## 5 Agro-Climatic Mapping
### Definition of Agro-Climatic Conditions  
Conditions for the same crop can even variate from one country to another. With the aim of knowing the different geo-climatic conditions of each crop in each region, an exhaustive search of reference information was performed to locate main areas of the different cash crops. Generally, these cartographic data are not very detailed, neither when obtained from remote sensing, nor from site inspections. Basically, they consist of schematic maps with general polygons without a scale or an adequate resolution obtained from national sources, for example, the Protected Areas Conservation Trust in Belize; the Ministry of Agriculture, Natural Resources and Rural Development in Haiti; the System of Information of Forest Resources of Costa Rica and the Guyana Lands and Surveys Commission, among others; and from global sources such as the United States Agency for International Development (USAID); the United States Geological Survey (USGS); the Famine Early Warning System Network (FEW Net); the Food and Agriculture Organization (FAO); the World Bank and the Interamerican Development Bank (BID). As is shown in Figure 5, the reference data is geolocated and classified to isolate the areas of interest in raster or vector format. The obtained layer is useful as a mask to outline and extract the agro-climatic conditions according to each selected crop and from a spatial combination between these conditions obtaining the potential areas in which a crop is cultivated. When the reference data is available, we use the range of conditions obtained in that country and we extrapolate the conditions for similar climatological countries without reference data of the crops. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Database** & **Variables** & **Ground Resolution** & **Scale/Applicability** & **Period** \\ \hline \multirow{6}{*}{WORLD CLIM} & monthly minimum, & & Global, Regional, \\  & mean and maximum & 30 s & National, \\  & temperature, precipitation, & (\(\sim\)1 km\({}^{2}\)) & Sub-national, \\  & solar radiation, & to 10 min & Province/District, \\  & wind speed and & (\(\sim\)340 km\({}^{2}\)) & Watershed/Basin, \\  & water vapour pressure & & Landscape & \\ \hline \multirow{6}{*}{SRTM} & \multirow{6}{*}{elevation data} & Global, \\  & & Regional, \\  & & National, \\ \cline{1-1}  & & Sub-national, \\ \cline{1-1}  & & Province/District, \\ \cline{1-1}  & & Watershed/Basin, \\ \cline{1-1}  & & Landscape & \\ \hline DSMW & soil data & 5 min & Global, Regional, \\ \cline{1-1}  & & (\(\sim\)170 km\({}^{2}\)) & National & \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Description of data used to define agro-climatic conditions. To define the geo-climatic conditions through the masks of the reference areas, the climatic data along with elevation data was spatially crossed with the reference areas in order to establish the maximum and minimum value inside those areas. These ranges of the agro-climatic variables for each crop and country was obtained by means of curves of accumulated area (CAA). In the CAA, the \(x\)-axis represents the values of the agro-climatic variable and the \(y\)-axis represents the accumulated area up to a certain value of the agro-climatic variable, therefore, a 100% in the \(y\)-axis corresponds to the total area of the reference map used. The CAA were computed as follows: at first (1) to filter the agro-climatic layers through the mask of the reference maps, then (2) to obtain the histogram of areas through counting the areas/pixels associated to agro-climatic values, and finally (3) to accumulate the areas of the histogram, in terms of percentage, according to the values of the agro-climatic variable. In Figure 6, we show as a sample the CAA obtained for Belize for the selected cash crops. In this study, the geo-climatic intervals were selected considering at least 95% of the accumulated area of the reference masks.