Combining Environmental Monitoring and Remote Sensing Technologies to Evaluate Cropping System Nitrogen Dynamics at the Field-Scale-Reference-Cited by-同舟云学术

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Combining Environmental Monitoring and Remote Sensing Technologies to Evaluate Cropping System Nitrogen Dynamics at the Field-Scale

Published:2019-02-20 Issue: Volume:3 Page:
ISSN:2571-581X
Container-title:Frontiers in Sustainable Food Systems
language:
Short-container-title:Front. Sustain. Food Syst.

Author:

Preza Fontes Giovani,Bhattarai Rabin,Christianson Laura E.,Pittelkow Cameron M.

Publisher

Frontiers Media SA

Subject

Horticulture,Management, Monitoring, Policy and Law,Agronomy and Crop Science,Ecology,Food Science,Global and Planetary Change

Reference51 articles.

1. Advances in remote sensing of agriculture: context description, existing operational monitoring systems and major information needs;Atzberger;Remote Sens.,2013

2. Novel monitoring systems to obtain dairy cattle phenotypes associated with sustainable production;Bell;Front. Sustain. Food Syst.,2018

3. 4R water quality impacts: an assessment and synthesis of forty years of drainage nitrogen losses;Christianson;J. Environ. Qual.

4. The MANAGE drain load database: review and compilation of more than fifty years of North American drainage nutrient studies;Christianson;Agric. Water Manag.

5. Assessment and synthesis of 50 years of published drainage phosphorus losses;Christianson;J. Environ. Qual.,2016

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1. Sentinel-2-based predictions of soil depth to inform water and nutrient retention strategies in dryland wheat;Agricultural Water Management;2023-11

2. Soybean seed composition prediction from standing crops using PlanetScope satellite imagery and machine learning;ISPRS Journal of Photogrammetry and Remote Sensing;2023-10

3. Monitoring rice grain protein accumulation dynamics based on UAV multispectral data;Field Crops Research;2023-04

4. Investigating tradeoffs in nitrogen loss pathways using an environmental damage cost framework;Agricultural & Environmental Letters;2023-03-30

5. Augmenting agroecosystem models with remote sensing data and machine learning increases overall estimates of nitrate-nitrogen leaching;Environmental Research Letters;2022-10-20

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