Algorithms for estimating green leaf area index in C3 and C4 crops for MODIS, Landsat TM/ETM+, MERIS, Sentinel MSI/OLCI, and Venμs sensors Anthony L. Nguy-Robertson & Anatoly A. Gitelson a Center for Advanced Land Management Information Technologies, School of Natural Resources, University of Nebraska–Lincoln, Lincoln, Nebraska, USA b Faculty of Civil and Environmental Engineering, Israel Insti...

T o help determine the utility of satellite data for analysis and inventory of Douglas-fir~western hemlock forests west of the Cascade Mountains crest in Oregon and Washington, USA, we evaluate relationships between spectral and texture variables derived from SPOT HR V 10 m panchromatic and LANDSAT TM 30 m multispectral data and 16 forest stand structural attributes. Texture of the HRV data was...

This paper deals with the evaluation of the performance of a set of classifiers on multispectral imagery with low dimensionality and low spatial and spectral resolutions. The original Landsat TM images and other 4 transformed sets are classified by 5 supervised and 2 unsupervised methods. The results for 7 land cover classes are compared and the performances of the methods for each set of input...

A standard method for assessing the accuracy of fire mapping derived from NOAA-AVHRR imagery was applied to five Landsat scenes sampling different regions across northern Australia. The procedure involved the undertaking of: (1) detailed ground verification exercises (using ground and aerial transects) at the time of Landsat overpasses; (2) assessment of the accuracy of fire mapping derived fro...

Methods: Field data on sagebrush species and structural characteristics collected in 2005 were regressed against spectral values and transformed indices derived from Landsat TM data. Step-wise regression methods were used to build (1) a combinedmodel that ignored species and physical differences in sagebrush, and (2) four different models that took those differences in account. Parsimonious mod...