Updated on June 14, 2024

·

Created on October 8, 2018

Pix4Dfields

Drone mapping software for aerial crop analysis and precision agriculture.

Developed By
  1. Parrot
Tested By
  • Precision Agronomics Australia
  • Stratus Imaging
Content Partners
Unknown

Product Description

Pix4Dfields is a photogrammetry software designed for precision agriculture and crop analysis.  It digitizes fields by converting drone images into orthomosaics, digital surface models, index maps, zones and prescription maps allowing maximization of operational efficiency.

Target SDGs

SDG 2: Zero Hunger

SDG 1: No Poverty

Market Suggested Retail Price

$2,600.00

Target Users (Target Impact Group)

Household

Distributors / Implementing Organizations

Pix4D

Regions

Worldwide

Manufacturing/Building Method

Software Development

Intellectural Property Type

Copyright

User Provision Model

Direct sales through webpage

Distributions to Date Status

Unknown

Geocoding supported (Y/N)

Yes

Visuals

2D Orthomosaic, 2D Digital Surface Model, Vegetation Index Maps, Zonation Maps, Prescription Maps

Application

Crop scouting, protection and production analysis

Type of data collected

Field and crop data

Data acquisition methods

Drone images

Open source code (Y/N)

No

Open source data (Y /N/ Other)

No

Data import/export formats

Inputs: JPEG images, Monochromatic TIFF, Multi-band TIFF (RGB / Infrared / thermal), 1 layer (no pyramid, no multi-page), 8, 10, 12, 14, 16 bit integer, floating point

Outputs: Orthomosaic (GeoTIFF file) and Index map (GeoTIFF file)

Telecommunication service required (Y/N)

No internet required

Device(s) required

Laptop, drone, cameras

Languages available (list)

English

Design Specifications

  • Supports image import from any standard RGB cameras and several multispectral cameras like Parrot Sequoia and MicaSense RedEdge
  • Supports import of field boundaries from farming management platforms, or directly input
  • Supports import of orthomosaics, DSMs and index maps
  • Instant mapping with no internet required
  • Vegetation indices supporterd: NDVI, NDRE, VARI, TGI, SIPI2, LCI, BNDVI, GNDVI
  • Supports split and double screen for interpretation and comparison
  • Supports aggregation of information from the vegetation index maps into zones and assign application rates
  • Outputs: Orthomosaic, Field boundaries, Vegetation index maps, Zonation maps, Prescription maps, Annotations

Technical Support

Pix4D: online and phone

Replacement Components

N/A

Lifecycle

N/A

Manufacturer Specified Performance Parameters

Accuracy: consistent and comparable maps throughout the season

Instant results: generation of high-resolution maps while in the field, without internet connection

Agriculture intuitive: layer comparison, zone and prescription tools

Collaboration: upload and access information between team members

Vetted Performance Status

Acquisition of plot statistical information (NDVI mean, median, stdev and min & max) from indices, helped understand the impact of different agricultural techniques over the crops. Pix4Dfield was updated with radiometric corrections, allowing to map bigger areas while reducing processing time. This reduces waiting times from several hours to minutes.

Safety

N/A

Complementary Technical Systems

Drones are required to capture the images that feed the software

Academic Research and References

Hovhannisyan, T., Efendyan, P., Vardanyan, M., 2018, Creation of a digital model of fields with application of DJI phantom 3 drone and the opportunities of its utilization in agriculture, Annals of Agrarian Science, Volume 16, Issue 2, , ISSN 1512-1887, Pages 177-180

Barrero, O.,  Perdomo, S., 2018, RGB and multispectral UAV image fusion for Gramineae weed detection in rice fields, Precision Agric

Maguire, M., Woldt, W., Neale,  C., Frew, E., Meyer, G., 2017, A Survey of Agricultural Image Processing for Unmanned Aircraft Systems,  ASABE Annual International Meeting

Yang, C., Suh, C., Westbrook, J., 2017, Early identification of cotton fields using mosaicked aerial multispectral imagery, J Appl Rem Sens 11(1) 016008

Barrero, O., Rojas, D., Gonzalez, C.,  2016, Weed detection in rice fields using aerial images and neural networks, 2016 XXI Symposium on Signal Processing, Images and Artificial Vision (STSIVA), Bucaramanga,  pp. 1-4

Ihsan, M., Somantri, L., Sugito, N., Himayah, S., Affriani, A., 2018, The Comparison of Stage and Result Processing of Photogrammetric Data Based on Online Cloud ProcessingIOP Conference Series: Earth and Environmental ScienceVolume 286IGEOS International Geography Seminar, Malaysia.

“Agricultural Drone Mapping: Crop Protection and Production.” n.d. Pix4D. Accessed June 14, 2024. https://www.pix4d.com/industry/agriculture/

“Pricing Plans for PIX4Dfields Agriculture Mapping Software.” n.d. Pix4D. Accessed June 14, 2024. https://www.pix4d.com/pricing/pix4dfields/

“AgOS —.” n.d. AgWorks. Accessed June 14, 2024. https://agworks.net/agos

Hype – Agriculture – Short 15s – Generic. 2021. https://www.dronedeploy.com/solutions/agriculture/

“Drone Ag: Farmers Who Know Drones – Software.” n.d. Drone Ag. Accessed June 14, 2024. https://droneag.farm/

“FarmMap4D – Map Your Place.” 2021. FarmMap4D – Map Your Place. July 12, 2021. https://www.farmmap4d.com.au/

“Agriculture.” n.d. Esri.Com. Accessed June 14, 2024. https://www.esri.com/en-us/industries/agriculture/overview

“THE 17 GOALS.” n.d. Sdgs.Un.Org. Accessed June 14, 2024. https://sdgs.un.org/goals

N.d. Ctfassets.Net. Accessed June 14, 2024. https://pix4d.com/wp-content/uploads/2018/06/Pix4Dfields_product_table.pdf

“PIX4Dfields: Drone Software for Agriculture Mapping.” n.d. Pix4D. Accessed June 14, 2024. https://www.pix4d.com/product/pix4dfields/

Pix4D. n.d. “Pix4D Account.” Pix4d.Com. Accessed June 14, 2024. https://account.pix4d.com/signup

“Pix4D Documentation.” n.d. Pix4d.Com. Accessed June 14, 2024. https://support.pix4d.com/hc/en-us#gsc.tab=0

“How Drone Mapping Makes On-Farm Test Plots Relevant.” 2017. Pix4D. December 5, 2017. https://pix4d.com/drone-mapping-making-on-farm-test-plots-even-more-relevant-for-everyone/

narinder. 2019. “BONUS: Drones in Agriculture – P4 Multispectral, Pix4DFields, and Optimum Workflow for Capturing Actionable Insights – Drone UTM.” Drone UTM. October 12, 2019. https://www.thedroneu.com/drones-in-agriculture-p4-multispectral-mapping/

“Mapping 100ha+ Rice Paddies with PIX4Dfields.” 2020. Pix4D. February 4, 2020. https://www.pix4d.com/blog/mapping-large-rice-paddies/

Compliance with regulations

N/A

Evaluation methods

Field tests with different organizations

 

Other Information

Pix4Dfields knowledge base

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