add literature

content/_applications_biomass.qmd

@@ -26,6 +26,10 @@ ALS data can be used indirectly through a chain of models to estimate soil carbo
 
 > errors in species composition have less impact on individual tree volume estimates than errors in height measurement. The implications of these results are that, with very accurate estimates of height provided by ALS and knowledge of what dominant species is expected in a stand, accurate estimates of volume can be generated in the absence of more detailed species composition information. [@tompalskiSimulatingImpactsError2014]
 
+> simulated data cannot yet replace real data but they can be helpful in some sites to extend training datasets when only a limited amount of real data is available. [@schaferAssessingPotentialSynthetic2023]
+
+> this study showcases the effectiveness of additive tree AGB models and highlights the potential of DNNs for enhanced AGB estimation. Compared deep learning and random forest models in terms of biomass estimation. Deep neural networks provided small performance gain compared to random forest. [@seelyModellingTreeBiomass2023]
+
 
 ::: {#fig-cwd}
 ![](https://media.springernature.com/full/springer-static/image/art%3A10.1186%2Fs13021-016-0048-7/MediaObjects/13021_2016_48_Fig5_HTML.gif?as=webp)

content/_applications_stand-inventory.qmd

@@ -26,6 +26,9 @@ The findings are important steps towards future individual-tree-based airborne l
 
 > Use of auxiliary ALS metrics substantially improved sampling efficiency. methods can aid practitioners in planning cost-effective and statistically rigorous forest inventory campaigns, particularly in determining where to re-sample within an existing plot network. [@goodbodyAirborneLaserScanning2023]
 
+> compared four inventory approaches for imputing stem frequency distributions from airborne laser scanner (ALS) data.
+> Accuracies obtained using the semi-ITC, ABA and EABA inventory approaches were significantly better than accuracies obtained using the ITC approach. [@noordermeerImputingStemFrequency2023]
+
 
 ::: {#fig-enhanced-stand-inventory}
 ![](https://www.researchgate.net/profile/Joanne-White/publication/323166566/figure/fig2/AS:593803119448065@1518585104493/Overview-of-the-steps-involved-in-implementing-the-area-based-approach-ABA_W640.jpg)

content/_applications_structure.qmd

@@ -44,6 +44,8 @@ Variables to describe the vertical structure of the vegetation (from @moudryVege
 > compared the performance of LiDAR and DAP data for characterizing canopy openings. 
 recommend that operational use of DAP in forests be limited to mapping large canopy openings [@dietmaierComparisonLiDARDigital2019]
 
+> DAP data do not provide analogous results to ALS data for canopy gap detection and mapping, and that ALS data enable markedly superior accuracy and detailed gap characterizations. [@whiteComparisonAirborneLaser2018]
+
 ::: {#fig-canopy-gaps}
 ![](https://raw.githubusercontent.com/carlos-alberto-silva/ForestGapR/master/readme/fig_4.png)
 

content/_lidar_photogrammetry_comparison.qmd

@@ -46,3 +46,4 @@ Comparison of ALS- and image-based canopy height model (from @whiteUtilityImageB
 
 > Recent advances in computer sciences "demonstrate the potential of large-scale mapping and monitoring of tree height" from aerial imagery using U-NET (without overlap and image matching) [@wagnerSubMeterTreeHeight2023]
 
+>  DAP data do not provide analogous results to ALS data for canopy gap detection and mapping in coastal temperate rainforests, and that ALS data enable markedly superior accuracy and detailed gap characterizations. [@whiteComparisonAirborneLaser2018]