Estimation of rice growth status, protein content and yield prediction using multi-satellite data

Wakamori, K.; Ichikawa, D.; Oguri, N.

doi:10.1109/igarss.2017.8128147

Cited by 9 publications

(4 citation statements)

References 2 publications

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“…The recorded biochemical parameters of the crop included the SPAD, LAI, and biomass. The SPAD is an important biochemical parameter for photosynthesis (Wakamori et al 2017), the LAI provides important information pertaining to agricultural production (Tao et al 2020), and biomass is a direct response to the growth status and environment of the crop and is closely related to the final yield (Zou et al 2018).…”

Section: Acquiring Biochemical Parameters Of Cropmentioning

confidence: 99%

Examining the relationship between coal mining subsidence and crop failure in plains with a high underground water table

et al. 2021

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Purpose The underground mining of coal leads to land subsidence and changes agricultural land into a water-logged area. This study aims to examine the relationship between coal mining subsidence and crop failure in plains with a high underground water table. Methods The Dongtan Coal Mine in Jining City of Shandong Province in China was selected as an example. Samples were gathered at gradient intervals based on the strike, dip, and angular bisector directions. The spatial variability and spatial correlation were analyzed by combining classical statistics and geostatistics. Results The order of the coefficient of variation in each parameter was as follows: the available phosphorus > available potassium > leaf area index (LAI) > biomass > soil moisture content > chlorophyll content (SPAD) > soil organic matter (SOM) > alkaline nitrogen (AN) > bulk density > elevation. Except the biomass had moderately spatially dependent, the other parameters all exhibited a strongly spatially dependent. At the level of 0.01, the correlation coefficient between SOM and AN was 0.67. The correlation coefficients relating biomass with SPAD and LAI were 0.70 and 0.69, respectively, and between SPAD and LAI was 0.68. The correlation coefficients between distance and altitude, distance and biomass, and altitude and biomass are 0.95, 0.67, and 0.65, respectively. Conclusion Coal mining leads to stretching and deformation of the ground, land subsidence, and changes in the physicochemical properties of the soil. In this case, the yield of aboveground crops is poor, but under the influence of external factors such as irrigation and breeding, the threat of coal mining to crop growth has been reduced.

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Section: Acquiring Biochemical Parameters Of Cropmentioning

confidence: 99%

Examining the relationship between coal mining subsidence and crop failure in plains with a high underground water table

et al. 2021

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“…4.23.The rice growth position and yield was predicted using multi-satellite data by using the image data of Landsat 7, 8 and Sentinel 2A [16]. The research was carried out in paddy field of northern part of Japan.…”

Section: 7mentioning

confidence: 99%

Crop Yield Prediction Techniques using Remote Sensing Data

Singh,

Sunila,

Kumar

2020

IJEAT

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Crop yield prediction is an art of forecasting the yield of crop before harvesting. Prediction of crop yield will be very useful for the government to make food policies, market price, import and export policies and proper warehousing well in time. The socio-economical impact of crop loss due to any natural disaster i.e. flood, drought can be minimized and humanitarian food assistance can be planned. The paper present a literature survey of various stastical method, empirical models,artificial neural network and machine learning regression techniques which are used with the data provided by the satellites. Many models are developed and results calculated are compared with the benchmark models are also presented.

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“…Dengan ini, petani mampu untuk mendapatkan pandangan menyeluruh kawasan tanaman padi dan mendapatkan maklumat kesihatan pokok yang tidak boleh dilihat secara pandangan mata kasar (Kazuki et al, 2017). (Wakamori, et al, 2017). Peta NDVI sesuai digunakan sebagai rujukan untuk memantau pertumbuhan tanaman serta mengesan lokasi sebarang kerosakan pada plot tanaman (Rosle, et al, 2019).…”

Section: Indeks Tumbuhanunclassified

Pemantauan Tanaman Padi Menggunakan Sistem Maklumat Geografi dan Imej Multispektral

Halip

Norasma

Fadzli³

et al. 2020

Adv Agric Food Res J

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This study is focused on paddy growth monitoring using Geographic Information System (GIS) and multispectral imagery via unmanned aerial vehicle (UAV). The objective of the study is to identify the best treatment that produces the highest yield. This combined technology is an effective farming management known as precision farming. UAV was used as a tool for field data capturing to produce orthophoto which will be a source for vegetative index and also for vector data digitizing purposes using ArcGIS 10.2. Data will be used as a source to analyze and monitor paddy growth. Geographical features that are digitized will able to provide farmer a full visual of their crop area such as crop layout, treatment type and also vegetative index. As a result, plot with treatment type Compost with Inoculum is able to produce the highest yield with 2494.7287 t/ha yield comparing to other treatment plots. However, treatment type U Grow producing the highest NDVI reading which is 0.4327 with yield producing only 2411.3080 t/ha lower than the plot with treatment type Compost with Inoculum. Maximum value of NDVI is not a guarantee of highest yield production. However, this research has shown that vegetative index value is able to become a benchmark for paddy growth monitoring while spatial analysis is able to make farming management more efficient. Other factors such as terrain model and effectiveness of current irrigation system can be a next sub topic for the research.

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Estimation of rice growth status, protein content and yield prediction using multi-satellite data

Cited by 9 publications

References 2 publications

Examining the relationship between coal mining subsidence and crop failure in plains with a high underground water table

Examining the relationship between coal mining subsidence and crop failure in plains with a high underground water table

Crop Yield Prediction Techniques using Remote Sensing Data

Pemantauan Tanaman Padi Menggunakan Sistem Maklumat Geografi dan Imej Multispektral

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