The Earth Observation-based Anomaly Detection (EOAD) system: A simple, scalable approach to mapping in-field and farm-scale anomalies using widely available satellite imagery-Reference-Cited by-同舟云学术

The Earth Observation-based Anomaly Detection (EOAD) system: A simple, scalable approach to mapping in-field and farm-scale anomalies using widely available satellite imagery

Published:2021-12 Issue: Volume:104 Page:102535
ISSN:0303-2434
Container-title:International Journal of Applied Earth Observation and Geoinformation
language:en
Short-container-title:International Journal of Applied Earth Observation and Geoinformation

Author:

Castillo-Villamor Liliana,Hardy Andy,Bunting Pete,Llanos-Peralta Willian,Zamora Miguel,Rodriguez Yeison,Gomez-Latorre Douglas A.

Funder

Douglas Bomford Trust

UK Space Agency

Publisher

Elsevier BV

Subject

Management, Monitoring, Policy and Law,Computers in Earth Sciences,Earth-Surface Processes,Global and Planetary Change

Reference62 articles.

1. World Agriculture Towards 2030/2015: The 2012 Revision;Alexandratos,2012

2. Assessing the accuracy of species distribution models: prevalence, kappa and the true skill statistic (TSS);Allouche;J. Appl. Ecol.,2006

3. Sentinel-2 cropland mapping using pixel-based and object-based time-weighted dynamic time warping analysis;Belgiu;Remote Sens. Environ.,2018

4. Object based image analysis for remote sensing;Blaschke;ISPRS Journal of Photogrammetry and Remote Sensing,2010

5. Forecasting crop yield using remotely sensed vegetation indices and crop phenology metrics;Bolton;Agric. For. Meteorol.,2013

Cited by 7 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Web-based spatial decision support system for precision agriculture: A tool for delineating dynamic management unit zones (MUZs);Smart Agricultural Technology;2024-08

2. Evaluation and analysis of target interpretation capability for novel rotating synthetic aperture system;Optics and Lasers in Engineering;2024-05

3. Aerospace Technologies in Grazing Livestock;Lecture Notes in Networks and Systems;2024

4. AgriSen-COG, a Multicountry, Multitemporal Large-Scale Sentinel-2 Benchmark Dataset for Crop Mapping Using Deep Learning;Remote Sensing;2023-06-07

5. UAV-Based Remote Sensing for Soybean FVC, LCC, and Maturity Monitoring;Agriculture;2023-03-16