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MULTISENSOR APPROACH TO OIL PALM PLANTATION MONITORING USING DATA FUSION AND GIS

机译:基于数据融合和GIS的油棕种植园多传感器方法

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Oil palm is recognized as the golden crop. It produces the highest oil yield among oil seed crops. Malaysia, as the world's second largest producer of palm oil, has 16 % of its lands planted with oil palms. To cope with the ever-increasing global demand on edible oil, additional areas of oil palm are forecasted to increase globally by 12 to 19 million hectares by 2050. Multisensor remote sensing plays an important role by providing relevant, timely and accurate information that can be developed into a plantation monitoring system to optimize production and sustainability. The use of synthetic aperture radar (SAR), a form of microwave remote sensing, in combination with visible and infrared (VIR) data has several distinct advantages, the biggest benefits being daylight and weather independent. SAR produces 'cloud-free' images. However, SAR image are difficult to interpret. Using optical remote sensing provides important physical parameters of the plantation using multispectral data acquisition. Both types of data are complementary and need to be exploited simultaneously to obtain a holistic view on the plantation. Using interferometric SAR a topographical surface and height profiles of oil palm plantations can be derived. The information is crucial in the effort of mapping the oil palms age profile in the country. With this monitored, a replanting program could be effectively installed to maximize national production. VIR remote sensing delivers information on the plants' health and stress along with other biophysical parameters. Therefore the study aims to discover a set of parameters for oil palm plantation monitoring, which are retrievable from multisensor remote sensing data. The parameters are validated through the collection of ground. It is anticipated to derive all relevant information for the oil palm industry to implement a sustainable plantation management. The workflow on the parameter extraction and information derivation is designed and optimized.
机译:油棕被认为是黄金作物。它在油料种子作物中产生最高的油产量。马来西亚是世界第二大棕榈油生产国,其16%的土地上种有油棕。为了应对全球对食用油的不断增长的需求,预计到2050年,全球油棕的额外面积将增加12到1900万公顷。多传感器遥感将通过提供相关,及时和准确的信息来发挥重要作用。发展成人工林监测系统,以优化生产和可持续性。合成孔径雷达(SAR)是微波遥感的一种形式,与可见光和红外(VIR)数据结合使用具有几个明显的优点,最大的好处是不受日光和天气的影响。 SAR产生“无云”图像。但是,SAR图像难以解释。使用光学遥感技术可通过多光谱数据采集为人工林提供重要的物理参数。两种类型的数据都是互补的,需要同时利用以获取有关人工林的整体视图。使用干涉SAR,可以得出油棕种植园的地形表面和高度轮廓。该信息对于绘制该国油棕树的年龄分布图至关重要。在此监视下,可以有效地制定补种计划,以最大限度地提高本国的产量。 VIR遥感可提供有关植物健康和胁迫以及其他生物物理参数的信息。因此,本研究旨在发现一套用于油棕种植监测的参数,这些参数可从多传感器遥感数据中检索得到。通过收集地面来验证参数。预计将获得有关油棕行业的所有相关信息,以实施可持续的人工林管理。设计并优化了参数提取和信息导出的工作流程。

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