IGSNRR OpenIR
Dynamic Recommendation of Substitute Locations for Inaccessible Soil Samples during Field Sampling Campaign
Zhao, Fang-He1,2; Qin, Cheng-Zhi1,2,3; Wei, Teng-Fei4; Ma, Tian-Wu3,4,5; Qi, Feng6; Liu, Jun-Zhi3,4,5; Zhu, A-Xing1,2,3,4,5,7
2019-03-04
Source PublicationISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION
ISSN2220-9964
Volume8Issue:3Pages:19
Corresponding AuthorQin, Cheng-Zhi(qincz@lreis.ac.cn)
AbstractField sampling is an important way of collecting soil information for the modeling and evaluation steps during digital soil mapping (DSM). However, some predesigned samples may not be accessible in the field due to natural or anthropogenic reasons. Simply abandoning the inaccessible samples or casually selecting substitutes from other locations may affect the quality of the corresponding DSM. To address this issue, we propose a new method of dynamically recommending substitute locations for inaccessible samples, which was implemented in a prototype system on a smart phone platform. The proposed method takes into concern the original sampling strategy and recommends substitute sample locations based on a measure of suitability index. The suitability index is calculated to incorporate a substitutive degree as well as the sampling cost involved. The substitutive degree depicts to what extent a substitute location may replace the original sample in the context of soil mapping, while the sampling cost characterizes the travel expense to the substitute location following the overall fieldwork route arrangements. The proposed method currently supports four commonly used sampling strategies, i.e., simple random sampling, stratified random sampling, grid sampling, and purposive sampling based on environmental similarity. Two substitute sampling scenarios, instant sampling and subsequent sampling, are considered by the proposed method, to adapt to surveyors' actual field sampling route arrangements when estimating the accessibility and sampling cost of potential substitute locations. Monte Carlo simulation experiments in a study area (about 5800 km(2)) located in Anhui province of China were conducted to use the proposed method to recommend substitute locations for two modeling sample sets designed based on purposive sampling strategy and stratified random sampling strategy respectively (59 points for each set) from other 224 previously obtained samples. Experimental results evaluated based on 57 independent evaluation samples showed that the proposed method was able to recommend substitute locations without affecting the performance of DSM, when less than 10% samples were replaced by substitute samples. A subsequent sampling scenario was revealed to incur lower sampling cost than an instant sampling scenario.
Keywordsoil sampling substitute locations sampling cost environmental similarity digital soil mapping
DOI10.3390/ijgi8030127
WOS KeywordORGANIC-MATTER CONCENTRATION ; DESIGN ; DENSITY ; REGION ; SCALE
Indexed BySCI
Language英语
Funding ProjectNational Natural Science Foundation of China[41431177] ; National Natural Science Foundation of China[41871300] ; Innovation Project of LREIS[O88RA20CYA] ; PAPD ; Outstanding Innovation Team in Colleges and Universities in Jiangsu Province
Funding OrganizationNational Natural Science Foundation of China ; Innovation Project of LREIS ; PAPD ; Outstanding Innovation Team in Colleges and Universities in Jiangsu Province
WOS Research AreaPhysical Geography ; Remote Sensing
WOS SubjectGeography, Physical ; Remote Sensing
WOS IDWOS:000464224200001
PublisherMDPI
Citation statistics
Document Type期刊论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/48136
Collection中国科学院地理科学与资源研究所
Corresponding AuthorQin, Cheng-Zhi
Affiliation1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China
2.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100049, Peoples R China
3.Jiangsu Ctr Collaborat Innovat Geog Informat Reso, Nanjing 210097, Jiangsu, Peoples R China
4.Nanjing Normal Univ, Minist Educ, Key Lab Virtual Geog Environm, Nanjing 210023, Jiangsu, Peoples R China
5.State Key Lab Cultivat Base Geog Environm Evolut, Nanjing 210023, Jiangsu, Peoples R China
6.Kean Univ, Sch Environm & Sustainabil Sci, 1000 Morris Ave, Union, NJ 07083 USA
7.Univ Wisconsin, Dept Geog, Madison, WI 53706 USA
Recommended Citation
GB/T 7714
Zhao, Fang-He,Qin, Cheng-Zhi,Wei, Teng-Fei,et al. Dynamic Recommendation of Substitute Locations for Inaccessible Soil Samples during Field Sampling Campaign[J]. ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION,2019,8(3):19.
APA Zhao, Fang-He.,Qin, Cheng-Zhi.,Wei, Teng-Fei.,Ma, Tian-Wu.,Qi, Feng.,...&Zhu, A-Xing.(2019).Dynamic Recommendation of Substitute Locations for Inaccessible Soil Samples during Field Sampling Campaign.ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION,8(3),19.
MLA Zhao, Fang-He,et al."Dynamic Recommendation of Substitute Locations for Inaccessible Soil Samples during Field Sampling Campaign".ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION 8.3(2019):19.
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