Investigating Grassland-Wetland Ecosystems and the Impacts of Environmental Change using Remote Sensing Big Data

草原和湿地是宝贵的生态系统，具有重要的生态和经济功能。在过去的几十年里，气候变化和人类活动引发的环境变化从全球到地方都对草原和湿地产生了巨大的影响。许多研究已经对草原和湿地进行了调查，以了解生态系统的损失和退化。然而，很少有人对草原和湿地进行紧密结合的调查。它们往往共存于一片风景中，草原是湿地的天然缓冲区。草原和湿地之间的过渡和转换对气候变化也很敏感。这种草原-湿地生态系统是许多动植物物种的重要栖息地，并为人类福祉提供基本的生态系统服务。环境干扰(如干旱、外来物种入侵和城市发展)可对这种混合生态系统产生重大影响，并导致生态系统服务退化或不可逆转的损失，这在以前的研究中没有得到很好的调查。遥感是监测生态系统的强大工具，特别是对草原--具有很大时空变化的湿地--的监测。遥感大数据包括不同平台(如卫星、飞机和无人机)获取的多种类型的图像(如光学、激光雷达、雷达和热成像)，能够从不同的角度和不同的尺度捕捉生态系统特征，从而为分析生态系统的损失和退化提供有价值的数据和见解。近年来，这样的大数据变得更加广泛，为生态系统监测提供了前所未有的机会。然而，这些大数据的利用，如多类型和多平台图像的融合，仍然具有挑战性。本研究的长期目标是利用遥感大数据研究草原湿地在环境变化下的损失和退化，了解其潜在的生态机制，为生态系统管理提供支持。在与不同领域的合作人员合作的同时，我将在未来五年实现以下短期目标：1)利用遥感大数据和先进的分析模型调查草原-湿地的生态特征和过程；2)利用长时间序列图像监测选定的草原-湿地生态系统的损失和退化；3)评估环境干扰(如干旱、野火和人类活动)对草原-湿地的影响，并评估生态系统弹性。希望本研究能加深我们对草原-湿地生态过程和潜在机制以及环境变化影响的认识。遥感大数据的探索和先进分析方法的发展也将推动这一大数据技术在生态系统监测中的采用。

Grasslands and wetlands are valuable ecosystems that have essential ecological and economic functions. Over the past few decades, environmental change induced by climate change and human activities has greatly affected grasslands and wetlands from the global to the local level. Many studies have investigated grasslands and wetlands for understanding ecosystem loss and degradation. However, few have investigated grasslands and wetlands cohesively. They often coexist in a landscape, and grasslands are natural buffers for wetlands. Transitions and conversions between grasslands and wetlands are also sensitive to climate change. Such grassland-wetland ecosystems are critical habitats for many plant and animal species and provide essential ecosystem services for human well-being. Environmental disturbances (e.g., droughts, invasion of non-native species, and urban development) can considerably influence such mixed ecosystems and cause degradation or irreversible loss of ecosystem services, which have not been well investigated in previous studies. Remote sensing is a powerful tool for monitoring ecosystems, especially for grasslands-wetlands that have substantial spatio-temporal variations. Remote sensing big data, which include multi-type images (e.g., optical, LiDAR, Radar, and thermal) acquired by different platforms (e.g., satellites, airplanes, and drones), are capable of capturing ecosystem features from different perspectives and at different scales, and thus providing valuable data and insights for analyzing ecosystem loss and degradation. Such big data have become more widely available in recent years, offering unprecedented opportunities for ecosystem monitoring. However, utilizations of these big data, such as the fusion of multi-type and multi-platform images, remains challenging. The long-term goal of this research is to investigate the loss and degradation of grasslands-wetlands under the environmental change using remote sensing big data and to understand underlying ecological mechanisms for supporting ecosystem management. While working with collaborators from different sectors, I will pursue the following short-term objectives over the next five years: 1) investigating ecological features and processes in grasslands-wetlands using remote sensing big data and advanced analytical models; 2) monitoring the loss and degradation of selected grassland-wetland ecosystems using a long time series of images; and 3) evaluating the impacts of environmental disturbances (e.g., droughts, wildfires, and human activities) on grasslands-wetlands and assessing ecosystem resilience. It is expected that this research will improve our understanding of ecological processes and underlying mechanisms in grasslands-wetlands together with the impacts of environmental change. The exploration of remote sensing big data and the development of advanced analytical methods will also promote the adoption of this big data technology in ecosystem monitoring.