Vegetation classification of Coffea on Hawaii Island using WorldView-2 satellite imagery
Vegetation classification of Coffea on Hawaii Island using WorldView-2 satellite imagery
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DOI：
10.1117/1.jrs.11.046005
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发表时间：
2017-10-13
影响因子：
1.7
通讯作者：
Manoukis, Nicholas C.
中科院分区：
文献类型：
--
作者：
Gaertner, Julie;Genovese, Vanessa Brooks;Manoukis, Nicholas C.
咖啡是世界热带地区的一种重要作物；约1.25亿人依靠咖啡农业维持生计。了解咖啡田的空间范围有助于管理和控制咖啡害虫，如哈密虫和其他以咖啡果实为寄主的害虫，如地中海果蝇，用于经济规划，并跟踪咖啡农业生态系统随时间的变化。我们提出了两种方法，利用夏威夷科纳地区的WorldView-2高分辨率光谱数据，利用遥感和地理空间技术检测阿拉比卡咖啡田。第一种方法是使用最大似然算法的基于像素的方法，基于104个地面真实测试多边形的分析，获得了72%的生产者准确率和69%的用户准确率(总准确率为68%)。第二种方法是基于对象的图像分析(OBIA)方法，它同时考虑了光谱和纹理信息，并提高了准确率，对于相同的测试区域，生产者准确率为76%，用户准确率为94%(总体准确率为81%)。我们的结论是，Obia方法在探测露天种植的咖啡田方面是有用的，并使用它来估计2012年科纳地区咖啡农业下约1050公顷的分布。(C)作者。由SPIE在知识共享署名3.0未移植许可下发布。
Coffee is an important crop in tropical regions of the world; about 125 million people depend on coffee agriculture for their livelihoods. Understanding the spatial extent of coffee fields is useful for management and control of coffee pests such as Hypothenemus hampei and other pests that use coffee fruit as a host for immature stages such as the Mediterranean fruit fly, for economic planning, and for following changes in coffee agroecosystems over time. We present two methods for detecting Coffea arabica fields using remote sensing and geospatial technologies on WorldView-2 high-resolution spectral data of the Kona region of Hawaii Island. The first method, a pixel-based method using a maximum likelihood algorithm, attained 72% producer accuracy and 69% user accuracy (68% overall accuracy) based on analysis of 104 ground truth testing polygons. The second method, an object-based image analysis (OBIA) method, considered both spectral and textural information and improved accuracy, resulting in 76% producer accuracy and 94% user accuracy (81% overall accuracy) for the same testing areas. We conclude that the OBIA method is useful for detecting coffee fields grown in the open and use it to estimate the distribution of about 1050 hectares under coffee agriculture in the Kona region in 2012. (C) The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License.