That's higher than the 138-percent average for premium gaming laptops as well as the results from the X9 (122 percent) and Eon 17-X (104 percent).
![msi burn recovery overlay msi burn recovery overlay](https://i.ytimg.com/vi/3tAogpJEQtA/maxresdefault.jpg)
When we measured for color reproduction, the Titan delivered a marvelous 178 percent of the sRGB gamut.
MSI BURN RECOVERY OVERLAY 1080P
The panel has a 60-Hertz refresh rate which isn't nearly as fast as the 1080p screen configuration with its 144Hz refresh and 3 millisecond response time, but it'll get the job done in a grand fashion. To prevent jaggies and the like, the display has Nvidia's G-Sync technology, which synchronizes the display with the GPU for smoother images. The overcast sky played up the bold, yet lowly earthen colors as I plodded toward my final destination.Ī screen this pretty shouldn't be marred by ugly screen tearing. And when I looked in just the right places I could see tiny veins of gold. The burnt red clay glistened as the gentle stream I crawled through meandered along, stirring up tiny pieces of gray sediment, taking it along for the ride. You never really think about mud, but I had quite a bit of time to think about it as I crawled into the enemy territory in Battlefield V. The actress' flawless chocolate complexion was further accentuated by her pumpkin-colored earrings and cerulean walls in the background. Details were so clear that I could see the individual curls of Issa Rae's dark brown hair as well as the deliberate blue and green paint strokes in her dandelion yellow UFO sweatshirt.
![msi burn recovery overlay msi burn recovery overlay](https://www.notebookcheck.net/fileadmin/_processed_/f/1/csm_Snap32_2337475f8a.png)
Watching the Little trailer was one of my favorite experiences. Whether I was gaming, watching movies or even typing up this review, the Titan's 17.3-inch, 4K screen produced sharp detail and jaw-dropping color on a seriously bright panel. Comparing with the other VI inversion models, the normalised difference phenology index derived from Sentinel-2 images estimated the vegetation parameters the most effectively and accurately, with a coefficient of determination (R 2) of 0.625 and relative root mean square error (RMSE%) of 18.105% for fresh AGB estimation and R 2 of 0.559 and RMSE% of 14.953% for LAI estimation.MSI has some of the best displays in the business. Sentinel-2 derived VIs yielded higher predictive accuracy than Landsat 8 for both fresh AGB and LAI. VIs derived from Sentinel-2 and Landsat 8 estimated fresh AGB and LAI at 80% accuracy. The results confirmed that vegetation parameters (AGB and LAI) and VIs decreased with increasing GI however, the decreasing trend was insignificant when the GI exceeded 0.69 Au/ha.
![msi burn recovery overlay msi burn recovery overlay](https://s3.manualzz.com/store/data/052370861_2-3c2bd4888f344274b7173cbcc6060f42-360x466.png)
Univariate linear mixed models were established between VIs and field measurements, and grazing intensities were considered as random factors. Field-measured fresh AGB and LAI data were collected from experimental grasslands with different grazing intensities (GI) in Hulunber, Inner Mongolia, China in 2019. Sentinel-2 and Landsat 8 were selected as data sources to estimate two vegetation parameters, fresh aboveground biomass (AGB) and leaf area index (LAI). In this study, we compared the performance of vegetation indices (VIs) obtained from two different sensors to estimate grassland vegetation parameters under different vegetation and soil conditions based on typical grassland biomass gradients formed by long-term controlled grazing experiments. Remote sensing methods are effective tools for monitoring and estimating grassland vegetation parameters. However, many of the world grasslands suffer from degradation caused mainly by overgrazing. Grasslands contribute considerably to the global carbon cycle and livestock production.