multispectral

简明释义

英[ˌmʌltiˈspektrəl]美[ˌmʌltiˈspektrəl;ˌmʌltaɪˈspek

adj. 多谱线的

英英释义

单词用法

同义词

反义词

例句

1.Based on the multispectral photography and photoelectric imaging technology, a real-time fusion system of multispectral imaging is developed.

在多光谱摄影和光电成像技术基础上，本文提出了一种可实时化的多光谱图像融合系统。

2.A hierarchical segmentation method is proposed for multispectral imagery by combining extended watershed transform and dynamics of contours.

综合扩展的分水岭变换和分水线动态范围，提出了适用于高分辨率多光谱图像的多尺度分割方法。

3.Multispectral and high resolution images fusion is presented.

论文对多光谱图像和高分辨图像进行了融合。

4.Theoretical analysis and calculation are given in this paper for "conical scanning" in object space. Its practicability in multispectral scanner is discussed.

本文对物方“圆锥”扫描进行了理论分析和计算，并讨论了这种扫描方案在多光谱扫描仪中的适用性。

5.A new multispectral image acquisition system based on liquid crystal tunable filter (LCTF) is proposed.

提出了一种新的基于液晶可调谐滤光片(LCTF)的多光谱图像采集系统。

6.So it is a great progress of remote sensing technology because it can solve many problems which multispectral image cann't solve.

因此，它能解决许多多光谱图像不能解决的问题，是遥感技术应用的一个重大飞跃。

7.A new method combining integer wavelet transform and linear prediction technique for lossless compression of airborne multispectral imagery is proposed in this paper.

首先探讨了基于提升方案的整数小波变换，结合线性预测技术，提出了一种机载多光谱遥感图像的无损压缩方法。

8.As one of a new technique in the quality inspection of food, the application of multispectral and multi-spectral imaging technique are already more and more popular.

多光谱技术与多光谱图像技术作为一种食品品质检测的新技术，其应用已越来越广泛。

9.Independent Component analysis is a new transform for multispectral or hyperspectral datasets.

是多光谱或超光谱数据集的一种新的转换方法。

10.The satellite uses multispectral sensors to capture images of the Earth's surface.

这颗卫星使用多光谱传感器捕捉地球表面的图像。

11.Farmers can analyze multispectral data to monitor crop health and optimize yield.

农民可以分析多光谱数据来监测作物健康并优化产量。

12.The multispectral imaging technique is essential for detecting water stress in plants.

这种多光谱成像技术对于检测植物的水分压力至关重要。

13.In archaeology, multispectral analysis helps uncover hidden structures beneath the soil.

在考古学中，多光谱分析有助于揭示地下隐藏的结构。

14.Wildlife researchers use multispectral cameras to track animal movements and habitat use.

野生动物研究人员使用多光谱相机跟踪动物的移动和栖息地使用情况。

作文

In recent years, the use of technology in various fields has significantly advanced, particularly in the realm of environmental monitoring and agriculture. One of the most fascinating developments is the application of multispectral (多光谱) imaging techniques. These techniques allow us to capture data across multiple wavelengths of light, which extends beyond what the human eye can perceive. This capability opens up a world of possibilities for researchers and practitioners alike. The concept of multispectral (多光谱) imaging involves utilizing sensors that can detect light in different spectral bands. Traditional photography captures images in the visible spectrum, which includes red, green, and blue light. However, multispectral (多光谱) sensors can collect information from infrared and ultraviolet wavelengths as well. This additional data is crucial for various applications, including agricultural assessments, land use planning, and environmental conservation. One of the primary uses of multispectral (多光谱) imaging is in precision agriculture. Farmers can utilize this technology to monitor crop health by analyzing how plants reflect light at different wavelengths. For instance, healthy vegetation reflects more near-infrared light compared to stressed or diseased plants. By employing multispectral (多光谱) imaging, farmers can identify areas in their fields that require attention, allowing them to optimize their resources and improve crop yields. Moreover, multispectral (多光谱) imaging is also instrumental in environmental monitoring. Scientists can track changes in land cover, deforestation rates, and even water quality by analyzing the spectral signatures of different surfaces. For example, wetlands can be monitored for their ecological health by examining how water, vegetation, and soil interact with light across various wavelengths. This information is vital for making informed decisions about conservation efforts and land management practices. In addition to agriculture and environmental science, multispectral (多光谱) imaging has applications in urban planning and disaster management. City planners can use this technology to assess urban heat islands, monitor green spaces, and evaluate the impact of development on local ecosystems. During natural disasters, multispectral (多光谱) imagery can assist in assessing damage and planning recovery efforts by providing detailed information about the affected areas. Despite its numerous advantages, the implementation of multispectral (多光谱) imaging does come with challenges. The technology can be expensive, and the data collected often requires specialized knowledge to interpret correctly. Additionally, there are concerns about privacy and data security, particularly when multispectral (多光谱) imaging is used in populated areas. In conclusion, the integration of multispectral (多光谱) imaging into various sectors presents exciting opportunities for innovation and improvement. As technology continues to evolve, we can expect to see even more applications of multispectral (多光谱) techniques that will enhance our understanding of the environment and optimize resource management. Embracing these advancements will undoubtedly lead to more sustainable practices and a better quality of life for future generations.

近年来，各个领域的技术应用显著进步，尤其是在环境监测和农业领域。最令人着迷的发展之一是应用多光谱成像技术。这些技术使我们能够捕捉跨越多个波长的数据，这超出了人眼能够感知的范围。这种能力为研究人员和从业者打开了一个充满可能性的世界。 多光谱成像的概念涉及利用可以检测不同光谱带的传感器。传统摄影在可见光谱中捕捉图像，包括红色、绿色和蓝色光。然而，多光谱传感器可以收集来自红外和紫外波长的信息。这些额外数据对于各种应用至关重要，包括农业评估、土地使用规划和环境保护。 多光谱成像的主要用途之一是在精准农业中。农民可以利用这项技术通过分析植物在不同波长下反射光的方式来监测作物健康。例如，健康的植被相比于受压或生病的植物，会反射更多的近红外光。通过采用多光谱成像，农民可以识别出田地中需要关注的区域，从而优化资源并提高作物产量。 此外，多光谱成像在环境监测中也发挥着重要作用。科学家可以通过分析不同表面的光谱特征来跟踪土地覆盖变化、森林砍伐率甚至水质。例如，通过检查水、植被和土壤如何与不同波长的光相互作用，可以监测湿地的生态健康。这些信息对于制定有关保护工作和土地管理实践的明智决策至关重要。 除了农业和环境科学，多光谱成像在城市规划和灾害管理中也有应用。城市规划者可以利用这项技术评估城市热岛、监测绿地以及评估开发对当地生态系统的影响。在自然灾害期间，多光谱图像可以帮助评估损害并规划恢复工作，提供有关受影响区域的详细信息。 尽管有众多优势，多光谱成像的实施确实面临挑战。这项技术可能成本高昂，收集的数据通常需要专业知识进行正确解读。此外，特别是在有人口的地区，隐私和数据安全方面的担忧也不容忽视。 总之，将多光谱成像整合到各个行业中，为创新和改进提供了令人兴奋的机会。随着技术的不断发展，我们可以期待看到多光谱技术的更多应用，这将增强我们对环境的理解并优化资源管理。拥抱这些进步无疑会导致更可持续的实践，并为未来几代人改善生活质量。