Abstract
Accurate spatial distribution information of native, mixed, and tame grasslands is essential for maintaining ecosystem health in the Prairie. This research aimed to use the latest monitoring technology to assess the remaining grasslands in Saskatchewan’s mixed grassland ecoregion (MGE). The classification approach was based on 78 raster-based variables derived from big remote sensing data of multispectral optical space-borne sensors such as MODIS and Sentinel-2, and synthetic aperture radar (SAR) space-borne sensors such as Sentinel-1. Principal component analysis (PCA) was used as a data dimensionality reduction technique to mitigate big data load and improve processing time. Random Forest (RF) was used in the classification process and incorporated the selected variables from 78 satellite-based layers and 2385 reference training points. Within the MGE, the overall accuracy of the classification was 90.2%. Native grassland had 98.20% of user’s accuracy and 88.40% producer’s accuracy, tame grassland had 81.4% user’s accuracy and 93.8% producer’s accuracy, whereas mixed grassland class had very low user’s accuracy (45.8%) and producer’s accuracy 82.83%. Approximately 3.46 million hectares (40.2%) of the MGE area are grasslands (33.9% native, 4% mixed, and 2.3% tame). This study establishes a novel analytical framework for reliable grassland mapping using big data, identifies future challenges, and provides valuable information for Saskatchewan and North America decision-makers.
Highlights
In Canada, native grasslands provide habitat for wildlife, conservation of biodiversity, and soil carbon sequestration [1]
Our research aims to develop a new machine learning (ML) workflow using big remote sensing data to distinguish between three (3) different grassland classes across 86,300 km2 in Saskatchewan, Canada
The preliminary data analysis of 17 years Normalized Difference Vegetation Index (NDVI) time-series for the pilot area showed normal fluctuations between the seasons and slight differences between the grassland classes. ∆xnt, ∆xnnt and ∆xtnt have the highest values in the period between 15 June to
Summary
In Canada, native grasslands provide habitat for wildlife, conservation of biodiversity, and soil carbon sequestration [1]. It is estimated that 21.8% of the global natural habitat has been transformed to human land uses, and more than 50% of the native land cover in North America, such as native grasslands, mixed forests, and savannas, have been lost [3]. This loss of grasslands was mainly due to cropland conversion, which is the greatest threat to native grassland in the Prairie [4]. Native grasslands have experienced significant invasion by exotic grasses and forbs, leading to parcels of land mixed with native and tame vegetation [5]. Assessing native grasslands is critical for effective wildlife conservation strategies for species-at-risk [4,6]
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