Work

Implementation of Python in the automation of crop analysis through Remote Sensors

Year: 2024

Type: article

Abstract: Agro-Industry 4.0 integrates advanced digital technologies in agriculture to improve efficiency and productivity through process automation and real-time data collection. This research applies information and communication technologies (ICT) to automate agricultural processes. Using Python, an application was developed to process images from sensors like SENTINEL, LANDSAT, and SEQUOIA to calculate vegetation indices, which help estimate chlorophyll content in plants. These indices are crucial for assessing crop nutritional status and support decision-making in crop management, optimizing development and improving agricultural performance.

Source: Journal of Enviromental Sciences and Natural Resources

DOI: 10.35429/jesn.2024.10.25.5.1.7

Authors: Alan Joel Servín-Prieto, Mónica Hernandez-Lopez, José María Juarez-Hernandez, Tania Elizabeth Velasquez Chavez

Institution: Instituto Tecnológico Superior de Lerdo

Language: English

Topic: Remote Sensing in Agriculture

Subfield: Ecology

Field: Environmental Science

Domain: Physical Sciences

SDGs: Zero hunger, Industry, innovation and infrastructure

Open Access status: hybrid

Funder: Tecnológico Nacional de México