Landsat bands were used to derive the albedo and Normalized Difference Vegetation Index. The thermal band was used to retrieve the land surface temperature (LST) and urban heat island (UHI). Results show that during the observed period, the city experienced a massive urban growth. The UHI was...
Landsat-TM data (bands 3, 4, and 5) were integrated with environmental data (degree-day, vapour pressure deficit, precipitation, and soil water holding capacity) for classifying forest cover types and estimating their biomass at the resolution of approximately one ha. The study area presents a ...
We filled the thermal, red, near-infrared, and surface reflectance shortwave bands by averaging the moving window, while the pixel's quality-assurance bands were filled by the maximum of the neighborhood of focal cells (worst case scenario). We found that filling L7 bands rather than filling ...
bandname=os.path.split(raster)(name,ext)=os.path.splitext(bandname)bandname=name[0:-6]# 提取文件名dataset_init=gdal.Open(raster)# 创建待输出的图gtiff_driver=gdal.GetDriverByName('GTiff')out_ds=gtiff_driver.Create(outfile_dir+"\\"+bandname+'.tif',dataset...
To avoid this problem, the following nonlinear stretching method was applied to those two bands for images in this area (band 4 was stretched using Equation (1)); Out_value 0 13)In_value(0:15)In_value2 (2) For each LTSS one movie loop was created to show the entire LTSS at a ...
Spectral Reflectance Properties of Snow in the Landsat Mss Bands PreviewDownload full text Access options DOI: 10.1080/07038992.1981.10855008 K. Staenza & H. Haefnera pages 41-50 Publishing models and article dates explained Published online: 01 Aug 2014 Alert me TOC email alert TOC RSS feed ...
Table 1. Coefficients of Fisher's classification functions obtained from the discriminant analysis based on seven Landsat images. Each of the four Fisher's classification functions resulting from combining the coefficients with the corresponding averaged values of the reflectance bands extracted from the ...
The performance of models could be explained by the scatterplots, which show the relationship between the observed AGB values and predicted AGB values (Fig. 3). They showed that the RF and XGBoost models worked better than the LR models with the same dataset. The SD values of the XGBoost ...
Table 3. Results of the beta regression models for each forest type: Simpson’s diversity index explained by SAX-metrics derived from Landsat NDVI time series. For beech SCH and beech at all “Exploratory” sites the Simpson’s diversity index was transformed, due to a few Simpson’s diversit...
Automated methods for mapping glacier ice utilize different bands of the electromagnetic (EM) spectrum. Debris-free glacier ice is highly reflective in the visible part of the EM spectrum (0.4–0.7 μm), less so in the near infrared (0.7–1.0 μm) portions of the EM spectrum, and is ...