Agriculture: Difference between revisions

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== Background Readings ==
 
* [https://doi.org/10.1016/j.agsy.2020.103016 Machine learning for large-scale crop yield forecasting]
* ''[https://link.springer.com/article/10.1007/s11069-017-3106-x Characterizing agricultural drought in the Karamoja subregion of Uganda with meteorological and satellite-based indices]''
* [https://www.mdpi.com/2072-4292/11/6/676 Remote Sensing Techniques for Soil Organic Carbon Estimation: A Review]
 
== Online Courses and Course Materials ==
 
* '''CGIAR-Platform for Big Data in Agriculture:''' A series of webinars for data management and data mining related to crop improvement and food security. Website [https://bigdata.cgiar.org/webinars/ here].
* '''Geocomputation with R:''' An open source book for geographic data analysis using R. Website [https://geocompr.robinlovelace.net/index.html here].
 
== Conferences, Journals, and Professional Organizations ==
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*'''Computers and Electronics in Agriculture:''' International journal covering computer hardware and software for solving problems in agriculture, agronomy and horticulture. Website [https://www.journals.elsevier.com/computers-and-electronics-in-agriculture here].
*'''Precision Agriculture:''' International Journal on Advances in Precision Agriculture. Website [https://www.springer.com/journal/11119 here].
*'''Remote Sensing in Agriculture and Vegetation''': Open-access journal focusing on remote sensing with special issues related to agricultural applications. Website [https://www.mdpi.com/journal/remotesensing/sections/RSAV here].
 
=== Workshops ===
 
* '''ICLR 2020 Workshop on''' '''Computer Vision for Agriculture:''' Exposes the progress and unsolved problems of computational agriculture to the AI research community. Website [https://www.cv4gc.org/cv4a2020/ here].
* '''CVPR 2020/2021 Workshop and Prize Challenge on Agriculture-Vision:''' Present recent progress on computer vision research for tackling impactful challenges in agriculture. Website [https://www.agriculture-vision.com/home here].
 
=== Professional Organizations and Conferences ===
 
* '''ISPA:''' International Society of Precision Agriculture. Website [https://www.ispag.org/ here].
* '''ECPA 2021:''' European Conference on Precision Agriculture. Website [https://www.ecpa2021.hu/ here].
* '''ASABE:''' American Society of Agricultural and Biological Engineers. Website [https://www.asabe.org/ here].
* '''ASABE AIM 2021:''' American Society of Agricultural and Biological Engineers Annual International Meeting. Website [https://www.asabemeetings.org/ here].
* '''GRSS-IEEE:''' The IEEE Geoscience and Remote Sensing Society. Website [https://www.grss-ieee.org/ here].
* '''IGARSS 2021:''' International Geoscience and Remote Sensing Symposium. Website [https://igarss2021.com/ here].
* '''ICGIRSA 2021:''' International Conference on GIS and Remote Sensing in Agriculture. Website [https://waset.org/gis-and-remote-sensing-in-agriculture-conference-in-june-2021-in-copenhagen here].
* '''DAGM:''' The German Association for Pattern Recognition. Website [https://www.dagm.de/the-german-association-for-pattern-recognition here].
* '''DAGM GCPR 2021:''' DAGM German Conference on Pattern Recognition. Website [https://dagm-gcpr.de/ here].
* '''SPIE:''' The International Society for Optics and Photonics. Website [https://spie.org/about-spie?SSO=1 here].
* '''SPIE conference:''' SPIE conference on Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping. Website [https://spie.org/si21/conferencedetails/autonomous-sensing-systems-agricultural?utm_id=rsi21scpw&SSO=1 here].
* '''WorldAgri-Tech Innovation Summit 2021:''' International summit for agri-business networking. Website [https://worldagritechinnovation.com/ here].
 
=== Groups and Labs ===
 
* '''Australian Centre for Field Robotics:''' Robotic institute focusing on autonomous robots that can work in outdoor environment. Website [https://www.sydney.edu.au/engineering/our-research/robotics-and-intelligent-systems/australian-centre-for-field-robotics.html Australian Centre for Field Roboticshere].
 
== Library and Tools ==
Some packages for working with remote sensing data are,
 
* [https://medium.com/sentinel-hub/introducing-'''eo-learn-ab37f2869f5c eo-learn]:''' A python package maintained by the European Space Agency, giving easy access to imagery from Sentinel satellites, as well as utilities for data processing. [https://github.com/sentinel-hub/eo-learn Github], [https://medium.com/sentinel-hub/introducing-eo-learn-ab37f2869f5c medium-post].
* '''RSCD:''' A MATLAB toolbox for remote sensing change detection. [https://github.com/Bobholamovic/ChangeDetectionToolbox Github].
* '''geemap:''' A Python package for interactive mapping with Google Earth Engine. [https://github.com/giswqs/geemap/tree/master/examples Github], [https://geemap.org/ website].
* A list of Python and R codes and different resources for geospatial analysis and EO data. [https://github.com/acgeospatial/awesome-earthobservation-code Github].
* An updated list of geospatial analysis tools. [https://github.com/sacridini/Awesome-Geospatial Github].
 
== Data ==
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=== Remote Crop Identification ===
 
* [https://arxiv.org/abs/2001.01306 '''Agriculture-Vision: A Large Aerial Image Database for Agricultural Pattern Analysis:''' A dataset composed of 94,986 aerial images from 3,432 farmlands across the United States. The images contains RGB channels and Near-infrared at a resolution of 10 cm per pixel. [https://www.agriculture-vision.com/dataset Dataset], and [https://arxiv.org/abs/2001.01306 paper] describing the dataset.
* LandCoverNet: A multispectral satellite imagery dataset acquired from Sentinel-2 and can be used for land cover classification. The dataset was created by the Radiant Earth Foundation. [http://registry.mlhub.earth/10.34911/rdnt.d2ce8i/ Dataset] and [https://radiant-mlhub.s3-us-west-2.amazonaws.com/landcovernet/Documentation.pdf documentation].
* '''CropHarvest''': The [https://openreview.net/forum?id=JtjzUXPEaCu CropHarvest dataset], compiled by researchers affiliated with NASA Harvest, provides a unified global dataset, API, and benchmarks for ML methods in crop-type mapping.
 
=== Kaggle datasets ===
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