Project scientific publications

2022

  • Ghassemi, B.; Immitzer, M.; Atzberger, C.; Vuolo, F. Evaluation of Accuracy Enhancement in European-Wide Crop Type Mapping by Combining Optical and Microwave Time Series. Land 2022, 11, 1397. https://doi.org/10.3390/land11091397.
  • Ghassemi, B.; Dujakovic, A.; Żółtak, M.; Immitzer, M.; Atzberger, C.; Vuolo, F. Designing a European-Wide Crop Type Mapping Approach Based on Machine Learning Algorithms Using LUCAS Field Survey and Sentinel-2 Data. Remote Sens. 2022, 14, 541. https://doi.org/10.3390/rs14030541
  • Tomáš Řezník, Lieven Raes, Andrew Stott, Bart De Lathouwer, Andrea Perego, Karel Charvát, Štěpán Kafka, Improving the documentation and findability of data services and repositories: A review of (meta)data management approaches, Computers & Geosciences, Volume 169, 2022, 105194, ISSN 0098-3004, https://doi.org/10.1016/j.cageo.2022.105194.
  • Li Z, Ding L, Xu D. Exploring the potential role of environmental and multi-source satellite data in crop yield prediction across Northeast China. Sci Total Environ. 2022 Apr 1;815:152880. doi: 10.1016/j.scitotenv.2021.152880. Epub 2022 Jan 6. PMID: 34998760.
  • Yongsheng Hong, Yiyun Chen, Songchao Chen, Ruili Shen, Bifeng Hu, Jie Peng, Nan Wang, Long Guo, Zhiqing Zhuo, Yuanyuan Yang, Yaolin Liu, Abdul Mounem Mouazen, Zhou Shi, Data mining of urban soil spectral library for estimating organic carbon, Geoderma, Volume 426, 2022, 116102, ISSN 0016-7061, https://doi.org/10.1016/j.geoderma.2022.116102
  • Chen D, Zhuang Q, Zhang W, Zhu L (2022) Estimation of Landsat-like daily evapotranspiration for crop water consumption monitoring using TSEB model and data fusion. PLoS ONE 17(5): e0267811. https://doi.org/10.1371/journal.pone.0267811

  • Chen, D.; Zhuang, Q.; Zhu, L.; Zhang, W. Comparison of Methods for Reconstructing MODIS Land Surface Temperature under Cloudy Conditions. Appl. Sci. 2022, 12, 6068. https://doi.org/10.3390/app12126068

  • Li, Z.; Qiu, Z.; Ge, H.; Du, C. Long-Term Dynamic of Cold Stress during Heading and Flowering Stage and Its Effects on Rice Growth in China. Atmosphere 2022, 13, 103. https://doi.org/10.3390/atmos13010103
  • Lu, R.; Wang, N.; Zhang, Y.; Lin, Y.; Wu, W.; Shi, Z. Extraction of Agricultural Fields via DASFNet with Dual Attention Mechanism and Multi-scale Feature Fusion in South Xinjiang, China. Remote Sens. 2022, 14, 2253. https://doi.org/10.3390/rs14092253
  • Zhang, S.; Zhao, R.; Wu, K.; Huang, Q.; Kang, L. Effects of the Rapid Construction of a High-Quality Plough Layer Based on Woody Peat in a Newly Reclaimed Cultivated Land Area. Agriculture 2022, 12, 31. https://doi.org/10.3390/agriculture12010031
  • Singha, A., Soothar, R.K., Wang, C. et al. Drought priming alleviated salinity stress and improved water use efficiency of wheat plants. Plant Growth Regul 96, 357–368 (2022). https://doi.org/10.1007/s10725-021-00781-x
  • Wang C, Ma H, Feng Z, Yan Z, Song B, Wang J, Zheng Y, Hao W, Zhang W, Yao M, Wang Y. Integrated organic and inorganic fertilization and reduced irrigation altered prokaryotic microbial community and diversity in different compartments of wheat root zone contributing to improved nitrogen uptake and wheat yield. Sci Total Environ. 2022 Oct 10;842:156952. doi: 10.1016/j.scitotenv.2022.156952. Epub 2022 Jun 22. PMID: 35752240.
  • Nan Wang, Jie Peng, Songchao Chen, Jingyi Huang, Hongyi Li, Asim Biswas, Yong He, Zhou Shi, Improving remote sensing of salinity on topsoil with crop residues using novel indices of optical and microwave bands, Geoderma, Volume 422, 2022, 115935, ISSN 0016-7061, https://doi.org/10.1016/j.geoderma.2022.115935
  • Nan Wang, Jie Peng, Jie Xue, Xianglin Zhang, Jingyi Huang, Asim Biswas, Yong He, Zhou Shi, A framework for determining the total salt content of soil profiles using time-series Sentinel-2 images and a random forest-temporal convolution network, Geoderma, Volume 409, 2022, 115656, ISSN 0016-7061, https://doi.org/10.1016/j.geoderma.2021.115656
  • Wu, Z.; Hua, W.; Luo, L.; Tanaka, K. Technical Efficiency of Maize Production and Its Influencing Factors in the World’s Largest Groundwater Drop Funnel Area, China. Agriculture 2022, 12, 649. https://doi.org/10.3390/agriculture12050649
  • Zhang, X.; Xue, J.; Chen, S.; Wang, N.; Shi, Z.; Huang, Y.; Zhuo, Z. Digital Mapping of Soil Organic Carbon with Machine Learning in Dryland of Northeast and North Plain China. Remote Sens. 2022, 14, 2504. https://doi.org/10.3390/rs14102504
  • Liu, Y.; Wu, K.; Li, X.; Li, X.; Cao, H. Adaptive Management of Cultivated Land Use Zoning Based on Land Types Classification: A Case Study of Henan Province. Land 2022, 11, 346. https://doi.org/10.3390/land11030346
  • Qiu, Z.; Ma, F.; Li, Z.; Xu, X.; Du, C. Development of Prediction Models for Estimating Key Rice Growth Variables Using Visible and NIR Images from Unmanned Aerial Systems. Remote Sens. 2022, 14, 1384. https://doi.org/10.3390/rs14061384
  • Qi Song, Bifeng Hu, Jie Peng, Hocine Bourennane, Asim Biswas, Thomas Opitz, Zhou Shi, Spatio-temporal variation and dynamic scenario simulation of ecological risk in a typical artificial oasis in northwestern China, Journal of Cleaner Production, Volume 369, 2022, 133302, ISSN 0959-6526, https://doi.org/10.1016/j.jclepro.2022.133302
  • Wang et al., “Comparison of Different Intercalibration Methods of Brightness Temperatures From FY-3D and AMSR2,” in IEEE Transactions on Geoscience and Remote Sensing, vol. 60, pp. 1-17, 2022, Art no. 5304217, doi: 10.1109/TGRS.2022.3176748.

  • Chen, D.; Zhuang, Q.; Zhu, L.; Zhang, W. Comparison of Methods for Reconstructing MODIS Land Surface Temperature under Cloudy Conditions. Appl. Sci. 2022, 12, 6068. https://doi.org/10.3390/app12126068

  • Felix Nyarko, Filip M.G. Tack, Abdul M. Mouazen, Potential of visible and near infrared spectroscopy coupled with machine learning for predicting soil metal concentrations at the regional scale, Science of The Total Environment, Volume 841, 2022, 156582, ISSN 0048-9697. https://doi.org/10.1016/j.scitotenv.2022.156582
  • Karapetsas, N.; Alexandridis, T.K.; Bilas, G.; Munnaf, M.A.; Guerrero, A.P.; Calera, M.; Osann, A.; Gobin, A.; Rezník, T.; Moshou, D.; Mouazen, A.M. Mapping Soil Properties with Fixed Rank Kriging of Proximally Sensed Soil Data Fused with Sentinel-2 Biophysical Parameter. Remote Sens. 2022, 14, 1639. https://www.mdpi.com/2072-4292/14/7/1639#cite
  • Javadi, S.H.; Guerrero, A.; Mouazen, A.M. Clustering and Smoothing Pipeline for Management Zone Delineation Using Proximal and Remote Sensing. Sensors 2022, 22, 645. https://doi.org/10.3390/s22020645
  • Charvát, Karel, Berzins, Raitis, Bergheim, Runar, Zadražil, František, Macura, Jan, Langovskis, Dailis, Šnevajs, Heřman, Kubíčková, Hana, Horáková, Šárka, & Charvát, Karel. (2022, June 29). Map Whiteboard As Collaboration Tool for Smart Farming Advisory Services. 15th International Conference on Precision Agriculture, Minneapolis, Minnesota, United States. https://doi.org/10.5281/zenodo.6864305 JOINT PUBLICATION WITH HORIZON 2020 PROJECTS

2021

  • Song, X. D., Yang, F., Wu, H. Y., Zhang, J., Li, D. C., Liu, F., Zhao, Y. G., Yang, J. L., Ju, B., Cai, C. F., Huang, B., Long, H. Y., Lu, Y., Sui, Y. Y., Wang, Q. B., Wu, K. N., Zhang, F. R., Zhang, M. K., Shi, Z., Ma, W. Z., … Zhang, G. L. (2021). Significant loss of soil inorganic carbon at the continental scale. National science review, 9(2), nwab120. https://doi.org/10.1093/nsr/nwab120
  • Geng, Z. Q., Qian, D. K., Hu, Z. Y., Wang, S., Yan, Y., van Loosdrecht, M., Zeng, R. J., & Zhang, F. (2021). Identification of Extracellular Key Enzyme and Intracellular Metabolic Pathway in Alginate-Degrading Consortia via an Integrated Metaproteomic/Metagenomic Analysis. Environmental science & technology, 55(24), 16636–16645. https://doi.org/10.1021/acs.est.1c05289
  • Li, Li and Wang, Yaosheng and Liu, Fulai, Alternate partial root-zone N-fertigation increases water use efficiency and N uptake of barley at elevated CO2, Agricultural Water Management, 2021, 258, C, 10.1016/j.agwat.2021.1071. https://doi.org/10.1016/j.agwat.2021.107168
  • Li Li, Jiayi Xing, Haiyang Ma, Fulai Liu, Yaosheng Wang, In situ determination of guard cell ion flux underpins the mechanism of ABA-mediated stomatal closure in barley plants exposed to PEG-induced drought stress, Environmental and Experimental Botany, Volume 187, 2021, 104468, ISSN 0098-8472, https://doi.org/10.1016/j.envexpbot.2021.104468.

  • Kang, L.; Zhao, R.; Wu, K.; Huang, Q.; Zhang, S. Impacts of Farming Layer Constructions on Cultivated Land Quality under the Cultivated Land Balance Policy. Agronomy 2021, 11, 2403. https://doi.org/10.3390/agronomy11122403.

  • Zhengchao Qiu, Fei Ma, Zhenwang Li, Xuebin Xu, Haixiao Ge, Changwen Du, Estimation of nitrogen nutrition index in rice from UAV RGB images coupled with machine learning algorithms, Computers and Electronics in Agriculture, Volume 189, 2021, 106421, ISSN 0168-1699, https://doi.org/10.1016/j.compag.2021.106421.

  • Soothar, R.K., Wang, C., Li, L. et al. Soil Salt Accumulation, Physiological Responses, and Yield Simulation of Winter Wheat to Alternate Saline and Fresh Water Irrigation in the North China Plain. J Soil Sci Plant Nutr 21, 2072–2082 (2021). https://doi.org/10.1007/s42729-021-00503-2
  • Tan et al., “A CNN-Based Self-Supervised Synthetic Aperture Radar Image Denoising Approach,” in IEEE Transactions on Geoscience and Remote Sensing, vol. 60, pp. 1-15, 2022, Art no. 5213615, doi: 10.1109/TGRS.2021.3104807.
  • Huanli Xing, Wenbin Zhou, Chao Wang, Li Li, Xiangnan Li, Ningbo Cui, Weiping Hao, Fulai Liu, Yaosheng Wang, Excessive nitrogen application under moderate soil water deficit decreases photosynthesis, respiration, carbon gain and water use efficiency of maize, Plant Physiology and Biochemistry, Volume 166, 2021, Pages 1065-1075, ISSN 0981-9428, https://doi.org/10.1016/j.plaphy.2021.07.014.

  • Xue, J.; Wang, Y.; Teng, H.; Wang, N.; Li, D.; Peng, J.; Biswas, A.; Shi, Z. Dynamics of Vegetation Greenness and Its Response to Climate Change in Xinjiang over the Past Two Decades. Remote Sens. 2021, 13, 4063. https://doi.org/10.3390/rs13204063.

  • Zhang, F., Qian, D. K., Geng, Z. Q., Dai, K., Zhang, W., Van Loosdrecht, M. C. M., & Zeng, R. J. (2021). Enhanced Methane Recovery from Waste-Activated Sludge by Alginate-Degrading Consortia: The Overlooked Role of Alginate in Extracellular Polymeric Substances: Environmental Science and Technology Letters, 8(1), 86-91. https://doi.org/10.1021/acs.estlett.0c00784.
  • Zhao, R.; Li, J.; Wu, K.; Kang, L. Cultivated Land Use Zoning Based on Soil Function Evaluation from the Perspective of Black Soil Protection. Land 2021, 10, 605. https://doi.org/10.3390/land10060605.
  • Zhao, R.; Wu, K. Soil Health Evaluation of Farmland Based on Functional Soil Management—A Case Study of Yixing City, Jiangsu Province, China. Agriculture 2021, 11, 583. https://doi.org/10.3390/agriculture11070583.
  • Zheng, Y., Li, X., Cao, H., Lei, L., Zhang, X., Han, D., Wang, J., & Yao, M. (2021). The assembly of wheat-associated fungal community differs across growth stages. Applied microbiology and biotechnology, 105(19), 7427–7438. https://doi.org/10.1007/s00253-021-11550-1.
  • Fang, P.; Yan, N.; Wei, P.; Zhao, Y.; Zhang, X. Aboveground Biomass Mapping of Crops Supported by Improved CASA Model and Sentinel-2 Multispectral Imagery. Remote Sens. 2021, 13, 2755. https://doi.org/10.3390/rs13142755.
  • Jiajia Liao, Chaoyue Yu, Zhe Feng, Huafu Zhao, Kening Wu, Xiaoyan Ma, Spatial differentiation characteristics and driving factors of agricultural eco-efficiency in Chinese provinces from the perspective of ecosystem services, Journal of Cleaner Production, Volume 288, 2021, 125466, ISSN 0959-6526, https://doi.org/10.1016/j.jclepro.2020.125466.
  • Ge, H.; Ma, F.; Li, Z.; Du, C. Grain Yield Estimation in Rice Breeding Using Phenological Data and Vegetation Indices Derived from UAV Images. Agronomy 2021, 11, 2439. https://doi.org/10.3390/agronomy11122439.
  • Ge, H.; Ma, F.; Li, Z.; Tan, Z.; Du, C. Improved Accuracy of Phenological Detection in Rice Breeding by Using Ensemble Models of Machine Learning Based on UAV-RGB Imagery. Remote Sens. 2021, 13, 2678. https://doi.org/10.3390/rs13142678.
  • Hongwei Zeng, Bingfang Wu, Miao Zhang, Ning Zhang, Abdelrazek Elnashar, Liang Zhu, Weiwei Zhu, Fangming Wu, Nana Yan, Wenjun Liu, Dryland ecosystem dynamic change and its drivers in Mediterranean region, Current Opinion in Environmental Sustainability, Volume 48, 2021, Pages 59-67, ISSN 1877-3435, https://doi.org/10.1016/j.cosust.2020.10.013 .
  • Wang, J.; Peng, J.; Li, H.; Yin, C.; Liu, W.; Wang, T.; Zhang, H. Soil Salinity Mapping Using Machine Learning Algorithms with the Sentinel-2 MSI in Arid Areas, China. Remote Sens. 2021, 13, 305. https://doi.org/10.3390/rs13020305.
  • Ge, H.; Ma, F.; Li, Z.; Du, C. Global Sensitivity Analysis for CERES-Rice Model under Different Cultivars and Specific-Stage Variations of Climate Parameters. Agronomy 2021, 11, 2446. https://doi.org/10.3390/agronomy11122446.
  • Abdelrazek Elnashar, Hongwei Zeng, Bingfang Wu, Ayele Almaw Fenta, Mohsen Nabil, Robert Duerler, Soil erosion assessment in the Blue Nile Basin driven by a novel RUSLE-GEE framework, Science of The Total Environment, Volume 793, 2021, 148466, ISSN 0048-9697, https://doi.org/10.1016/j.scitotenv.2021.148466.
  • Mouazen, A.M.; Nyarko, F.; Qaswar, M.; Tóth, G.; Gobin, A.; Moshou, D. Spatiotemporal Prediction and Mapping of Heavy Metals at Regional Scale Using Regression Methods and Landsat 7. Remote Sens. 2021, 13, 4615. https://www.mdpi.com/2072-4292/13/22/4615
  • Szigeti, N.; Berki, I.; Vityi, A.; Rasran, L. Shelterbelts Planted on Cultivated Fields Are Not Solutions for the Recovery of Former Forest-Related Herbaceous Vegetation. Land 2021, 10, 930. https://doi.org/10.3390/land10090930
  • Abdul Mounem Mouazen and Zhou Shi, 2021. Estimation and Mapping of Soil Properties Based on Multi-Source Data Fusion. Remote Sensing 2021, 13(5), 978. https://doi.org/10.3390/rs13050978
  • Yongsheng Hong, Yiyun Chen, Ruili Shen, Songchao Chen, Gang Xu, Hang Cheng, Long Guo, Zushuai Wei, Jian Yang, Yaolin Liu, Zhou Shi, Abdul M. Mouazen, Diagnosis of cadmium contamination in urban and suburban soils using visible-to-near-infrared spectroscopy, Environmental Pollution, Volume 291, 2021, 118128, ISSN 0269-7491. https://doi.org/10.1016/j.envpol.2021.118128
  • Řezník, T; Herman, L.; Klocová, M.; Leitner, F.; Pavelka, T.; Leitgeb, S.; Trojanová, K.; Štampach, R.; Moshou, D.; Mouazen, A.M.; Alexandridis, T.K.; Hrádek, J.; Lukas, V.; Širůček, P. 2021. Towards the Development and Verification of a 3D-Based Advanced Optimised Farm Machinery Trajectory Algorithm. Sensors 2021, 21, 2980, (IF (2019) = 3.275). https://doi.org/10.3390/s21092980
  • Chen S C, Xu H Y, Xu D Y, etc. Evaluating validation strategies on the performance of soil property prediction from regional to continental spectral data. Geoderma. 2021, 400, 15159. https://doi.org/10.1016/j.geoderma.2021.115159
  • Ge H X, Xiang H T, Ma F, etc. Estimating plant nitrogen concentration of rice through fusing VI and color moments derived from UAV-RGB Images. Remote Sensing. 2021, 13, 1620. https://www.mdpi.com/2072-4292/13/9/1620
  • Tomáš Řezník, Jan Chytrý and Kateřina Trojanová, 2021. Machine Learning-Based Processing Proof-of-Concept Pipeline for Semi-Automatic Sentinel-2 Imagery Download, Cloudiness Filtering, Classifications and Updates of Open Land Use/Land Cover Datasets, International Journal of Geo-Information. 2021, 10, 102. https://www.mdpi.com/2220-9964/10/2/102/pdf
  • Zhao, R. et al. Discussion on the Unified Survey and evaluation of Cultivated Land Quality at Country Scale for China’s 3rd National Land Survey: A Case Study of Wen County, Henan Province. Sustainability, 2021, 13, 2513. https://www.mdpi.com/2071-1050/13/5/2513
  • Guo Y M, Xiang H T, Li Z W, etc. Prediction of rice yield in East China based on climate and agronomic traits data using ANN and PLSR. Agronomy. 2021, 11, 282. https://www.mdpi.com/2073-4395/11/2/282

2020

  • Li, L., Ma, H., Xing, J., Liu, F. and Wang, Y. (2020), Effects of water deficit and nitrogen application on leaf gas exchange, phytohormone signaling, biomass and water use efficiency of oat plants. J. Plant Nutr. Soil Sci., 183: 695-704. https://doi.org/10.1002/jpln.202000183.
  • Ding-Kang Qian, Zi-Qian Geng, Ting Sun, Kun Dai, Wei Zhang, Raymond Jianxiong Zeng, Fang Zhang, Caproate production from xylose by mesophilic mixed culture fermentation,  Bioresource Technology, Volume 308, 2020, 123318, ISSN 0960-8524, https://doi.org/10.1016/j.biortech.2020.123318.
  • Moussa Tankari, Chao Wang, Haiyang Ma, Xiangnan Li, Li Li, Rajesh Kumar Soothar, Ningbo Cui, Mainassara Zaman-Allah, Weiping Hao, Fulai Liu, Yaosheng Wang, Drought priming improved water status, photosynthesis and water productivity of cowpea during post-anthesis drought stress, Agricultural Water Management, Volume 245, 2021, 106565, ISSN 0378-3774, https://doi.org/10.1016/j.agwat.2020.106565.
  • Wang, N.; Xue, J.; Peng, J.; Biswas, A.; He, Y.; Shi, Z. Integrating Remote Sensing and Landscape Characteristics to Estimate Soil Salinity Using Machine Learning Methods: A Case Study from Southern Xinjiang, China. Remote Sens. 2020, 12, 4118. https://doi.org/10.3390/rs12244118.
  • Fang Zhang, Ding-Kang Qian, Xian-Bin Wang, Kun Dai, Ting Wang, Wei Zhang, Raymond Jianxiong Zeng, Stimulation of methane production from benzoate with addition of carbon materials, Science of The Total Environment, Volume 723, 2020, 138080, ISSN 0048-9697, https://doi.org/10.1016/j.scitotenv.2020.138080
  • Xiao-Dong Song, David G. Rossiter, Feng Liu, Hua-Yong Wu, Xiao-Rui Zhao, Qi Cao, Gan-Lin Zhang, Can pedotransfer functions based on environmental variables improve soil total nutrient mapping at a regional scale?, Soil and Tillage Research, Volume 202, 2020, 104672, ISSN 0167-1987, https://doi.org/10.1016/j.still.2020.104672.
  • Qiu Z C, Xiang H T, Ma F, etc. Qualifications of rice growth indicators optimized at different growth stages using UAV digital imagery. Remote Sensing. 2020, 12, 3228. https://www.mdpi.com/2072-4292/12/19/3228
  • Tomáš Řezník, Petr Kubíek, Lukáš Herman, Tomáš Pavelka, Šimon Leitgeb, Martina Klocová, Filip Leitner, 2020. Visualizations of Uncertainties in Precision Agriculture: Lessons Learned from Farm Machinery. Applied Sciences, 10(17), 6132; DOI 10.3390/app10176132. https://www.mdpi.com/2076-3417/10/17/6132/htm
  • Tomáš Řezník, Tomáš Pavelka, Lukáš Herman, Vojtěch Lukas, Petr Širůček, Šimon Leitgeb, and Filip Leitner 2020. Prediction of Yield Productivity Zones from Landsat 8 and Sentinel-2A/B and Their Evaluation Using Farm Machinery Measurements. https://www.mdpi.com/2072-4292/12/12/1917/htm
  • Xu X Y, Xu D Y, Chen S C, etc. Rapid determination of soil class bases on Visible-Near Infrared, Mid-Infrared spectroscopy and data fusion. Remote Sensing. 2020, 12, 1512. https://www.mdpi.com/2072-4292/12/9/1512
  • Chapter entitled “Interpolation of Data Measured by Field Harvesters: Deployment, Comparison and Verification” in the book “Environmental Software Systems. Data Science in Action 13th IFIP WG 5.11 International Symposium, ISESS 2020, Wageningen, The Netherlands, February 5–7, 2020, Proceedings”, published by Springer. https://link.springer.com/chapter/10.1007/978-3-030-39815-6_25
  • Song XD, et al. Paleotopography continues to drive surface to deep-layer interactions in a subtropical Critical Zone Observatory. Journal of Applied Geophysics, 2020, 175:103987. https://doi.org/10.1016/j.jappgeo.2020.103987
  • Song XD, et al. Can pedotransfer functions based on environmental variables improve soil total nutrient mapping at a regional scale? Soil and Tillage Research, 2020, 202:104672. https://doi.org/10.1016/j.still.2020.104672
  • Palma R., Janiak B., Reznik T., Schleidt K., Kozel, J., De Sousa L., Egmond F., Mouazen A. M., Moshou, D. (2020) Global Soil Information System (GloSIS) Ontology. SIEUSOIL project. http://w3id.org/glosis/model
  • Yang Qijun, et al. Advancement and Revelation of the Research on Soil Quality Assessment on Large Spatial Scales. Acta Pedologica Sinica, 2020, 57(3): 565-578 (in Chinese). http://dx.doi.org/10.11766/trxb201908120364

2019

  • Soothar, R. K., Zhang, W., Zhang, Y., Tankari, M., Mirjat, U., & Wang, Y. (2019). Evaluating the performance of SALTMED model under alternate irrigation using saline and fresh water strategies to winter wheat in the North China Plain. Environmental science and pollution research international, 26(33), 34499–34509. https://doi.org/10.1007/s11356-019-06540-w.
  • Feng Liu, Gan-Lin Zhang, Xiaodong Song, Decheng Li, Yuguo Zhao, Jinling Yang, Huayong Wu, Fei Yang, High-resolution and three-dimensional mapping of soil texture of China, Geoderma, Volume 361, 2020, 114061, ISSN 0016-7061, https://doi.org/10.1016/j.geoderma.2019.114061.
  • Zhao Rui, et al. Soil Health Evaluation at a County level Based on Ecosystem Service Function. Chinese Journal of Soil Science, 2020 51(2): 269-279 (in Chinese).
  • Řezník, T.; Pavelka, T.; Herman, L.; Leitgeb, Š.; Lukas, V.; Širůček, P. Deployment and Verifications of the Spatial Filtering of Data Measured by Field Harvesters and Methods of Their Interpolation: Czech Cereal Fields between 2014 and 2018. Sensors 2019, 19, 4879. https://www.mdpi.com/1424-8220/19/22/4879
  • Řezník, T., Konečný, M., and Charvát, K.: Innovative Geospatial and Cartographic Approaches to Identification, Analysis, and Visualisation of Land Degradation, Abstr. Int. Cartogr. Assoc., 1, 312, 2019. https://doi.org/10.5194/ica-abs-1-312-2019
  • Wu Ke-Ning, et al. Soil Quality ad Functions: from Science to Experiences – Review of the Wageningen Soil Conference 2019. Chinese Journal of Soil Science, 2020 51(1): 241-244 (in Chinese).
  • Nora Szigeti, Imre Berki, Andrea Vityi, Danile Winkler, Ecological role of different habitats in soil-relates biodiversity in an agroforestry landscape.
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