Rice Yield Estimation Using Below Cloud Remote Sensing Images Acquired by Unmanned Airborne Vehicle System

Teoh, Chin Chuang; Nadzim, N. Mohd; Shahmihaizan, M.J. Mohd; Izani, I Mohd Khairil; Faizal, K; Shukry, H.B. Mohd

doi:10.18517/ijaseit.6.4.898

Cited by 19 publications

(10 citation statements)

References 8 publications

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“…Numerous studies used and combined satellite imagery with regression models for the yield estimation of agricultural crops [4][5][6]. However, early rice yield estimation studies used nonderived elements for regression analysis; for instance, one study employed the reflection spectrum and the actual rice yield [7,8]. However, this method is only applicable to the spatial distribution of the relative yield of rice.…”

Section: Introductionmentioning

confidence: 99%

Yield Estimation of Paddy Rice Based on Satellite Imagery: Comparison of Global and Local Regression Models

Shiu

Chuang

2019

Remote Sensing

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Precisely estimating the yield of paddy rice is crucial for national food security and development evaluation. Rice yield estimation based on satellite imagery is usually performed with global regression models; however, estimation errors may occur because the spatial variation is not considered. Therefore, this study proposed an approach estimating paddy rice yield based on global and local regression models. In our study area, the overall per-field data might not available because it took lots of time and manpower as well as resources. Therefore, we gathered and accumulated 26 to 63 ground survey sample fields, accounting for about 0.05% of the total cultivated areas, as the training samples for our regression models. To demonstrate whether the spatial autocorrelation or spatial heterogeneity exists and dominates the estimation, global models including the ordinary least squares (OLS), support vector regression (SVR), and the local model geographically weighted regression (GWR) were used to build the yield estimation models. We obtained the representative independent variables, including 4 original bands, 11 vegetation indices, and 32 texture indices, from SPOT-7 multispectral satellite imagery. To determine the optimal variable combination, feature selection based on the Pearson correlation was used for all of the regression models. The case study in Central Taiwan rendered that the error rate was between 0.06% and 13.22%. Through feature selection, the GWR model’s performance was more relatively stable than the OLS model and nonlinear SVR model for yield estimation. Where the GWR model considers the spatial autocorrelation and spatial heterogeneity of the relationships between the yield and the independent variables, the OLS and nonlinear SVR models lack this feature; this led to the rice yield estimation of GWR in this study be more stable than those of the other two models.

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Section: Introductionmentioning

confidence: 99%

Yield Estimation of Paddy Rice Based on Satellite Imagery: Comparison of Global and Local Regression Models

Shiu

Chuang

2019

Remote Sensing

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“…Rice (Oryza sativa L.) is the record primary food crop in the global [1]. It role is an important cereal crop for world food security and is used to food more than 3 billion persons on an everyday calorie intake of between 50 to 80% [2].…”

Section: Introductionmentioning

confidence: 99%

DNA Isolation and Optimization of ISSR-PCR Reaction System in Oryza sativa L.

Mohamad¹,

Alhasnawi²,

Kadhimi³

et al. 2017

International Journal on Advanced Science, Engineering and Information Technology

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Abstract-Inter simple sequence repeats (ISSRs) have been utilized widely for molecular markers in analyzing the genetic diversity and phylogenetic and regions in the genome flanked by microsatellite sequences. PCR amplification of these regions using a single primer yields multiple amplification products that can be used as a dominant multilocus marker system for the study of genetic variation in various organisms. For this study provides, DNA isolation, adjusting in six factors (Buffer, MgCl 2 , dNTPs, ISSR primers, Template DNA and Taq polymerase) at six levels, and optimization of PCR temperature for the ISSR reaction was 60-45 °C, primers screening on indica rice (Oryza sativa). In this research, simple method of DNA isolation by using seedling. The objective of the present investigation was to assess the optimizations and quantification. Has been shown that stalk enhanced the maximum value of genomic. The results show that 100 ISSR primers were examined as well as, 56 ISSR primers was productively amplified. Optimum components for PCR reactions were 5.0 μl of 5X PCR Buffer, 1.5 μl of 25mM MgCl 2 , 1 μl of 10 mM dNTP, 1 μl of 10 Μm ISSR primers, 2 μl Template DNA, and 0.1 μl of 5 units/ml Taq polymerase. Based on this study, has brought out some information on the relationship between these ISSR primers will be applied further for molecular profiling as well as response evaluation in rice varieties.

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“…Research was conducted by Teoh C.C. et al [5,6]. However, in these studies, in our opinion, limited data sets were used, and the developed model based on the NDVI, which was easily saturated when the leaf canopy closed, does not give sufficient forecast accuracy.…”

Section: Introductionmentioning

confidence: 99%

Monitoring of rice agrophiocenoses in relation to their states

et al. 2021

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The aim of the research was to study the production process of rice agrophytocenoses and carry out their geoinformation monitoring to develop a methodology for automated mapping of their condition and forecasting yield. Small varietal differences in the productivity of photosynthesis of plants of intensive and extensive rice varieties on different backgrounds of mineral nutrition were noted. When a closed crop is formed, the nature of the distribution of assimilates over the organs of the plant and the shoot is the main physiological mechanism for the formation of different yields of the studied genotypes and their resistance to the effects of unfavorable environmental factors. With the onset of the flowering phase, the differences in the mass of panicle and stem of shoots in intensive and extensive rice genotypes are very significant. Research has been carried out to study the optical properties of cenoses of varieties and their relationship with the morphophysiological characteristics of plants and yield to monitor the state of their crops. It was shown that the value of the vegetation index (NDVI) has a positive relationship with signs of photosynthetic activity of plants and their nitrogen status. Linear regression equations have been obtained, which make it possible to assess the degree of relationship between yield and vegetation index NDVI.

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Rice Yield Estimation Using Below Cloud Remote Sensing Images Acquired by Unmanned Airborne Vehicle System

Cited by 19 publications

References 8 publications

Yield Estimation of Paddy Rice Based on Satellite Imagery: Comparison of Global and Local Regression Models

Yield Estimation of Paddy Rice Based on Satellite Imagery: Comparison of Global and Local Regression Models

DNA Isolation and Optimization of ISSR-PCR Reaction System in Oryza sativa L.

Monitoring of rice agrophiocenoses in relation to their states

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