Jove
Visualize
联系我们

相关概念视频

GIS Software, Hardware, and Sources of GIS Data01:23

GIS Software, Hardware, and Sources of GIS Data

95
A Geographic Information System (GIS) combines specialized software and hardware to effectively manage, analyze, and present spatial and related data. GIS software includes critical functionalities such as a user interface for easy navigation, database management tools for handling spatial and attribute data, and data retrieval features for efficient access. Analytical tools transform raw data into insights, while display functions produce maps and reports in various formats for effective...
95
Light Acquisition02:16

Light Acquisition

8.5K
In order to produce glucose, plants need to capture sufficient light energy. Many modern plants have evolved leaves specialized for light acquisition. Leaves can be only millimeters in width or tens of meters wide, depending on the environment. Due to competition for sunlight, evolution has driven the evolution of increasingly larger leaves and taller plants, to avoid shading by their neighbors with contaminant elaboration of root architecture and mechanisms to transport water and nutrients.
8.5K
Selected Data About Geographic Locations01:25

Selected Data About Geographic Locations

49
Geographic Information Systems (GIS) rely on two core types of data: spatial data and attribute data.Spatial DataSpatial data defines the physical location of features within a coordinate system, typically expressed in terms of latitude and longitude. It provides precise positioning for elements like roads, rivers, or buildings.Attribute DataAttribute data complements spatial data by adding descriptive information about these features. For example, a road's spatial data includes its start and...
49
Levels of Use of a GIS01:29

Levels of Use of a GIS

72
Geographic Information Systems (GIS) operate across three levels of application, each representing an increasing degree of complexity: data management, analysis, and prediction. These levels reflect the expanding functionality and versatility of GIS technology in handling spatial data for diverse purposes.Data ManagementAt its foundational level, GIS serves as a tool for data management, enabling the input, storage, retrieval, and organization of spatial data. This level is often employed in...
72
Key Elements for Plant Nutrition02:35

Key Elements for Plant Nutrition

18.8K
Like all living organisms, plants require organic and inorganic nutrients to survive, reproduce, grow and maintain homeostasis. To identify nutrients that are essential for plant functioning, researchers have leveraged a technique called hydroponics. In hydroponic culture systems, plants are grown—without soil—in water-based solutions containing nutrients. At least 17 nutrients have been identified as essential elements required by plants. Plants acquire these elements from the...
18.8K
Plant Breeding and Biotechnology01:59

Plant Breeding and Biotechnology

19.0K
Crop cultivation has a long history in human civilization, with records showing the cultivation of cereal plants beginning at around 8000 BC. This early plant breeding was developed primarily to provide a steady supply of food.
19.0K

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Natural forests of the world - a 2020 baseline for deforestation and degradation monitoring.

Scientific data·2025
Same author

The importance of distinguishing between natural and managed tree cover gains in the moist tropics.

Nature communications·2025
Same author

New directions in mapping the Earth's surface with citizen science and generative AI.

iScience·2025
Same author

Annual 30-m maps of global grassland class and extent (2000-2022) based on spatiotemporal Machine Learning.

Scientific data·2024
Same author

Dynamic global-scale crop and irrigation monitoring.

Nature food·2023
Same author

Measuring the world's cropland area.

Nature food·2023
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关实验视频

Updated: Jul 23, 2025

Cereal Crop Ear Counting in Field Conditions Using Zenithal RGB Images
11:49

Cereal Crop Ear Counting in Field Conditions Using Zenithal RGB Images

Published on: February 2, 2019

9.3K

建立一个基于社区的开放的协调参考数据库,用于全球作物映射.

Hendrik Boogaard1, Arun Kumar Pratihast1, Juan Carlos Laso Bayas2

  • 1Wageningen Environmental Research (WENR), Wageningen University & Research, Wageningen, Netherlands.

PloS one
|July 13, 2023
PubMed
概括

全球范围内现在可以使用一个新的和的作物参考数据 (超过7500万个观测) 开放访问存储库. 该倡议支持开发和验证准确的作物类型和耕地测绘产品.

更多相关视频

Measuring the Structure, Composition, and Change of Underwater Environments with Large-area Imaging
09:19

Measuring the Structure, Composition, and Change of Underwater Environments with Large-area Imaging

Published on: April 18, 2025

633
A Telemetric, Gravimetric Platform for Real-Time Physiological Phenotyping of Plant–Environment Interactions
15:30

A Telemetric, Gravimetric Platform for Real-Time Physiological Phenotyping of Plant–Environment Interactions

Published on: August 5, 2020

11.6K

相关实验视频

Last Updated: Jul 23, 2025

Cereal Crop Ear Counting in Field Conditions Using Zenithal RGB Images
11:49

Cereal Crop Ear Counting in Field Conditions Using Zenithal RGB Images

Published on: February 2, 2019

9.3K
Measuring the Structure, Composition, and Change of Underwater Environments with Large-area Imaging
09:19

Measuring the Structure, Composition, and Change of Underwater Environments with Large-area Imaging

Published on: April 18, 2025

633
A Telemetric, Gravimetric Platform for Real-Time Physiological Phenotyping of Plant–Environment Interactions
15:30

A Telemetric, Gravimetric Platform for Real-Time Physiological Phenotyping of Plant–Environment Interactions

Published on: August 5, 2020

11.6K

科学领域:

  • 地球科学 地球科学 地球科学
  • 农业科学 农业科学
  • 数据科学数据科学数据科学

背景情况:

  • 可靠的作物类型和耕地地图取决于高质量的参考数据.
  • 在全球范围内收集和协调各种作物参考数据存在重大挑战,包括数据共享限制.

研究的目的:

  • 建立一个基于社区的,开放的和协调的全球参考数据库.
  • 为了促进农业地球观测的模型培训和产品验证.

主要方法:

  • 来自各种来源的汇总和协调数据,包括GEOGLAM JECAM,辐射MLHub,CGIAR,NASA Harvest和公民科学平台.
  • 从2016年开始收集和标准化数据,评估空间,时间和主题质量.
  • 开发了一个具有标准化元数据的存储库,使得很大一部分可公开访问.

主要成果:

  • 创建了一个全球存储库,包含大约7500万个协调的作物观测数据.
  • 通过严格的评估规则确保数据质量.
  • 统一数据的很大一部分是公开可用的.

结论:

  • 该存储库为校准深度学习算法和验证作物监测地球观测产品提供了宝贵的资源.
  • 建议继续支持和制度化这一开放数据倡议,以促进农业监测的进步.