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Online collection of all digital USGS 1:24K scale topographic maps (as well as various other GIS data) covering the United States, available as a free download. NPScape United States Department of the Interior National Park Service NPScape is a landscape dynamics monitoring project that provides landscape-level data, tools, and evaluations for ...
2011 Enhanced vegetation index based on MODIS Terra data. The enhanced vegetation index (EVI) is an 'optimized' vegetation index designed to enhance the vegetation signal with improved sensitivity in high biomass regions and improved vegetation monitoring through a de-coupling of the canopy background signal and a reduction in atmosphere influences.
The index is given as: = (+) (+ +) where L is a canopy background adjustment factor. An L value of 0.5 in reflectance space was found to minimize soil brightness variations and eliminate the need for additional calibration for different soils. The transformation was found to nearly eliminate soil-induced variations in vegetation indices. [1]
6- monthly NDVI average for Australia, 1 Dec 2012 to 31 May 2013 [1]. A vegetation index (VI) is a spectral imaging transformation of two or more image bands designed to enhance the contribution of vegetation properties and allow reliable spatial and temporal inter-comparisons of terrestrial photosynthetic activity and canopy structural variations.
It has a high correlation with the true state of vegetation on the ground. The index is easy to interpret: NDVI will be a value between -1 and 1. An area with nothing growing in it will have an NDVI of zero. NDVI will increase in proportion to vegetation growth. An area with dense, healthy vegetation will have an NDVI of one.
McFeeters index: If looking for water bodies or change in water level (e.g. flooding), then it is advisable to use the green and NIR spectral bands [18] or green and SWIR spectral bands. Modification of normalised difference water index (MNDWI) has been suggested for improved detection of open water by replacing NIR spectral band with SWIR. [19]
A supervised classification is a system of classification in which the user builds a series of randomly generated training datasets or spectral signatures representing different land-use and land-cover (LULC) classes and applies these datasets in machine learning models to predict and spatially classify LULC patterns and evaluate classification accuracies.
Leaf area index (LAI) is a dimensionless quantity that characterizes plant canopies. It is defined as the one-sided green leaf area per unit ground surface area (LAI = leaf area / ground area, m 2 / m 2) in broadleaf canopies. [1] In conifers, three definitions for LAI have been used: Half of the total needle surface area per unit ground ...