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Yuchun Pan
National Engineering Research Center for Information Technology in Agriculture, Beijing 100097, China

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Journal article
Published: 10 June 2021 in Remote Sensing
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Lodging is one of the main problems in maize production. Assessing the self-recovery ability of maize plants after lodging at different growth stages is of great significance for yield loss assessment and agricultural insurance claims. The objective of this study was to quantitatively analyse the effects of different growth stages and lodging severity on the self-recovery ability of maize plants using UAV-LiDAR data. The multi-temporal point cloud data obtained by the RIEGL VUX-1 laser scanner were used to construct the canopy height model of the lodging maize. Then the estimated canopy heights of the maize at different growth stages and lodging severity were obtained. The measured values were used to verify the accuracy of the canopy height estimation and to invert the corresponding lodging angle. After verifying the accuracy of the canopy height, the accuracy parameter of the tasselling stage was R2 = 0.9824, root mean square error (RMSE) = 0.0613 m, and nRMSE = 3.745%. That of the filling stage was R2 = 0.9470, RMSE = 0.1294 m, and nRMSE = 9.889%, which showed that the UAV-LiDAR could accurately estimate the height of the maize canopy. By comparing the yield, canopy height, and lodging angle of maize, it was found that the self-recovery ability of maize at the tasselling stage was stronger than that at the filling stage, but the yield reduction rate was 14.16~26.37% higher than that at the filling stage. The more serious the damage of the lodging is to the roots and support structure of the maize plant, the weaker is the self-recovery ability. Therefore, the self-recovery ability of the stem tilt was the strongest, while that of root lodging and root stem folding was the weakest. The results showed that the UAV-LiDAR could effectively assess the self-recovery ability of maize after lodging.

ACS Style

XueQian Hu; Lin Sun; Xiaohe Gu; Qian Sun; Zhonghui Wei; Yuchun Pan; Liping Chen. Assessing the Self-Recovery Ability of Maize after Lodging Using UAV-LiDAR Data. Remote Sensing 2021, 13, 2270 .

AMA Style

XueQian Hu, Lin Sun, Xiaohe Gu, Qian Sun, Zhonghui Wei, Yuchun Pan, Liping Chen. Assessing the Self-Recovery Ability of Maize after Lodging Using UAV-LiDAR Data. Remote Sensing. 2021; 13 (12):2270.

Chicago/Turabian Style

XueQian Hu; Lin Sun; Xiaohe Gu; Qian Sun; Zhonghui Wei; Yuchun Pan; Liping Chen. 2021. "Assessing the Self-Recovery Ability of Maize after Lodging Using UAV-LiDAR Data." Remote Sensing 13, no. 12: 2270.

Journal article
Published: 03 June 2021 in Sustainability
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Rural areas are a natural, economic and social complex with multiple functions. Identifying rural multifunction scientifically is the basis for promoting efficient rural spatial planning and sustainable development strategy. In this paper, we calculated and characterized the rural production-living-ecological (PLE) functions at a grid scale of 300 × 300 m in Miyun District by establishing an evaluation index system. Several types of rural functional area were identified with the help of an ISO cluster unsupervised classification tool. Three main results were found as follows. (1) The values of the production, living, ecological functions and multifunction ranged from 0–0.101, 0–0.204, 0.009–0.241 and 0.009–0.302, respectively. Ecological function was dominant in this area. (2) The overall spatial patterns of production and living functions showed the characteristic of being “high in the south and low in the north”, and areas with high values were almost distributed around urban areas and the Miyun Reservoir. While for the ecological function and multifunction, they possessed the opposite characteristics to production and living functions, with high values concentrated in the mountainous areas in the northwest, northeast, east and south of Miyun District. (3) According to the clustering results, rural multifunction of Miyun District was divided into four types: ecological conservation, employment and residence, recreation and potential development, with the area proportions of 44.22%, 17.92%, 20.73% and 17.13%, respectively. Each functional type showed a characteristic of agglomeration. In the future, the study of rural multifunction at micro scales should be paid more attention to better understand the functional differences within the country. This research can provide a decision-making reference for demarcation of rural production-living-ecological space and compilation of spatial planning.

ACS Style

Ziyan Yin; Yu Liu; Yuchun Pan. Evaluation and Classification of Rural Multifunction at a Grid Scale: A Case Study of Miyun District, Beijing. Sustainability 2021, 13, 6362 .

AMA Style

Ziyan Yin, Yu Liu, Yuchun Pan. Evaluation and Classification of Rural Multifunction at a Grid Scale: A Case Study of Miyun District, Beijing. Sustainability. 2021; 13 (11):6362.

Chicago/Turabian Style

Ziyan Yin; Yu Liu; Yuchun Pan. 2021. "Evaluation and Classification of Rural Multifunction at a Grid Scale: A Case Study of Miyun District, Beijing." Sustainability 13, no. 11: 6362.

Review
Published: 29 September 2020 in Remote Sensing
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The detection, quantification, diagnosis, and identification of plant diseases is particularly crucial for precision agriculture. Recently, traditional visual assessment technology has not been able to meet the needs of precision agricultural informatization development, and hyperspectral technology, as a typical type of non-invasive technology, has received increasing attention. On the basis of simply describing the types of pathogens and host–pathogen interaction processes, this review expounds the great advantages of hyperspectral technologies in plant disease detection. Then, in the process of describing the hyperspectral disease analysis steps, the articles, algorithms, and methods from disease detection to qualitative and quantitative evaluation are mainly summarizing. Additionally, according to the discussion of the current major problems in plant disease detection with hyperspectral technologies, we propose that different pathogens’ identification, biotic and abiotic stresses discrimination, plant disease early warning, and satellite-based hyperspectral technology are the primary challenges and pave the way for a targeted response.

ACS Style

Ning Zhang; Guijun Yang; Yuchun Pan; Xiaodong Yang; Liping Chen; ChunJiang Zhao. A Review of Advanced Technologies and Development for Hyperspectral-Based Plant Disease Detection in the Past Three Decades. Remote Sensing 2020, 12, 3188 .

AMA Style

Ning Zhang, Guijun Yang, Yuchun Pan, Xiaodong Yang, Liping Chen, ChunJiang Zhao. A Review of Advanced Technologies and Development for Hyperspectral-Based Plant Disease Detection in the Past Three Decades. Remote Sensing. 2020; 12 (19):3188.

Chicago/Turabian Style

Ning Zhang; Guijun Yang; Yuchun Pan; Xiaodong Yang; Liping Chen; ChunJiang Zhao. 2020. "A Review of Advanced Technologies and Development for Hyperspectral-Based Plant Disease Detection in the Past Three Decades." Remote Sensing 12, no. 19: 3188.

Journal article
Published: 10 April 2020 in ISPRS International Journal of Geo-Information
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Complex geographical spatial sampling usually encounters various multi-objective optimization problems, for which effective multi-objective optimization algorithms are much needed to help advance the field. To improve the computational efficiency of the multi-objective optimization process, the archived multi-objective simulated annealing (AMOSA)-II method is proposed as an improved parallelized multi-objective optimization method for complex geographical spatial sampling. Based on the AMOSA method, multiple Markov chains are used to extend the traditional single Markov chain; multi-core parallelization technology is employed based on multi-Markov chains. The tabu-archive constraint is designed to avoid repeated searches for optimal solutions. Two cases were investigated: one with six typical traditional test problems, and the other for soil spatial sampling optimization applications. Six performance indices of the two cases were analyzed—computational time, convergence, purity, spacing, min-spacing and displacement. The results revealed that AMOSA-II performed better which was more effective in obtaining preferable optimal solutions compared with AMOSA and NSGA-II. AMOSA-II can be treated as a feasible means to apply in other complex geographical spatial sampling optimizations.

ACS Style

Xiaolan Li; Bingbo Gao; Zhongke Bai; Yuchun Pan; Yunbing Gao. An Improved Parallelized Multi-Objective Optimization Method for Complex Geographical Spatial Sampling: AMOSA-II. ISPRS International Journal of Geo-Information 2020, 9, 236 .

AMA Style

Xiaolan Li, Bingbo Gao, Zhongke Bai, Yuchun Pan, Yunbing Gao. An Improved Parallelized Multi-Objective Optimization Method for Complex Geographical Spatial Sampling: AMOSA-II. ISPRS International Journal of Geo-Information. 2020; 9 (4):236.

Chicago/Turabian Style

Xiaolan Li; Bingbo Gao; Zhongke Bai; Yuchun Pan; Yunbing Gao. 2020. "An Improved Parallelized Multi-Objective Optimization Method for Complex Geographical Spatial Sampling: AMOSA-II." ISPRS International Journal of Geo-Information 9, no. 4: 236.

Journal article
Published: 23 March 2020 in Sustainability
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Mastering the regional spatial differences of ecosystem service supply and ecosystem service demand is of great significance to scientifically planning the development and utilization of national land and maintaining healthy development of ecosystems. Based on the relationship analysis of ecosystem service supply and ecosystem service demand, this study explored the regional ecosystem service supply by ecosystem service value based on grid data and constructed an ecosystem service demand evaluation model that integrated the construction land ecosystem service demand equivalent for static aspects and the point of interest (POI) kernel density estimation for dynamic aspects on the basis of land use and POI data. In the end, it put forward a region division method for ecosystem service supply and ecosystem service demand and conducted an empirical analysis of Haidian District, Beijing. The following results were concluded: (1) the ecosystem service value of different grids in Haidian District was between RMB (Chinese monetary unit, Yuan) 0 and RMB 2.4787 million. In terms of spatial distribution, the ecosystem service supply took on an obvious trend of gradual decrease from the northwest to the southeast, with major ecosystem service supply coming from the northwest. (2) The construction land ecosystem service demand equivalent of Haidian District was characterized by a multicenter cluster: the high equivalent area was in the southeast, while the equivalent of the northwest was relatively low. POI kernel density estimation demonstrated cluster distribution, with a high kernel density estimation in the southeast, a lower kernel density estimation in the central part, and the lowest kernel density estimation in the northwest. The ecosystem service demand index also showed cluster distribution: high index in the southeast, low index in the northwest, and prominent sudden changes from the central part to the south. (3) The bivariate local spatial autocorrelation cluster diagram method was used to divide five types of ecosystem service supply and ecosystem service demand, namely non-significant correlation region, high ecosystem service supply and high ecosystem service demand region, high ecosystem service supply and low ecosystem service demand region, low ecosystem service supply and high ecosystem service demand region, low ecosystem service supply and low ecosystem service demand region. Grids with the highest ratio belonged to the non-significant correlation region; the distribution of low ecosystem service supply and high ecosystem service demand region had the greatest concentration, mainly in the southeast; the grids of high ecosystem service supply and low ecosystem service demand region were mainly present in the northwest and in a continuous way; the grids of low ecosystem service supply and low ecosystem service demand region, and high ecosystem service supply and high ecosystem service demand region were extremely few, with sporadic distribution in the central part. The research results could provide a basis for the adjustment and fine management of regional land use structure.

ACS Style

Xiumei Tang; Yu Liu; Yuchun Pan. An Evaluation and Region Division Method for Ecosystem Service Supply and Demand Based on Land Use and POI Data. Sustainability 2020, 12, 2524 .

AMA Style

Xiumei Tang, Yu Liu, Yuchun Pan. An Evaluation and Region Division Method for Ecosystem Service Supply and Demand Based on Land Use and POI Data. Sustainability. 2020; 12 (6):2524.

Chicago/Turabian Style

Xiumei Tang; Yu Liu; Yuchun Pan. 2020. "An Evaluation and Region Division Method for Ecosystem Service Supply and Demand Based on Land Use and POI Data." Sustainability 12, no. 6: 2524.

Conference paper
Published: 09 January 2019 in Lecture Notes in Control and Information Sciences
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Spatial structure analysis is beneficial to guide soil nutrients management. This paper developed a method for spatial structure of soil nutrients and analyzed these change characteristics from 2000 to 2007 using geographic information system (GIS) technology for Daxing district of Beijing, China. The results of spatial structure were obtained and occupied space proportions of total kjeldahl nitrogen (TN), alkali-hydrolyzable nitrogen (AN), organic matter (OM), available phosphorus (AP) and available potassium (AK) were 0.33, 0.22, 0.25, 0.03, 0.16 for 2000 and 0.32, 0.25, 0.23, 0.03, 0.17 for 2007, respectively. The change characteristics and influence factors for spatial structure of soil nutrients were systematically analyzed. Increased soil nutrients were exhibited three belts on the whole, whereas decreased soil nutrients were located in other regions. Natural factors and human activities drove these changes of soil nutrients. This study provides a reference for future related research.

ACS Style

Shiwei Dong; Yuchun Pan; Bingbo Gao. Spatial Structure Change Analysis of Cultivated Soil Nutrients in Urban Fringe of North China. Lecture Notes in Control and Information Sciences 2019, 134 -142.

AMA Style

Shiwei Dong, Yuchun Pan, Bingbo Gao. Spatial Structure Change Analysis of Cultivated Soil Nutrients in Urban Fringe of North China. Lecture Notes in Control and Information Sciences. 2019; ():134-142.

Chicago/Turabian Style

Shiwei Dong; Yuchun Pan; Bingbo Gao. 2019. "Spatial Structure Change Analysis of Cultivated Soil Nutrients in Urban Fringe of North China." Lecture Notes in Control and Information Sciences , no. : 134-142.

Journal article
Published: 28 September 2018 in Sustainability
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To increase the spatial resolution of Soil Moisture Active Passive (SMAP), this study modifies the downscaling factor model based on the Temperature Vegetation Drought Index (TVDI) using data from the Project for On-Board Autonomy (PROBA-V). In the modified model, TVDI parameters were derived from the temperature-vegetation space and the Enhanced Vegetation Index (EVI). This study was conducted in the north China region using SMAP, PROBA-V, and Moderate Resolution Imaging Spectroradiometer satellite images. The 9-km spatial resolution SMAP data was downscaled to 0.3-km spatial resolution soil moisture using a modified downscaling method. Downscaling accuracies from the original and modified downscaling factor models were compared based on field observations. The results show that both methods generated similar spatial distributions in which soil moisture estimates increased as vegetation coverage increased from built-up areas to forest. However, based on the root mean square error between observations and estimations, the modified model demonstrated an increased estimation accuracy of 4.2% for soil moisture compared to the original method. This study also implies that downscaled soil moisture shows promise as a data source for subsequent watershed scale studies.

ACS Style

Shu-Di Fan; Yue-Ming Hu; Lu Wang; Zhen-Hua Liu; Zhou Shi; Wen-Bin Wu; Yu-Chun Pan; Guang-Xing Wang; A-Xing Zhu; Bo Li. Improving Spatial Soil Moisture Representation through the Integration of SMAP and PROBA-V Products. Sustainability 2018, 10, 3459 .

AMA Style

Shu-Di Fan, Yue-Ming Hu, Lu Wang, Zhen-Hua Liu, Zhou Shi, Wen-Bin Wu, Yu-Chun Pan, Guang-Xing Wang, A-Xing Zhu, Bo Li. Improving Spatial Soil Moisture Representation through the Integration of SMAP and PROBA-V Products. Sustainability. 2018; 10 (10):3459.

Chicago/Turabian Style

Shu-Di Fan; Yue-Ming Hu; Lu Wang; Zhen-Hua Liu; Zhou Shi; Wen-Bin Wu; Yu-Chun Pan; Guang-Xing Wang; A-Xing Zhu; Bo Li. 2018. "Improving Spatial Soil Moisture Representation through the Integration of SMAP and PROBA-V Products." Sustainability 10, no. 10: 3459.

Journal article
Published: 15 July 2018 in Sustainability
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Mercury is one of the five most toxic heavy metals to the human body. In order to select a high-precision method for predicting the mercury content in soil using hyperspectral techniques, 75 soil samples were collected in Guangdong Province to obtain the soil mercury content by chemical analysis and hyperspectral data based on an indoor hyperspectral experiment. A multiple linear regression (MLR), a back-propagation neural network (BPNN), and a genetic algorithm optimization of the BPNN (GA-BPNN) were used to establish a relationship between the hyperspectral data and the soil mercury content and to predict the soil mercury content. In addition, the feasibility and modeling effects of the three modeling methods were compared and discussed. The results show that the GA-BPNN provided the best soil mercury prediction model. The modeling R2 is 0.842, the root mean square error (RMSE) is 0.052, and the mean absolute error (MAE) is 0.037; the testing R2 is 0.923, the RMSE is 0.042, and the MAE is 0.033. Thus, the GA-BPNN method is the optimum method to predict soil mercury content and the results provide a scientific basis and technical support for the hyperspectral inversion of the soil mercury content.

ACS Style

Li Zhao; Yue-Ming Hu; Wu Zhou; Zhen-Hua Liu; Yu-Chun Pan; Zhou Shi; Lu Wang; Guang-Xing Wang. Estimation Methods for Soil Mercury Content Using Hyperspectral Remote Sensing. Sustainability 2018, 10, 2474 .

AMA Style

Li Zhao, Yue-Ming Hu, Wu Zhou, Zhen-Hua Liu, Yu-Chun Pan, Zhou Shi, Lu Wang, Guang-Xing Wang. Estimation Methods for Soil Mercury Content Using Hyperspectral Remote Sensing. Sustainability. 2018; 10 (7):2474.

Chicago/Turabian Style

Li Zhao; Yue-Ming Hu; Wu Zhou; Zhen-Hua Liu; Yu-Chun Pan; Zhou Shi; Lu Wang; Guang-Xing Wang. 2018. "Estimation Methods for Soil Mercury Content Using Hyperspectral Remote Sensing." Sustainability 10, no. 7: 2474.

Journal article
Published: 23 January 2016 in Agricultural Research
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Based on the logarithmic mean Divisia index (LMDI) method, this study systematically analyzes the change in gross output value of planting industry in China during 1990–2012 , reveals the contribution of total sown areas of farm crops, planting structure, per hectare output of crop and price level of crop on gross output value of planting industry and identifies significant contributors to the changes at different times, thereby providing reference for the rapid growth in gross output value of planting industry in China. The following results are obtained: (1) The gross output value of planting industry in China was increased by 995.31 billion Yuan during 1990–2012; during those nine crops, rice had the maximum increment in gross output value, while peanut increased at the fastest rate; the output value of rice, wheat and maize occupied an important position, but showed overall downward trend with fluctuation. (2) The cumulative contributions of total sown area of farm crops, planting structure, per hectare output of crop and price level of crop on the gross output value were 88.64, −24.18, 228.22 and 702.63 billion Yuan, respectively. Price level of crop and per hectare output of crop were the main contributors to the rapid increase in gross output value of planting industry; from the view of respective crops, the effects of price level of crop and per hectare output of crop in those nine crops were positive; the rapid rise in the price of rice, maize, wheat, cotton and peanut, superimposed with the significant increase in the per hectare output of cotton and the planting proportion of maize, obviously promoted gross output value of planting industry during 1990–2012. (3) The gross output value of planting industry in China was closely related to national macroeconomic policies. The rise of crop price was the major contributor to increase in gross output value of planting industry during 1990–1996; the overall decline in the price of crop and the planting proportion led to significant decline in gross output value during 1997–2003; the rebound rise in the price of crop and the rapid increase in per hectare output of crop resulted in significant increase in gross output value of planting industry during 2004–2012.

ACS Style

Yu Liu; Bing-Bo Gao; Yu-Chun Pan. Changes in Gross Output Value of Planting Industry and Their Decomposition of Crops in China Based on the LMDI Model. Agricultural Research 2016, 5, 89 -97.

AMA Style

Yu Liu, Bing-Bo Gao, Yu-Chun Pan. Changes in Gross Output Value of Planting Industry and Their Decomposition of Crops in China Based on the LMDI Model. Agricultural Research. 2016; 5 (1):89-97.

Chicago/Turabian Style

Yu Liu; Bing-Bo Gao; Yu-Chun Pan. 2016. "Changes in Gross Output Value of Planting Industry and Their Decomposition of Crops in China Based on the LMDI Model." Agricultural Research 5, no. 1: 89-97.

Journal article
Published: 29 December 2015 in Sustainability
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Statistical analysis of land-use change plays an important role in sustainable land management and has received increasing attention from scholars and administrative departments. However, the statistical process involving spatial overlay analysis remains difficult and needs improvement to deal with mass land-use data. In this paper, we introduce a spatio-temporal flow network model to reveal the hidden relational information among spatio-temporal entities. Based on graph theory, the constant condition of saturated multi-commodity flow is derived. A new method based on a network partition technique of spatio-temporal flow network are proposed to optimize the transition statistical process. The effectiveness and efficiency of the proposed method is verified through experiments using land-use data in Hunan from 2009 to 2014. In the comparison among three different land-use change statistical methods, the proposed method exhibits remarkable superiority in efficiency.

ACS Style

Yipeng Zhang; Yunbing Gao; Bingbo Gao; Yuchun Pan; Mingyang Yan. An Efficient Graph-based Method for Long-term Land-use Change Statistics. Sustainability 2015, 8, 9 .

AMA Style

Yipeng Zhang, Yunbing Gao, Bingbo Gao, Yuchun Pan, Mingyang Yan. An Efficient Graph-based Method for Long-term Land-use Change Statistics. Sustainability. 2015; 8 (1):9.

Chicago/Turabian Style

Yipeng Zhang; Yunbing Gao; Bingbo Gao; Yuchun Pan; Mingyang Yan. 2015. "An Efficient Graph-based Method for Long-term Land-use Change Statistics." Sustainability 8, no. 1: 9.

Journal article
Published: 07 November 2011 in Mathematical and Computer Modelling
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Since van Groenigen and Stein (1998) proposed the SSA+MMSD (Spatial Simulated Annealing + Minimization of the Mean of Shortest Distances criterion) method, this method has found many applications in the optimization of sampling designs. However, it is computationally inefficient due to the complexity of this method itself. Initially in this paper, we analyze the computational complexity associated with this method from both SSA and MMSD aspects. And then, we propose some corresponding revisions (including the initial solution, perturbation rules, as well as the objective function) accordingly so as to reduce its computations. Finally, we evaluate the efficiency improvement via comparing some efficiency indexes of both original and modified methods (including the total perturbations needed, valid and better candidate designs generating rates of the perturbations, and the rate of objective function decline). Analysis and experimental results indicate that the modified method is much more efficient than the original one; in C++ implementations, the mean execution time needed for the modified method is only about 1/3 of that of the original.

ACS Style

Baisong Chen; Yuchun Pan; Jihua Wang; Zhuo Fu; Zhixuan Zeng; Yanbing Zhou; Yongping Zhang. Even sampling designs generation by efficient spatial simulated annealing. Mathematical and Computer Modelling 2011, 58, 670 -676.

AMA Style

Baisong Chen, Yuchun Pan, Jihua Wang, Zhuo Fu, Zhixuan Zeng, Yanbing Zhou, Yongping Zhang. Even sampling designs generation by efficient spatial simulated annealing. Mathematical and Computer Modelling. 2011; 58 (3-4):670-676.

Chicago/Turabian Style

Baisong Chen; Yuchun Pan; Jihua Wang; Zhuo Fu; Zhixuan Zeng; Yanbing Zhou; Yongping Zhang. 2011. "Even sampling designs generation by efficient spatial simulated annealing." Mathematical and Computer Modelling 58, no. 3-4: 670-676.