ground objects identification

简明释义

地物识别

英英释义

例句

1.The app uses AI for real-time ground objects identification 地面物体识别 during outdoor activities.

该应用程序利用人工智能在户外活动中进行实时地面物体识别 ground objects identification。

2.The satellite imagery can be processed for ground objects identification 地面物体识别 to monitor urban development.

卫星图像可以被处理以进行地面物体识别 ground objects identification，以监测城市发展。

3.The drone's software is designed for ground objects identification 地面物体识别 to enhance its navigation capabilities.

这款无人机的软件旨在进行地面物体识别 ground objects identification，以增强其导航能力。

4.In military operations, accurate ground objects identification 地面物体识别 is crucial for targeting.

在军事行动中，准确的地面物体识别 ground objects identification 对于打击目标至关重要。

5.Researchers are developing algorithms for better ground objects identification 地面物体识别 in agricultural fields.

研究人员正在开发算法，以在农业领域实现更好的地面物体识别 ground objects identification。

作文

In recent years, the field of remote sensing has gained significant attention due to its applications in various domains such as agriculture, environmental monitoring, and urban planning. One of the critical components of remote sensing is ground objects identification, which refers to the process of detecting and classifying objects on the Earth's surface based on data collected from sensors. This process is essential for creating accurate maps and understanding the changes occurring in our environment. The importance of ground objects identification cannot be overstated. For instance, in agriculture, farmers can utilize this technology to monitor crop health, assess soil conditions, and optimize resource allocation. By identifying different types of crops and their health status, farmers can make informed decisions that lead to increased yields and reduced waste. Similarly, in urban planning, city officials can use ground objects identification to analyze land use patterns, track urban sprawl, and plan for infrastructure development. Technological advancements have greatly enhanced the capabilities of ground objects identification. With the advent of high-resolution satellite imagery and aerial drones, the accuracy and efficiency of this process have improved dramatically. Machine learning algorithms are now being employed to automate the identification process, allowing for faster analysis and reducing human error. These technologies enable researchers and practitioners to identify objects such as buildings, roads, water bodies, and vegetation with remarkable precision. However, despite the advancements, challenges remain in the field of ground objects identification. One significant issue is the variability of ground objects due to factors such as seasonal changes, weather conditions, and human activities. For example, a forested area may appear differently in winter compared to summer, which can complicate the identification process. Additionally, the presence of shadows, occlusions, and overlapping objects can hinder accurate detection. Researchers are continually working on improving algorithms and methods to address these challenges, ensuring that ground objects identification remains reliable and effective. Moreover, the applications of ground objects identification extend beyond agriculture and urban planning. Environmental scientists use this technology to monitor deforestation, track wildlife habitats, and assess the impact of climate change. By identifying changes in land cover and land use, they can develop strategies to mitigate environmental degradation. Furthermore, disaster management agencies rely on ground objects identification to assess damage after natural disasters, helping them allocate resources effectively during recovery efforts. In conclusion, ground objects identification is a vital process that plays a crucial role in various fields, including agriculture, urban planning, and environmental monitoring. As technology continues to evolve, the accuracy and efficiency of this process will likely improve, leading to better decision-making and resource management. The ongoing research and development in this area highlight the significance of ground objects identification in understanding and addressing the challenges facing our planet today.

近年来，由于其在农业、环境监测和城市规划等各个领域的应用，遥感领域受到了广泛关注。遥感的一个关键组成部分是地面物体识别，它指的是基于从传感器收集的数据检测和分类地球表面物体的过程。这个过程对于创建准确的地图和理解我们环境中发生的变化至关重要。地面物体识别的重要性不容小觑。例如，在农业中，农民可以利用这项技术监控作物健康、评估土壤状况并优化资源配置。通过识别不同类型的作物及其健康状态，农民可以做出明智的决策，从而提高产量并减少浪费。同样，在城市规划中，市政官员可以使用地面物体识别来分析土地使用模式、跟踪城市扩张，并规划基础设施发展。技术进步大大增强了地面物体识别的能力。随着高分辨率卫星图像和航空无人机的出现，这一过程的准确性和效率显著提高。机器学习算法现在被用于自动化识别过程，使分析速度更快，减少人为错误。这些技术使研究人员和从业者能够以惊人的精确度识别建筑物、道路、水体和植被等物体。然而，尽管取得了进展，地面物体识别领域仍然存在挑战。一项重大问题是由于季节变化、天气条件和人类活动导致的地面物体的变异性。例如，森林地区在冬季与夏季的外观可能有所不同，这会使识别过程变得复杂。此外，阴影、遮挡和重叠物体的存在可能会妨碍准确检测。研究人员正在不断努力改进算法和方法，以应对这些挑战，确保地面物体识别保持可靠和有效。此外，地面物体识别的应用超越了农业和城市规划。环境科学家利用这项技术监测森林砍伐、追踪野生动物栖息地以及评估气候变化的影响。通过识别土地覆盖和土地利用的变化，他们可以制定减缓环境退化的策略。此外，灾害管理机构依赖于地面物体识别在自然灾害后评估损失，帮助他们在恢复工作中有效分配资源。总之，地面物体识别是一个至关重要的过程，在农业、城市规划和环境监测等多个领域发挥着重要作用。随着技术的不断发展，这一过程的准确性和效率可能会进一步提高，从而改善决策和资源管理。在这一领域持续进行的研究和开发突显了地面物体识别在理解和应对当今世界所面临的挑战中的重要性。