## 4 Experiment
### Results and Discussion
#### 4.2.4 MODIS-NDVI Downscaling Based on the Elastic Window  
The experiment involved downscaling 23 coarse spatial resolution MOD13Q1 NDVI images to a finer resolution within the study area of Province Shandong in the year 2010 using the elastic window method described in Section 3.2. The land cover class maps were obtained through the ISO-DATA classification of Landsat images, as shown in Table 3. The results of the downscaling experiment are presented in Figure 10, where the images are listed in row-major order based on 16-day intervals. Figure 8: The underdetermined pixel proportions of regular window (dot) and elastic window (triangle) of mixed scales from 5 to 50. Due to the large size of the study region, images with a spatial resolution of 30 m occupy a significant amount of computer memory. The Dell workstation (i5, 8G) with a Windows-based operating system was used for the experiment. The source code of the method was compiled with ENVI 5.4 desktop software ([[https://envi.geoscene.cn/](https://envi.geoscene.cn/)]([https://envi.geoscene.cn/](https://envi.geoscene.cn/)) accessed on 18 June 2023). To overcome this limitation, the high-resolution NDVI data images were resampled and segmented into small domains, resulting in a striping phenomenon in the mosaic image. Nevertheless, the high-resolution NDVI data images exhibit clear details and provide spatial information. Isolated outlier pixels are almost non-existent in Figure 10, indicating that the elastic-window-based downscaling method can effectively handle various land surface conditions over a wide area and mitigate the underdetermined problem to a certain extent. A comparison of the 23 high-resolution NDVI images throughout the year reveals noticeable changes in the land surface during vegetation growth periods. Figure 11 presents the high-resolution NDVI time series curves for several land cover types within the study area of Shandong Province. The dashed line in the figure represents the NDVI curve of MOD13Q1 products at the same geographic location. It can be observed that the range of NDVI values for typical land cover types is greater in high-resolution pixels compared to low-resolution pixels at the same scale. The fluctuation trends of the generated high-resolution NDVI curves throughout the year align with the original MOD13Q1 NDVI curves. Notably, for the built-up land cover type, significant differences in NDVI values can be observed at multiple time points between the original NDVI values and the downscaling values. However, the overall fluctuation trend remains consistent. For cropland, the generated NDVI curve exhibits a similar trend to the original curve, with higher NDVI values in the fine-resolution data. The NDVI values show a sudden decrease and subsequent increase in the 14 th period, indicating that the generated NDVI curve captures the cultivation characteristics of two crops per year in the study area, similar to the original NDVI curve. On forest land, the trend of the NDVI curve changes after construction is consistent with the original curve, and the values are generally higher. Similarly, on grassland, the constructed NDVI curve shows good consistency with the original NDVI curve in terms of trends and values. However, for wetlands, there is a noticeable difference between the generated NDVI curve and the original curve. The fluctuation amplitude of the generated curve is smaller and smoother, with values generally fluctuating around zero. In the case of water, the generated curve is generally lower than the original curve, consistently below zero, and exhibits relatively small variation compared to the original curve. Figure 9: The running time comparison between the fixed window (size increasing from 3 to 45 by 2 steps) and the elastic window (triangle). To evaluate the accuracy and reliability of the generated fine NDVI compared to the original MODIS-NDVI, an accuracy assessment was conducted.