Variable rate fertilization based on spectral index and remote sensing

2010 ◽  
Author(s):  
Shuqiang Li ◽  
Minzan Li ◽  
Yongjun Ding ◽  
Ruijiao Zhao
Keyword(s):  
Remote Sensing ◽  
Spectral Index ◽  
Variable Rate

Use of geographic information systems and remote sensing as automated tool for variable rate irrigation prescriptions

2019 ◽  
Author(s):  
◽  
Anh Thi Tuan Nguyen
Keyword(s):  
Remote Sensing ◽  
Real Time ◽  
Regression Models ◽  
Field Data ◽  
Irrigation Management ◽  
Irrigation Scheduling ◽  
Crop Growth ◽  
Variable Rate ◽  
Water Application ◽  
Center Pivot

[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT REQUEST OF AUTHOR.] Economic as well as water shortage pressure on agricultural use of water has placed added emphasis on efficient irrigation management. Center pivot technology has made great improvement with variable rate irrigation (VRI) technology to vary water application spatially and temporally to maximize the economic and environmental return. Proper management of VRI systems depends on correctly matching the pivot application to specific field temporal and areal conditions. There is need for a tool to accurately and inexpensively define dynamic management zones, to sense within-field variability in real time, and control variable rate water application so that producers are more willing to adopt and utilize the advantages of VRI systems. This study included tests of the center pivot system uniformity performance in 2014 at Delta Research Center in Portageville, MO. The goal of this research was to develop MOPivot software with an algorithm to determine unique management areas under center pivot systems based on system design and limitations. The MOPivot tool automates prescriptions for VRI center pivot based on non-uniform water needs while avoiding potential runoff and deep percolation. The software was validated for use in real-time irrigation management in 2018 for VRI control system of a Valley 8000 center pivot planted to corn. The water balance model was used to manage irrigation scheduling. Field data, together with soil moisture sensor measurement of soil water content, were used to develop the regression model of remote sensing-based crop coefficient (Kc). Remote sensing vegetation index in conjunction with GDD and crop growth stages in regression models showed high correlation with Kc. Validation of those regression models was done using Centralia, MO, field data in 2016. The MOPivot successfully created prescriptions to match system capacity of the management zone based on system limitations for center pivot management. Along with GIS data sources, MOPivot effectively provides readily available graphical prescription maps, which can be edited and directly uploaded to a center pivot control panel. The modeled Kc compared well with FAO Kc. By combining GDD and crop growth in the models, these models would account for local weather conditions and stage of crop during growing season as time index in estimating Kc. These models with Fraction of growth (FrG) and cumulative growing degree days (cGDD) had a higher coefficient of efficiency, higher Nash-Sutcliffe coefficient of efficiency and higher Willmott index of agreement. Future work should include improvement in the MOPivot software with different crops and aerial remote sensing imagery to generate dynamic prescriptions during the season to support irrigation scheduling for real-time monitoring of field conditions.

scholarly journals Evaluation of variable rate irrigation using a remote-sensing-based model

2018 ◽  
Vol 203 ◽  
pp. 63-74 ◽  
Author(s):  
J. Burdette Barker ◽  
Derek M. Heeren ◽  
Christopher M.U. Neale ◽  
Daran R. Rudnick
Keyword(s):  
Remote Sensing ◽  
Variable Rate ◽  
Variable Rate Irrigation

Remote sensing mapping of soil and plants as basis for a variable-rate nutrient application system

2004 ◽  
Author(s):  
Bent S. Bennedsen ◽  
Lene K. Christensen ◽  
Anders Pedersen ◽  
Lars S. Jensen ◽  
Niels E. Nielsen
Keyword(s):  
Remote Sensing ◽  
Variable Rate ◽  
Application System ◽  
Remote Sensing Mapping

scholarly journals Economic Comparison of Satellite, Plane and UAV-Acquired NDVI Images for Site-Specific Nitrogen Application: Observations from Italy

Agronomy ◽  
2021 ◽  
Vol 11 (11) ◽  
pp. 2098
Author(s):  
Marco Sozzi ◽  
Ahmed Kayad ◽  
Stefano Gobbo ◽  
Alessia Cogato ◽  
Luigi Sartori ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Decision Making ◽  
Optical Properties ◽  
High Resolution ◽  
Economic Benefits ◽  
Decision Making Process ◽  
Variable Rate ◽  
Nitrogen Application ◽  
Sensing Platforms ◽  
Medium Resolution

Defining the most profitable remote sensing platforms is a difficult decision-making process, as it requires agronomic and economic considerations. In this paper, the price and profitability of three levels of remote sensing platforms were evaluated to define a decision-making process. Prices of satellite, plane and UAV-acquired vegetation indices were collected in Italy during 2020 and compared to the economic benefits resulting from variable rate nitrogen application, according to a bibliographic meta-analysis performed on grains. The quality comparison of these three technologies was performed considering the error propagation in the NDVI formula. The errors of the single bands were used to assess the optical properties of the sensors. Results showed that medium-resolution satellite data with good optical properties could be profitably used for variable rate nitrogen applications starting from 2.5 hectares, in case of medium resolution with good optical properties. High-resolution satellites with lower optical quality were profitable starting from 13.2 hectares, while very high-resolution satellites with good optical properties could be profitably used starting from 76.8 hectares. Plane-acquired images, which have good optical properties, were profitable starting from 66.4 hectares. Additionally, a reference model for satellite image price is proposed.

scholarly journals Portable snapshot spectral imaging for agriculture

2018 ◽  
pp. 221-225 ◽  
Author(s):  
András Jung ◽  
René Michels ◽  
Rainer Graser
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Hyperspectral Imaging ◽  
Management Strategies ◽  
Variable Rate ◽  
Sensing Applications ◽  
Regular Variable ◽  
Remote Sensing Applications ◽  
Video Sensors ◽  
Areas Of Interest

High-resolution proximal and remote sensing applications can consolidate sustainable, prevention- and precision-oriented crop management strategies to decrease production risks. This paper shows significant perspectives, own developments and technical aspects of high resolution remote sensing in the context of field applications. Moreover, we provide an overview of snapshot hyperspectral imaging and potential field video sensors to identify areas of interest for their future development. One of the main conclusions of our paper is that non-scanning snapshot hyperspectral imaging technology may enable researchers to overcome the gap in the “point to image” transition of field sensing, while providing a flexible solution for regular variable-rate applications.

scholarly journals Sensitivity of a Ratio Vegetation Index Derived from Hyperspectral Remote Sensing to the Brown Planthopper Stress on Rice Plants

Sensors ◽  
2019 ◽  
Vol 19 (2) ◽  
pp. 375 ◽  
Author(s):  
Ye Tan ◽  
Jia-Yi Sun ◽  
Bing Zhang ◽  
Meng Chen ◽  
Yu Liu ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Spectral Index ◽  
Vegetation Index ◽  
Brown Planthopper ◽  
Surface Model ◽  
Rice Plants ◽  
Quadratic Curve ◽  
End Products ◽  
Quadratic Surface ◽  
Potential Applications

Remote sensing end-products related to vegetation have potential applications in monitoring the health of crops. The sensitivity of a spectral index to crop stress determines its application prospect. Our aim in this study was to explore the sensitivity of a ratio vegetation index (RVI) to identify the damage caused by brown planthoppers (BPHs) on rice plants, and to evaluate the potential application of hyperspectral end-products to monitor population size of BPH. Different numbers of the second-instar nymphs were released onto potted rice at the tillering stage. The plants were exposed to BPH for two, four, six, and eight days, and reflectance from the damaged rice was measured using a hyperspectral spectroradiometer. Measurements were done again two, four, and six days after exposure (recover days), and then the spectral index RVI746/670 was compared among rice plants infested with different numbers of BPH. The relationships between RVI746/670, the number of BPH and exposure day were simulated by linear and curve models. BPH damage resulted in a decreased spectral index RVI746/670 of rice plants. RVI746/670 well indicated the damage of rice plants caused by six–eight BPH nymphs per plant in six–eight days, but the index could not identify the damage of these nymphs in two days. The RVI746/670 showed a two–four-day delay to indicate a slight BPH damage. The spectral index RVI746/670 could indicate the physiologic compensation of plants for the feeding of BPH and the post-effect of BPH damage on rice. The RVI746/670 of rice showed a quadratic curve relation with the number of BPH nymphs and a quadratic or linear relation with the exposure day. The recover day had no significant effects on RVI746/670. The RVI746/670 (Y) could be simulated by a quadratic surface model based on the number of BPH (N) and exposure day (T): Y = 3.09427 + 0.59111T + 0.44296N − 0.03683T2 − 0.03035N2 − 0.08188NT (R2 = 0.5228, p < 0.01). In summary, the spectral index RVI746/670 of rice is sensitive to damage caused by BPH.

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