【数据科学赛】有害藻华检测挑战赛 #图像检测 #$30,000 #NASA

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更多比赛信息见 CompHub主页

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以下内容摘自比赛主页（点击文末阅读原文进入）

Part1赛题介绍

题目

Tick Tick Bloom: Harmful Algal Bloom Detection Challenge

举办平台

DrivenData

主办方

背景

Inland water bodies provide a variety of critical services for both human and aquatic life, including drinking water, recreational and economic opportunities, and marine habitats. A significant challenge water quality managers face is the formation of harmful algal blooms (HABs). One of the major types of HABs is cyanobacteria. HABs produce toxins that are poisonous to humans and their pets, and threaten marine ecosystems by blocking sunlight and oxygen. Manual water sampling, or “in situ” sampling, is generally used to monitor cyanobacteria in inland water bodies. In situ sampling is accurate, but time intensive and difficult to perform continuously.

内陆水体为人类和水生生物提供各种关键服务，包括饮用水、娱乐和经济机会以及海洋栖息地。水质管理者面临的一个重大挑战是有害藻华 (HAB) 的形成。 HAB 的主要类型之一是蓝细菌。 HAB 产生对人类及其宠物有毒的毒素，并通过阻挡阳光和氧气威胁海洋生态系统。人工取水或“原位”取样通常用于监测内陆水体中的蓝藻。原位采样是准确的，但时间密集且难以连续执行。

Part2时间安排

Competition End Date: Feb. 17, 2023, 11:59 p.m. UTC

Part3奖励机制

Place	Prize Amount
1st	$12,000
2nd	$9,000
3rd	$6,000

Bonus prize	Prize Amount
1st	$2,000
2nd	$1,000

BONUS PRIZE: BEST WRITE-UPS OF METHODS

The 5 top-scoring performers in this competition will be invited to submit a brief write-up of their modeling methodology. A bonus prize will be awarded to the two best write-ups as selected by a judging panel based on factors including model interpretability and robustness.

Part4赛题描述

Your goal in this challenge is to use satellite imagery to detect and classify the severity of cyanobacteria blooms in small, inland water bodies. The resulting algorithm will help water quality managers better allocate resources for in situ sampling, and make more informed decisions around public health warnings for critical resources like drinking water reservoirs. Ultimately, more accurate and more timely detection of algal blooms helps keep both the human and marine life that rely on these water bodies safe and healthy.

您在这项挑战中的目标是使用卫星图像检测和分类小型内陆水体中蓝藻水华的严重程度。由此产生的算法将帮助水质管理者更好地为原位采样分配资源，并围绕饮用水水库等关键资源的公共卫生警告做出更明智的决策。最终，更准确、更及时地检测藻类大量繁殖有助于确保依赖这些水体的人类和海洋生物的安全和健康。

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