林业人工智能测验

当您参加测验时，就会出现答案和解释。

1. 激光雷达主要测量什么来帮助绘制森林地图？
   • 使用定时激光脉冲构建 3D 结构的距离
   • 叶子的化学成分
   • 地下土壤 pH 值
   • 树冠上方的风速
2. 基于卫星的GLAD警报如何识别可能的新的森林砍伐？
   • Use only a chainsaw audio classifier
   • Compare recent Landsat images with historical imagery to flag canopy disturbance
   • Infer tree loss from a single weather station
   • Count fire trucks in a region
3. 雨林连接（Rainforest Connection）的守护者（Guardian）系统分析什么以检测非法伐木活动？
   • Only satellite radar images
   • Only tree-ring samples
   • Acoustic recordings for chainsaw patterns and other threats
   • A hotel booking database
4. 美国林务局的一项火灾蔓延研究使用了哪些输入数据与机器学习结合？
   • Only tree species names
   • Hotel occupancy and room rates
   • Only satellite image captions
   • Weather, hydroclimate, fuels, and topography
5. 地球上大约有多少土地被森林覆盖？
   • 约31%
   • 约5%
   • 约60%
   • 约90%
6. 为什么人工智能对于测量补偿市场的森林碳特别有价值？
   • 它消除了任何现场测量的需要
   • 它提供了大面积生物量的可扩展、可重复的估计
   • 它以物理方式去除空气中的碳
   • 它设定了碳信用额的法定价格
7. How can LiDAR-derived canopy measurements contribute to biomass estimation?
   • They directly measure carbon content in every tree
   • They eliminate the need for field calibration
   • Canopy structure and height can be combined with reference data to estimate forest biomass
   • They identify tree species without any other data
8. Why do forest-biomass maps need independent validation?
   • Because satellites cannot capture any forest data
   • Because validation makes uncertainty disappear
   • Because every forest has the same biomass per hectare
   • Remote-sensing estimates depend on models and should be compared with reference measurements