Remote sensing plays a critical role in long-term monitoring of biodiversity across spatial and temporal scales and technological and analytical advances are combining to broaden potential…

This is a $1,212,339 cooperative agreement awarded by the Shared Services Center of the National Aeronautics and Space Administration (NASA) to Sonoma State University, a public university in California. The agreement, titled "Soundscapes to Landscapes (S2L)," aims to advance animal diversity monitoring using next-generation and existing Earth-observing satellites.

The project engages citizen scientists to collect field data on bird diversity through bioacoustics, assesses the accuracy of bioacoustics for species detection and monitoring, and tests the potential of spaceborne remote sensing technologies, including hyperspectral, lidar, and synthetic aperture radar, for spatial modeling of species occupancy and richness. The findings will be used to understand factors related to conserving animal diversity and identify areas with societal value, such as carbon storage.

This agreement does not have a set-aside designation and is part of Sonoma State University's broader efforts to support federal agencies through scientific research, educational outreach, and technology development across disciplines like biology, physics, and environmental science.

Remote sensing plays a critical role in long-term monitoring of biodiversity across spatial and temporal scales and technological and analytical advances are combining to broaden potential applications focused on animal diversity. In particular, lidar provides measurements of 3D vertical vegetation structure related to animal habitat and organismal and functional diversity. Imaging spectroscopy can detect canopy foliar chemistry, spectral-chemical diversity related to plant functional and floristic diversity, and map plant species and land cover, variables related to animal habitat. The synergy of space-based imaging spectrometer and lidar sensors has great potential for global biodiversity assessment and monitoring, leading the 2017-2027 decadal survey for earth science and applications from space to recommend these sensors as high-priority missions. Spatial models that characterize aspects of biodiversity, such as species distributions or richness, from remote sensing predictor variables need extensive and representative in situ species data for calibration and validation. Citizen science (CS), where public volunteers are enlisted in scientific inquiry, has been successful in collecting large amounts of in situ species presence data while engaging the public in science and environmental issues. In addition, new low-cost technology for automated species identification through sound recordings (bioacoustics) in combination with CS may further increase species observations. Soundscapes to landscapes (S2L) seeks to advance animal diversity monitoring from next-generation and existing earth-observing satellites. Driven by CS composed of students, birder watchers and landowners, the project uses sound recordings from field sites and a cloud-based bioacoustics analysis platform to identify bird species by their calls and then predict their presence at sites. We engage CS with field campaigns that deploy recorders to sites on public and private lands, through a series of ?bird blitz? Workshops for bioacoustics work, and call identification modeling for motivated bird enthusiasts. The S2L science team uses CS bioacoustics-based bird data in a unified analytical framework to explore the benefits and trade-offs in spaceborne imaging spectrometer, lidar, and existing land imagers for spatial modeling of avian diversity and use of products in conservation planning. The project has four main goals: 1) involve citizen scientists in the collection of field information on bird diversity through bioacoustics 2) assess the accuracy and precision of bioacoustics for the detection and monitoring of individual species and richness 3) test the potential of spaceborne hyperspectral, lidar, synthetic aperture radar (SAR), and multispectral optical sensors for spatial modeling of species occupancy and overall species richness and, 4) use occupancy/richness maps to better understand factors related to conserving animal diversity and identify those areas in the landscape with complementary societal value (e.g., carbon storage). We focus our investigation in sonoma county of northern california, an area with a diverse range of natural vegetation, urban and agricultural gradients, recent fire disturbance, as well as a rich suite of remote sensing data. The investigation includes spaceborne lidar (global ecosystem dynamics investigation lidar - gedi) and imaging spectrometer (hyperspectral infrared imager - hyspiri) sensors, simulated from airborne sensors, and multi-seasonal SAR and multispectral optical sensors on existing satellites (e.g., landsat, sentinels). We use data from these sensors, environmental spatial predictors, bioacoustics-based species presence/absence, and statistical and modeling analyses to assess the relative strengths, weaknesses, and synergies of current and future remote sensing technology for predicting the spatial distribution of individual avian species and overall richness across a range of ecosystems.