Integrating remote sensing with ecology and evolution to advance biodiversity conservation

J Cavender-Bares, FD Schneider, MJ Santos… - Nature Ecology & …, 2022 - nature.com
Remote sensing has transformed the monitoring of life on Earth by revealing spatial and
temporal dimensions of biological diversity through structural, compositional and functional …

[HTML][HTML] NASA's surface biology and geology designated observable: A perspective on surface imaging algorithms

K Cawse-Nicholson, PA Townsend, D Schimel… - Remote Sensing of …, 2021 - Elsevier
Abstract The 2017–2027 National Academies' Decadal Survey, Thriving on Our Changing
Planet, recommended Surface Biology and Geology (SBG) as a “Designated Targeted …

[HTML][HTML] Individual tree-crown detection in RGB imagery using semi-supervised deep learning neural networks

BG Weinstein, S Marconi, S Bohlman, A Zare, E White - Remote Sensing, 2019 - mdpi.com
Remote sensing can transform the speed, scale, and cost of biodiversity and forestry
surveys. Data acquisition currently outpaces the ability to identify individual organisms in …

A best-practice guide to predicting plant traits from leaf-level hyperspectral data using partial least squares regression

AC Burnett, J Anderson, KJ Davidson… - Journal of …, 2021 - academic.oup.com
Partial least squares regression (PLSR) modelling is a statistical technique for correlating
datasets, and involves the fitting of a linear regression between two matrices. One …

Combining transfer learning and hyperspectral reflectance analysis to assess leaf nitrogen concentration across different plant species datasets

L Wan, W Zhou, Y He, TC Wanger, H Cen - Remote Sensing of …, 2022 - Elsevier
Accurate estimation of leaf nitrogen concentration (LNC) is critical to characterize ecosystem
and plant physiological processes for example in carbon fixation. Remote sensing can …

UAVs as remote sensing platforms in plant ecology: review of applications and challenges

Z Sun, X Wang, Z Wang, L Yang, Y Xie… - Journal of Plant …, 2021 - academic.oup.com
Abstract Aims Unmanned aerial vehicles (UAVs), ie drones, have recently emerged as cost-
effective and flexible tools for acquiring remote sensing data with fine spatial and temporal …

Climate change effects on pathogen emergence: Artificial intelligence to translate big data for mitigation

KA Garrett, DP Bebber, BA Etherton… - Annual Review of …, 2022 - annualreviews.org
Plant pathology has developed a wide range of concepts and tools for improving plant
disease management, including models for understanding and responding to new risks from …

Hyperspectral imagery to monitor crop nutrient status within and across growing seasons

N Liu, PA Townsend, MR Naber, PC Bethke… - Remote Sensing of …, 2021 - Elsevier
Imaging spectroscopy provides the opportunity to monitor nutrient status of vegetation. In
crops, prior studies have generally been limited in scope, either to a small wavelength range …

From spectra to plant functional traits: Transferable multi-trait models from heterogeneous and sparse data

E Cherif, H Feilhauer, K Berger, PD Dao… - Remote Sensing of …, 2023 - Elsevier
Large-scale information on several vegetation properties ('plant traits') is critical to assess
ecosystem functioning, functional diversity and their role in the Earth system. Hyperspectral …

Field spectroscopy of canopy nitrogen concentration in temperate grasslands using a convolutional neural network

RR Pullanagari, M Dehghan-Shoar, IJ Yule… - Remote Sensing of …, 2021 - Elsevier
As an essential feature of plant autotrophy, Nitrogen (N) is the major nutrient affecting plant
growth in terrestrial ecosystems, thus is of not only fundamental scientific interest, but also a …