Investigating the use of a leaf trait-based approach to remotely measure tropical forest productivity

热带森林和稀树草原占陆地碳循环的60%。因此，了解这些地区的碳固存率，沿着预计的变化，对于预测未来气候至关重要。中分辨率成像光谱仪卫星提供两种产品来测量植被覆盖地区的总初级生产力（GPP）和净初级生产力（NPP）。然而，人们对这些产品准确估计热带森林全球初级生产力和净初级生产力的大小和空间格局的能力表示怀疑（Cleveland等人，2015年）。显然，在这些区域需要一种新的方法。该建议旨在研究使用一种新的基于叶性状的方法来遥感热带森林生产力。利用叶片光谱学、机载高光谱数据和偏最小二乘回归分析，它将在现有文献的基础上表明，通过根据实地收集的值校准SENTINEL卫星数据，可以准确地估计碳循环过程，如叶片光合作用、呼吸作用和木本生产力。最终，它打算在谷歌地球引擎（一个处理卫星图像的云计算平台）中绘制热带森林生产力地图，供公众和科学使用。在这一领域为我的硕士论文进行的初步研究非常有前途，并且，在北方亚利桑那大学担任研究学者一年后，我与Chris Doughty教授合作扩展了这项工作，我相信我处于独特的位置来进行这项研究并推进这一新颖和新兴的领域。

Tropical forests and savannahs account for 60% of terrestrial carbon cycling. Thus, understanding rates of carbon sequestration in these areas, along with projected changes, is vital for predicting future climate. MODIS satellites offer two products to measure gross primary productivity (GPP) and net primary productivity (NPP) across vegetated areas. Yet significant doubt has been cast on the ability of these products to accurately estimate the magnitude and spatial patterns of GPP and NPP over tropical forests (Cleveland et al. 2015). It is clear that in these regions a new methodology is required. This proposal aims to investigate the use of a novel leaf trait-based approach to remotely sense tropical forest productivity. Using leaf spectroscopy, airborne hyperspectral data and partial least square regression analysis (PLSR), it will build on existing literature to show that carbon cycling processes, such as leaf photosynthesis, respiration and woody productivity, can be accurately estimated by calibrating SENTINEL satellite data on field-collected values. Ultimately, it intends to create maps of tropical forest productivity in Google Earth Engine (a cloud computing platform for processing satellite imagery) for public and scientific use. Initial research carried out for my MSc dissertation in this area was very promising, and, following a year-long position as Research Scholar at Northern Arizona University, where I collaborated with Prof. Chris Doughty to expand this work, I believe I am uniquely placed to undertake this research and advance this novel and emerging field.