Agricultural Landscape Understanding At Country-Scale

Radhika Dua, Nikita Saxena, Aditi Agarwal, Alex Wilson, Gaurav Singh +30 more
11/8/2024
cs.CVcs.AIcs.CY

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Abstract

Agricultural landscapes are quite complex, especially in the Global South where fields are smaller, and agricultural practices are more varied. In this paper we report on our progress in digitizing the agricultural landscape (natural and man-made) in our study region of India. We use high resolution imagery and a UNet style segmentation model to generate the first of its kind national-scale multi-class panoptic segmentation output. Through this work we have been able to identify individual fields across 151.7M hectares, and delineating key features such as water resources and vegetation. We share how this output was validated by our team and externally by downstream users, including some sample use cases that can lead to targeted data driven decision making. We believe this dataset will contribute towards digitizing agriculture by generating the foundational baselayer.

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Cite this paper

@article{dua2024agricultural,
  title  = {Agricultural Landscape Understanding At Country-Scale},
  author = {Radhika Dua and Nikita Saxena and Aditi Agarwal and Alex Wilson and Gaurav Singh and Hoang Tran and Ishan Deshpande and Amandeep Kaur and Gaurav Aggarwal and Chandan Nath and Arnab Basu and Vishal Batchu and Sharath Holla and Bindiya Kurle and Olana Missura and Rahul Aggarwal and Shubhika Garg and Nishi Shah and Avneet Singh and Dinesh Tewari and Agata Dondzik and Bharat Adsul and Milind Sohoni and Asim Rama Praveen and Aaryan Dangi and Lisan Kadivar and E Abhishek and Niranjan Sudhansu and Kamlakar Hattekar and Sameer Datar and Musty Krishna Chaithanya and Anumas Ranjith Reddy and Aashish Kumar and Betala Laxmi Tirumala and Alok Talekar},
  year   = {2024},
  eprint = {2411.05359},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2411.05359v1}
}

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