Assessment Model of the Soil Fertility Potential of Yatsuda Rice Fields Based on Humus Derived Nitrogen Balance Using UAV Hyperspectral Sensor

Abstract. In order to maintain environmentally friendly agriculture, it is necessary to apply fertilizers based on an assessment of the potential of agricultural land. However, the effects of soil microorganisms based on bioanalysis have not been fully examined, and because of the unexplored nature of the effects, chemical fertilizers are often applied in excess of what is necessary. The purpose of this study is to construct a model that enables evaluation of the nitrogen balance in the process from reservoir to paddy field by adding the effect of the amount of humus-derived nitrogen to the model developed by the authors. For this purpose, the biomass of rice and weeds were detected from hyperspectral images mounted on a UAV, and the growth processes of rice and weeds were grasped with GIS to estimate the amount of nitrogen fixation in rice plants by estimating the biomass of rice and weeds separately. Furthermore, using soil microbial diversity and activity values (BIOTREX), we qualitatively evaluated the contribution of soil microorganisms to nitrogen fixation in paddy rice, built a model that can evaluate the nitrogen cycle derived from organic nitrogen supplied from reservoirs, and estimated the nitrogen balance. The results showed that this model can be used to evaluate the potential of agricultural land as an indicator of the need for fertilizer application.

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Publication Details

Journal
˜The œinternational archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciences
Published
2026-07-30
DOI
https://doi.org/10.5194/isprs-archives-xlix-b3-2026-1067-2026
Primary Topic
Remote Sensing in Agriculture
Type
article
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article

Assessment Model of the Soil Fertility Potential of Yatsuda Rice Fields Based on Humus Derived Nitrogen Balance Using UAV Hyperspectral Sensor

Shintaro Goto, Yuya Tanaka, Kyohei Sato
˜The œinternational archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciences
Remote Sensing in Agriculture
article

Assessment Model of the Soil Fertility Potential of Yatsuda Rice Fields Based on Humus Derived Nitrogen Balance Using UAV Hyperspectral Sensor

Shintaro Goto, Yuya Tanaka, Kyohei Sato
article en

Abstract

Abstract. In order to maintain environmentally friendly agriculture, it is necessary to apply fertilizers based on an assessment of the potential of agricultural land. However, the effects of soil microorganisms based on bioanalysis have not been fully examined, and because of the unexplored nature of the effects, chemical fertilizers are often applied in excess of what is necessary. The purpose of this study is to construct a model that enables evaluation of the nitrogen balance in the process from reservoir to paddy field by adding the effect of the amount of humus-derived nitrogen to the model developed by the authors. For this purpose, the biomass of rice and weeds were detected from hyperspectral images mounted on a UAV, and the growth processes of rice and weeds were grasped with GIS to estimate the amount of nitrogen fixation in rice plants by estimating the biomass of rice and weeds separately. Furthermore, using soil microbial diversity and activity values (BIOTREX), we qualitatively evaluated the contribution of soil microorganisms to nitrogen fixation in paddy rice, built a model that can evaluate the nitrogen cycle derived from organic nitrogen supplied from reservoirs, and estimated the nitrogen balance. The results showed that this model can be used to evaluate the potential of agricultural land as an indicator of the need for fertilizer application.

˜The œinternational archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciencesVol. XLIX-B3-2026
Rissho University (JP)
Zero hunger
Openalex Percentile: Top 10%
Remote Sensing in Agriculture
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