Zobrazeno 1 - 10
of 821
pro vyhledávání: '"crop-mapping"'
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 18, Pp 1817-1826 (2025)
Precise and timely crop type mapping delivers insights into crop growth statistics and ensures food security for growing economies. Automated mapping is crucial in several agricultural applications, including crop wear assessment and yield forecastin
Externí odkaz:
https://doaj.org/article/48b58e08feb24587aa35749036a058d4
Publikováno v:
Smart Agricultural Technology, Vol 9, Iss , Pp 100660- (2024)
High-precision mapping of agricultural crops in complex planting areas is a prerequisite for precision agricultural management. This paper first proposes a novel multi-task neural network, Multi-task Multi-Scale Convolutional Pooling Unet (MSCPUnet),
Externí odkaz:
https://doaj.org/article/17a7669795ab4ab08dc5df5494df28f9
Autor:
Hannah R. Kerner, Catherine Nakalembe, Benjamin Yeh, Ivan Zvonkov, Sergii Skakun, Inbal Becker-Reshef, Amy McNally
Publikováno v:
Science of Remote Sensing, Vol 10, Iss , Pp 100140- (2024)
The Tigray War was an armed conflict that took place primarily in the Tigray region of northern Ethiopia from November 3, 2020 to November 2, 2022. Given the importance of agriculture in Tigray to livelihoods and food security, determining the impact
Externí odkaz:
https://doaj.org/article/a32fde6ad78442b4ae45f8b2627ca3bc
Publikováno v:
Ecological Informatics, Vol 83, Iss , Pp 102836- (2024)
Agricultural land use and management fundamentally impacts the condition of natural resources like waterbodies, soils, and biodiversity. Modelling the anthropogenic effects on those resources over time requires detailed knowledge of the temporal and
Externí odkaz:
https://doaj.org/article/58288f99865b489d9cf11c0ce0736807
Publikováno v:
International Journal of Applied Earth Observations and Geoinformation, Vol 133, Iss , Pp 104085- (2024)
Automatic crop mapping is essential for various agricultural applications. Although fully convolutional networks (FCNs) have shown effectiveness in crop mapping, they rely on labor-intensive pixel-level annotations. Weakly supervised semantic segment
Externí odkaz:
https://doaj.org/article/61c23912ca014c708f4905cacd255d2d
Autor:
Swarnendu Sekhar Ghosh, Dipankar Mandal, Sandeep Kumar, Narayanarao Bhogapurapu, Biplab Banerjee, Paul Siqueira, Avik Bhattacharya
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 18683-18702 (2024)
Accurate crop classification with synthetic aperture radar (SAR) data is a significant area of research and translating into practice from local to regional scale crop inventory mapping. With the growing accessibility to abundant data sources from bo
Externí odkaz:
https://doaj.org/article/03fa2ef80bb74aefadf4434085e71389
Publikováno v:
IEEE Access, Vol 12, Pp 130800-130815 (2024)
Driven by abundant satellite imagery, machine learning-based approaches have recently been promoted to generate high-resolution crop cultivation maps to support many agricultural applications. One of the major challenges faced by these approaches is
Externí odkaz:
https://doaj.org/article/fb0fc4041b874332aface1fff50bdd70
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 14630-14639 (2024)
Crop mapping is crucial for agricultural management and yield prediction. Currently, remote sensing-based crop mapping over a large region is still challenging due to the requirement of sufficient in-season crop samples, which is commonly costly and
Externí odkaz:
https://doaj.org/article/fb85c75e1dfb4282abada080baf41960
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 13077-13088 (2024)
Large-scale crop mapping not only requires high-quality remote sensing data, but also has high requirements for multisource data organization and interpretation. How to make full use of multisource remote sensing data and combine it with artificial i
Externí odkaz:
https://doaj.org/article/716ddd0c5aeb434b9789bddfd85b87f1
Autor:
Weijia Chen, Guilin Liu
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 450-463 (2024)
Accurately mapping crop cultivation types is essential for the sustainable development of precision agriculture. Environmental restrictions on crop growth, such as soil salinization in arid zones, generally lead to spatial crop growth heterogeneity w
Externí odkaz:
https://doaj.org/article/fdcff44e35bc4a9ab43ac7b1031af0ec