Remote sensing-derived national land cover land use maps: a comparison for Malawi
Remote sensing-derived national land cover land use maps: a comparison for Malawi
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DOI：
10.1080/10106049.2014.952355
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发表时间：
2015-03
影响因子：
3.8
通讯作者：
B. Haack;R. Mahabir;J. Kerkering
中科院分区：
文献类型：
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作者：
B. Haack;R. Mahabir;J. Kerkering
可靠的土地覆被/土地利用（LCLU）信息以及随时间的变化对于气候变化文件中的绿色家用气体（GHG）报告非常重要。四个不同的组织根据2010年马拉维的卫星图像独立制作了LCLU地图，用于温室气体报告。本分析比较了这四项活动的程序和结果。采用了四种不同的分类方法：传统的视觉解释，分割和视觉标签，数字聚类与视觉识别和监督签名提取与应用程序的决策规则，然后由分析师编辑。一个努力没有报告分类准确性和其他三个非常相似和优秀的整体主题准确性范围从85%到89%。然而，尽管这些高主题的准确性有非常显着的差异，结果。全国森林的比例为18.2%至28.7%，耕地的比例为40.5%至53.7%。这些重大差异令马拉维的遥感科学家和决策者感到关切。
Reliable land cover land use (LCLU) information, and change over time, is important for Green House Gas (GHG) reporting for climate change documentation. Four different organizations have independently created LCLU maps from 2010 satellite imagery for Malawi for GHG reporting. This analysis compares the procedures and results for those four activities. Four different classification methods were employed; traditional visual interpretation, segmentation and visual labelling, digital clustering with visual identification and supervised signature extraction with application of a decision rule followed by analyst editing. One effort did not report classification accuracy and the other three had very similar and excellent overall thematic accuracies ranging from 85 to 89%. However, despite these high thematic accuracies there were very significant differences in results. National percentages for forest ranged from 18.2 to 28.7% and cropland from 40.5 to 53.7%. These significant differences are concerns for both remote-sensing scientists and decision-makers in Malawi.