arXiv Machine Learning By Kylen Solvik, Luis Gustavo Carvalho, Marcia N. Macedo

Mapping small reservoirs across Brazil from 1984 to 2025

Read the original on arXiv Machine Learning →

arXiv:2606. 00675v2 Announce Type: replace Abstract: Water research in Brazil largely overlooks the widespread damming of small streams for agricultural uses including watering cattle, farm-scale hydropower, irrigation, and aquaculture.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

arXiv AI
Jun 17

A geometric and deep learning reproducible pipeline for monitoring floating anthropogenic debris in urban rivers using in situ cameras

arXiv:2510. 23798v2 Announce Type: replace-cross Abstract: The proliferation of floating anthropogenic debris in rivers has emerged as a pressing environmental concern, exerting a detrimental influence on biodiversity, water quality, and human activities such as navigation and recreation.

By Gauthier Grimmer, Romain Wenger, Cl\'ement Flint, Germain Forestier, Gilles Rixhon, Valentin Chardon
arXiv AI
Jun 2

CAFOSat: A Strongly Annotated Dataset for Infrastructure-Aware CAFO Mapping Using High-Resolution Imagery

arXiv:2606. 00548v1 Announce Type: cross Abstract: Concentrated Animal Feeding Operations (CAFOs) play an important role in agricultural production but are also associated with environmental, public health, and disease surveillance concerns.

By Oishee Bintey Hoque, Nibir Chandra Mandal, Mandy L Wilson, Samarth Swarup, Madhav Marathe, Abhijin Adiga