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Article ; Online: Dynamic Harvest Index Estimation of Winter Wheat Based on UAV Hyperspectral Remote Sensing Considering Crop Aboveground Biomass Change and the Grain Filling Process

Jianqiang Ren / Ningdan Zhang / Xingren Liu / Shangrong Wu / Dandan Li

Remote Sensing, Vol 14, Iss 1955, p

2022 Volume 1955

Abstract: The crop harvest index (HI) is of great significance for research on the application of crop variety breeding, crop growth simulation, crop management in precision agriculture and crop yield estimation, among other topics. To obtain spatial information ... ...

Abstract	The crop harvest index (HI) is of great significance for research on the application of crop variety breeding, crop growth simulation, crop management in precision agriculture and crop yield estimation, among other topics. To obtain spatial information on the crop dynamic HI (D-HI), taking winter wheat as the research object and fully considering the changes in crop biomass and the grain filling process from the flowering period to the maturity period, the dynamic f G (D- f G ) parameter was estimated as the ratio between the aboveground biomass accumulated in different growth periods, from the flowering stage to the maturity stage, and the aboveground biomass in the corresponding periods. Based on the D- f G parameter estimation using unmanned aerial vehicle (UAV) hyperspectral remote sensing data, a technical method for obtaining spatial information on the winter wheat D-HI was proposed and the accuracy of the proposed method was verified. A correlation analysis was performed between the normalized difference spectral index (NDSI), which was calculated using pairs of any two bands of the UAV hyperspectral spectrum, and the measured D- f G . Based on this correlation analysis, the center of gravity of the local maximum region of R 2 was used to determine the sensitive band center to accurately estimate D- f G . On this basis, remote sensing estimation of the D- f G was realized by using the NDSI constructed by the sensitive hyperspectral band centers. Finally, based on the D- f G remote sensing parameters and the D-HI estimation model, spatial information on the D-HI of winter wheat was accurately obtained. The results revealed five pairs of sensitive hyperspectral band centers (i.e., λ (476 nm, 508 nm), λ (444 nm, 644 nm), λ (608 nm, 788 nm), λ (724 nm, 784 nm) and λ (816 nm, 908 nm)) for D- f G estimation, and the results of the D- f G remote sensing estimation showed high precision. The root mean square error (RMSE) was between 0.0436 and 0.0604, the normalized RMSE (NRMSE) was between 10.31% and 14.27% and ...
Keywords	winter wheat ; harvest index ; unmanned aerial vehicle ; hyperspectral remote sensing ; sensitive band selection ; NDSI ; Science ; Q
Subject code	333
Language	English
Publishing date	2022-04-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Comparison of Regional Winter Wheat Mapping Results from Different Similarity Measurement Indicators of NDVI Time Series and Their Optimized Thresholds

Fangjie Li / Jianqiang Ren / Shangrong Wu / Hongwei Zhao / Ningdan Zhang

Remote Sensing, Vol 13, Iss 1162, p

2021 Volume 1162

Abstract: Generally, there is an inconsistency between the total regional crop area that was obtained from remote sensing technology and the official statistical data on crop areas. When performing scale conversion and data aggregation of remote sensing-based crop ...

Abstract	Generally, there is an inconsistency between the total regional crop area that was obtained from remote sensing technology and the official statistical data on crop areas. When performing scale conversion and data aggregation of remote sensing-based crop mapping results from different administrative scales, it is difficult to obtain accurate crop planting area that match crop area statistics well at the corresponding administrative level. This problem affects the application of remote sensing-based crop mapping results. In order to solve the above problem, taking Fucheng County of Hebei Province in the Huanghuaihai Plain of China as the study area, based on the Sentinel-2 normalized difference vegetation index (NDVI) time series data covering the whole winter wheat growth period, the statistical data of the regional winter wheat planting area were regarded as reference for the winter wheat planting area extracted by remote sensing, and a new method for winter wheat mapping that is based on similarity measurement indicators and their threshold optimizations (WWM-SMITO) was proposed with the support of the shuffled complex evolution-University of Arizona (SCE-UA) global optimization algorithm. The accuracy of the regional winter wheat mapping results was verified, and accuracy comparisons with different similarity indicators were carried out. The results showed that the total area accuracy of the winter wheat area extraction by the proposed method reached over 99.99%, which achieved a consistency that was between the regional remote sensing-based winter wheat planting area and the statistical data on the winter wheat planting area. The crop recognition accuracy also reached a high level, which showed that the proposed method was effective and feasible. Moreover, in the accuracy comparison of crop mapping results based on six different similarity indicators, the winter wheat distribution that was extracted by root mean square error (RMSE) had the best recognition accuracy, and the overall accuracy and kappa ...
Keywords	crop mapping ; similarity ; crop area statistical data ; total amount control ; global optimization algorithm ; Science ; Q
Subject code	333
Language	English
Publishing date	2021-03-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: A New Method for Winter Wheat Mapping Based on Spectral Reconstruction Technology

Shilei Li / Fangjie Li / Maofang Gao / Zhaoliang Li / Pei Leng / Sibo Duan / Jianqiang Ren

Remote Sensing, Vol 13, Iss 1810, p

2021 Volume 1810

Abstract: Timely and accurate estimation of the winter wheat planting area and its spatial distribution is essential for the implementation of crop growth monitoring and yield estimation, and hence for the development of national agricultural production and food ... ...

Abstract	Timely and accurate estimation of the winter wheat planting area and its spatial distribution is essential for the implementation of crop growth monitoring and yield estimation, and hence for the development of national agricultural production and food security. In remotely sensed winter wheat mapping based on spectral similarity, the reference curve is obtained by averaging multiple standard curves, which limits mapping accuracy. We propose a spectral reconstruction method based on singular value decomposition (SR-SVD) for winter wheat mapping based on the unique growth characteristics of crops. Using Sentinel-2 A/B satellite data, we tested the SR-SVD method in Puyang County, and Shenzhou City, China. Performance was increased, with the optimal overall accuracy and the Kappa of Puyang County and Shenzhou City were 99.52% and 0.99, and 98.26% and 0.97, respectively. We selected the spectral angle mapper (SAM) and Euclidean Distance (ED) as the similarity measures. Compared to spectral similarity methods, the SR-SVD method significantly improves mapping accuracy, as it avoids excessive extraction, can identify more detailed information, and is advantageous in distinguishing non-winter wheat pixels. Three commonly used supervised classification methods, support vector machine (SVM), maximum likelihood (ML), and minimum distance (MD) were used for comparison. Results indicate that SR-SVD has the highest mapping accuracy and greatly reduces the number of misidentified pixels. Therefore, the SR-SVD method can achieve high-precision crop mapping and provide technical support for monitoring regional crop planting structure information.
Keywords	Sentinel-2 satellite ; NDVI time series ; singular value decomposition (SVD) ; winter wheat mapping ; crop classification ; Science ; Q
Subject code	333
Language	English
Publishing date	2021-05-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article: Long-term effects of biochar addition and straw return on N2O fluxes and the related functional gene abundances under wheat-maize rotation system in the North China Plain

Liu, Xingren / Jianqiang Ren / Qingwen Zhang / Chong Liu

Applied soil ecology. 2019 Mar., v. 135

2019

Abstract: To evaluate long-term effects of biochar addition and straw return (SR) on N2O fluxes in wheat-maize rotation system, a 2-year field experiment following a 7-year biochar addition and SR was investigated in an intensively managed agricultural soil in the ...

Abstract	To evaluate long-term effects of biochar addition and straw return (SR) on N2O fluxes in wheat-maize rotation system, a 2-year field experiment following a 7-year biochar addition and SR was investigated in an intensively managed agricultural soil in the North China Plain (NCP). Four treatments were included: 1) no biochar addition (CK); 2) biochar treatment with 4.5 t ha−1 yr−1 (C1); 3) biochar treatment with 9.0 t ha−1 yr−1 (C2); and 4) all the wheat/maize straw return (SR). The results showed the annual cumulative N2O emissions from C1 treatment were increased by 15.9–16.5%, while C2 treatment suppressed the annual cumulative N2O emissions by 22.8–26.3%. In comparison, straw return suppressed N2O emissions by 13.4–43.6% in the wheat season but increased N2O emissions remarkably by 45.3–53.9% in the maize season. Biochar addition enhanced the copies of AOA, AOB, nirK, nirS, and nosZ genes, while straw return decreased the copies of AOB, nirK, nirS, and nosZ genes at the high N2O emission period in the maize season. The production of N2O in the maize season was mainly driven by the AOB and nosZ genes, and by AOB gene in the wheat season. These results suggest that application of 9.0 t ha−1 yr−1 biochar is a more optimum agricultural strategy for reducing N2O emission in the wheat-maize system.
Keywords	agricultural soils ; biochar ; corn ; corn straw ; field experimentation ; genes ; greenhouse gas emissions ; long term effects ; nitrous oxide ; nitrous oxide production ; wheat ; China
Language	English
Dates of publication	2019-03
Size	p. 44-55.
Publishing place	Elsevier B.V.
Document type	Article
ZDB-ID	1196758-4
ISSN	0929-1393
ISSN	0929-1393
DOI	10.1016/j.apsoil.2018.11.006
Database	NAL-Catalogue (AGRICOLA)

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Article ; Online: Lane Detection in Video-Based Intelligent Transportation Monitoring via Fast Extracting and Clustering of Vehicle Motion Trajectories

Jianqiang Ren / Yangzhou Chen / Le Xin / Jianjun Shi

Mathematical Problems in Engineering, Vol

2014 Volume 2014

Keywords	Mathematics ; QA1-939 ; Science ; Q ; Engineering (General). Civil engineering (General) ; TA1-2040 ; Technology ; T
Language	English
Publishing date	2014-01-01T00:00:00Z
Publisher	Hindawi Publishing Corporation
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Lane Detection in Video-Based Intelligent Transportation Monitoring via Fast Extracting and Clustering of Vehicle Motion Trajectories

Jianqiang Ren / Yangzhou Chen / Le Xin / Jianjun Shi

Mathematical Problems in Engineering, Vol

2014 Volume 2014

Keywords	Mathematics ; QA1-939 ; Science ; Q ; Engineering (General). Civil engineering (General) ; TA1-2040 ; Technology ; T
Language	English
Publishing date	2014-01-01T00:00:00Z
Publisher	Hindawi Publishing Corporation
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article: Simulated NH4+-N Deposition Inhibits CH4 Uptake and Promotes N2O Emission in the Meadow Steppe of Inner Mongolia, China

LIU, Xingren / Jianqiang REN / Leiming ZHANG / Qingwen ZHANG / Shenggong LI

Soil Science Society of China Pedosphere. 2017 Apr., v. 27, no. 2

2017

Abstract: Few studies are conducted to quantify the effects of enhanced N deposition on soil nitrous oxide (N2O) emission and methane (CH4) uptake in the meadow steppe of Inner Mongolia, China. A two-year field experiment was conducted to assess the effects of ... ...

Abstract	Few studies are conducted to quantify the effects of enhanced N deposition on soil nitrous oxide (N2O) emission and methane (CH4) uptake in the meadow steppe of Inner Mongolia, China. A two-year field experiment was conducted to assess the effects of nitrogen (N) deposition rates (0, 10, and 20 kg N ha−1 year−1 as (NH4)2SO4) on soil N2O and CH4 fluxes. The seasonal and diurnal variations of soil N2O and CH4 fluxes were determined using the static chamber-gas chromatography method during the two growing seasons of 2008 and 2009. Soil temperature, moisture and mineral N (NH4+-N and NO3−-N) concentration were simultaneously measured. Results showed that low level of (NH4)2SO4 (10 kg N ha−1 year−1) did not significantly affect soil CH4 and N2O fluxes and other variables. High level of (NH4)2SO4 (20 kg N ha−1 year−1) significantly increased soil NO3−-N concentration by 24.1% to 35.6%, decreased soil CH4 uptake by an average of 20.1%, and significantly promoted soil N2O emission by an average of 98.2%. Soil N2O emission responded more strongly to the added N compared to CH4 uptake. However, soil CH4 fluxes were mainly driven by soil moisture, followed by soil NO3−-N concentration. Soil N2O fluxes were mainly driven by soil temperature, followed by soil moisture. Soil inorganic N availability was a key integrator of soil CH4 uptake and N2O emission. These results suggest that the changes of availability of inorganic N induced by the increased N deposition in soil may affect the CH4 and N2O fluxes in the cold semi-arid meadow steppe over the short term.
Keywords	ammonium nitrogen ; ammonium sulfate ; chromatography ; cold ; diurnal variation ; field experimentation ; greenhouse gas emissions ; growing season ; meadows ; methane ; methane production ; nitrogen ; nitrous oxide ; soil temperature ; soil water ; steppes ; China
Language	English
Dates of publication	2017-04
Size	p. 306-317.
Publishing place	Elsevier Ltd
Document type	Article
ZDB-ID	1090441-4
ISSN	1002-0160
ISSN	1002-0160
DOI	10.1016/S1002-0160(17)60318-7
Database	NAL-Catalogue (AGRICOLA)

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Article ; Online: The Estimation of Regional Crop Yield Using Ensemble-Based Four-Dimensional Variational Data Assimilation

Zhiwei Jiang / Zhongxin Chen / Jin Chen / Jianqiang Ren / Zongnan Li / Liang Sun

Remote Sensing, Vol 6, Iss 4, Pp 2664-

2014 Volume 2681

Abstract: To improve crop model performance for regional crop yield estimates, a new four-dimensional variational algorithm (POD4DVar) merging the Monte Carlo and proper orthogonal decomposition techniques was introduced to develop a data assimilation strategy ... ...

Abstract	To improve crop model performance for regional crop yield estimates, a new four-dimensional variational algorithm (POD4DVar) merging the Monte Carlo and proper orthogonal decomposition techniques was introduced to develop a data assimilation strategy using the Crop Environment Resource Synthesis (CERES)-Wheat model. Two winter wheat yield estimation procedures were conducted on a field plot and regional scale to test the feasibility and potential of the POD4DVar-based strategy. Winter wheat yield forecasts for the field plots showed a coefficient of determination (R2) of 0.73, a root mean square error (RMSE) of 319 kg/ha, and a relative error (RE) of 3.49%. An acceptable yield at the regional scale was estimated with an R2 of 0.997, RMSE of 7346 tons, and RE of 3.81%. The POD4DVar-based strategy was more accurate and efficient than the EnKF-based strategy. In addition to crop yield, other critical crop variables such as the biomass, harvest index, evapotranspiration, and soil organic carbon may also be estimated. The present study thus introduces a promising approach for operationally monitoring regional crop growth and predicting yield. Successful application of this assimilation model at regional scales must focus on uncertainties derived from the crop model, model inputs, data assimilation algorithm, and assimilated observations.
Keywords	four-dimensional variation ; crop model ; data assimilation ; yield estimation ; leaf area index ; remote sensing ; Science ; Q
Subject code	333
Language	English
Publishing date	2014-03-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article: Effects of Simulated NH4 + Deposition on CO2 Fluxes in the Hulun Buir Meadow Steppe of Inner Mongolia, China

Xingren, Liu / Leiming, Zhang / Caihong, Zhang / Jianqiang, Ren / Shenggong, Li

Journal of resources and ecology

Volume v. 6,, Issue no. 3

Abstract: Atmospheric nitrogen (N) deposition may affect carbon (C) sequestration in terrestrial ecosystem. The main objective of this paper was to test the hypothesis that N addition would increase CO₂ emission in the N limited meadow steppe in Inner Mongolia, ... ...

Abstract	Atmospheric nitrogen (N) deposition may affect carbon (C) sequestration in terrestrial ecosystem. The main objective of this paper was to test the hypothesis that N addition would increase CO₂ emission in the N limited meadow steppe in Inner Mongolia, China. Response of CO₂ fluxes to simulated N deposition was studied in the growing season of 2008 and 2009 by static chamber and gas chromatograph techniques. Parallel to the flux measurements, soil temperature, soil moisture, TOC, DOC, soil NH₄ ⁺ and NO₃ ⁻ were measured at the same time. The results indicated that two-year N additions had no significant effect on NH₄ ⁺, but slightly increased NO₃ ⁻ in the later period. The HN treatment tended to increase CO₂ fluxes in the two years, and LN treatment tended to decrease CO₂ fluxes in 2008, and shifted to increase CO₂ fluxes in later growing season of 2009. N addition significantly increased the aboveground biomass and root biomass. The correlation between CO₂ fluxes and moisture or temperature factors did not significantly change due to N addition, but N addition enhanced the moisture sensitivity of CO₂ fluxes as well as the temperature sensitivity of CO₂ fluxes. These results suggest that the increasing ammonium N deposition would be likely to stimulate CO₂ fluxes in the meadow steppe of Inner Mongolia, China.
Keywords	biomass ; nitrates ; meadows ; growing season ; ammonium nitrogen ; carbon dioxide ; nitrogen ; soil temperature ; soil water ; gas chromatography ; steppes ; greenhouse gas emissions ; carbon ; ammonium compounds ; terrestrial ecosystems ; aboveground biomass
Language	English
Document type	Article
ISSN	1674-764X
Database	AGRIS - International Information System for the Agricultural Sciences and Technology

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