INTRA-FIELD CROP YIELD VARIABILITY BY ASSIMILATING CUBESAT LAI IN THE APSIM CROP MODEL

Autor: M. G. Ziliani, M. U. Altaf, B. Aragon, R. Houborg, T. E. Franz, Y. Lu, J. Sheffield, I. Hoteit, M. F. McCabe

Publikováno v: The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLIII-B3-2022, Pp 1045-1052 (2022)

Predicting within-field crop yield early in the season can help address crop production challenges to improve farmers’ economic return. While yield prediction with remote sensing has been a research aim for years, it is only recently that observati

Externí odkaz: https://doaj.org/article/e0095bc535d44079a0fc197a0e943ac6

S-И X-ДИАПАЗОННАЯ ПАТЧ-АНТЕННА ДЛЯ НАНОСПУТНИКОВ CUBESAT.

Autor: Мейрамбекулы, Н.¹, Карибаев, Б. А.¹ beibitkaribaev7@gmail.com, Темирбаев, А. А.¹, Иманбаева, А. К.¹

Publikováno v: Recent Contributions to Physics. 2021, Vol. 78 Issue 3, p90-96. 7p.

Robust mosaicking of maize fields from aerial imagery.

Autor: Aktar, Rumana¹ (AUTHOR), Kharismawati, Dewi Endah^1,2,3 (AUTHOR), Palaniappan, Kannappan^1,2 (AUTHOR), Aliakbarpour, Hadi^1,2 (AUTHOR), Bunyak, Filiz^1,2 (AUTHOR), Stapleton, Ann E.⁴ (AUTHOR), Kazic, Toni^1,2,3 (AUTHOR) kazict@missouri.edu

Publikováno v: Applications in Plant Sciences. Aug2020, Vol. 8 Issue 8, p1-15. 15p.

Table of contents.

Publikováno v: IEEE Transactions on Geoscience & Remote Sensing; Dec2021, Vol. 59 Issue 12, p9825-9828, 4p

Spatial Data Science

Autor: Dr. John P. Wilson

Spatial Data Science will show GIS scientists and practitioners how to add and use new analytical methods from data science in their existing GIS platforms. By explaining how the spatial domain can provide many of the building blocks, it's critical f