attention parts of annotation persons. One annotated sentence may be ambiguous compared with other four sentences. However, previous methods, treat...Show More
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