Citation: | Zhang Surong, Wang Daming, Yang Junquan, Zhang Jing, Wang Jianhua, Zhang Donghui, Tong Yunxiao, Jin Zhibin, Chen Donglei. 2024. Quantitative remote sensing inversion of elements in soils: Advances in research and future prospects[J]. Geology in China, 51(5): 1664−1675. DOI: 10.12029/gc20231011002 |
This paper is the result of agricultural geological survey engineering.
Soil quality is closely related to human activities. Given that traditional methods fall short in achieving the large−scale dynamic monitoring of soil quality, the quantitative inversion of elements in soils using hyperspectral remote sensing, which proves macroscopic, real−time, in−situ, and fast, has emerged as a hot topic and challenge in the field of remote sensing application.
This paper explores three methods for quantitative remote sensing inversion of elements in soils: direct quantitative inversion, indirect quantitative inversion using correlations among the elements, and quantitative inversion based on plant spectra. Specifically, this paper systematically summarizes the primary principles, advantages, and current research status of these methods and proposes future trends in relevant fields from the perspective of interdisciplinary integration.
The commonly used methods for the quantitative inversion of elements in soils face challenges when applied on a large scale. Among these, the indirect inversion based on the spectra of plant leaves or canopies is considered the most reliable. Achievements in ecological geochemistry enable the identification of the unique spectral effects of target elements in different plants, which assists in determining the principle of the plant spectrum−based quantitative inversion of elements in soils.
More in−depth research based on big data mining and the physicochemical properties of soils while promoting interdisciplinary integration represents a favorable direction for achieving breakthroughs in wide−area monitoring technology for elements in soils.
[1] |
Ali W, Mao K, Zhang H, Junaid M, Xu N, Rasool A, Feng X B, Yang Z G. 2020. Comprehensive review of the basic chemical behaviours, sources, processes, and endpoints of trace element contamination in paddy soil−rice systems in rice−growing countries[J]. Journal of Hazardous Materials, 397: 122720.
|
[2] |
Allbed A, Kumar L. 2013. Soil salinity mapping and monitoring in arid and semi−arid regions using remote sensing technology: A review[J]. Advances in Remote Sensing, 2(4): 373−385.
|
[3] |
Bouaziz M, Matschullat J, Gloaguen R. 2011. Improved remote sensing detection of soil salinity from a semi−arid climate in Northeast Brazil[J]. Comptes Rendus − Géoscience, 343(11/12): 795−803.
|
[4] |
Carra J B, Fabris M, Dieckow J, Brito O R, Vendrame P R S, Macedo D S T L. 2019. Near−infrared spectroscopy coupled with chemometrics tools: A rapid and non−destructive alternative on soil evaluation[J]. Communications in Soil Science and Plant Analysis, 50(4): 421−434.
|
[5] |
Chen Xingfu. 1994. Symptoms of plant nutrient deficiency[J]. Anhui Forestry, (6): 28(in Chinese).
|
[6] |
Cheng Yongsheng, Zhou Yao. 2021. Research progress and trend of quantitative monitoring of hyperspectral remote sensing for heavy metals in soil[J]. The Chinese Journal of Nonferrous Metals, 31(11): 3450−3467 (in Chinese with English abstract).
|
[7] |
Confalonieri M, Fornasier F, Ursino A, Boccardi F, Pintus B, Odoardi M. 2001. The potential of near infrared reflectance spectroscopy as a tool for the chemical characterisation of agricultural soils[J]. Journal of Near Infrared Spectroscopy, 9(1): 1385−1388.
|
[8] |
Cong Yingxin. 2019. Analysis of the harm of excessive trace elements on crops in the Western Liaoning Region[J]. Modern Rural Science and Technology, (2): 31(in Chinese).
|
[9] |
Ding Qiuhong, Tang Tao, Wang Lingguang, Chen Shuwang, Xing Dehe. 2021. Geochemical study on selenium in rock−soil−plant in northern Liaoning Province[J]. Geology and Resources, 30(5): 570−576,636 (in Chinese with English abstract).
|
[10] |
Feng Minling, Li Shengan, Liu Mingyang, Ye Shaomei, Xiao Dongmei, Mo Xuehui. 2022. Study on the determination of residual distribution of multiple metal elements in rice[J]. Agriculture and Technology, 42(1): 24−27 (in Chinese).
|
[11] |
Fu P J, Yang K M, Meng F, Zhang W, Cui Y, Feng F S, Yao G B. 2022. A new three−band spectral and metal element index for estimating soil arsenic content around the mining area[J]. Process Safety and Environmental Protection, 157: 27−36.
|
[12] |
Garajeh M K, Malakyar F, Weng Q, Feizizadeh B, Lake T. 2021. An automated deep learning convolutional neural network algorithm applied for soil salinity distribution mapping in Lake Urmia, Iran[J]. Science of the Total Environment, 778: 146253.
|
[13] |
Gholizadeh A, Saberioon M, Ben−Dor E, Boruvka L. 2018. Monitoring of selected soil contaminants using proximal and remote sensing techniques: Background, state−of−the−art and future perspectives[J]. Critical Reviews in Environmental Science and Technology, 48(3): 243−278.
|
[14] |
Gu Zhoulei, Xu Xiaohui, An Haibo. 2021. Study on the enrichment of nickel, copper, and zinc elements in soil by corn crops[J]. Agriculture and Technology, 41(23): 19−22 (in Chinese).
|
[15] |
Guo Xuefei, Cao Ying, Jiao Runcheng, Nan Yun. 2020. Overview of hyperspectral remote sensing monitoring method of soil heavy metals[J]. Urban Geology, 15(3): 320−326 (in Chinese with English abstract).
|
[16] |
Hong Tao, Kong Xiangsheng, Yue Xiangfei. 2022. Translocation and accumulation of selenium and heavy metals in paddy soil−rice plant system in Danzhai County, Guizhou Province[J]. Earth and Environment, 50(1): 58−65 (in Chinese with English abstract).
|
[17] |
Hunt G R. 1979. Near−infrared (1.3−2.4 mm) spectra of alteration minerals − potential for use in remote sensing[J]. Geophysics, 44(12): 1974−1986.
|
[18] |
Ji W J, Shi Z, Huang J Y, Li S. 2014. In situ measurement of some soil properties in paddy soil using visible and near−infrared spectroscopy[J]. Plos One, 9(8): e105708.
|
[19] |
Jiang Zonghao. 2020. Effect of Different Selenium Contents in the Soil on Yield−related Traits and Selenium Uptake of Wheat[D]. Xi’an: College of Agronomy Northwest A&F University, 1−54 (in Chinese with English abstract).
|
[20] |
Khanam R, Kumar A, Nayak A, Shahid M, Tripathi R, Vijayakumar S, Bhaduri D, Kumar U, Mohanty S, Panneerselvam P, Chatterjee D, Satapathy B, Pathak H. 2020. Metal(loid)s (As, Hg, Se, Pb and Cd) in paddy soil: Bioavailability and potential risk to human health[J]. Science of the Total Environment, 699: 134330.
|
[21] |
Khosravi V, Ardejani F D, Yousefi S, Aryafar A. 2018. Monitoring soil lead and zinc contents via combination of spectroscopy with extreme learning machine and other data mining methods[J]. Geoderma, 318: 29−41.
|
[22] |
Lai Shuya, Dong Qiuyao, Song Chao, Yang Zhenjing, Yan Mingjiang. 2023. Distribution characteristics and health risk assessment of vanadium and cobalt in surface soil of the Tongbai−Biyang Area, Henan Province[J]. Geology in China, 50(1): 222−236 (in Chinese with English abstract).
|
[23] |
Liu Changbing, Li Weinong, Sun Linlin. 2022. The mechanism and countermeasures of sugar beet deficiency in Xinjiang[J]. New Agriculture, (6): 37−38 (in Chinese).
|
[24] |
Liu Yanping, Luo Qing, Cheng Hefa. 2020. Application and development of hyperspectral remote sensing technology to determine the heavy metal content in soil[J]. Journal of Agro−Environment Science, 39(12): 2699−2709 (in Chinese with English abstract).
|
[25] |
Luo Junli, Liu Hongjun, Wang Li. 1998. The relationship between plant diseases and nutrient deficiency[J]. Henan Agriculture, (11): 15(in Chinese).
|
[26] |
Mei Zhong, Wang Zhixue, Mei Sha, Jiang Zhoulei, Mei Shufang, Shu Xiaoli, Wu Dianxing. 2016. Study on rice high in zinc content[J]. Journal of Nuclear Agricultural Sciences, 30(8): 1515−1523 (in Chinese with English abstract).
|
[27] |
Mirzaei M, Verrelst J, Marofi S, Abbasi M, Azadi H. 2019. Eco−friendly estimation of heavy metal contents in grapevine foliage using in−field hyperspectral data and multivariate analysis[J]. Remote Sensing, 11(23): 2731.
|
[28] |
Moros J, Vallejuelo S F D, Gredilla A, Diego D A, Madariaga J M, Garrigues S, Guardia M D L. 2009. Use of reflectance infrared spectroscopy for monitoring the metal content of the estuarine sediments of the Nerbioi−Ibaizabal River (Metropolitan Bilbao, Bay of Biscay, Basque Country)[J]. Environmental Science & Technology, 43(24): 9314−9320.
|
[29] |
Ouyang Yuan, Liu Hong, Li Guangming, Ma Dongfang, Zhang Linkui, Huang Hanxiao, Zhang Jinghua, Zhang Tengjiao, Liu Xiao, Zhao Yinbing, LiFu. 2023. Mineral search prediction based on Random Forest algorithm−A case study on porphyry−epithermal copper polymetallic deposits in the western Gangdise metallogenic belt[J]. Geology in China, 50(2): 303−330 (in Chinese with English abstract).
|
[30] |
Qiao B Y, He X K, Liu Y J, Zhang H, Zhang L T, Liu L M, Reineke A, Liu W X, Müller J. 2022. Maize characteristics estimation and classification by spectral data under two soil phosphorus levels[J]. Remote Sensing, 14(3): 493.
|
[31] |
Qu Y H, Jiao S H, Liu S H, Zhu Y Q. 2015. Retrieval of copper pollution information from hyperspectral satellite data in a vegetation cover mining area[J]. Spectroscopy and Spectral Analysis, 35(11): 3176−3181.
|
[32] |
Rahman M A, Hasegawa H, Rahman M M, Islam M, Tasmen A. 2007. Effect of arsenic on photosynthesis, growth and yield of five widely cultivated rice (Oryza sativa L.) varieties in Bangladesh[J]. Chemosphere, 67(6): 1072−1079.
|
[33] |
Shen Q, Xia K, Zhang S , Kong C, Hu Q, Yang S. 2019. Hyperspectral indirect inversion of heavy−metal copper in reclaimed soil of iron ore area[J]. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 222: 117191.
|
[34] |
Shi T Z, Liu H Z, Chen Y Y, Wang J J, Wu G F. 2016. Estimation of arsenic in agricultural soils using hyperspectral vegetation indices of rice[J]. Journal of Hazardous Materials, 308: 243−252.
|
[35] |
Sun Guifang, Yang Guangsui. 2002. Research progress on zinc in soil plant system[J]. Journal of South China University of Tropical Agriculture, 8(2): 22−30 (in Chinese).
|
[36] |
Tong Qingxi, Zhang Bing, Zhang Lifu. 2016. Current progress of hyperspectral remote sensing in China[J]. Journal of Remote Sensing, 20(5): 689−707 (in Chinese with English abstract).
|
[37] |
Tong Qingxi, Zhang Bing, Zheng Lanfen. 2006. Hyperspectral Remote Sensing—Principles, Techniques and Applications[M]. Beijing: Higher Education Press, 18−25(in Chinese).
|
[38] |
Tu Yexin, Fei Teng. 2016. From vegetation hyperspectral remote sensing to the diagnosis of soil heavy metal pollution[J]. Hubei Agricultural Sciences, 55(6): 1361−1368 (in Chinese with English abstract).
|
[39] |
Wang C, Feng M C, Yang W D, Ding G W, Wang H Q, Li Z H, Sun H, Shi C C. 2016. Use of spectral character to evaluate soil organic matter[J]. Soil Science Society of America Journal, 80(4): 1078−1088.
|
[40] |
Wang Changyu, Zhang Surong, Liu Jihong, Xing Yi, Yang Junquan. 2019. Evaluation of the characteristic land resources with Zn, Se and their ecological effects in Raoyang county of Hebei province[J]. Geological Survey and Research, 42(1): 49−56 (in Chinese with English abstract).
|
[41] |
Wang Chengchen, Tian Wen, Xiang Ping, Xu Wumei, Guan Dongxing, Ma Qiying. 2022. Mechanism of heavy metal uptake and transport in soil−rice/wheat system and regulation measures for safe production[J]. China Environmental Science, 42(2): 794−807 (in Chinese with English abstract).
|
[42] |
Wang Daming, Qin Kai, Li Zhizhong, Zhao Yingjun, Chen Weitao, Gan Yiqun. 2018. Retrieval of organic matter content in black soil based on airborne hyperspectral remote sensing data: Taking Jiansanjiang District in Heilongjiang Province as an example[J]. Earth Science, 43(6): 1−19 (in Chinese with English abstract).
|
[43] |
Wang Jianhua, Li Yang, Liang Shuneng, Sun Xiaofei. 2022. The study of land desertification recognition and extraction based on hyperspectral satellite data[J]. North China Geology, 45(4): 60−67 (in Chinese with English abstract).
|
[44] |
Wang Jianhua, Zuo Ling, Li Zhizhong, Mu Huayi, Zhou Ping, Yang Jiajia, Zhao Yingjun, Qin Kai. 2021. A detection method of trace metal elements in black soil based on hyperspectal technology: Geological implications[J]. Journal of Geomechanics, 27(3): 418−429 (in Chinese with English abstract).
|
[45] |
Wei L F, Yuan Z R, Wang Z X, Zhao L Y, Zhang Y X, Lu X Y, Cao L Q. 2020. Hyperspectral inversion of soil organic matter content based on a combined spectral index model[J]. Sensors, 20(10): 2777.
|
[46] |
Xi Xiaohuan. 2004. Eco−geochemical research and eco−geochemica evaluation[J]. Gepphycical & Geochemical Exploration, 28(1): 10−15 (in Chinese with English abstract).
|
[47] |
Xi Xiaohuan. 2005. Multi−purpose regional geochemical survey and ecogeochemistry: New direction of Quaternary research and application[J]. Quaternary Sciences, 25(3): 269−274 (in Chinese with English abstract).
|
[48] |
Xiao Hailong, Ma Yuan, Zhou Huicheng, Zhang Chengjun, Yao Yujiao, Chen Jiangang, Zhang Degang. 2022. Characteristics of soil trace elements and vegetation and their relationships in degraded alpine steppe in Sanjiangyuan region[J]. Acta Agrestia Sinica, 30(8): 1925−1933 (in Chinese with English abstract).
|
[49] |
Yang Lingyu, Gao Xiaohong, Zhang Wei, Shi Feifei, He Linhua, Jia Wei. 2016. Estimating heavy metal concentrations in topsoil from vegetation reflectance spectra of hyperion images: A case study of Yushu County, Qinghai, China[J]. Chinese Journal of Applied Ecology, 27(6): 1775−1784 (in Chinese with English abstract).
|
[50] |
Yang Zhongfang, Xi Xiaohuan, Cheng Hangxin, Zhou Guohua, Chen Deyou, Zhang Jianxin, Yuan Xiaojun, Fen Haiyan, Chen Jiawei, Liu Aihua, Tang Qifeng, Yu Tao. 2005. The core and counter measures of regional ecological geochemical assessment[J]. Quaternary Sciences, 25(3): 275−284 (in Chinese with English abstract).
|
[51] |
Yu H, Kong B, Wang G X, Du R X, Qie G P. 2018. Prediction of soil properties using a hyperspectral remote sensing method[J]. Archives of Agronomy and Soil Science, 64(4): 546−559.
|
[52] |
Zeng Huizhen, Xu Qingsheng, Xu Jiansheng, Liu Bangzhen, Gao Huayan, Wang Xinhua. 2013. Identification and correction of plant deficiency disorders[J]. Modern Horticulture, (17): 59(in Chinese).
|
[53] |
Zhang Chengming, Zhou Xinbin, Gao Axiang. 2017. Uptake and accumulation of selenium and iron coating rice root at different growth stages[J]. Acta Pedologica Sinaca, 54(3): 693−702 (in Chinese with English abstract).
|
[54] |
Zhang Dong, Li Yongchun, Su Rilige, Yuan Guoli, Tai Surigala, Wang Yongliang, Chen Guodong, Zhou Wenhui, Du Yuchunzi, Yang Jianyu. 2023. Ecological health risk assessment of soil heavy metals in Wuyuan County, Inner Mongolia[J]. Geology in China, 51(1): 248−263 (in Chinese with English abstract).
|
[55] |
Zhang Donghui, Zhao Yingjun, Zhao Ningbo, Qin Kai, Pei Chengkai, Yang Yuechao. 2019. A new indirect extraction method for selenium content in black soil from hyperspectral data[J]. Spectroscopy and Spectral Analysis, 39(7): 2237−2243 (in Chinese with English abstract).
|
[56] |
Zhang Jiandong, Wang Li, He Litao, Liu Xuejun, Liu Limin, Luo Kunli. 2022. Distribution characteristics of selenium in rocks, soils and agricultural products of Langao[J]. Chinese Journal of Soil Science, 53(1): 195−203 (in Chinese with English abstract).
|
[57] |
Zhang Jingjing, Zhou Weihong, Zhou Mengmeng, Liu Ying, Du Xiaolong, Li Jianlong. 2018. Research status, principles and prospects of hyperspectral remote sensing monitoring of heavy metal pollution in large−scale soil[J]. Jiangsu Agricultural Sciences, 46(12): 9−13 (in Chinese).
|
[58] |
Zhang Liangpei, He Jiang, Yang Qianqian, Xiao Yi, Yuan Qiangqiang. 2022. Data−driven multi−source remote sensing data fusion: progress and challenges[J]. Acta Geodaetica et Cartographica Sinica, 51(7): 1317−1337 (in Chinese with English abstract).
|
[59] |
Zhang Lixia, Peng Jianming, Ma Jie. 2010. Study progress on nutrient deficiency of plants[J]. Chinese Agricultural Science Bulletin, 26(8): 157−163 (in Chinese with English abstract).
|
[60] |
Zhang Lizhou, Wand Dianwu, Zhang Yuming, Cheng Yisong, Li Hongjun, Hu Chunsheng. 2010. Diagnosis of N nutrient status of cornusing digital image processing technique[J]. Chinese Journal of Eco−Agriculture, 18(6): 1340−1344 (in Chinese with English abstract).
|
[61] |
Zhang Weili, Kolbe H, Zhang Renlian, Zhang Dingxiang, Bai Zhanguo, Zhang Jing, Shi Huading. 2022. Overview of soil survey works in main countries of world[J]. Scientia Agricultura Sinica, 55(18): 3565−3583 (in Chinese with English abstract).
|
[62] |
Zhao Xinna, Yang Zhongfang, Yu Tao. 2023. Review on heavy metal pollution and remediation technology in the soil of mining areas[J]. Geology in China, 50(1): 84−101 (in Chinese with English abstract).
|
[63] |
Zhou Guohua, Zeng Daoming, He Ling, Zhu Xiaoting, Sun Binbin, Bai Jinfeng, Zhou Ziyi. 2015. Eco−geochemical characteristics of the Tieguanyin Tea Gardens in Fujian Province[J]. Geology in China, 42(6): 2008−2018 (in Chinese with English abstract).
|
[64] |
Zhou Guohua. 2020. Research progress of selenium−enriched land resources and evaluation methods[J]. Rock and Mineral Analysis, 39(3): 319−336 (in Chinese with English abstract).
|
[65] |
陈兴福. 1994. 植物缺素症状[J]. 安徽林业, (6): 28.
|
[66] |
成永生, 周瑶. 2021. 土壤重金属高光谱遥感定量监测研究进展与趋势[J]. 中国有色金属学报, 31(11): 3450−3467. doi: 10.11817/j.ysxb.1004.0609.2021-42086
|
[67] |
丛迎新. 2019. 辽西地区微量元素过量对农作物的危害分析[J]. 现代农村科技, (2): 31.
|
[68] |
丁秋红, 唐韬, 王龄广, 陈树旺, 邢德和. 2021. 辽宁北部地区岩石−土壤−植物中硒元素地球化学研究[J]. 地质与资源, 30(5): 570−576,636.
|
[69] |
冯敏铃, 李盛安, 刘铭扬, 叶少媚, 肖冬梅, 莫学辉. 2022. 测定水稻中多种金属元素残留分布的研究[J]. 农业与技术, 42(1): 24−27.
|
[70] |
谷周雷, 许晓慧, 安海波. 2021. 玉米作物对土壤中镍铜锌元素富集情况的研究[J]. 农业与技术, 41(23): 19−22.
|
[71] |
郭学飞, 曹颖, 焦润成, 南赟. 2020. 土壤重金属污染高光谱遥感监测方法综述[J]. 城市地质, 15(3): 320−326.
|
[72] |
洪涛, 孔祥胜, 岳祥飞. 2022. 贵州丹寨县土壤−水稻中硒和重金属的积累及迁移特征[J]. 地球与环境, 50(1): 58−65.
|
[73] |
姜宗昊. 2020. 土壤中不同硒含量对小麦产量相关性状和硒吸收利用的影响[D]. 西安: 西北农林科技大学, 1−54.
|
[74] |
赖书雅, 董秋瑶, 宋超, 振京, 严明疆. 2023. 河南省桐柏−泌阳地区表层土壤钒和钴的分布特征及健康风险评价[J]. 中国地质, 50(1): 222−236. doi: 10.12029/gc20210611001
|
[75] |
刘长兵, 李蔚农, 孙琳琳. 2022. 新疆甜菜缺素症发生机理及应对措施[J]. 新农业, (6): 37−38. doi: 10.3969/j.issn.1002-4298.2022.6.xinny202206030
|
[76] |
刘彦平, 罗晴, 程和发. 2020. 高光谱遥感技术在土壤重金属含量测定领域的应用与发展[J]. 农业环境科学学报, 39(12): 2699−2709. doi: 10.11654/jaes.2020-0944
|
[77] |
罗俊丽, 刘红君, 王力. 1998. 植物病害与缺素的关系[J]. 河南农业, (11): 15.
|
[78] |
梅忠, 王治学, 梅沙, 蒋宙蕾, 梅淑芳, 舒小丽, 吴殿星. 2016. 高锌水稻研究进展[J]. 核农学报, 30(8): 1515−1523. doi: 10.11869/j.issn.100-8551.2016.08.1515
|
[79] |
欧阳渊, 刘洪, 李光明, 马东方, 张林奎, 黄瀚霄, 张景华, 张腾蛟, 柳潇, 赵银兵, 李富. 2023. 基于随机森林算法的找矿预测—以冈底斯成矿带西段斑岩—浅成低温热液型铜多金属矿为例[J]. 中国地质, 50(2): 303−330.
|
[80] |
屈永华, 焦思红, 刘素红, 朱叶青. 2015. 从高光谱卫星数据中提取植被覆盖区铜污染信息[J]. 光谱学与光谱分析, 35(11): 3176−3181.
|
[81] |
孙桂芳, 杨光穗. 2002. 土壤−植物系统中锌的研究进展[J]. 华南热带农业大学学报, 8(2): 22−30.
|
[82] |
童庆禧, 张兵, 张立福. 2016. 中国高光谱遥感的前沿进展[J]. 遥感学报, 20(5): 689−707.
|
[83] |
童庆禧, 张兵, 郑兰芬. 2006. 高光谱遥感−原理、技术与应用[M]. 北京: 高等教育出版社, 18−25.
|
[84] |
涂晔昕, 费腾. 2016. 从植被高光谱遥感到土壤重金属污染诊断的研究进展[J]. 湖北农业科学, 55(6): 1361−1368.
|
[85] |
汪大明, 秦凯, 李志忠, 赵英俊, 陈伟涛, 甘义群. 2018. 基于航空高光谱遥感数据的黑土地有机质含量反演: 以黑龙江省建三江地区为例[J]. 地球科学, 43(6): 1−19.
|
[86] |
王昌宇, 张素荣, 刘继红, 邢怡, 杨俊泉. 2019. 河北省饶阳县富锌、硒特色土地及其生态效应评价[J]. 地质调查与研究, 42(1): 49−56.
|
[87] |
王成尘, 田稳, 向萍, 徐武美, 管冬兴, 马奇英. 2022. 土壤−水稻/小麦重金属吸收机制与安全调控[J]. 中国环境科学, 42(2): 794−807. doi: 10.3969/j.issn.1000-6923.2022.02.034
|
[88] |
王建华, 李阳, 梁树能, 孙小飞. 2022. 基于高光谱卫星数据的土地沙化识别及提取研究[J]. 华北地质, 45(4): 60−67.
|
[89] |
王建华, 左玲, 李志忠, 穆华一, 周萍, 杨佳佳, 赵英俊, 秦凯. 2021. 基于高光谱技术的黑土地微量金属元素探测方法及地学意义[J]. 地质力学学报, 27(3): 418−429. doi: 10.12090/j.issn.1006-6616.2021.27.03.038
|
[90] |
奚小环. 2004. 生态地球化学与生态地球化学评价[J]. 物探与化探, 28(1): 10−15.
|
[91] |
奚小环. 2005. 多目标区域地球化学调查与生态地球化学—第四纪研究与应用的新方向[J]. 第四纪研究, 25(3): 269−274. doi: 10.3321/j.issn:1001-7410.2005.03.001
|
[92] |
肖海龙, 马源, 周会程, 张成君, 姚玉娇, 陈建纲, 张德罡. 2022. 三江源退化高寒草原土壤微量元素与植被特征及其关系[J]. 草地学报, 30(8): 1925−1933.
|
[93] |
杨灵玉, 高小红, 张威, 史飞飞, 何林华, 贾伟. 2016. 基于Hyperion影像植被光谱的土壤重金属含量空间分布反演—以青海省玉树县为例[J]. 应用生态学报, 27(6): 1775−1784.
|
[94] |
杨忠芳, 奚小环, 成杭新, 周国华, 陈德友, 张建新, 袁晓军, 冯海艳, 陈家玮, 刘爱华, 汤奇峰, 余涛. 2005. 区域生态地球化学评价核心与对策[J]. 第四纪研究, 25(3): 275−284. doi: 10.3321/j.issn:1001-7410.2005.03.002
|
[95] |
曾慧珍, 许庆胜, 徐建生, 刘邦贞, 高华岩, 王信华. 2013. 植物缺素症的识别及矫正[J]. 现代园艺, (17): 59. doi: 10.3969/j.issn.1006-4958.2013.17.042
|
[96] |
张城铭, 周鑫斌, 高阿祥. 2017. 水稻不同生育期对硒吸收累积及铁膜的吸附特性[J]. 土壤学报, 54(3): 693−702. doi: 10.11766/trxb201609090340
|
[97] |
张栋, 李永春, 苏日力格, 袁国礼, 邰苏日嘎拉, 王永亮, 陈国栋, 周文辉, 杜雨春子, 杨建雨. 2023. 内蒙古五原县某地土壤重金属生态健康风险评价[J]. 中国地质, 51(1): 248−263.
|
[98] |
张东辉, 赵英俊, 赵宁博, 秦凯, 裴承凯, 杨越超. 2019. 一种间接从高光谱数据中提取黑土硒含量的新方法[J]. 光谱学与光谱分析, 39(7): 2237−2243.
|
[99] |
张建东, 王丽, 赫栗涛, 刘学军, 刘利民, 雒昆利. 2022. 岚皋县岩石、土壤和农产品中硒分布规律研究[J]. 土壤通报, 53(1): 195−203.
|
[100] |
张静静, 周卫红, 邹萌萌, 刘影, 杜小龙, 李建龙. 2018. 高光谱遥感监测大面积土壤重金属污染的研究现状、原理及展望[J]. 江苏农业科学, 46(12): 9−13.
|
[101] |
张丽霞, 彭建明, 马洁. 2010. 植物营养缺素研究进展[J]. 中国农学通报, 26(8): 157−163.
|
[102] |
张良培, 何江, 杨倩倩, 肖屹, 袁强强. 2022. 数据驱动的多源遥感信息融合研究进展[J]. 测绘学报, 51(7): 1317−1337. doi: 10.11947/j.issn.1001-1595.2022.7.chxb202207021
|
[103] |
张立周, 王殿武, 张玉铭, 程一松, 李红军, 胡春胜. 2010. 数字图像技术在夏玉米氮素营养诊断中的应用[J]. 中国生态农业学报, 18(6): 1340−1344.
|
[104] |
张维理, Kolbe H, 张认连, 张定祥, 白占国, 张晶, 师华定. 2022. 世界主要国家土壤调查工作回顾[J]. 中国农业科学, 55(18): 3565−3583. doi: 10.3864/j.issn.0578-1752.2022.18.008
|
[105] |
赵鑫娜, 杨忠芳, 余涛. 2023. 矿区土壤重金属污染及修复技术研究进展[J]. 中国地质, 50(1): 84−101. doi: 10.12029/gc20220702001
|
[106] |
周国华, 曾道明, 贺灵, 朱晓婷, 孙彬彬, 白金峰, 周子琦. 2015. 福建铁观音茶园生态地球化学特征[J]. 中国地质, 42(6): 2008−2018.
|
[107] |
周国华. 2020. 富硒土地资源研究进展与评价方法[J]. 岩矿测试, 39(3): 319−336.
|