Imaging spectroscopy reveals topographic variability effects on grassland functional traits and drought responses

Functional traits and their variations are essential indicators of plant metabolism, growth, distribution, and survival and determine how a plant and an ecosystem function. Under the same climatic condition, traits can vary significantly between species and within the same species growing in different topographic conditions. When drought stress occurs, plants growing in these conditions may respond in various ways as their tolerance and adaptability are influenced by differences in topography. Insights into topographic variability-driven trait variation and drought response can improve our prediction of ecosystem functioning and ecological impacts. Imaging spectroscopy enables accurate identification of plant species, extraction of functional traits, and characterization of topography-driven and drought-related impacts on trait variation across spatial scales. However, applying this data in a heterogeneous grassland ecosystem is challenging as species are small, high mixed, spectrally a..., , , # Data and Codes: Imaging spectroscopy reveals topographic variability effects on grassland functional traits and drought responses

## Data

### Hyperspectral images (hyperspectral\_images):

Hyperspectral images used in this study include **20160823_HSI.tif** for the year of 2016 and **20170820_HSI_INT_N.tif** for the year of 2017. Both datasets have 301 bands ranging from 400 nm to 1000 nm with a spectral interval of 2 nm. The reflectance values of pixels in the **20170820_HSI_INT_N.tif** dataset are scaled up by multiplying the original reflectance by 10000 and stored in the integer data format. Hyperspectral images were acquired on 23 August 2016 and 20 August 2017 by a Mirco-Hyperspec VNIR push-broom sensor (Headwall Photonics Inc, USA), operated on a JetRanger helicopter.

### Species classification training data (species\_classification\_training\_data):

This dataset contains the training and test datasets in shapefile format for species classification model training and valida...