English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

This study aimed at investigating the potential of vegetation indices and precipitation-related variables derived from remote sensing to assess rangeland production in the arid environment of the Moroccan Oriental region and identifying the challenges linked to that particular biome. Vegetation indices (VIs) and the Standardized Precipitation Index (SPI) computed at various aggregation periods were first integrated into a Random Forest model. In a second step, we studied in more detail the linear relationship between rangeland biomass and one of the spectral indices (ARVI) for the various vegetation formations present in the area. We concluded that, mostly due to the presence of alfa steppes (Stipa tenacissima), and especially to a large proportion of non-photosynthetic vegetation, it is not possible to accurately estimate rangeland production with a global model in this region. We recommend separating Stipa tenacissima from the other species in models and focusing on methods aimed at studying dry and non-photosynthetic vegetation to improve the quality of the prediction for alfa steppes.

remote sensing

Estimation of Rangeland Production in the Arid Oriental Region (Morocco) Combining Remote Sensing Vegetation and Rainfall Indices: Challenges and Lessons Learned