Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Light Acquisition02:16

Light Acquisition

8.6K
In order to produce glucose, plants need to capture sufficient light energy. Many modern plants have evolved leaves specialized for light acquisition. Leaves can be only millimeters in width or tens of meters wide, depending on the environment. Due to competition for sunlight, evolution has driven the evolution of increasingly larger leaves and taller plants, to avoid shading by their neighbors with contaminant elaboration of root architecture and mechanisms to transport water and nutrients.
8.6K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Air quality management during the G20 summit: strategies for urban pollution reduction.

Environmental monitoring and assessment·2026
Same author

Correlates of Inconsistent Condom use During Sexual Intercourse among Hijra and Transgender Population in India: Evidence from National Integrated Biological and Behavioral Surveillance 2014-15.

Indian journal of community medicine : official publication of Indian Association of Preventive & Social Medicine·2026
Same author

Stigma, HIV Risk Behavior, and HIV Seropositivity among Hijra and Transgender in India: Insights from Integrated Biological and Behavioral Surveillance.

Indian journal of public health·2025
Same author

A framework for EO-based National Agricultural Monitoring (EO-NAM) for the African Context.

NPJ sustainable agriculture·2025
Same author

HIV prevalence and associated risk factors among people who inject drugs in four states of central India: Findings from the 17th round of HIV sentinel surveillance.

International journal of STD & AIDS·2025
Same author

Assessment of targeted intervention programs on STI symptoms among Hijra and transgender in India: analysis of national level integrated biological and behavioral surveillance.

AIDS care·2025

Related Experiment Video

Updated: Sep 10, 2025

Cereal Crop Ear Counting in Field Conditions Using Zenithal RGB Images
11:49

Cereal Crop Ear Counting in Field Conditions Using Zenithal RGB Images

Published on: February 2, 2019

9.4K

Helmets Labeling Crops: Kenya Crop Type Dataset Created via Helmet-Mounted Cameras and Deep Learning.

Catherine Nakalembe1, Ivan Zvonkov2, Hannah Kerner3

  • 1Department of Geographical Sciences, University of Maryland, College Park, MD, 20742, USA. cnakalem@umd.edu.

Scientific Data
|August 27, 2025
PubMed
Summary

This study introduces a new dataset of 4,925 validated crop-type data points from Kenya, collected using citizen science and deep learning. This resource aids agricultural monitoring and food security assessments in data-scarce regions.

More Related Videos

Combining Eye-tracking Data with an Analysis of Video Content from Free-viewing a Video of a Walk in an Urban Park Environment
08:25

Combining Eye-tracking Data with an Analysis of Video Content from Free-viewing a Video of a Walk in an Urban Park Environment

Published on: May 7, 2019

9.1K
Imaging and Analysis for Quantifying Maize (Zea mays) Abiotic Stress Phenotypes
06:41

Imaging and Analysis for Quantifying Maize (Zea mays) Abiotic Stress Phenotypes

Published on: March 28, 2025

1.0K

Related Experiment Videos

Last Updated: Sep 10, 2025

Cereal Crop Ear Counting in Field Conditions Using Zenithal RGB Images
11:49

Cereal Crop Ear Counting in Field Conditions Using Zenithal RGB Images

Published on: February 2, 2019

9.4K
Combining Eye-tracking Data with an Analysis of Video Content from Free-viewing a Video of a Walk in an Urban Park Environment
08:25

Combining Eye-tracking Data with an Analysis of Video Content from Free-viewing a Video of a Walk in an Urban Park Environment

Published on: May 7, 2019

9.1K
Imaging and Analysis for Quantifying Maize (Zea mays) Abiotic Stress Phenotypes
06:41

Imaging and Analysis for Quantifying Maize (Zea mays) Abiotic Stress Phenotypes

Published on: March 28, 2025

1.0K

Area of Science:

  • Agricultural Science
  • Remote Sensing
  • Data Science

Background:

  • Effective agricultural monitoring is crucial for food security, especially in Kenya, which faces climate extremes.
  • Smallholder farming regions often lack detailed, up-to-date crop-type maps due to high field data collection costs.
  • Existing data gaps hinder accurate agricultural assessments and informed decision-making.

Purpose of the Study:

  • To present an inaugural, validated dataset of crop-type data for Kenya.
  • To address the challenge of limited crop-type information in data-scarce agricultural regions.
  • To support evidence-based agricultural decision-making and improve food security assessments.

Main Methods:

  • Collected 4,925 georeferenced crop-type data points across Kenya during the 2021 and 2022 long-rain seasons.
  • Utilized a citizen science network and institutional partners for image data collection via GoPro cameras.
  • Developed and implemented a deep learning pipeline for processing images into reliable crop-type datasets with rigorous quality control.

Main Results:

  • Generated a novel dataset of 4,925 validated crop-type data points for Kenyan agriculture.
  • Demonstrated the feasibility of using citizen science and deep learning for large-scale crop-type mapping.
  • Ensured data integrity through robust quality control measures.

Conclusions:

  • The new dataset is a valuable open-science resource for agricultural monitoring in Kenya.
  • This approach can help bridge data gaps and improve the accuracy of food production assessments.
  • The findings support enhanced agricultural decision-making to mitigate food insecurity.