The Perils of Misusing Remote Sensing Data: The Case of Forest Cover

L. Fergusson, S. Saavedra, Juan F. Vargas
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引用次数: 4

Abstract

Research on deforestation has grown exponentially due to the availability of satellite-based measures of forest cover. One of the most popular is Global Forest Change (GFC). Using GFC, we estimate that the Colombian civil conflict increases ‘forest cover’. Using an alternative source that validates the same remote sensing images in the ground, we find the opposite effect. This occurs because, in spite of its name, GFC measures tree cover, including vegetation other than native forest. Most users of GFC seem unaware of this. In our case, most of the conflicting results are explained by GFC’s misclassification of oil palm crops as ‘forest’. Our findings call for caution when using automated classification of imagery for specific research questions.
误用遥感数据的危险:以森林覆盖为例
由于有了基于卫星的森林覆盖测量方法,关于森林砍伐的研究呈指数增长。其中最受欢迎的是全球森林变化(GFC)。使用GFC,我们估计哥伦比亚内战增加了“森林覆盖”。使用另一种来源来验证地面上相同的遥感图像,我们发现了相反的效果。之所以会出现这种情况,是因为尽管它的名字是GFC,但它测量的是树木覆盖,包括原生森林以外的植被。大多数GFC用户似乎没有意识到这一点。在我们的案例中,大多数相互矛盾的结果都可以用GFC将油棕作物错误地分类为“森林”来解释。我们的研究结果呼吁在使用图像自动分类进行特定研究问题时要谨慎。
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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