Results from the spatial analysis

5.3.2.1 Calculation of the suitable lands for the cardamom expansion

GIS allows calculating the maximum suitable amount of land to grow cardamom in the territory of the studied communities knowing the requirements of this crop, and filtering these requirements with the GIS software, as shown in the following section. For example, the depth of the roots of cardamom is just up to 30 centimetres, so they do not require deep soils. The type of soils they require are rich in organic matter or compost, always wet soils, but well drained, so it grows better in slopes between 5-20%. The climate must be warm, very wet, ideally tropical areas with available shady areas. Cardamom only grows in medium altitudes ranging from 600 to 1500 meters.

Villagers’ houses are scattered inside a small part of their territory, which is considered the urban area. It is located in the closest corner of their land to the main road, and it occupies 8.4 ha in community E and 6.5 ha in the case of community F of their total lands. It was assumed that all the other current land uses apart from the urban area was selectable for the cardamom expansion. I filtered the area inside the altitudes with the DEM map (Figure 24), and calculated a slope layer from the DEM layer, from where we selected the slopes between 5% and 20% (Figure 25).

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Chapter 5

Figure 24. Map of the suitable lands regarding the required elevation for cardamom cultivation.

Figure 25. Map of the suitable lands regarding the required slope for cardamom cultivation

Checking the soil map allowed to find out that the type of soil is not a limiting factor for the cardamom expansion in this area, as I could check that both communities are located completely inside a soil area called Chacalté, which has a limestone base, and although it has a high percentage of clay, it is characterized by good drainage, that together with steep terrain helps to avoid ponding. This soil is around 50 centimetres deep, so it is enough for cardamom cultivation. It is relevant to mention that this type of soil is highly prone to erosion, and this is already one of the

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Spatial Analysis in MuSIASEM Tarik Serrano Tovar

greatest concerns for cultivation in the area, as reported by the peasants themselves. Proximity to water sources is not a problem in our cases because cardamom does not require irrigation in our area due to the high annual precipitation of 3600 mm. If this was not the case, a buffer could be made with GIS (as shown previously in Figure 21 and Figure 22) with the courses of water in the area obtained in the maps, in order to check which zones are within a determined distance from the water resources. Finally, using the DEM layer it is possible to obtain the relief with the hillshade function, and the slope orientation towards the cardinal points, to estimate the areas of solar radiation. In the case of the cardamom this was not required because it grows in shady areas under other trees, so solar radiation was not a problem.

As a result of the previous calculations, I obtained that the resulting area suitable for cultivating cardamom in community E is 85.4 ha, and in community F it is 34.5 ha (Figure 26). Note that the level of accuracy depends on the spatial resolution of the layer maps used in GIS for the calculation. In this case the DEM and the slope map used had a resolution of 90 meters per pixel, so at this local scale the calculation of hectares is just an approximation good enough to estimate a possible scenario.

Figure 26. Map reflecting the suitable area for the cardamom expansion.

As expected, the distance from the houses to the location of the suitable area for the cardamom expansion obtained in our calculations is logically similar to the distances of the current cardamom plots (i.e. their current plots are within the limits of this area). As a result, in this case there are not significant differences for the commuting time to these lands in the new scenario.

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Chapter 5 5.3.2.2 Calculation of distances for working as daily labourers in the agro-industries

Data for simulating this scenario is taken from the information gathered in another village (community B) of the area. The detailed information about the material and methods to collect this information can be seen at Mingorría et al. (2014). In that case, the community members were mainly working as daily labourers in the oil-palm agro-industries of the valley, and their village was located next to the main road. When simulating this scenario in community E and F, we must take into account that these communities are quite far from the road, so we have to measure with maps the length of the paths from the households to the main road in order to calculate the extra time for transportation that the workers from community E and F have to invest in this scenario. The time is calculated using the average speed described in section 5.2.2.4. Once on the road, the companies pick up the workers and take them to the different industrial plantations. For this stage of the transport we took the average time found in Mingorría et al. (2014) of some other communities located in the valley.

When estimating the time that the daily labourers have to walk every day to the point on the main road where they are supposed to be picked up, we took into account the time for going and return every day, and the average amount of working days per year. As a result, the measured distance of 2,750 meters from community E to the pick-up stop means that the labourers have to add 140 minutes for transportation each day of work (around 2 hours and 20 minutes per day). In the case of community F this distance is 3,500 meters, meaning 175 minutes walking (almost 3 extra hours per day). These results demonstrate that distance is not a trivial feature and that with this kind of spatial analysis tools we can quickly check for changes in the time allocation profile of the system due to investments in transport time when commuting distances change.