A new method to improve temporal resolution of remote sensing imaging

2011 ◽  
Author(s):  
Huabo Sun ◽  
Lei Yan ◽  
Shuwei Li
Keyword(s):  
Remote Sensing ◽  
Temporal Resolution ◽  
New Method

STARS: A New Method for Multitemporal Remote Sensing

2013 ◽  
Vol 51 (4) ◽  
pp. 1897-1913 ◽  
Author(s):  
Marcio Pupin Mello ◽  
Carlos A. O. Vieira ◽  
Bernardo F. T. Rudorff ◽  
Paul Aplin ◽  
Rafael D. C. Santos ◽  
...  
Keyword(s):  
Remote Sensing ◽  
New Method ◽  
Multitemporal Remote Sensing

scholarly journals Remote Sensing Is Changing Our View of the Coast: Insights from 40 Years of Monitoring at Narrabeen-Collaroy, Australia

2018 ◽  
Vol 10 (11) ◽  
pp. 1744 ◽  
Author(s):  
Kristen Splinter ◽  
Mitchell Harley ◽  
Ian Turner
Keyword(s):  
Remote Sensing ◽  
Data Collection ◽  
Temporal Resolution ◽  
Monitoring Program ◽  
Google Earth ◽  
Airborne Lidar ◽  
Data Collection Program ◽  
Insight Into ◽  
Collection Program

Narrabeen-Collaroy Beach, located on the Northern Beaches of Sydney along the Pacific coast of southeast Australia, is one of the longest continuously monitored beaches in the world. This paper provides an overview of the evolution and international scientific impact of this long-term beach monitoring program, from its humble beginnings over 40 years ago using the rod and tape measure Emery field survey method; to today, where the application of remote sensing data collection including drones, satellites and crowd-sourced smartphone images, are now core aspects of this continuing and much expanded monitoring effort. Commenced in 1976, surveying at this beach for the first 30 years focused on in-situ methods, whereby the growing database of monthly beach profile surveys informed the coastal science community about fundamental processes such as beach state evolution and the role of cross-shore and alongshore sediment transport in embayment morphodynamics. In the mid-2000s, continuous (hourly) video-based monitoring was the first application of routine remote sensing at the site, providing much greater spatial and temporal resolution over the traditional monthly surveys. This implementation of video as the first of a now rapidly expanding range of remote sensing tools and techniques also facilitated much wider access by the international research community to the continuing data collection program at Narrabeen-Collaroy. In the past decade the video-based data streams have formed the basis of deeper understanding into storm to multi-year response of the shoreline to changing wave conditions and also contributed to progress in the understanding of estuary entrance dynamics. More recently, ‘opportunistic’ remote sensing platforms such as surf cameras and smartphones have also been used for image-based shoreline data collection. Commencing in 2011, a significant new focus for the Narrabeen-Collaroy monitoring program shifted to include airborne lidar (and later Unmanned Aerial Vehicles (UAVs)), in an enhanced effort to quantify the morphological impacts of individual storm events, understand key drivers of erosion, and the placing of these observations within their broader regional context. A fixed continuous scanning lidar installed in 2014 again improved the spatial and temporal resolution of the remote-sensed data collection, providing new insight into swash dynamics and the often-overlooked processes of post-storm beach recovery. The use of satellite data that is now readily available to all coastal researchers via Google Earth Engine continues to expand the routine data collection program and provide key insight into multi-decadal shoreline variability. As new and expanding remote sensing technologies continue to emerge, a key lesson from the long-term monitoring at Narrabeen-Collaroy is the importance of a regular re-evaluation of what data is most needed to progress the science.

scholarly journals A New Method on Calibrating PSF of Remote Sensing Space Plane Arraycamera

2017 ◽  
Vol 114 ◽  
pp. 03011
Author(s):  
Wei Liu ◽  
HuiTing Gao ◽  
ShiXiang Cao ◽  
Wei Tan ◽  
YunFei Bao
Keyword(s):  
Remote Sensing ◽  
New Method

Technological advances to improve the quantification of volcanic emissions

2021 ◽  
Author(s):  
Christopher Fuchs ◽  
Jonas Kuhn ◽  
Nicole Bobrowski ◽  
Ulrich Platt
Keyword(s):  
Remote Sensing ◽  
Temporal Resolution ◽  
Volcanic Activity ◽  
Imaging Techniques ◽  
Correlation Spectroscopy ◽  
Trace Gas ◽  
Optical Absorption Spectroscopy ◽  
Integration Time ◽  
Volcanic Plume ◽  
Flux Measurements

<p>Variations in volcanic trace gas composition and fluxes are a valuable indicator for changes in magmatic systems and therefore allow monitoring of the volcanic activity. An established method to measure trace gas emissions is to use remote sensing techniques like, for example, Differential Optical Absorption Spectroscopy (DOAS) and more recently SO<sub>2</sub>-cameras, that can quantify volcanic sulphur dioxide (SO<sub>2</sub>) emissions during quiescent degassing and eruptive phases, making it possible to correlate fluxes with volcanic activity. </p><p>We present flux measurements of volcanic SO<sub>2</sub> emissions based on the novel remote sensing technique of Imaging Fabry-Pérot Interferometer Correlation Spectroscopy (IFPICS) in the UV spectral range. The basic principle of IFPICS lies in the application of an Fabry-Pérot Interferometer (FPI) as wavelength selective element. The FPIs periodic transmission profile is matched to the periodic spectral absorption features of SO<sub>2</sub>, resulting in high spectral information for its detection. This technique yields a higher trace gas selectivity and sensitivity than imaging approaches based on interference filters, e.g. SO<sub>2</sub>-cameras and an increased spatio-temporal resolution over spectroscopic imaging techniques, e.g. imaging DOAS. Hence, IFPICS shows reduced cross sensitivities to broadband absorption (e.g. to ozone, aerosols), which allows the application to weaker volcanic SO<sub>2</sub> emitters and increases the range of possible atmospheric conditions. It further raises the possibility to apply IFPICS to other trace gas species like, for example, bromine monoxide, that still can be characterized with a high spatial and temporal resolution (< 1 HZ).</p><p>In October 2020, we acquired SO<sub>2</sub> column density distribution images of Mt Etna volcanic plume with a detection limit of 2x10<sup>17</sup> molec cm<sup>-2</sup>, 1 s integration time, 400x400 pixel spatial, and 0.3 Hz temporal resolution.  We compare the SO<sub>2</sub> fluxes retrieved by IFPICS with simultaneous flux measurements using the mutli-axis DOAS technique.</p>

scholarly journals Harmonizing Multi-Source Remote Sensing Images for Summer Corn Growth Monitoring

2019 ◽  
Vol 11 (11) ◽  
pp. 1266 ◽  
Author(s):  
Mingzheng Zhang ◽  
Dehai Zhu ◽  
Wei Su ◽  
Jianxi Huang ◽  
Xiaodong Zhang ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Time Series ◽  
Kalman Filter ◽  
Spatial Resolution ◽  
Temporal Resolution ◽  
Meteorological Data ◽  
High Temporal Resolution ◽  
Growth Monitoring ◽  
Landsat 8 ◽  
Data Set

Continuous monitoring of crop growth status using time-series remote sensing image is essential for crop management and yield prediction. The growing season of summer corn in the North China Plain with the period of rain and hot, which makes the acquisition of cloud-free satellite imagery very difficult. Therefore, we focused on developing image datasets with both a high temporal resolution and medium spatial resolution by harmonizing the time-series of MOD09GA Normalized Difference Vegetation Index (NDVI) images and 30-m-resolution GF-1 WFV images using the improved Kalman filter model. The harmonized images, GF-1 images, and Landsat 8 images were then combined and used to monitor the summer corn growth from 5th June to 6th October, 2014, in three counties of Hebei Province, China, in conjunction with meteorological data and MODIS Evapotranspiration Data Set. The prediction residuals ( Δ P R K ) in NDVI between the GF-1 observations and the harmonized images was in the range of −0.2 to 0.2 with Gauss distribution. Moreover, the obtained phenological curves manifested distinctive growth features for summer corn at field scales. Changes in NDVI over time were more effectively evaluated and represented corn growth trends, when considered in conjunction with meteorological data and MODIS Evapotranspiration Data Set. We observed that the NDVI of summer corn showed a process of first decreasing and then rising in the early growing stage and discuss how the temperature and moisture of the environment changed with the growth stage. The study demonstrated that the synthesized dataset constructed using this methodology was highly accurate, with high temporal resolution and medium spatial resolution and it was possible to harmonize multi-source remote sensing imagery by the improved Kalman filter for long-term field monitoring.

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