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Monitoring crop phenology using a smartphone based near-surface remote sensing approach

Authors :
Hufkens, Koen; Melaas, Eli K.; Mann, Michael L.; Foster, Timothy; Ceballos, Francisco; Robles, Miguel; Kramer, Berber
http://orcid.org/0000-0001-8699-5114 Ceballos, Francisco; http://orcid.org/0000-0003-2151-8282 Robles, Miguel; http://orcid.org/0000-0001-7644-6613 Kramer, Berber
Hufkens, Koen; Melaas, Eli K.; Mann, Michael L.; Foster, Timothy; Ceballos, Francisco; Robles, Miguel; Kramer, Berber
http://orcid.org/0000-0001-8699-5114 Ceballos, Francisco; http://orcid.org/0000-0003-2151-8282 Robles, Miguel; http://orcid.org/0000-0001-7644-6613 Kramer, Berber
Source :
Agricultural and Forest Meteorology 265(February 2019): 327-337
Publication Year :
2019

Abstract

PR<br />IFPRI3; ISI; CRP2; CRP7; 1 Fostering Climate-Resilient and Sustainable Food Supply; 2 Promoting Healthy Diets and Nutrition for all; PBI<br />MTID; PIM<br />CGIAR Research Program on Policies, Institutions, and Markets (PIM); CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS); CGIAR Platform for Big Data in Agriculture (Big Data)<br />Smallholder farmers play a critical role in supporting food security in developing countries. Monitoring crop phenology and disturbances to crop growth is critical in strengthening farmers’ ability to manage production risks. This study assesses the feasibility of using crowdsourced near-surface remote sensing imagery to monitor winter wheat phenology and identify damage events in northwest India. In particular, we demonstrate how streams of pictures of individual smallholder fields, taken using inexpensive smartphones, can be used to quantify important phenological stages in agricultural crops, specifically the wheat heading phase and how it can be used to detect lodging events, a major cause of crop damage globally. Near-surface remote sensing offers granular visual field data, providing detailed information on the timing of key developmental phases of winter wheat and crop growth disturbances that are not registered by common satellite remote sensing vegetation indices or national crop cut surveys. This illustrates the potential of near-surface remote sensing as a scalable platform for collecting high-resolution plot-specific data that can be used in supporting crop modeling, extension and insurance schemes to increase resilience to production risk and enhance food security in smallholder agricultural systems.

Details

Database :
OAIster
Journal :
Agricultural and Forest Meteorology 265(February 2019): 327-337
Notes :
English, English
Publication Type :
Electronic Resource
Accession number :
edsoai.on1079909891
Document Type :
Electronic Resource