An accuracy assessment of satellite-derived rangeland fractional cover

IF 7 2区 环境科学与生态学 Q1 ENVIRONMENTAL SCIENCES Ecological Indicators Pub Date : 2025-02-24 DOI:10.1016/j.ecolind.2025.113267
Georgia R. Harrison , Matthew Rigge , Timothy J. Assal , Cara Applestein , Darren K. James , Sarah E. McCord
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Abstract

Satellite-derived maps of vegetation cover provide detailed information about vegetation spatiotemporal patterns and are increasingly used to better understand and manage rangelands. Despite their utility, questions remain regarding the regional and site level accuracy for these maps, especially compared to field-collected data. We conducted an accuracy assessment of the Rangeland Analysis Platform (RAP), using over 17,000 field plots sampled through nationwide rangeland vegetation monitoring programs in the continental U.S. We observed higher overall nationwide map error compared to previous validations of RAP, and absolute error (Mean Absolute Error [MAE] and Root Mean Square Error [RMSE]) was highest for perennial herbaceous and bare ground and lowest for trees (MAE range = 2.98 –10.22 %). There were also differences in map agreement with field data across ecoregions. Generally, map agreement was highest in the Great Basin and lowest in the Great Plains and Desert Southwest. Additionally, we assessed the suitability of using RAP in riparian and wetland areas, which are absent in the current version’s training. Errors for bare ground in riparian areas were lower than errors of upland accuracy assessments (upland MAE = 10.22 %, riparian MAE = 7.22 %), but for all other functional groups, riparian error was higher (ΔMAE range: 0.21 – 20.49 %). We examine how our results could inform regional applications of fractional cover data while considering error and uncertainty and identify areas for potential model improvement. Our findings inform the use of RAP regionally and provide a technique for evaluating other vegetation mapping products for use in rangeland management.
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基于卫星的牧场覆盖度精度评估
卫星生成的植被覆盖图提供了关于植被时空格局的详细信息,越来越多地用于更好地了解和管理牧场。尽管这些地图很实用,但它们在区域和站点级别的准确性方面仍然存在问题,特别是与实地收集的数据相比。我们通过美国大陆的全国牧场植被监测项目对牧场分析平台(RAP)进行了精度评估,发现与之前的RAP验证相比,全国范围内的总体地图误差更高,多年生草本和裸地的绝对误差(平均绝对误差[MAE]和均方根误差[RMSE])最高,树木的绝对误差最低(MAE范围为2.98 - 10.22%)。不同生态区域的地图与实地数据的一致性也存在差异。总体而言,地图一致性在大盆地地区最高,在大平原和西南沙漠地区最低。此外,我们还评估了在河岸和湿地地区使用RAP的适宜性,这在当前版本的培训中是缺失的。河岸区裸地的误差低于高地精度评估的误差(高地MAE = 10.22%,河岸MAE = 7.22%),但对于所有其他功能组,河岸误差更高(ΔMAE范围:0.21 - 20.49%)。我们研究了我们的结果如何在考虑误差和不确定性的同时,为分数覆盖数据的区域应用提供信息,并确定了潜在的模型改进领域。我们的研究结果为RAP的区域使用提供了依据,并为评估其他用于牧场管理的植被制图产品提供了一种技术。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Ecological Indicators
Ecological Indicators 环境科学-环境科学
CiteScore
11.80
自引率
8.70%
发文量
1163
审稿时长
78 days
期刊介绍: The ultimate aim of Ecological Indicators is to integrate the monitoring and assessment of ecological and environmental indicators with management practices. The journal provides a forum for the discussion of the applied scientific development and review of traditional indicator approaches as well as for theoretical, modelling and quantitative applications such as index development. Research into the following areas will be published. • All aspects of ecological and environmental indicators and indices. • New indicators, and new approaches and methods for indicator development, testing and use. • Development and modelling of indices, e.g. application of indicator suites across multiple scales and resources. • Analysis and research of resource, system- and scale-specific indicators. • Methods for integration of social and other valuation metrics for the production of scientifically rigorous and politically-relevant assessments using indicator-based monitoring and assessment programs. • How research indicators can be transformed into direct application for management purposes. • Broader assessment objectives and methods, e.g. biodiversity, biological integrity, and sustainability, through the use of indicators. • Resource-specific indicators such as landscape, agroecosystems, forests, wetlands, etc.
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