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\begin{landscape}\begin{table}[p]\caption{List of LiDAR metrics used and their relation to forest structure}\label{tab:LiDAR_Metrics}\centering\begin{center}\begin{tabular}{p{7.5cm}|p{11.5cm}}{\bf LiDAR metric} & {\bf Relation to forest structure} \\\hline \\[-1.5ex]Persistent Green (from hereon referred to as FPC) & Similar to FPC but not affected by grasslands, this is a summary of the foliage at the time of measure, derived from Landsat. \\[1ex]L-band LHH & Backscatter from LHH may be used to measure big trucks and branches (double bounce). \\[1ex]L-band LHV & Backscatter from LHV may be used for measuring canopy (volume scattering). \\[1ex]Mean height (non ground returns only) & Useful measure for deriving other parameters such as change over time. \\ [1ex]Min height (non ground returns only) & Measure of the lowest vegetation height - indication of understory presence. \\[1ex]Max height (non ground returns only) & Relates to emergence or taller trees, potentially relating to age of trees. \\[1ex]SD height (non ground returns only) & Measures the variation in height which can be related to the age of species or understory presence. \\[1ex]Skewness height & The height distributing can be skewed from a normal distribution which may reflect trends in the tree age composition of the forest. \\[1ex]Gap fraction & A measure of the density of the canopy. Gap fraction can also be used to show canopy cover, i.e., the inverse of gap fraction is equal to canopy cover. \\[1ex]Kurtosis height & Describes the "peakedness" of distribution and may be related to the presence of understory in the forest. \\[1ex]Height-Scaled Canopy Openness Index (HSCOI) & Effectively the sum of the inverse canopy density scaled by the relative height with respect to the kernel window. \\ [1ex]Percentiles 5\,-\,100 & Used to describe the distribution of returns at different heights. \\[1ex]\hline\end{tabular}\end{center}\end{table}\end{landscape}
Thanks in advance!