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Showing 1 to 19 of 19 for “"Crop Monitoring"”.

  1. Agricultural Crop Monitoring with Computer Vision

    Precision agriculture allows farmers to efficiently use their resources with site-specific applications. The current work looks to computer vision for the data collection method necessary for such a smart field, including cameras sensitive to visual (430-650~nm), near infrared (NIR,750-900~nm), …

    vt Repository record for Agricultural Crop Monitoring with Computer Vision (opens in a new tab)

  2. A phenology-guided deep learning framework for near real-time crop monitoring

    Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2026-05-01

    uiuc Repository record for A phenology-guided deep learning framework for near real-time crop monitoring (opens in a new tab)

  3. Robotics in high tunnel agriculture: perception-driven harvesting and crop monitoring in unstructured environments

    Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2025-10-20 without embargo terms

    uiuc Repository record for Robotics in high tunnel agriculture: perception-driven harvesting and crop monitoring in unstructured environments (opens in a new tab)

  4. Crop monitoring and yield estimation using polarimetric SAR and optical satellite data in southwestern Ontario

    … been proven as an efficient source to extract crop information and monitor crop growth conditions over large areas. In local- to subfield-scale crop monitoring studies, both high spatial resolution and high temporal resolution of the image data are important. However, the acquisition of optical …

    uwo Repository record for Crop monitoring and yield estimation using polarimetric SAR and optical satellite data in southwestern Ontario (opens in a new tab)

  5. ADVANCING NATIONAL-SCALE HIGH-RESOLUTION CROP MAPPING USING REMOTE SENSING

    … on accurate, spatially explicit information on crop distribution. This dissertation advances national-scale crop type mapping in large countries by integrating remote sensing, sample-based field surveys, and machine learning to support both long-term and near-real-time agricultural monitoring. …

    maryland Repository record for ADVANCING NATIONAL-SCALE HIGH-RESOLUTION CROP MAPPING USING REMOTE SENSING (opens in a new tab)

  6. Evaluation of the UAV-Based Multispectral Imagery and Its Application for Crop Intra-Field Nitrogen Monitoring and Yield Prediction in Ontario

    … survey in agriculture. In addition, UAV-based crop monitoring and methods are new challenge of remote sensing application in agriculture. First, in my thesis the potential of UAV-based imagery was investigated to monitor spatial and temporal variation of crop status in comparison with RapidEye. …

    uwo Repository record for Evaluation of the UAV-Based Multispectral Imagery and Its Application for Crop Intra-Field Nitrogen Monitoring and Yield Prediction in Ontario (opens in a new tab)

  7. Informing on Crop Water-Use, Stress, and Growth with Integrated Satellite Remote Sensing and Modeling

    <p>Improving crop monitoring, both spatially and temporally, is a key factor in adapting agriculture to the effects of seasonal variability and climate change. Since 2014, numerous space-based remote sensing platforms have been deployed to increase land surface monitoring, with an objective to …

    cuny-grad Repository record for Informing on Crop Water-Use, Stress, and Growth with Integrated Satellite Remote Sensing and Modeling (opens in a new tab)

  8. Mapping the maize growth period using multi-temporal sentinel 1 and 2 imagery: a case study in Kasisi area of Chongwe district.

    Effective agricultural monitoring is essential for ensuring food security and efficient resource management. This study aimed to use Synthetic Aperture Radar (SAR) from Sentinel 1 and Optical imagery from Sentinel 2 multi spectral instrument (MSI) for mapping and monitoring Maize fields in the …

    zimbabwe Repository record for Mapping the maize growth period using multi-temporal sentinel 1 and 2 imagery: a case study in Kasisi area of Chongwe district. (opens in a new tab)

  9. Mapping the maize growth period using multi-temporal sentinel 1 and 2 imagery: a case study in Kasisi area of Chongwe district.

    Effective agricultural monitoring is essential for ensuring food security and efficient resource management. This study aimed to use Synthetic Aperture Radar (SAR) from Sentinel 1 and Optical imagery from Sentinel 2 multi spectral instrument (MSI) for mapping and monitoring Maize fields in the …

    zambia Repository record for Mapping the maize growth period using multi-temporal sentinel 1 and 2 imagery: a case study in Kasisi area of Chongwe district. (opens in a new tab)

  10. Earth observation technologies for improved agricultural decision support systems in South Africa

    … practices in South Africa, focusing on crop monitoring, water use efficiency, and land management. Firstly, a systematic review of remote sensing applications in Southern African agriculture, evaluating key advancements, challenges, and opportunities was conducted to document the key …

    western-cape Repository record for Earth observation technologies for improved agricultural decision support systems in South Africa (opens in a new tab)

  11. Accurate Target Geolocation and Vision-Based Landing with Application to Search and Engage Missions for Miniature Air Vehicles

    … military applications. Examples include: fire monitoring, search and rescue, traffic monitoring, crop monitoring, convoy protection, border surveillance, troop support, law enforcement, natural disaster relief, and aerial photography. The application of MAVs tends to center on the ability of …

    byu Repository record for Accurate Target Geolocation and Vision-Based Landing with Application to Search and Engage Missions for Miniature Air Vehicles (opens in a new tab)

  12. Autonomous Multi-Sensor and Web-Based Decision Support for Crop Diagnostics in Greenhouse

    … machine vision guided plant sensing and monitoring system was designed and constructed to continuously monitor plant related features: color (red-green-blue, hue-saturation-luminance, and color brightness), morphology (top projected canopy area), textural (entropy, energy, contrast, and …

    arizona-thes Repository record for Autonomous Multi-Sensor and Web-Based Decision Support for Crop Diagnostics in Greenhouse (opens in a new tab)

  13. Unmanned Aerial System for Monitoring Crop Status

    … cost of UAS with the need for increased crop yields under minimal applications of agrochemicals, and the immense potential for UAS in commercial agriculture becomes immediately apparent. What the agriculture community needs is a cost effective method for the field-wide monitoring of crops …

    vt Repository record for Unmanned Aerial System for Monitoring Crop Status (opens in a new tab)

  14. Techniques for Processing Airborne Imagery for Multimodal Crop Health Monitoring and Early Insect Detection

    During their growth, crops may experience a variety of health issues, which often lead to a reduction in crop yield. In order to avoid financial loss and sustain crop survival, it is imperative for farmers to detect and treat crop health issues. Interest in the use of unmanned aerial vehicles …

    vt Repository record for Techniques for Processing Airborne Imagery for Multimodal Crop Health Monitoring and Early Insect Detection (opens in a new tab)

  15. RoboFly: Towards Autonomous Flight of a Multimodal Insect-Scale Robot

    … search and rescue in disaster response, and crop monitoring for smart agriculture. Insect-sized flapping-wing robots draw inspiration from nature's tiny machines such as flies and bees. Earlier iterations of these robots have successfully demonstrated hovering flight. However, there are some …

    washington Repository record for RoboFly: Towards Autonomous Flight of a Multimodal Insect-Scale Robot (opens in a new tab)

  16. BlueBird: national-scale real-time crop cover classification using multi-stage deep learning approach

    An effective real-time crop cover classification prediction is essential to real-time large-scale crop monitoring. High resolution satellite optical data containing distinguishable signals of different crop types have been used by recent crop cover classification studies. However, existing works …

    uiuc Repository record for BlueBird: national-scale real-time crop cover classification using multi-stage deep learning approach (opens in a new tab)

  17. Integration Of Small Unmanned Aircraft Systems Into Precision Agriculture: Putting The Power Of Remote Sensing Into The Hands Of Farmers

    … to other proven remote sensing platforms for crop analysis. A review of the current sUAS regulations and a possible solution for speedy and safe integration will also be presented.</p>

    nodak Repository record for Integration Of Small Unmanned Aircraft Systems Into Precision Agriculture: Putting The Power Of Remote Sensing Into The Hands Of Farmers (opens in a new tab)