## Goal of the Competition
Birds are excellent indicators of biodiversity change since they are highly mobile and have diverse habitat requirements. Changes in species assemblage and the number of birds can thus indicate the success or failure of a restoration project. However, frequently conducting traditional observer-based bird biodiversity surveys over large areas is expensive and logistically challenging. In comparison, passive acoustic monitoring (PAM) combined with new analytical tools based on machine learning allows conservationists to sample much greater spatial scales with higher temporal resolution and explore the relationship between restoration interventions and biodiversity in depth.

<img title=”Sholicola” src="https://storage.googleapis.com/kaggle-media/competitions/BirdCLEF/sholicola-ian_lockwood_inset.jpeg" style="float: right; width: 250px">

For this competition, you'll use your machine-learning skills to identify under-studied [Indian bird species](https://stateofindiasbirds.in/) by sound. Specifically, you'll develop computational solutions to process continuous audio data and recognize the species by their calls. The best entries will be able to train reliable classifiers with limited training data. If successful, you'll help advance ongoing efforts to protect avian biodiversity in the Western Ghats, India, including those led by [V. V. Robin's Lab at IISER Tirupati](https://www.skyisland.in/). 

## Context
In the face of rapid anthropogenic pressures of habitat modification and climate change, we need to utilize the latest conservation tools and technologies to monitor biodiversity. Through the Kaggle competition, we aim to carry out automated detection and classification of bird species of the Western Ghats from soundscapes. 

The Western Ghats are a Global Biodiversity Hotspot, with the mountain range running along the southwestern coast of India. It is home to diverse ecosystems that support extraordinary levels of biodiversity. These ecosystems range from high-elevation forest-grassland mosaics to tropical dry deciduous forests to wet-evergreen rainforests, to name a few. Additionally, this region is home to large human populations whose livelihoods depend on the forests and the natural resources the region provides. From an avifaunal perspective, this region is home to high levels of bird diversity, with several endemic and endangered species found nowhere else. However, this mountain range is undergoing drastic landscape and climatic changes that negatively affect biodiversity. Hence, we need conservation technologies and tools to help us assess and monitor bird diversity rapidly. 

The broader goals for this Kaggle competition include:
(1) Identify endemic bird species of the sky-islands of the Western Ghats in soundscape data.
(2) Detect/classify endangered bird species (species of conservation concern) featuring limited training data.
(3) Detect/classify nocturnal bird species which are poorly understood.

Thanks to your innovations, it will be easier for researchers and conservation practitioners to survey avian population trends accurately. As a result, they'll be able to evaluate threats and adjust their conservation actions regularly and more effectively.

This competition is collaboratively organized by (alphabetic order) the Chemnitz University of Technology, Google Research, Indian Institute of Science Education and Research (IISER) Tirupati, K. Lisa Yang Center for Conservation Bioacoustics at the Cornell Lab of Ornithology, LifeCLEF, and Xeno-canto.