Derivation of forest stand metrics through the use of LiDAR and 4-band multi-spectral digital imagery

遥感数据已成功地与地面调查数据相结合，以便得出林分的量度，特别是对于相当同质的森林类型。不列颠哥伦比亚省拥有加拿大最复杂的海岸、干燥带、内陆湿润带和亚寒带森林。不列颠哥伦比亚省的林业目前面临着在一次重大的山地松甲虫流行之后寻找经济木材供应的挑战。因此，更好地利用遥感技术和现有的地面数据来确定林分指标，如林分物种，体积和原木块大小是至关重要的。该项目将演示如何将激光雷达数据和4波段多光谱图像与标准巡航数据相结合，以确定林分物种，体积和原木块大小，从而对活立木库存进行更可靠的估计，然后将其纳入关键决策。一旦实施，所开发的方法将使森林管理人员能够使用先进的工具，通过确保正确的原木配置文件进入正确的加工设施，以优化木材生产，从而做出更好的战略和运营决策。如果提议的方法被证明在不列颠哥伦比亚省的多样化森林中有效，那么在加拿大其他地方应用可能会更容易。

Remote-sensing data have successfully been combined with ground inventory data in order to derive forest stand metrics, especially for fairly homogeneous forest types. British Columbia has some of the most complex costal, dry belt, interior wet belt, and sub boreal forests in Canada. Forest industry in British Columbia is currently facing challenges of finding economical wood supplies in the aftermath of a major Mountain Pine Beetle epidemic. Therefore, it is critical to make better use of remote-sensing technology and existing ground data to identify forest stand metrics such as forest stand species, volume, and log piece sizes. This project will demonstrate how LiDAR data and 4-band multi-spectral imagery can be combined with standard cruise data to identify forest stand species, volume, and log piece size resulting in more reliable estimates of standing timber inventories, which will then be integrated into key decision making. Once implemented, the developed methodology will empower forest managers with advanced tools to make better strategic and operational decisions by ensuring the right log profiles are going to the right processing facilities for optimization of lumber production. If the proposed approach is proven to work in the diverse forests of BC, it will likely be easier to apply elsewhere in Canada.