Karolina Koval, redactora científica senior en EOS Data Analytics

Karolina Koval

Redactora científica senior en EOS Data Analytics

Karolina se ha embarcado en una trayectoria profesional única que la ha llevado del periodismo a una licenciatura en ciencias, tecnología, ingeniería y matemáticas (STEM, por sus siglas en inglés), lo que la ha conducido a su camino actual, la escritura sobre la ciencia y tecnología profunda.

Karolina, que actualmente cursa una licenciatura en Ciencias en Penn State, combina su pasión por la escritura con sus conocimientos técnicos, contribuyendo a la documentación técnica sobre los satélites de observación de la Tierra y el procesamiento de datos de éstos. También destaca a la hora de comunicar el valor científico de las soluciones de EOSDA en la agricultura de precisión, la silvicultura de precisión y la monitorización medioambiental de una forma accesible para todos.

Como defensora del empoderamiento personal, Karolina participa activamente en el feminismo de quinta ola, esforzándose por representar y elevar a las mujeres ucranianas en la comunidad STEM global. Su compromiso con esta idea se manifiesta mediante su afiliación a prestigiosas organizaciones como la Association for Women in Science (AWIS), Women in Technology (WIT) y Blue & White Society, que cuenta con la mayor red de antiguos alumnos de Estados Unidos, con más de 750.000 profesionales influyentes.

Artículos de este autor

Enabel Helps African Farmers By Using SatTech
  • Case study

Enabel Helps African Farmers By Using SatTech

Enabel assists farmers in Africa in building a thriving and sustainable future by employing satellite imagery analytics offered by EOSDA Crop Monitoring.

Complete Farmer Connects 5,000+ Farmers To SatTech
  • Case study

Complete Farmer Connects 5,000+ Farmers To SatTech

Complete Farmer harnesses satellite imagery analytics through the EOSDA Crop Monitoring API, fostering a thriving network of farmers across Africa, leading to remarkable improvements in crop yields.

EOSDA Custom Neural Net: Deforestation Detection
  • EOSDA Forest Monitoring

EOSDA Custom Neural Net: Deforestation Detection

The Science team at EOS Data Analytics has developed a custom algorithm for intelligent detection and tracking of deforestation in tropical regions using LEO satellite images as a data source.

The Morning Star’s Gradient Implements Remote Sensing
  • Case study

The Morning Star’s Gradient Implements Remote Sensing

The Morning Star combines in-ground sensor data with satellite imagery analytics to ensure proper irrigation and increase tomato yields in California.

Multilayer, Disease Risk & More: New In EOSDA Crop Monitoring
  • EOSDA Crop Monitoring

Multilayer, Disease Risk & More: New In EOSDA Crop Monitoring

EOSDA Crop Monitoring is growing, introducing highly demanded precision agriculture features. Discover July-September 2023 updates: Multilayer Maps, Disease Risk, Crop Rotation, and more.

UAB iAGRO Pioneers Precision AgriTech In Lithuania
  • Case study

UAB iAGRO Pioneers Precision AgriTech In Lithuania

UAB iAgro is pioneering in the field of precision agriculture in Lithuania by consulting growers based on remote sensing analytics.

How To Comply With New EUDR Using Satellite Solutions
  • Forestry

How To Comply With New EUDR Using Satellite Solutions

The new EU Deforestation-free regulation EUDR is revolutionizing the way that commodities are imported to Europe. EOS Data Analytics experts share the main takeaways and recommendations on how to comply.

Agrinova Grows By Offering Satellite Data Analytics
  • Case study

Agrinova Grows By Offering Satellite Data Analytics

Agricultural consulting Agrinova Group has been using EOSDA Crop Monitoring for over two years now, pioneering remote sensing services in the European Union and Eastern Europe.

Variable Rate Seeding: Technology Application & Benefits
  • Agricultural practices

Variable Rate Seeding: Technology Application & Benefits

EOSDA Crop Monitoring streamlines precision agriculture with Variable Rate Seeding maps. Methods of using vegetation indices for applying variable rate seeding are discussed in this simple guide.