PMID- 35501443
OWN - NLM
STAT- MEDLINE
DCOM- 20220923
LR  - 20220923
IS  - 1614-7499 (Electronic)
IS  - 0944-1344 (Linking)
VI  - 29
IP  - 44
DP  - 2022 Sep
TI  - A spatial directivity-based sensitivity analysis to farmland quality evaluation 
      in arid areas.
PG  - 66359-66372
LID - 10.1007/s11356-022-20531-4 [doi]
AB  - Multi-criteria decision-making (MCDM) is an important means for evaluating 
      resources and environment, and sensitivity analysis can enhance understand the 
      robustness of evaluation results. Spatial visualization has been used in 
      sensitivity analysis of MCDM, but the sensitivity results are still generally 
      summarized by presenting traditional statistical measurements that omit the 
      spatial information. To address this issue, this paper proposed a novel spatially 
      measurement approach of sensitivity analysis by introducing the spatial 
      barycenter model (SBM), which overcame the limitations of existing statistical 
      methods and provided the spatial directivity of uncertainty for the MCDM results. 
      According to our proposed method and its application in farmland quality 
      evaluation (FQE) in an arid area of China, the mean of the absolute average 
      change rate (MACR) and the SBM were applied to test the sensitivity of farmland 
      quality to different evaluation factors from both numerical and spatial 
      perspectives. From the numerical perspective, the soil organic matter and 
      irrigation capacity were the most sensitive factors determined by the MACR. From 
      the spatial perspective, the >/=10  degrees C accumulated temperature (AT) and 
      precipitation were the most sensitive factors measured by the SBM. Based on the 
      SBM, the spatial configuration of farmland quality index was most sensitive to 
      increase of AT in a northwesterly direction. Calculating the SBM is 
      computationally inexpensive and provides a straightforward indication of spatial 
      direction for the changes of FQE results with changes of parameters. This means 
      it can provide improved understandings and new insights into the comprehensive 
      measurement of sensitivity analysis and agricultural production layout.
CI  - (c) 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, 
      part of Springer Nature.
FAU - Li, Dajing
AU  - Li D
AD  - Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic 
      Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 
      100101, China.
AD  - University of Chinese Academy of Sciences, Beijing, 100049, China.
FAU - Zhang, Hongqi
AU  - Zhang H
AD  - Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic 
      Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 
      100101, China.
FAU - Xu, Erqi
AU  - Xu E
AD  - Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic 
      Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 
      100101, China. xueq@igsnrr.ac.cn.
LA  - eng
PT  - Journal Article
DEP - 20220502
PL  - Germany
TA  - Environ Sci Pollut Res Int
JT  - Environmental science and pollution research international
JID - 9441769
RN  - 0 (Soil)
SB  - IM
MH  - *Agriculture
MH  - China
MH  - Farms
MH  - *Soil
OTO - NOTNLM
OT  - Arid area
OT  - Farmland protection
OT  - Farmland quality evaluation
OT  - Multi-criteria decision-making
OT  - Sensitivity analysis
EDAT- 2022/05/03 06:00
MHDA- 2022/09/24 06:00
CRDT- 2022/05/02 23:21
PHST- 2021/12/21 00:00 [received]
PHST- 2022/04/26 00:00 [accepted]
PHST- 2022/05/03 06:00 [pubmed]
PHST- 2022/09/24 06:00 [medline]
PHST- 2022/05/02 23:21 [entrez]
AID - 10.1007/s11356-022-20531-4 [pii]
AID - 10.1007/s11356-022-20531-4 [doi]
PST - ppublish
SO  - Environ Sci Pollut Res Int. 2022 Sep;29(44):66359-66372. doi: 
      10.1007/s11356-022-20531-4. Epub 2022 May 2.