scholarly journals Crop Growth Monitoring with Drone-Borne DInSAR

2020 ◽  
Vol 12 (4) ◽  
pp. 615 ◽  
Author(s):  
Gian Oré ◽  
Marlon S. Alcântara ◽  
Juliana A. Góes ◽  
Luciano P. Oliveira ◽  
Jhonnatan Yepes ◽  
...  
Keyword(s):  
Optical Sensors ◽  
Precision Agriculture ◽  
Information Source ◽  
Crop Growth ◽  
Radar Interferometry ◽  
Synthetic Aperture ◽  
Growth Monitoring ◽  
Synthetic Aperture Radar Interferometry ◽  
L Band ◽  
Growth Deficit

Accurate, high-resolution maps of for crop growth monitoring are strongly needed by precision agriculture. The information source for such maps has been supplied by satellite-borne radars and optical sensors, and airborne and drone-borne optical sensors. This article presents a novel methodology for obtaining growth deficit maps with an accuracy down to 5 cm and a spatial resolution of 1 m, using differential synthetic aperture radar interferometry (DInSAR). Results are presented with measurements of a drone-borne DInSAR operating in three bands—P, L and C. The decorrelation time of L-band for coffee, sugar cane and corn, and the feasibility for growth deficit maps generation are discussed. A model is presented for evaluating the growth deficit of a corn crop in L-band, starting with 50 cm height. This work shows that the drone-borne DInSAR has potential as a complementary tool for precision agriculture.

scholarly journals Mapping arctic landfast ice extent using L-band synthetic aperture radar interferometry

2011 ◽  
Vol 115 (12) ◽  
pp. 3029-3043 ◽  
Author(s):  
Franz J. Meyer ◽  
Andrew R. Mahoney ◽  
Hajo Eicken ◽  
Casey L. Denny ◽  
Hyunjin C. Druckenmiller ◽  
...  
Keyword(s):  
Synthetic Aperture Radar ◽  
Radar Interferometry ◽  
Synthetic Aperture ◽  
Synthetic Aperture Radar Interferometry ◽  
Landfast Ice ◽  
L Band ◽  
Aperture Radar

Deformation information extraction method based on differential synthetic aperture radar interferometry

2020 ◽  
Vol 39 (4) ◽  
pp. 5311-5318
Author(s):  
Zhengquan Hu ◽  
Yu Liu ◽  
Xiaowei Niu ◽  
Guoping Lei
Keyword(s):  
Remote Sensing ◽  
Synthetic Aperture Radar ◽  
Adaptive Filtering ◽  
Extraction Method ◽  
Deformation Monitoring ◽  
Radar Interferometry ◽  
Synthetic Aperture ◽  
Filtering Method ◽  
Synthetic Aperture Radar Interferometry ◽  
Aperture Radar

As aerospace technology, computer technology, network communication technology and information technology become more and more perfect, a variety of sensors for measurement and remote sensing are constantly emerging, and the ability to acquire remote sensing data is also continuously enhanced. Synthetic Aperture Radar Interferometry (InSAR) technology greatly expands the function and application field of imaging radar. Differential InSAR (DInSAR) developed based on InSAR technology has the advantages of high precision and all-weather compared with traditional measurement methods. However, DInSAR-based deformation monitoring is susceptible to spatiotemporal coherence, orbital errors, atmospheric delays, and elevation errors. Since phase noise is the main error of InSAR, to determine the appropriate filtering parameters, an iterative adaptive filtering method for interferogram is proposed. For the limitation of conventional DInSAR, to improve the accuracy of deformation monitoring as much as possible, this paper proposes a deformation modeling based on ridge estimation and regularization as a constraint condition, and introduces a variance component estimation to optimize the deformation results. The simulation experiment of the iterative adaptive filtering method and the deformation modeling proposed in this paper shows that the deformation information extraction method based on differential synthetic aperture radar has high precision and feasibility.

Detection of geohazards in the Bailong River Basin using synthetic aperture radar interferometry

Landslides ◽  
2015 ◽  
Vol 13 (5) ◽  
pp. 1273-1284 ◽  
Author(s):  
Yi Zhang ◽  
Xingmin Meng ◽  
Guan Chen ◽  
Liang Qiao ◽  
Runqiang Zeng ◽  
...  
Keyword(s):  
Synthetic Aperture Radar ◽  
River Basin ◽  
Radar Interferometry ◽  
Synthetic Aperture ◽  
Synthetic Aperture Radar Interferometry ◽  
Bailong River Basin ◽  
Aperture Radar

scholarly journals Iceberg topography and volume classification using TanDEM-X interferometry

2019 ◽  
Vol 13 (7) ◽  
pp. 1861-1875 ◽  
Author(s):  
Dyre O. Dammann ◽  
Leif E. B. Eriksson ◽  
Son V. Nghiem ◽  
Erin C. Pettit ◽  
Nathan T. Kurtz ◽  
...  
Keyword(s):  
Synthetic Aperture Radar ◽  
Radar Interferometry ◽  
Synthetic Aperture ◽  
Maximum Height ◽  
Polar Regions ◽  
Classification Approach ◽  
Single Pass ◽  
Synthetic Aperture Radar Interferometry ◽  
Marine Habitats ◽  
Maritime Operations

Abstract. Icebergs in polar regions affect water salinity, alter marine habitats, and impose serious hazards on maritime operations and navigation. These impacts mainly depend on the iceberg volume, which remains an elusive parameter to measure. We investigate the capability of TanDEM-X bistatic single-pass synthetic aperture radar interferometry (InSAR) to derive iceberg subaerial morphology and infer total volume. We cross-verify InSAR results with Operation IceBridge (OIB) data acquired near Wordie Bay, Antarctica, as part of the OIB/TanDEM-X Antarctic Science Campaign (OTASC). While icebergs are typically classified according to size based on length or maximum height, we develop a new volumetric classification approach for applications where iceberg volume is relevant. For icebergs with heights exceeding 5 m, we find iceberg volumes derived from TanDEM-X and OIB data match within 7 %. We also derive a range of possible iceberg keel depths relevant to grounding and potential impacts on subsea installations. These results suggest that TanDEM-X could pave the way for future single-pass interferometric systems for scientific and operational iceberg mapping and classification based on iceberg volume and keel depth.

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