A spatial assessment of land suitability for maize farming in Kenya

Wanyama, Dan; Mighty, Mario; Sim, Sunhui; Koti, Francis T.

doi:10.1080/10106049.2019.1648564

Cited by 24 publications

(15 citation statements)

References 22 publications

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“…Climate change continues to affect economies in most developing nations, especially those relying heavily on natural processes for their livelihoods. Agriculture remains the backbone of many of these nations [76][77][78][79][80][81][82], yet agriculture's vulnerability to climate change effects cannot be contested. Climate-related natural hazards, including extensive flooding, extended droughts [83], landslides [28] among others, have significantly impacted agricultural production and endangered lives.…”

Section: Precipitation and Vegetation Change In The Meementioning

confidence: 99%

Persistent Vegetation Greening and Browning Trends Related to Natural and Human Activities in the Mount Elgon Ecosystem

2020

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Many developing nations are facing severe food insecurity partly because of their dependence on rainfed agriculture. Climate variability threatens agriculture-based community livelihoods. With booming population growth, agricultural land expands, and natural resource extraction increases, leading to changes in land use and land cover characterized by persistent vegetation greening and browning. This can modify local climate variability due to changing land–atmosphere interactions. Yet, for landscapes with significant interannual variability, such as the Mount Elgon ecosystem in Kenya and Uganda, characterizing these changes is a difficult task and more robust methods have been recommended. The current study combined trend (Mann–Kendall and Sen’s slope) and breakpoint (bfast) analysis methods to comprehensively examine recent vegetation greening and browning in Mount Elgon at multiple time scales. The study used both Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) and Climate Hazards group Infrared Precipitation with Stations (CHIRPS) data and attempted to disentangle nature- versus human-driven vegetation greening and browning. Inferences from a 2019 field study were valuable in explaining some of the observed patterns. The results indicate that Mount Elgon vegetation is highly variable with both greening and browning observable at all time scales. Mann–Kendall and Sen’s slope revealed major changes (including deforestation and reforestation), while bfast detected most of the subtle vegetation changes (such as vegetation degradation), especially in the savanna and grasslands in the northeastern parts of Mount Elgon. Precipitation in the area had significantly changed (increased) in the post-2000 era than before, particularly in 2006–2010, thus influencing greening and browning during this period. The greenness–precipitation relationship was weak in other periods. The integration of Mann–Kendall and bfast proved useful in comprehensively characterizing vegetation greenness. Such a comprehensive description of Mount Elgon vegetation dynamics is an important first step to instigate policy changes for simultaneously conserving the environment and improving livelihoods that are dependent on it.

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Section: Precipitation and Vegetation Change In The Meementioning

confidence: 99%

Persistent Vegetation Greening and Browning Trends Related to Natural and Human Activities in the Mount Elgon Ecosystem

2020

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“…Topographic, climate, soil, and property ratings were developed to integrate a numerical rating scale ranging between 1 and 9. As a result, participatory objective values were assigned to various classes of individual themes, based on the degree of effect of individual categories on the Eragrostis tef Zucc and Hordeum Vulgare L potential crop suitability analysis of the area as suggested [ 16 , 24 , 32 , 39 ]. The spatial decision support system was produced based on the influence percentage on selected agricultural crops' potential from the reconciled field points of view of agronomists, agro-ecologists, community, agricultural, and natural resource management, the condition and nature of the study area, and a review of literature analysis.…”

Section: Discussionmentioning

confidence: 99%

“…Yet the capacity of available resources and technologies to satisfy the demands of this growing population for food and other agricultural commodities remains uncertain in Sub-Saharan Africa (SSA). In the present situation, the agriculture sector in this region is also facing thoughtful challenges due to the aridity of the climate and inappropriate utilization of cultivation [ 15 , 16 ]. The United Nations has estimated that urbanization in SSA has soared from 15% in 1940 to 40% in 2010 and is projected to reach 60% in 2050.…”

Section: Introductionmentioning

confidence: 99%

Modeling Eragrostis tef Zucc and Hordeum vulgare L cropland in response to food insecurity in the Southwestern parts of Ethiopia

Abebe¹,

Deribew²,

Alemu³

et al. 2023

Heliyon

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“…The climate plays a very important role in agricultural production, and its influence is mainly reflected in terms of heat, moisture, and sunshine. In terms of heat, the average temperature in the crop growth season determines the growing period and ripening of crops [13]. The amount of precipitation affects crop growth and yields [10].…”

Section: Climate Characteristicsmentioning

confidence: 99%

“…Cli-matic factors have large variability at a regional scale, and different climatic conditions determine land use to a large extent, which is a prerequisite for agricultural production [10,11]. These have been demonstrated in evaluation studies of tobacco areas in Shandong Province (1.57 million ha), China [12], and maize areas in Kenya (58.44 million ha) [13]. These study areas include many provinces and cities, as well as a number of different climatic conditions.…”

Section: Introductionmentioning

confidence: 96%

Evaluation of Agricultural Land Suitability Based on RS, AHP, and MEA: A Case Study in Jilin Province, China

Han

Chen

et al. 2021

Agriculture

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The suitability evaluation of agricultural land at the regional scale is of great significance for protecting land and water resources and building sustainable agricultural systems. Based on climate, soil, topographical, and surface water resources, land suitability index (LSI) data for maize, rice, and soybeans are established using an analytical hierarchy process and matter element analysis (AHP–MEA) model in Jilin Province, China. The results show that there is a significant positive linear correlation between the LSI and the measured yield, which indicates that the model has an ideal effect and certain reference and extension significance. The main limiting factors for maize and soybean planting are pH, total nitrogen (TN), available phosphorus (AP), and soil texture, while water shortage limits rice planting. Different spatial structure optimization schemes for planting are established using the LSI and measured yield, along with economic indices. This study shows that the scheme that integrates policy and cost can make full use of land and water resources and promote the economic growth of agriculture. After optimization, the planting areas of maize, rice, and soybeans were 7.22, 2.44, and 0.71 million ha, respectively, representing an increase of 15.71 billion yuan over the agricultural GDP for the existing planting structure. It is expected that this study will provide a basis for follow-up studies on crop cultivation suitability.

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A spatial assessment of land suitability for maize farming in Kenya

Cited by 24 publications

References 22 publications

Persistent Vegetation Greening and Browning Trends Related to Natural and Human Activities in the Mount Elgon Ecosystem

Persistent Vegetation Greening and Browning Trends Related to Natural and Human Activities in the Mount Elgon Ecosystem

Modeling Eragrostis tef Zucc and Hordeum vulgare L cropland in response to food insecurity in the Southwestern parts of Ethiopia

Evaluation of Agricultural Land Suitability Based on RS, AHP, and MEA: A Case Study in Jilin Province, China

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