Zobrazeno 1 - 10
of 1 173
pro vyhledávání: '"Crop monitoring"'
Autor:
Vikneswaran Jeya Kumaran, Nur Adibah Mohidem, Nik Norasma Che’Ya, Wan Fazilah Fazlil Ilahi, Jasmin Arif Shah, Zulhilmy Sahwee, Norhakim Yusof, Mohammad Husni Omar
Publikováno v:
Egyptian Journal of Remote Sensing and Space Sciences, Vol 27, Iss 4, Pp 628-636 (2024)
There is very little to no literature on the use of geotagging to monitor crops from aerial photos, even though many technologies have been created to do so. Current crop monitoring methods, relying on field data and lab analysis, are inefficient due
Externí odkaz:
https://doaj.org/article/d47150e215c14c2481347432418815e3
Autor:
C. Rajadel-Lambistos, E. Izquierdo-Verdiguier, A. Moreno-Martínez, M. P. Maneta, S. Begueria, J. S. Kimball, N. Clinton, C. Atzberger, G. Camps-Valls, S.W. Running
Publikováno v:
International Journal of Digital Earth, Vol 17, Iss 1 (2024)
Timely and accurate crop acreage information is essential for food security and the informed decision-making by governmental bodies and stakeholders in the agro-economic system. Surveys and fieldwork are expensive and time consuming, and the informat
Externí odkaz:
https://doaj.org/article/ef4a452d39bf45249fca2b41f7f93b47
AppleLeafNet: a lightweight and efficient deep learning framework for diagnosing apple leaf diseases
Autor:
Muhammad Umair Ali, Majdi Khalid, Majed Farrash, Hassan Fareed M. Lahza, Amad Zafar, Seong-Han Kim
Publikováno v:
Frontiers in Plant Science, Vol 15 (2024)
Accurately identifying apple diseases is essential to control their spread and support the industry. Timely and precise detection is crucial for managing the spread of diseases, thereby improving the production and quality of apples. However, the dev
Externí odkaz:
https://doaj.org/article/b59d6248510742a5a83ac49dc4ffe07b
Autor:
Manish Yadav, B.B. Vashisht, Niharika Vullaganti, Prem Kumar, S.K. Jalota, Arun Kumar, Prashant Kaushik
Publikováno v:
Agricultural Water Management, Vol 304, Iss , Pp 109091- (2024)
In recent years, precision agriculture has seen a substantial increase in the use of unmanned aerial vehicles (UAVs). They have shown great potential in spraying, nutrient application, irrigation scheduling, field mapping, yield estimation, and crop
Externí odkaz:
https://doaj.org/article/e9baf9b077174340bf1c8f39ccacbec6
Publikováno v:
Information Processing in Agriculture, Vol 11, Iss 2, Pp 228-236 (2024)
Crop height measurement is widely used to analyze and estimate the overall crop condition and the amount of biomass production. Not only is manual measurement on a large scale time-consuming but also it is not practical. Besides, advanced equipment i
Externí odkaz:
https://doaj.org/article/ed981491fb9344e6bc075ad0bc0601fb
Autor:
Vijendra Kumar, Kul Vaibhav Sharma, Naresh Kedam, Anant Patel, Tanmay Ram Kate, Upaka Rathnayake
Publikováno v:
Smart Agricultural Technology, Vol 8, Iss , Pp 100487- (2024)
The article provides a comprehensive review of the use of the Internet of Things (IoT) in agriculture, along with its advantages and disadvantages. However, it's important to recognize that IoT holds immense potential for generating new ideas that co
Externí odkaz:
https://doaj.org/article/714c0d8a0b5041d69a3147a5525c1793
Autor:
Manal Abdullah Alohali, Fuad Al-Mutiri, Kamal M. Othman, Ayman Yafoz, Raed Alsini, Ahmed S. Salama
Publikováno v:
AIMS Mathematics, Vol 9, Iss 4, Pp 10185-10207 (2024)
Smart agricultural techniques employ current information and communication technologies, leveraging artificial intelligence (AI) for effectually managing the crop. Recognizing rice seedlings, which is crucial for harvest estimation, traditionally dep
Externí odkaz:
https://doaj.org/article/cea514d6cecf46f0948b96104641caa7
Autor:
Khilola Amankulova, Nizom Farmonov, Enas Abdelsamei, Jozsef Szatmari, Waleed Khan, Mohamed Zhran, Jamshid Rustamov, Sharifboy Akhmedov, Maksudxon Sarimsakov, Laszlo Mucsi
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 13694-13707 (2024)
This study aimed to develop a new method for combining Sentinel-2 and PlanetScope (PS) imagery. The normalized difference vegetation indices (NDVI) data were retrieved from the Earth observation satellites S2 Level-2A and PS Level-3 surface reflectan
Externí odkaz:
https://doaj.org/article/a2aab4c8ef234bf8946545c2058c5b43
Autor:
Annalisa Milella, Stefan Rilling, Arianna Rana, Rocco Galati, Antonio Petitti, Mark Hoffmann, Jacob Livin Stanly, Giulio Reina
Publikováno v:
IEEE Access, Vol 12, Pp 47942-47949 (2024)
Robotic and multi-sensor technologies are increasingly being adopted in a number of agricultural applications, including seeding, weeding, harvesting, fertilization, and crop monitoring and analysis. However, the lack of interoperability and the pred
Externí odkaz:
https://doaj.org/article/d251843da3e046ae874d536abd3ef869
Autor:
Qinxin Zhao, Qinghua Xie, Xing Peng, Kunyu Lai, Jinfei Wang, Haiqiang Fu, Jianjun Zhu, Yang Song
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 6875-6893 (2024)
This study investigates the application of coherence and backscattering, derived from time-series Sentinel-1 synthetic aperture radar imagery of a crop season (18 scenes with a 12-day revisit cycle), for crop growth monitoring and classification in t
Externí odkaz:
https://doaj.org/article/cbc3bf733e064fd0b09e02d3b895a5b2