Timely monitoring of global plant biogeochemical processes demands fast and highly accurate estimation of plant nutrition status, which is often estimated based on hyperspectral data. However, few such studies have been conducted on degraded vegetation. In this study, complete combinations of either original reflectance or first-order derivative spectra have been developed to quantify leaf nitrogen (N), phosphorus (P), and potassium (K) contents of tree, shrub, and grass species using hyperspectral datasets from light, moderate, and severely degraded vegetation sites in Helin County, China. Leaf N, P, and K contents were correlated to identify suitable combinations. The most effective combinations were those of reflectance difference (Dij), normalized differences (ND), first-order derivative (FD), and first-order derivative difference (FD(D)). Linear regression analysis was used to further optimize sensitive band-based combinations, which were compared with 43 frequently used empirical spectral indices. The proposed hyperspectral indices were shown to effectively quantify leaf N, P, and K content (R2 > 0.5, p < 0.05), confirming that hyperspectral data can be potentially used for fine scale monitoring of degraded vegetation.employed in biomes such as grasslands and savannas 1,18-20 , crops 21 , and trees 22 . A study of maize leaf P content found that 540, 720, 740, and 850 nm are the most sensitive bands for detection of P in both the vegetation production stage and the flowering stage 21 .The spectral region which most closely relates to leaf P content has been found to overlay the spectral region which demonstrates water absorbing traits (1000-2500 nm) 19 . Bands which are indicative of leaf P also lie in the region of 580-710 nm, although this varies among different case studies. The confusion between water absorption and sensitivity to sampling sites makes it difficult to identify the most suitable bands for leaf P estimation. In this study, we aimed to select several sensitive bands from the 500 available and develop a complete combination of reflectance and its first-order derivative (FD) from tree, shrub, and grass species in various degraded vegetation sites, with the objective of developing more general hyperspectral indices for the estimation of leaf P content.Finally, potassium (K) is also a key plant requirement, present mostly as K + ions in vacuoles. K provides regulatory control over processes such as transpiration, starch synthesis, sucrose translocation, respiration, and lipid synthesis 23 . Plants deficient in K exhibit limited growth, metabolism, and stress defense 24 , leading to lower overall biomass and coverage and changes to leaf color. If a K deficiency occurs at the vegetation level, this can accelerate the degradation process. Soils in many broad-acre semiarid areas have become deficient in K, resulting in a decrease of K in the canopy and stem 25,26 .Remote sensing of leaf N, P, or K contents is a challenging task due to the lack of direct absorption features that can be observed in t...