The use of remote sensing in landscape and social reconstruction

由佛罗里达大学（University of Florida）领导的一个跨学科国际研究小组将对墨西哥南部玛雅低地不同土地利用制度和定居模式下的土地利用历史和景观恢复能力进行研究。科学家们将特别关注梯田景观，研究关键的文化（如人口密度）、生态（如土壤和地形）和气候（如年降水量）因素如何影响土地利用模式的变化。先前的研究记录了部分低地的离散梯田系统，重要的是表明这些景观有时是密集管理和耕种的。将土壤科学、古民族植物学、遥感和考古学与现有的“大环境数据”（地面上碳储存的激光雷达调查）相结合，该研究将调查这些农业系统的生态和定居模式，批判性地评估这些系统在玛雅低地的恢复能力。梯田的建造仅仅是为了应对人口压力吗？为什么梯田会建在特定的地区？为什么它们能在某些生态环境中存活，而在其他环境中却不能？低地的梯田是否增加了当地景观的恢复力？社区建好露台系统后会维护吗？在世界各地，解决景观复原力问题，特别是与小农农业有关的问题至关重要，这样我们才能更好地设计、规划、组织和维护对文化和生态变化具有复原力的系统。该项目促进了国际合作，并为提高学生参与度提供了研究机会。该项目将调查墨西哥南部玛雅低地农业强度增加对景观的长期影响。它将对从恰帕斯州向北延伸到尤卡坦和金塔纳罗奥州的遥感（激光雷达）横断面进行清查和分析。这些调查最初是为了环境目的而收集的，作为墨西哥南部REDD+碳清单的一部分，这些调查提供了人类改造景观和景观恢复力的独特扩展调查。具体来说，它将探讨前哥伦布时期集约化农业改造景观的形式和空间分布如何受到定居密度的影响。本研究还将研究当地环境变化对梯田形态和分布的影响。为了解决这些问题，该团队将处理、分析、盘点和注释玛雅低地现有的激光雷达横断面。这些信息将与区域环境数据、挖掘、土壤剖面和新的高精度无人机激光雷达野外调查相结合，以评估土地利用强度和土地利用变化。该项目将开发新的方法和指标，用于研究农业系统和土地变化。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

An interdisciplinary and international team of researchers, led by the University of Florida, will conduct research on the history of land use and landscape resilience under different land use regimes and settlement patterns in the Maya lowlands of southern Mexico. Specifically focused on terraced landscapes, the scientists will investigate how key cultural (e.g., population density), ecological (e.g., soil and topography), and climatological (e.g., annual precipitation) factors influence changing patterns of agrarian land use. Previous research has documented discrete systems of terracing in parts of the lowlands, importantly demonstrating that these landscapes were sometimes intensively curated and cultivated. Combining soil science, paleoethnobotany, remote sensing, and archaeology with existing "big environmental data" (LiDAR surveys of Above Ground Carbon Storage), the research will investigate these agrarian systems across ecologies and settlement patterns, critically evaluating the resilience of these systems across the Maya lowlands. Are terraces constructed only in response to population pressure? Why are terraces built in particular regions? Why do they endure in certain ecological settings and not in others? Does terracing in the lowlands increase local landscape resilience? Do communities maintain terrace systems once they are built? Throughout the world, questions of landscape resilience, especially related to smallholder agriculture are vitally important to address, so that we can better design, plan, organize and maintain systems that are resilient to cultural and ecological change. This project fosters international collaborations and provides research opportunities for enhancing student engagement.The project will investigate the long-term landscape impacts of increasing agricultural intensity in the Maya lowlands of southern Mexico. It will inventory and analyze remote sensing (LiDAR) transects extending from the states of Chiapas north to Yucatan and Quintana Roo. Originally collected for environmental purposes as part of the REDD+ carbon inventory of southern Mexico, these surveys offer a uniquely expansive survey of human modified landscapes and landscape resilience. Specifically, it will explore how the form and spatial distribution of Pre-Columbian intensive agricultural modifications of the landscape are influenced by settlement density. The research will also study the influence of local environmental variability on the form and distribution of terracing. To address these questions, the team will process, analyze, inventory, and annotate existing LiDAR transects from across the Maya lowlands. This information will be combined with regional environmental data, excavation, soil profiles, and new high precision UAV LiDAR field surveys in order to evaluate land use intensity and land use change. The project will develop new methods and metrics for studying agrarian systems and agrarian change through time.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.