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首页> 外文期刊>Forests >Phenology-Based Method for Mapping Tropical Evergreen Forests by Integrating of MODIS and Landsat Imagery
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Phenology-Based Method for Mapping Tropical Evergreen Forests by Integrating of MODIS and Landsat Imagery

机译:MODIS与Landsat影像相结合的基于现象学的热带常绿森林制图方法

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Updated extent, area, and spatial distribution of tropical evergreen forests from inventory data provides valuable knowledge for research of the carbon cycle, biodiversity, and ecosystem services in tropical regions. However, acquiring these data in mountainous regions requires labor-intensive, often cost-prohibitive field protocols. Here, we report about validated methods to rapidly identify the spatial distribution of tropical forests, and obtain accurate extent estimates using phenology-based procedures that integrate the Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat imagery. Firstly, an analysis of temporal profiles of annual time-series MODIS Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), and Land Surface Water Index (LSWI) was developed to identify the key phenology phase for extraction of tropical evergreen forests in five typical lands cover types. Secondly, identification signatures of tropical evergreen forests were selected and their related thresholds were calculated based on Landsat NDVI, EVI, and LSWI extracted from ground true samples of different land cover types during the key phenology phase. Finally, a map of tropical evergreen forests was created by a pixel-based thresholding. The developed methods were tested in Xishuangbanna, China, and the results show: (1) Integration of Landsat and MODIS images performs well in extracting evergreen forests in tropical complex mountainous regions. The overall accuracy of the resulting map of the case study was 92%; (2) Annual time series of high-temporal-resolution remote sensing images (MODIS) can effectively be used for identification of the key phenology phase (between Julian Date 20 and 120) to extract tropical evergreen forested areas through analysis of NDVI, EVI, and LSWI of different land cover types; (3) NDVI and LSWI are two effective metrics (NDVI ≥ 0.670 and 0.447 ≥ LSWI ≥ 0.222) to depict evergreen forests from other land cover types during the key phenology phase in tropical complex mountainous regions. This method can make full use of the Landsat and MODIS archives as well as their advantages for tropical evergreen forests geospatial inventories, and is simple and easy to use. This method is suggested for use with other similar regions.
机译:通过清单数据更新的热带常绿森林的范围,面积和空间分布,为研究热带地区的碳循环,生物多样性和生态系统服务提供了宝贵的知识。但是,在山区获取这些数据需要劳动强度大,成本高昂的现场协议。在这里,我们将报告经过验证的方法,以快速识别热带森林的空间分布,并使用基于物候学的方法(结合了中等分辨率成像光谱仪(MODIS)和Landsat图像)获得准确的范围估计。首先,对年度时间序列MODIS归一化植被指数(NDVI),增强植被指数(EVI)和地表水指数(LSWI)的时间剖面进行了分析,以确定热带常绿森林提取的关键物候期。五种典型的土地覆被类型。其次,根据关键物候期从不同土地覆盖类型的地面真实样本中提取的Landsat NDVI,EVI和LSWI,选择热带常绿森林的识别特征并计算其相关阈值。最后,通过基于像素的阈值创建了热带常绿森林地图。在中国西双版纳进行了测试,结果表明:(1)Landsat和MODIS影像的融合在热带复杂山区常绿森林的提取中表现良好。案例研究结果图的整体准确性为92%; (2)通过对NDVI,EVI的分析,可以将高时间分辨率遥感影像(MODIS)的年度时间序列有效地用于识别关键物候期(朱利安日期20和120之间),从而提取热带常绿森林地区。土地覆盖类型不同的低收入WI; (3)NDVI和LSWI是两个有效指标(NDVI≥0.670和0.447≥LSWI≥0.222),用于描述热带复杂山区关键物候期的其他土地覆盖类型的常绿森林。这种方法可以充分利用Landsat和MODIS档案,以及它们对于热带常绿森林地理空间清单的优势,并且简单易用。建议将此方法与其他类似区域一起使用。

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