Spectral vegetation indices are frequently used to estimate vegetation biophysical/biochemical characteristics. In general they have been proposed to reduce spectral effects caused by external factors such as the atmosphere and the soil background. This study evaluated narrow band vegetation indices for estimation of vegetation leaf area index. The study takes advantage of using a dataset colle...

soil salinity has been a large problem in arid and semi arid regions. preparation of such maps is useful for natural resource managers. old methods of preparing such maps require a lot of time and cost. multi-spectral remotely sensed dates due to the broad vision and repeating of these imageries is suitable for provide saline soil maps. this investigation is conducted to provide saline soil map...

Monitoring the components of crop canopies with remote sensing can help us understand the within-canopy variation in spectral properties and resolve the sources of uncertainties in the spectroscopic estimation of crop foliar chemistry. To date, the spectral properties of leaves and panicles in crop canopies and the shadow effects on their spectral variation remain poorly understood due to the i...

The Brazilian Cerrado biome comprises a vertically structured mosaic of grassland, shrubland, and woodland physiognomies with distinct phenology patterns. In this study, we investigated the utility of spectral vegetation indices in differentiating these physiognomies and in monitoring their seasonal dynamics. We obtained high spectral resolution reflectances, during the 2000 wet and dry seasons...

Cloud detection is a fundamental step for optical satellite image applications. Although existing deep learning method can provide more accurate cloud result. However, performance of these methods rely on large number label samples, whose collection time-consuming and high cost. In addition, challenging in brightness scenes due to object have similar spectral feature. this study, we propose ind...

We extend our previous work on complexity indices for the travelling salesman problem (TSP) using graph spectral techniques of data mining. A complexity index is an invariant of an instance I by which we can predict the execution time of an exact algorithm for TSP for I. We consider the symmetric travelling salesman problem with instances I represented by complete weighted graphs G. Intuitively...