10 Agriculture jobs in Langley

Job Title: Rater – Crop Classification in Satellite and Street View Images

Project Goal

The objective of this project is to classify crop types from satellite imagery by leveraging high-quality crop labels derived from street-view images of fields, providing a scalable ground-truth dataset for agricultural research and AI training.

Responsibilities

• Review satellite and street-view images to determine crop type or classify areas as uncultivated based on visual cues.
• Follow established workflows and annotation protocols to ensure consistent and accurate labeling.
• Apply domain knowledge to identify crop types even under partial occlusion.
• Maintain accuracy, attention to detail, and consistency across large volumes of images.

Workflow

• Agricultural Area Presence – Confirm if agricultural fields occupy more than a defined percentage (e.g., 40%) of the image view.
• Field Visibility Assessment – Evaluate visibility of the field:

• Partially Occluded but Identifiable – Annotate the crop type or mark as uncultivated.
• Clearly Visible and Identifiable – Proceed to assign the correct crop label.

Qualifications

• Academic Background : Bachelor’s degree (or higher) in Agriculture, Agronomy, Crop Science, Agricultural Engineering, Horticulture, or a related field.
• Hands-on Experience : Knowledge in Geography, Remote Sensing, Environmental Science, or GIS with exposure to crop identification.
• Agriculture Experience : Previous involvement in crop identification, agricultural surveys, or image annotation.
• Visual Identification Skills : Ability to distinguish crop types from both partial and full views.

Preferred Skills

• Strong attention to detail and familiarity with diverse crop types.
• Prior experience using image annotation tools and platforms is an advantage.
• Ability to work independently and deliver results under defined timelines.

Job Title: Rater – Crop Classification in Satellite and Street View Images

Project Goal

The objective of this project is to classify crop types from satellite imagery by leveraging high-quality crop labels derived from street-view images of fields, providing a scalable ground-truth dataset for agricultural research and AI training.

Responsibilities

• Review satellite and street-view images to determine crop type or classify areas as uncultivated based on visual cues.
• Follow established workflows and annotation protocols to ensure consistent and accurate labeling.
• Apply domain knowledge to identify crop types even under partial occlusion.
• Maintain accuracy, attention to detail, and consistency across large volumes of images.

Workflow

• Agricultural Area Presence – Confirm if agricultural fields occupy more than a defined percentage (e.g., 40%) of the image view.
• Field Visibility Assessment – Evaluate visibility of the field:

• Partially Occluded but Identifiable – Annotate the crop type or mark as uncultivated.
• Clearly Visible and Identifiable – Proceed to assign the correct crop label.

Qualifications

• Academic Background : Bachelor’s degree (or higher) in Agriculture, Agronomy, Crop Science, Agricultural Engineering, Horticulture, or a related field.
• Hands-on Experience : Knowledge in Geography, Remote Sensing, Environmental Science, or GIS with exposure to crop identification.
• Agriculture Experience : Previous involvement in crop identification, agricultural surveys, or image annotation.
• Visual Identification Skills : Ability to distinguish crop types from both partial and full views.

Preferred Skills

• Strong attention to detail and familiarity with diverse crop types.
• Prior experience using image annotation tools and platforms is an advantage.
• Ability to work independently and deliver results under defined timelines.

Job Title: Rater – Crop Classification in Satellite and Street View Images

Project Goal

The objective of this project is to classify crop types from satellite imagery by leveraging high-quality crop labels derived from street-view images of fields, providing a scalable ground-truth dataset for agricultural research and AI training.

Responsibilities

• Review satellite and street-view images to determine crop type or classify areas as uncultivated based on visual cues.
• Follow established workflows and annotation protocols to ensure consistent and accurate labeling.
• Apply domain knowledge to identify crop types even under partial occlusion.
• Maintain accuracy, attention to detail, and consistency across large volumes of images.

Workflow

• Agricultural Area Presence – Confirm if agricultural fields occupy more than a defined percentage (e.g., 40%) of the image view.
• Field Visibility Assessment – Evaluate visibility of the field:

• Partially Occluded but Identifiable – Annotate the crop type or mark as uncultivated.
• Clearly Visible and Identifiable – Proceed to assign the correct crop label.

Qualifications

• Academic Background : Bachelor’s degree (or higher) in Agriculture, Agronomy, Crop Science, Agricultural Engineering, Horticulture, or a related field.
• Hands-on Experience : Knowledge in Geography, Remote Sensing, Environmental Science, or GIS with exposure to crop identification.
• Agriculture Experience : Previous involvement in crop identification, agricultural surveys, or image annotation.
• Visual Identification Skills : Ability to distinguish crop types from both partial and full views.

Preferred Skills

• Strong attention to detail and familiarity with diverse crop types.
• Prior experience using image annotation tools and platforms is an advantage.
• Ability to work independently and deliver results under defined timelines.

Job Title: Rater – Crop Classification in Satellite and Street View Images

Project Goal

The objective of this project is to classify crop types from satellite imagery by leveraging high-quality crop labels derived from street-view images of fields, providing a scalable ground-truth dataset for agricultural research and AI training.

Responsibilities

• Review satellite and street-view images to determine crop type or classify areas as uncultivated based on visual cues.
• Follow established workflows and annotation protocols to ensure consistent and accurate labeling.
• Apply domain knowledge to identify crop types even under partial occlusion.
• Maintain accuracy, attention to detail, and consistency across large volumes of images.

Workflow

• Agricultural Area Presence – Confirm if agricultural fields occupy more than a defined percentage (e.g., 40%) of the image view.
• Field Visibility Assessment – Evaluate visibility of the field:

• Partially Occluded but Identifiable – Annotate the crop type or mark as uncultivated.
• Clearly Visible and Identifiable – Proceed to assign the correct crop label.

Qualifications

• Academic Background : Bachelor’s degree (or higher) in Agriculture, Agronomy, Crop Science, Agricultural Engineering, Horticulture, or a related field.
• Hands-on Experience : Knowledge in Geography, Remote Sensing, Environmental Science, or GIS with exposure to crop identification.
• Agriculture Experience : Previous involvement in crop identification, agricultural surveys, or image annotation.
• Visual Identification Skills : Ability to distinguish crop types from both partial and full views.

Preferred Skills

• Strong attention to detail and familiarity with diverse crop types.
• Prior experience using image annotation tools and platforms is an advantage.
• Ability to work independently and deliver results under defined timelines.

Job Title: Rater – Crop Classification in Satellite and Street View Images

Project Goal

The objective of this project is to classify crop types from satellite imagery by leveraging high-quality crop labels derived from street-view images of fields, providing a scalable ground-truth dataset for agricultural research and AI training.

Responsibilities

• Review satellite and street-view images to determine crop type or classify areas as uncultivated based on visual cues.
• Follow established workflows and annotation protocols to ensure consistent and accurate labeling.
• Apply domain knowledge to identify crop types even under partial occlusion.
• Maintain accuracy, attention to detail, and consistency across large volumes of images.

Workflow

• Agricultural Area Presence – Confirm if agricultural fields occupy more than a defined percentage (e.g., 40%) of the image view.
• Field Visibility Assessment – Evaluate visibility of the field:

• Partially Occluded but Identifiable – Annotate the crop type or mark as uncultivated.
• Clearly Visible and Identifiable – Proceed to assign the correct crop label.

Qualifications

• Academic Background : Bachelor’s degree (or higher) in Agriculture, Agronomy, Crop Science, Agricultural Engineering, Horticulture, or a related field.
• Hands-on Experience : Knowledge in Geography, Remote Sensing, Environmental Science, or GIS with exposure to crop identification.
• Agriculture Experience : Previous involvement in crop identification, agricultural surveys, or image annotation.
• Visual Identification Skills : Ability to distinguish crop types from both partial and full views.

Preferred Skills

• Strong attention to detail and familiarity with diverse crop types.
• Prior experience using image annotation tools and platforms is an advantage.
• Ability to work independently and deliver results under defined timelines.

• Education:
• Expérience:
• Education
  
• No degree, certificate or diploma
• Tasks
  
• Clear and collect brush and debris from fields, pens and other work areas
• Clear fields of wood and stones
• Cut agricultural crops
• Divide fresh harvested produce into marketable lots and non-marketable lots
• Dose water saturation, light and temperature as instructed for crop growth and development
• Greenhouse cleaning
• Hand harvesting vegetables
• Harvest seedlings
• Mixing fertilizer
• Pack fruits and vegetables
• Plant, cultivate and irrigate crops
• Clean work area
• Fertilize and spray crops
• Harvest crops
• Examine product for quality and its readiness for the market
• Experience
  
• Experience an asset
• Durée de l'emploi: Permanent
• Langue de travail: Anglais
• Heures de travail: 40 hours per week

English

Work must be completed at the physical location. There is no option to work remotely.