Remote sensing — a tool for site-specific N management in sugar beet production without impacts on technical beet quality?

2001 ◽  
pp. 338-339
Author(s):  
M. Bauer ◽  
S. Reusch ◽  
T. Engels ◽  
F. Wiesler
Keyword(s):  
Remote Sensing ◽  
Sugar Beet ◽  
Site Specific ◽  
N Management

Analysis of Remote Sensing based Vegetation Indices (VIs) for Unmanned Aerial System (UAS): A Review

2020 ◽  
Vol 3 (2) ◽  
pp. 58-73
Author(s):  
Vijay Bhagat ◽  
Ajaykumar Kada ◽  
Suresh Kumar
Keyword(s):  
Remote Sensing ◽  
Spatial Data ◽  
Satellite Remote Sensing ◽  
Vegetation Indices ◽  
Unmanned Aerial System ◽  
Sustainable Land Management ◽  
Efficient Tool ◽  
Site Specific ◽  
The Earth ◽  
Interesting Area

Unmanned Aerial System (UAS) is an efficient tool to bridge the gap between high expensive satellite remote sensing, manned aerial surveys, and labors time consuming conventional fieldwork techniques of data collection. UAS can provide spatial data at very fine (up to a few mm) and desirable temporal resolution. Several studies have used vegetation indices (VIs) calculated from UAS based on optical- and MSS-datasets to model the parameters of biophysical units of the Earth surface. They have used different techniques of estimations, predictions and classifications. However, these results vary according to used datasets and techniques and appear very site-specific. These existing approaches aren’t optimal and applicable for all cases and need to be tested according to sensor category and different geophysical environmental conditions for global applications. UAS remote sensing is a challenging and interesting area of research for sustainable land management.

Directed sampling using remote sensing with a response surface sampling design for site-specific agriculture

2006 ◽  
Vol 53 (2) ◽  
pp. 98-112 ◽  
Author(s):  
Glenn J. Fitzgerald ◽  
Scott M. Lesch ◽  
Edward M. Barnes ◽  
William E. Luckett
Keyword(s):  
Remote Sensing ◽  
Response Surface ◽  
Sampling Design ◽  
Surface Sampling ◽  
Site Specific

Improving Nitrogen Fertilization in Rice by Site-Specific N Management

2011 ◽  
pp. 943-952 ◽  
Author(s):  
Shaobing Peng ◽  
Roland J. Buresh ◽  
Jianliang Huang ◽  
Xuhua Zhong ◽  
Yingbin Zou ◽  
...  
Keyword(s):  
Nitrogen Fertilization ◽  
Site Specific ◽  
N Management

scholarly journals Site-specific nitrogen management in winter wheat supported by low-altitude remote sensing and soil data

2020 ◽  
Author(s):  
F. Argento ◽  
T. Anken ◽  
F. Abt ◽  
E. Vogelsanger ◽  
A. Walter ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Winter Wheat ◽  
Nitrogen Management ◽  
Site Specific ◽  
Low Altitude

scholarly journals Investigating temporal field sampling strategies for site-specific calibration of three soil moisture–neutron intensity parameterisation methods

2015 ◽  
Vol 19 (7) ◽  
pp. 3203-3216 ◽  
Author(s):  
J. Iwema ◽  
R. Rosolem ◽  
R. Baatz ◽  
T. Wagener ◽  
H. R. Bogena
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Satellite Remote Sensing ◽  
Cosmic Ray ◽  
Sampling Strategies ◽  
Site Specific ◽  
Neutron Intensity ◽  
Soil Wetness ◽  
Semi Arid

Abstract. The Cosmic-Ray Neutron Sensor (CRNS) can provide soil moisture information at scales relevant to hydrometeorological modelling applications. Site-specific calibration is needed to translate CRNS neutron intensities into sensor footprint average soil moisture contents. We investigated temporal sampling strategies for calibration of three CRNS parameterisations (modified N0, HMF, and COSMIC) by assessing the effects of the number of sampling days and soil wetness conditions on the performance of the calibration results while investigating actual neutron intensity measurements, for three sites with distinct climate and land use: a semi-arid site, a temperate grassland, and a temperate forest. When calibrated with 1 year of data, both COSMIC and the modified N0 method performed better than HMF. The performance of COSMIC was remarkably good at the semi-arid site in the USA, while the N0mod performed best at the two temperate sites in Germany. The successful performance of COSMIC at all three sites can be attributed to the benefits of explicitly resolving individual soil layers (which is not accounted for in the other two parameterisations). To better calibrate these parameterisations, we recommend in situ soil sampled to be collected on more than a single day. However, little improvement is observed for sampling on more than 6 days. At the semi-arid site, the N0mod method was calibrated better under site-specific average wetness conditions, whereas HMF and COSMIC were calibrated better under drier conditions. Average soil wetness condition gave better calibration results at the two humid sites. The calibration results for the HMF method were better when calibrated with combinations of days with similar soil wetness conditions, opposed to N0mod and COSMIC, which profited from using days with distinct wetness conditions. Errors in actual neutron intensities were translated to average errors specifically to each site. At the semi-arid site, these errors were below the typical measurement uncertainties from in situ point-scale sensors and satellite remote sensing products. Nevertheless, at the two humid sites, reduction in uncertainty with increasing sampling days only reached typical errors associated with satellite remote sensing products. The outcomes of this study can be used by researchers as a CRNS calibration strategy guideline.

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