A5057914574- Spectroscopy and Chemometric Analyses
- Remote Sensing in Agriculture
- Remote Sensing and Land Use
- Smart Agriculture and AI
- Leaf Properties and Growth Measurement
- Water resources management and optimization
- Hydrological Forecasting Using AI
- Solar Radiation and Photovoltaics
- Irrigation Practices and Water Management
- Greenhouse Technology and Climate Control
- Plant Water Relations and Carbon Dynamics
- Energy Load and Power Forecasting
- Remote Sensing and LiDAR Applications
- Advanced Chemical Sensor Technologies
- Geophysical and Geoelectrical Methods
- Water Quality Monitoring and Analysis
- Remote-Sensing Image Classification
- Hydraulic flow and structures
- Wind Energy Research and Development
- Hydrocarbon exploration and reservoir analysis
- Sensor Technology and Measurement Systems
- Power System Reliability and Maintenance
- Water Systems and Optimization
- Agricultural Economics and Practices
- Soil Geostatistics and Mapping
Bangladesh Rice Research Institute
2022-2023
Bangladesh Agricultural Research Institute
2022
Gyeongsang National University
2016-2018
Indian Agricultural Research Institute
1988-1991
Indian Institute of Soil and Water Conservation
1987
Precise forecasting of reference evapotranspiration (ET0) is one the critical initial steps in determining crop water requirements, which contributes to reliable management and long-term planning world’s scarce sources. This study provides daily prediction multi-step forward ET0 utilizing a long short-term memory network (LSTM) bi-directional LSTM (Bi-LSTM) model. For predictions, model’s accuracy was compared that other artificial intelligence-based models commonly used forecasting,...
본 연구는 초분광 영상을 이용하여 오이 및 수박과 같 은 박과 묘의 수분함량을 추정하기 위해 수행되었다. 오 이와 수박 묘 샘플에 수분 스트레스를 가한 후 영상 취득 시스템을 오이와 잎을 촬 영하여 반사율을 계산하였고, 건조기를 해당 모종의 측정하였다. 마지막으로 영상의 반사 율과 부분최소제곱회귀분석을 통해 수분함량 추정모델을 개발하였다. 추 정모델은 R2 0.73, RMSE 1.45%, RE 1.58%의 성능을 보였으며, 추정모델은 0.66, 1.06%, 1.14%의 보였다. 유효범위를 넘어가는 극단치를 제거하여 모델의 다시 분석한 결과, 경우 0.79, 1.10%, 1.20으로 상승하였다. 묘를 함께 분석하여 모델을 제작한 0.67, 1.26, 1.36으 로 분석되었다. 모델이 모델보다 비교적 높은 보였는데, 이러한 원인은 오이의 변이 가 넓게 분포되어 있었기 때문이라고 판단된다. 또한 데 이터셋에서 제거한 결과 정확도 정밀도가 결론적으 추정모델들의 추정선의 기울기 차가...
Recently, remote sensing technology as a nondestructive method has been utilized to detectthe quantity and quality of crops using unmanned aerial system. To predict vegetation growth(leaf dry mass nitrogen content) soybean, two index(NDVI Green NDVI)were calculated from images acquired by multi-spectral camera mounted on UAV eachprediction models between growth index were evaluated. As result, there wasno significant difference when each stage foreach yellow black bean compared other....
Application of remote sensing and GIS has great potential in crop monitoring retrospectively can set the strategies management practices as to maximize yield grain quality. In this study, UAV data were utilized predict protein content. Total images differentiated into two groups cloud free shadowed. On one hand for samples, vegetation index, NDVI derived from canopy spectral reflectance was significantly correlated final content (R2=0.553, RMSE=0.210%, n=14). other hand, shadowed result...
Background: This research was performed to develop moisture content model for solanaceae seedlings, such as chili pepper and tomato, based on hyperspectral imagery. Methods: After exposing high temperature, the reflectance of (n=45) tomato seedlings were calculated using imagery, all measured. Then predicting models estimating developed with PLS Regression analysis by two factors Results: As a result, chilli showed 0.68 R2, 1.43% RMSE 1.61% RE, which indicate accuracy precision...
Background: Hyperspectral camera is useful for finding a wavelength range that can estimate growth by using wide spectrum (400-1000nm) ranges. It possible to apply precision agriculture through determination of accurate harvest season, amount applied fertilizer and so on according estimation growth. The objective this study was the radish hyperspectral image depending vegetation stages. Methods: images Radish Chinese cabbage were acquired at intervals 2 weeks in midday. divided into crop...
Background: Chinese cabbage of the typical crop in Asia is crucial source supply containing abundant fibroid materials, minerals. It required to forecast and diagnose growth by remote sensing (RS), GPS GIS for precision production management cabbage. The objective this study was develop model estimating (Fresh weight, leaf area) with spectral information multispectral image acquired using unmanned aerial system depending on vegetation stages. Methods: test field planted normal planting...
In this research, the ground based hyperspectral reflectance of Chinese cabbage and radish depending on vegetation growth stages was compared to each other. The classifiers namely decision tree, random forest support vector machine were tested check feasibility classification difference in reflectance. ability classifier with overall accuracy kappa coefficient stages. spectral merging applied find out optimal bands make new multispectral sensor commercial band pass filter full width at half...
Abstract Reference evapotranspiration (ET 0 ) is an important driver in managing scarce water resources and making decisions on real-time future irrigation scheduling. Therefore, accurate prediction of ET crucial management. In this study, the was performed employing several optimization algorithms tuned Fuzzy Inference System (FIS) Tree (FT) models, for first time, whose generalization capability tested using data from other stations. The FISs FTs were developed through parameter tuning...