Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2021 Jan 28;10(2):125.
doi: 10.3390/land10020125.

Evaluation of Land Suitability Methods with Reference to Neglected and Underutilised Crop Species: A Scoping Review

Hillary Mugiyo  1 , Vimbayi G P Chimonyo  1 , Mbulisi Sibanda  1   2 , Richard Kunz  3 , Cecilia R Masemola  1 , Albert T Modi  1 , Tafadzwanashe Mabhaudhi  1   3
Affiliations

Evaluation of Land Suitability Methods with Reference to Neglected and Underutilised Crop Species: A Scoping Review

Hillary Mugiyo et al. Land (Basel). .

Abstract

In agriculture, land use and land classification address questions such as "where", "why" and "when" a particular crop is grown within a particular agroecology. To date, there are several land suitability analysis (LSA) methods, but there is no consensus on the best method for crop suitability analysis. We conducted a scoping review to evaluate methodological strategies for LSA. Secondary to this, we assessed which of these would be suitable for neglected and underutilised crop species (NUS). The review classified LSA methods reported in articles as traditional (26.6%) and modern (63.4%). Modern approaches, including multi-criteria decision-making (MCDM) methods such as analytical hierarchy process (AHP) (14.9%) and fuzzy methods (12.9%); crop simulation models (9.9%) and machine learning related methods (25.7%) are gaining popularity over traditional methods. The MCDM methods, namely AHP and fuzzy, are commonly applied to LSA while crop models and machine learning related methods are gaining popularity. A total of 67 parameters from climatic, hydrology, soil, socio-economic and landscape properties are essential in LSA. Unavailability and the inclusion of categorical datasets from social sources is a challenge. Using big data and Internet of Things (IoT) improves the accuracy and reliability of LSA methods. The review expects to provide researchers and decision-makers with the most robust methods and standard parameters required in developing LSA for NUS. Qualitative and quantitative approaches must be integrated into unique hybrid land evaluation systems to improve LSA.

Keywords: MCDM; NUS; hybrid land evaluation systems; land management; machine learning.

PubMed Disclaimer

Conflict of interest statement

Conflicts of Interest: The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
(a) The percentage distribution of land suitability methods published from 1993 to 2019. (Analytical hierarchy process (AHP), Crop Simulation Models (CSM), Machine learning method (ML/MLM), traditional method (TM)). (b) The hybrid land evaluation systems, the combination was selected from land suitability methods published from 1993 to 2019. (Analytical hierarchy process (AHP), crop simulation models (CSM), machine learning method (MLM), traditional method (TM)).
Figure 2
Figure 2. MCDM classification split between MADM and MODM.
See this image and copyright information in PMC

References

    1. James H. Population, Development, and the Environment: Challenges to Achieving the Sustainable Development Goals in the Asia Pacific. London, UK: Palgrave Macmillan; 2019.
    1. UN DESA. World Population Projected to Reach 98 Billion in 2050, and 112 Billion in 2100. Department of Economic and Social Affairs; [accessed on 26 January 2021]. Available online: https://www.un.org/development/desa/en/news/population/world-population-....
    1. Onyutha C. African food insecurity in a changing climate: The roles of science and policy. Food Energy Secur. 2019;8:e00160. doi: 10.1002/fes3.160. - DOI
    1. Duku C, Zwart SJ, Van Bussel LG, Hein L. Quantifying trade-offs between future yield levels, food availability and forest and woodland conservation in Benin. Sci Total Environ. 2018:1581–1589. doi: 10.1016/j.scitotenv.2017.06.115. - DOI - PubMed
    1. Toulmin C. Securing land and property rights in sub-Saharan Africa: The role of local institutions. Land Use Policy. 2009;26:10–19. doi: 10.1016/j.landusepol.2008.07.006. - DOI

Publication types

LinkOut - more resources