1 Introduction
2 Materials and methods
2.1 Study area
Fig. 1 Spatial distribution of wheatgrowing areas of the study area 
2.2 Data collection and preprocessing
Table 1 Rules to determine the severity levels 
Level  1  2  3  4  5 

I  ≤10  10< I ≤20  20< I ≤30  30< I ≤40  >40 
2.3 Selection of vegetation indices
Table 2 Selected vegetation indices in this study 
Vegetation index  Abbreviation  Formula 

Simple Ratio Index^{［25］}  SRI  SRI= ${R}_{\mathrm{N}\mathrm{I}\mathrm{R}}/{R}_{\mathrm{R}\mathrm{e}\mathrm{d}}$ （4） 
Normalized Difference Vegetation Index^{［26］}  NDVI  NDVI = $\left({R}_{\mathrm{N}\mathrm{I}\mathrm{R}}{R}_{\mathrm{R}\mathrm{e}\mathrm{d}}\right)/\left({R}_{\mathrm{N}\mathrm{I}\mathrm{R}}+{R}_{\mathrm{R}\mathrm{e}\mathrm{d}}\right)$ （5） 
Normalized Difference Greenness Index^{［27］}  NDGI  NDGI = $\left({R}_{\mathrm{N}\mathrm{I}\mathrm{R}}{R}_{\mathrm{G}\mathrm{r}\mathrm{e}\mathrm{e}\mathrm{n}}\right)/\left({R}_{\mathrm{N}\mathrm{I}\mathrm{R}}+{R}_{\mathrm{G}\mathrm{r}\mathrm{e}\mathrm{e}\mathrm{n}}\right)$ （6） 
SoilAdjusted Vegetation Index^{［28］}  SAVI  SAVI = $1.5\left({R}_{\mathrm{N}\mathrm{I}\mathrm{R}}{R}_{\mathrm{R}\mathrm{e}\mathrm{d}}\right)/\left({R}_{\mathrm{N}\mathrm{I}\mathrm{R}}+{R}_{\mathrm{R}\mathrm{e}\mathrm{d}}+0.5\right)$ （7） 
Enhanced Vegetation Index^{［29］}  EVI  EVI = $2.5\left({R}_{\mathrm{N}\mathrm{I}\mathrm{R}}{R}_{\mathrm{R}\mathrm{e}\mathrm{d}}\right)/\left({R}_{\mathrm{N}\mathrm{I}\mathrm{R}}+6{R}_{\mathrm{R}\mathrm{e}\mathrm{d}}7.5{R}_{\mathrm{B}\mathrm{l}\mathrm{u}\mathrm{e}}+1\right)$ （8） 
Triangular Vegetation Index^{［30］}  TVI  $\mathrm{T}\mathrm{V}\mathrm{I}=0.5\left[120\left({R}_{\mathrm{N}\mathrm{I}\mathrm{R}}{R}_{\mathrm{G}\mathrm{r}\mathrm{e}\mathrm{e}\mathrm{n}}\right)200\left({R}_{\mathrm{R}\mathrm{e}\mathrm{d}}{R}_{\mathrm{G}\mathrm{r}\mathrm{e}\mathrm{e}\mathrm{n}}\right)\right]$ （9） 
Differential Vegetation Index^{［31］}  DVI  DVI= ${R}_{\mathrm{N}\mathrm{I}\mathrm{R}}{R}_{\mathrm{R}\mathrm{e}\mathrm{d}}$ （10） 
Structure Insensitive Pigment Index^{［32］}  SIPI  $\mathrm{S}\mathrm{I}\mathrm{P}\mathrm{I}=\left({R}_{\mathrm{N}\mathrm{I}\mathrm{R}}{R}_{\mathrm{B}\mathrm{l}\mathrm{u}\mathrm{e}}\right)/\left({R}_{\mathrm{N}\mathrm{I}\mathrm{R}}+{R}_{\mathrm{B}\mathrm{l}\mathrm{u}\mathrm{e}}\right)\text{}$ （11） 

2.4 Estimation of LST
Fig. 2 The LST of Jinzhou estimated by the Landst8 TIRS image on 22 May 2014 
2.5 Spatialtemporal fusion of MOD11A1 and Landsat8 LST
2.6 Construction of monitoring models
3 Results and discussion
3.1 Validation of the monitoring results
Table 3 Comparison of the accuracies using the four monitoring models 
Model  Confusion matrix  Accuracy assessment indicator  

Healthy  Mild  Severe  User accuracy/%  Producer accuracy/%  Overall accuracy/%  k  
LSTSVM  Healthy  14  7  0  66.7  63.6  63.8  0.38 
Mild  8  25  4  83.8  65.8  
Severe  0  6  5  45.5  55.6  
SLSTSVM  Healthy  14  7  0  66.7  82.4  76.8  0.59 
Mild  3  32  2  86.5  74.4  
Severe  0  4  7  63.6  77.8  
MLSTSVM  Healthy  15  6  0  71.4  88.2  73.9  0.54 
Mild  2  32  3  86.5  71.1  
Severe  0  7  4  36.4  57.1  
SMLSTSVM  Healthy  16  5  0  76.2  84.2  81.2  0.67 
Mild  3  33  1  89.2  78.6  
Severe  0  4  7  63.6  87.5 
3.2 Mapping of wheat powdery mildew
Fig. 3 Comparison of monitoring wheat powdery mildew by the SLSTSVM model and SMLSTSVM model（a） Disease severities of wheat powdery mildew derived from the SLSTSVM model （b） Disease severities of wheat powdery mildew derived from the SMLSTSVM model 