Evaluando el desempeño de índices espectrales para identificar humedales alto andinos

IF 0.4 Q4 REMOTE SENSING Revista de Teledeteccion Pub Date : 2019-06-27 DOI:10.4995/RAET.2019.10580
J. Aponte-Saravia, J. E. Ospina-Noreña
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引用次数: 1

Abstract

High Andean wetlands are habitats critical to life forms that have adapted to these extreme high mountain ecosystems, and for living beings that inhabit the lower parts of the basin; they are spaces that contain high diversity of flora and fauna characteristic of these places and are strongly associated with the water component. There lies the importance of identifying and monitoring ecosystems, using easy applicable methods and allowing results every two weeks approximately, they are inexpensive and highly reliable. Methods of monitoring in short periods, they are economically profitable and provide reliable information, they correspond to the evaluations by satellite images, specifically applying the methods of spectral indices. Thereby, the objective of the research was to evaluate the performance of six indices, considered to be the most used to identify high Andean wetlands (humidity index at surface level, normalized difference water index, normalized difference vegetation index, enhanced vegetation index, index of vegetation to the surface and tasseled CAP vegetation), in periods of low precipitation, using imagery Landsat 8 OLI. Comparing the performance of those indexes in the identification of wetlands through cross-validation and bootstrap statistical learning, the index that showed better performance was tasseled CAP vegetation, revealing the lowest value of the average of the mean square error of iterations between the test failure rate and training. The index tasseled CAP vegetation, shows greater reliability to identify and evaluate high Andean wetlands.
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评估光谱指数在识别高安第斯湿地中的性能
高安第斯湿地是适应这些极端高山生态系统的生命形式以及居住在盆地较低地区的生物的关键栖息地;这些空间包含了这些地方特有的高度多样性的动植物,并与水成分密切相关。重要的是识别和监测生态系统,使用简单适用的方法,大约每两周得出一次结果,这些方法既便宜又高度可靠。短期监测方法,经济上有利可图,提供可靠的信息,与卫星图像的评估相对应,特别是应用光谱指数的方法。因此,研究的目的是评估六个指标的性能,这些指标被认为是最常用于识别高安第斯湿地的指标(地表湿度指数、归一化差异水指数、归一化不同植被指数、增强植被指数、地表植被指数和流苏状CAP植被),在低降水期,使用Landsat 8 OLI图像。通过交叉验证和bootstrap统计学习比较这些指标在湿地识别中的表现,表现出更好表现的指标是流苏状CAP植被,显示出测试失败率和训练之间迭代均方误差的平均值最低。该指数流苏状CAP植被,显示出更高的可靠性,以识别和评估高安第斯湿地。
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来源期刊
Revista de Teledeteccion
Revista de Teledeteccion REMOTE SENSING-
CiteScore
1.80
自引率
14.30%
发文量
11
审稿时长
10 weeks
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