GIS-AHP Based Suitability Assessment Model for Smallholder Coffee Plantations: A Case Study from Jember, Indonesia

3.1 Spatial model of smallholder coffee plantation areas

The spatial model of coffee plantation areas in Jember Regency was developed through spatial mapping using a visual interpretation approach that integrated land-use attributes, state-owned and privately owned plantation data, and satellite imagery to delineate coffee plantation zones. The initial mapping stage involved data separation and correction through a feature selection process. This procedure generated a spatial delineation of scattered smallholder coffee plantation areas, as illustrated in Figure 2 and Figure 3.

Figure 2. Jember Regency land cover

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Figure 3. Smallholder coffee plantations incision

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Attribute and geographic data selection and elimination were performed using satellite imagery (as described in the methodology section) to obtain the results that served as the initial area for assessing the suitability of smallholder coffee plantations. This initial step is essential to the spatial model, serving as the foundation for land suitability evaluation, as it functions as the foundational basis for suitability assessment. The process was necessary due to the unavailability of spatial data on the cultivation areas of smallholder coffee plantations. Specifically, the spatial pattern data revealed that the cultivation area of smallholder coffee plantations covered 6,393.2 ha. The resulting plantation area differs slightly from the 2025 data reported by the Central Statistics Agency of Jember Regency [24], which recorded an area of 6,382.45 ha. These discrepancies arise from variations in digitization accuracy, differences in analysis periods, conceptual definitions, and constraints applied to plantation land, data sources, and scales, mapping techniques, and the spatial extent of the analysis [25].

3.2 Analysis of suitability criteria and indicators for smallholder coffee plantations

Assessing land suitability for coffee plantations requires the identification of factors that directly affect land conditions and nutrient availability for plant growth [26, 27]. The availability of plant nutrients is determined by the crop's genetic characteristics and the agronomic practices employed by farmers. Concurrently, the physical land conditions that affect suitability are evaluated based on eight key indicators: soil type, elevation, slope gradient, road network, river network, residential areas, location of agro-industries, and forest areas.

The indicators selected to determine the land suitability level of coffee plantations were soil type, elevation, and slope gradient. Soil type and elevation are indicators that significantly influence the growth requirements of coffee plantation land, as they provide water, nutrients, and appropriate conditions for the development of coffee plants [28]. Coffee requires land with good drainage to prevent waterlogging around the roots. It also demands soil with a loose texture and rich in organic matter to ensure optimal aeration and nutrient supply for its growth [29, 30]. Elevation significantly impacts coffee growth and quality by influencing ambient temperature, humidity, solar radiation, and rainfall, with optimal conditions often found at specific altitudes. Higher elevations typically result in cooler temperatures, less humidity, and different sunlight exposure, which can enhance coffee bean characteristics, including flavor profiles and biochemical composition, leading to higher quality coffee [31]. Slope gradient serves as a critical topographic factor as it directly influences the soil solum, which refers to the depth of the soil profile from the surface to the parent material. Steeper slopes are typically associated with shallower soil solum due to higher erosion rates and limited soil development, which restricts root penetration and water retention capacity. Consequently, coffee plants grown on steep slopes often exhibit suboptimal growth performance [32, 33].

Five additional indicators influencing the coffee plantation suitability model include road networks, river networks, residential area, agroindustrial location, and forest area. Among these, road infrastructure serves as a critical determinant of plantation development, facilitating the transportation of inputs and outputs as well as market access [34]. Proximity to road networks enhances accessibility, thereby improving the efficiency of plantation operations and reducing logistical constraints [35].

Sufficient year-round water availability from river networks is essential for sustaining plantation management and ensuring optimal crop productivity [36]. The residential area in close proximity to coffee plantations may intensify human activities that disrupt plant growth and elevate environmental and socio-economic pressures, thereby posing potential threats to the long-term sustainability of coffee cultivation systems [37]. Furthermore, the spatial location of coffee agroindustries plays a pivotal role in determining transportation efficiency and value chain dynamics, ultimately influencing the income and economic sustainability of smallholder coffee farmers [38]. Forest areas represent designated zones intended for long-term conservation and ecological balance. In practice, however, forest lands are frequently utilized for non-forestry purposes, particularly coffee cultivation [39]. Therefore, it is essential to understand the functional roles of forest areas and their suitability for coffee plantation development. The spatial representation of the indicators influencing suitability levels is shown in Figures 4-11.

Figure 4. Soil type map

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Figure 5. Elevation map

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Figure 6. Slope gradient map

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Figure 7. Road network map

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Figure 8. River network map

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Figure 9. Resident area map

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Figure 10. Smallholder coffee agroindustry map

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Figure 11. Forest area map

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3.3 Mathematical model for evaluating smallholder coffee plantation suitability

The selected suitability indicators facilitate an integrated mapping approach that captures the combined effects of biophysical conditions and anthropogenic factors arising from natural processes and human activities [40]. Each indicator was represented within a scoring classification framework, with scores ranked according to the respective land suitability classes for coffee plantations. The ranking procedure served as an analytical technique to depict varying levels of spatial relevance within the model. The assigned scores are relative measures rather than fixed values, and may vary depending on the contextual characteristics and parameters of the specific case study [41].

Soil types in Jember Regency were categorized into five categories for scoring purposes: mollic-ochric andosols, vitric andosols, eutric regosols, eutric fluvisols, and litosol. Among these categories, Andosols were identified as the most suitable soil type for coffee plantations [42]. Andosol is a type of soil found in mountainous areas, with shallow soil, a crushed structure, high porosity, and high dust and organic matter content [43]. Soil suitability scores were subsequently assigned based on literature references and expert assessments, as presented in Table 3. Subsequently, the remaining indicators were represented proportionally based on their distance from the coffee plantations. Buffer-based proximity analysis was applied to map distances between coffee plantations and key spatial networks, with road network distances reaching up to approximately 15 km in Jember Regency. This distance was then divided into five classes, each assigned a corresponding suitability score, and so forth, as presented in Table 5. All indicators were classified into five ordinal score classes, where higher scores indicate relatively more suitable conditions for coffee plantation development. The classification scores (1–5) assigned to each indicator in Table 5 were developed using a combined approach that integrates scientific literature [18], Good Agriculture Practices (GAP) on coffee document [44], expert judgment, government officers, and smallholder coffee farmers. The scoring system is therefore grounded in both empirical evidence and contextual field knowledge, ensuring that the suitability classes reflect the ecological requirements of coffee as well as the local production environment in Jember Regency.

Table 5. The scoring classification of indicators’ suitability and their weighting

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In order to construct the mathematical model, each indicator was subsequently assigned a weight representing its relative importance. The weighting process is determined based on a priority ranking scale. Indicator and criterion comparisons relied on expert judgment and were ranked using consistent logical criteria. The resulting indicator weights are presented in Table 3. Aggregated expert assessments indicate that elevation is the most influential indicator affecting the potential of coffee plantations. These weights were then applied as coefficients in the mathematical model used to assess coffee plantation suitability. Furthermore, each indicator score is denoted as follows: STS (soil type score), ES (elevation score), SGS (slope gradient score), DFRd (distance to road network), DFRr (distance to river network), DFRt (distance to settlement areas), DFCA (distance from coffee agroindustry), and FA (forest area). The indicator evaluation process is carried out through a spatial model utilizing Geographic Information Systems (GIS). The mathematical model equation is expressed as:

X_i = 0.184STS + 0.186ES + 0.079SGS + 0.146DFRd + 0.079DFRr + 0.083DFRt + 0.082DFCA + 0.161FA

The mathematical formulation was used to calculate composite indicator scores that define the suitability level (X_i) at each location. The computation of plantation potential is conducted through a spatial overlay process. Each indicator is overlaid sequentially onto the coffee plantation map; this process produced an integrated thematic map layer containing attribute information for each indicator. Attribute values at specific locations were subsequently converted into ordinal scales, as described earlier. Based on the formulated equation, the total score is calculated to represent the overall suitability level or the potential classification of smallholder coffee plantations, as presented in the following section.

3.4 Classification of coffee plantation suitability levels

The total score analysis indicates that the mapping model was applied to 3,159 spatial records. Based on the previously established equation, the results show that the minimum total score was 1.316, whereas the maximum reached 4.678, as illustrated in Figure 12.

Figure 12. The total score measurement of coffee plantations

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The aggregated total scores served as the basis for classifying the suitability levels of smallholder coffee plantations. As outlined in the Methods section, the classification was divided into three categories, with a CID value of 1.3842. Based on this CID value, the interval thresholds for each suitability class were established, as presented in Table 4. Each plantation area was subsequently assigned to a suitability class according to its calculated value. This classification reflects the number and severity of limiting land characteristics [45]. Referring to the land suitability level of coffee plantations, the classification results indicate that 57.96% of smallholder coffee plantations are located in potential plantation areas; the remaining plantation areas are classified as developing and non-potential categories, as detailed numerically in Table 6.

Table 6. Coffee plantations suitability rate area

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Based on the obtained results, it is evident that smallholder coffee plantation areas classified as developing and non-potential require improvement and should receive attention from decision-makers to enhance their potential. Non-potential smallholder coffee plantation areas face constraining factors that hinder their productivity, whereas developing plantation areas are expected to promote better management of smallholder coffee plantations. Therefore, the evaluation of smallholder coffee plantation areas needs to be prioritized to ensure the holistic availability of coffee raw materials and support the sustainability of the coffee industry. In this regard, the role and function of the government in strengthening smallholder coffee plantation enterprises must be emphasized. Spatially appropriate directions for smallholder coffee plantation development should also be considered. Furthermore, this suitability assessment is expected to assist smallholder coffee farmers in understanding the legal status of their land. Overall, the classification map of smallholder coffee plantation suitability levels is illustrated in Figure 13. Through this spatial classification, decision-makers will be directly supported in implementing empowerment programs for smallholder coffee farmers at the right time and in the most appropriate locations.

Figure 13. The suitability rate map of smallholder coffee plantations

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The model results indicate that 57.96% of the assessment area falls into the “potential” suitability class. This relatively high proportion reflects the agroecological characteristics of Jember Regency, which is historically recognized as a favorable environment for Coffea robusta cultivation. A significant portion of the landscape lies above 600 masl, which aligns with optimal ecological conditions for robusta coffee as reported in regional agronomic studies. Elevation is one of the strongest positive drivers in the model, as confirmed by its high AHP weight. Much of the area is dominated by Andosols and Inceptisols, known for good drainage and organic matter content, and by moderate slope gradients (15–40%), which support perennial crop cultivation in upland regions. Although some agricultural areas are distant from processing centers, the majority remain within an economically viable accessibility range (< 12 km), supporting efficient value-chain integration. This aligns with Jember’s well-established coffee processing industry and large downstream capacity. The “potential” classification is consistent with the competitive position of Jember as one of East Java’s major robusta producers, supported by dense processing networks, established supply chains, and active smallholder participation. The presence of large-scale agroindustry (i.e., roasting, grinding, and export-oriented intermediaries) enhances the strategic importance of identifying zones for future expansion.

Non-potential coffee plantation covers only 9.32% of the total area. A cross-analysis of spatial overlays indicates that these areas have extreme slopes (> 40%), which are associated with erosion risks, shallow rooting depths, and low mechanization feasibility. The protected forest classification also influences land-use conversions, which are restricted by regulations, thus eliminating the possibility of plantation development regardless of biophysical suitability. Very low accessibility, including areas located >12 km from roads or coffee agro-industry centers, increases production and transportation costs.

A spatial overlay of the eight individual indicator maps (Figures 4-11) confirms that “non-potential” areas tend to show multiple interacting constraints rather than a single limiting factor. Conversely, “potential” areas typically show at least four high-scoring indicators in combination, most commonly: favorable elevation, moderate slopes, suitable soil types, and reasonable proximity to transport and processing facilities. This multi-criteria convergence explains the high proportion of “potential” areas and supports the validity of the classification results.