scholarly journals Defining the Spatial Resolution Requirements for Crop Identification Using Optical Remote Sensing

2014 ◽  
Vol 6 (9) ◽  
pp. 9034-9063 ◽  
Author(s):  
Fabian Löw ◽  
Grégory Duveiller
Keyword(s):  
Remote Sensing ◽  
Spatial Resolution ◽  
Optical Remote Sensing ◽  
Resolution Requirements

scholarly journals Remote Sensing for Crop Water Management: from Experiments to User-Driven Services

2016 ◽  
Author(s):  
Alfonso Calera ◽  
Isidro Campos ◽  
Anna Osann ◽  
Guido D´Urso ◽  
Massimo Menenti
Keyword(s):  
Remote Sensing ◽  
Spatial Resolution ◽  
Meteorological Data ◽  
Irrigation Scheduling ◽  
Web Gis ◽  
Optical Remote Sensing ◽  
Crop Water ◽  
Biophysical Parameters ◽  
Water Requirements ◽  
Crop Water Requirements

The experiences gathered during the past 30 years support the operational use of irrigation scheduling based on frequent multi-spectral image data. Currently, the operational use of dense time series of multispectral imagery at high spatial resolution makes monitoring of crop biophysical parameters feasible, capturing crop water use across the growing season, with suitable temporal and spatial resolutions. These achievements, and the availability of accurate forecasting of meteorological data, allow for precise predictions of crop water requirements with unprecedented spatial resolution. This information is greatly appreciated by the end users, i.e. professional farmers or decision-makers, and can be provided in an easy-to-use manner and in near-real-time by using the improvements achieved in web-GIS methodologies. This paper reviews the most operational and explored methods based on optical remote sensing for the assessment of crop water requirements, identifying strengths and weaknesses and proposing alternatives to advance towards full operational application of this methodology. In addition, we provide a general overview of the tools which facilitates co-creation and collaboration with stakeholders, paying special attention to these approaches based on web-GIS tools.

Towards a high spatial resolution limit for pixel-based interpretations of optical remote sensing data

2008 ◽  
Vol 41 (11) ◽  
pp. 1724-1732 ◽  
Author(s):  
Jean-Luc Widlowski ◽  
Thomas Lavergne ◽  
Bernard Pinty ◽  
Nadine Gobron ◽  
Michel M. Verstraete
Keyword(s):  
Remote Sensing ◽  
Spatial Resolution ◽  
High Spatial Resolution ◽  
Remote Sensing Data ◽  
Optical Remote Sensing ◽  
Resolution Limit ◽  
Sensing Data

scholarly journals Deep Memory Connected Neural Network for Optical Remote Sensing Image Restoration

2018 ◽  
Vol 10 (12) ◽  
pp. 1893 ◽  
Author(s):  
Wenjia Xu ◽  
Guangluan Xu ◽  
Yang Wang ◽  
Xian Sun ◽  
Daoyu Lin ◽  
...  
Keyword(s):  
Neural Network ◽  
Remote Sensing ◽  
Image Restoration ◽  
Spatial Resolution ◽  
Remote Sensing Image ◽  
Global Memory ◽  
Great Success ◽  
Optical Remote Sensing ◽  
Remote Sensing Images ◽  
Feature Maps

The spatial resolution and clarity of remote sensing images are crucial for many applications such as target detection and image classification. In the last several decades, tremendous image restoration tasks have shown great success in ordinary images. However, since remote sensing images are more complex and more blurry than ordinary images, most of the existing methods are not good enough for remote sensing image restoration. To address such problem, we propose a novel method named deep memory connected network (DMCN) based on the convolutional neural network to reconstruct high-quality images. We build local and global memory connections to combine image detail with global information. To further reduce parameters and ease time consumption, we propose Downsampling Units, shrinking the spatial size of feature maps. We verify its capability on two representative applications, Gaussian image denoising and single image super-resolution (SR). DMCN is tested on three remote sensing datasets with various spatial resolution. Experimental results indicate that our method yields promising improvements and better visual performance over the current state-of-the-art. The PSNR and SSIM improvements over the second best method are up to 0.3 dB.

scholarly journals Onboard equipment of L- and X-bands synthesized aperture radars for remote sensing of the Earth with higher resolution: requirements and implementation

2019 ◽  
Vol 30 ◽  
pp. 15032
Author(s):  
Mikhail Rovkin
Keyword(s):  
Remote Sensing ◽  
Spatial Resolution ◽  
Flight Tests ◽  
Bench Tests ◽  
The Earth ◽  
X Band ◽  
Main Components ◽  
Onboard Equipment ◽  
Resolution Requirements

Requirements to the equipment of dual (L - and X-) band SAR, realizing increase of spatial resolution due to expansion of a spectrum of sounding signals are set. The technical decision of the main components of the onboard equipment and the results of bench tests of the layout of small - sized SAR of L - and X-bands for remote sensing of the Earth prepared for flight tests are described.

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