Leaf Area Index of forests using ALS, Landsat and ground measurements in magura national park (SE Poland).

Leaf Area Index (LAI) is one of the crucial characteristics describing forest canopy structure and is significant for biomass assessments which are important for characterizing forest ecosystems and rational management of wood resources. The main goal of this research was to estimate Leaf Area Index of forests located within borders of the Magura National Park (MNP) situated in the area of the Flysch Carpathians, Poland. Examined forest communities belong to two different vegetation layers in altitudinal zonation: foothills zone, up to 530 m a.s.l., and forest zone, located higher.
In situ ground indirect measurements of LAI were performed using a LAI-2000 Plant Canopy Analyzer. They were achieved within the scanned swath of the airborne laser scanning (ALS) with a density of 4 points/m²> and Landsat images. Both Landsat images and ALS data were used to calculate the LAI. Field measurements were carried out between 23 and 29 August 2013 using two LAI-2000 Plant Canopy Analyzers. The campaign was organized just after the date of ALS data acquisition (22.08.2013). Several spectral vegetation indices (NDVI, IPVI, MSR, GNDVI among others) were tested in order to obtain the spatial distribution of LAI estimated on the basis of Landsat images as a comparison to LAI derived from ALS data. The GNDVI index was chosen as the best predictor of Leaf Area Index (R² = 0.705; r = 0.840). The results indicate that ALS offers an accurate tool for mapping leaf area index for forests at local or regional scale and that it is suitable for verification of LAI derived through passive optical remote sensing techniques over large areas. The results indicate that ALS-derived point density and Landsat vegetation indices are correlated and that ALS results present an acceptable accuracy of LAI estimations for all forest classes (R² = 0.5526). The comparison of ALS LAI and field measurements gave satisfactory results. The coefficient of determination for all forest classes in this case was equal to 0.456.

叶面积指数（Leaf Area Index, LAI）是描述森林冠层结构的核心特征之一，其对于森林生物量评估具有关键意义，而生物量评估是表征森林生态系统与实现林木资源合理经营的重要环节。本研究的核心目标为估算位于波兰弗利希喀尔巴阡山脉区域的马古拉国家公园（Magura National Park, MNP）辖区内森林的叶面积指数。所研究的森林群落按照海拔分带划分为两类不同的植被层：海拔不超过530米的山麓带，以及海拔更高的森林带。
本研究采用LAI-2000植物冠层分析仪（LAI-2000 Plant Canopy Analyzer）开展LAI的原位地面间接测量，测量区域覆盖了密度为4点/平方米以上的机载激光扫描（Airborne Laser Scanning, ALS）扫描条带范围，并结合陆地卫星（Landsat）影像数据。研究同时利用Landsat影像与ALS数据开展LAI反演。野外测量于2013年8月23日至29日间完成，共使用两台LAI-2000植物冠层分析仪。本次野外作业紧接ALS数据获取日期（2013年8月22日）启动。为获取基于Landsat影像反演得到的LAI空间分布，并与ALS反演得到的LAI结果进行对比，本研究测试了多款光谱植被指数，包括归一化差异植被指数（Normalized Difference Vegetation Index, NDVI）、垂直植被指数（Infrared Percentage Vegetation Index, IPVI）、修正土壤调节植被指数（Modified Soil Adjusted Vegetation Index, MSR）以及绿色归一化差异植被指数（Green Normalized Difference Vegetation Index, GNDVI）等。最终选取GNDVI作为叶面积指数的最优预测因子（决定系数R²=0.705，相关系数r=0.840）。研究结果表明，机载激光扫描技术可作为局地或区域尺度下森林叶面积指数空间制图的精准工具，同时其也适用于验证基于大区域被动光学遥感技术反演得到的叶面积指数。结果同时显示，ALS反演得到的点密度与Landsat植被指数具有相关性，且针对所有森林类型，ALS反演得到的LAI估算结果均具备可接受的精度（决定系数R²=0.5526）。将ALS反演得到的LAI与野外实测数据进行对比，结果同样令人满意：本次研究中所有森林类型的决定系数均为0.456。