树冠高度绘图仪:结合 GEDI 和多源数据预测全球树冠高度的谷歌地球引擎应用程序

IF 4.8 2区 环境科学与生态学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Environmental Modelling & Software Pub Date : 2024-11-12 DOI:10.1016/j.envsoft.2024.106268
Cesar Alvites, Hannah O'Sullivan, Saverio Francini, Marco Marchetti, Giovanni Santopuoli, Gherardo Chirici, Bruno Lasserre, Michela Marignani, Erika Bazzato
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引用次数: 0

摘要

美国国家航空航天局(NASA)的全球生态系统动力学调查(GEDI)任务收集的空间和时间上不连续的冠层高度足迹可在谷歌地球引擎(GEE)云计算平台上访问。本研究介绍了一个名为 "冠层高度绘图器(CH-GEE)"的开源、用户友好、无代码的 GEE 网络应用程序(可在 https://ee-calvites1990.projects.earthengine.app/view/ch-gee 上获取),该程序通过将 GEDI 与多源遥感数据集成,自动生成特定区域的(10 米)高分辨率冠层高度地图:哥白尼数据和 GEE 数据目录中的地形数据。CH-GEE 采用机器学习算法,利用 GEE 平台的大数据和云计算功能,生成全球范围内地方到国家尺度的校准冠层高度图。CH-GEE 允许自定义 GEDI 和预测因子的地理区域、算法和时间窗口。由 CH-GEE 生成的树冠高度已通过意大利国家森林资源清查在 110,000 平方公里范围内进行了多尺度验证(基于国家的 R 平方 = 0.89,RMSE = 17%)。CH-GEE 的准确性和可扩展性使其适用于森林监测。
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Canopy height Mapper: A google earth engine application for predicting global canopy heights combining GEDI with multi-source data
Spatially and temporally discontinuous canopy height footprints collected by NASA's GEDI (Global Ecosystem Dynamics Investigation) mission are accessible on the Google Earth Engine (GEE) cloud computing platform. This study introduces an open-source, user-friendly, code-free GEE web application called Canopy Height Mapper (CH-GEE), available at https://ee-calvites1990.projects.earthengine.app/view/ch-gee, which automatically generates (10 m) high-resolution canopy height maps for a specific area by integrating GEDI with multi-source remote sensing data: Copernicus and topographical data from the GEE data catalogue. CH-GEE generates local-to-country scale calibrated canopy height maps worldwide using machine learning algorithms and leveraging the GEE platform's big data and cloud computing capabilities. CH-GEE allows customization of geographic area, algorithms and time windows for GEDI and predictors. Canopy heights generated by CH-GEE were validated using the Italian National Forest Inventory across 110,000 km2 at multiple scales (Country-based R-squared = 0.89, RMSE = 17%). CH-GEE's accuracy and scalability make it suitable for forest monitoring.
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来源期刊
Environmental Modelling & Software
Environmental Modelling & Software 工程技术-工程:环境
CiteScore
9.30
自引率
8.20%
发文量
241
审稿时长
60 days
期刊介绍: Environmental Modelling & Software publishes contributions, in the form of research articles, reviews and short communications, on recent advances in environmental modelling and/or software. The aim is to improve our capacity to represent, understand, predict or manage the behaviour of environmental systems at all practical scales, and to communicate those improvements to a wide scientific and professional audience.
期刊最新文献
Probability analysis of shallow landslides in varying vegetation zones with random soil grain-size distribution Variable sensitivity analysis in groundwater level projections under climate change adopting a hybrid machine learning algorithm Taxonomy of purposes, methods, and recommendations for vulnerability analysis Canopy height Mapper: A google earth engine application for predicting global canopy heights combining GEDI with multi-source data Integrated STL-DBSCAN algorithm for online hydrological and water quality monitoring data cleaning
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