Integrating Analytical Hierarchy Process with GIS and Satellite Remote Sensing to Assess Land Suitability for Sustainable Tea Production in Bangladesh

Land suitability evaluation is crucial for assessing environmental limitations that inhibit higher yield and productivity in tea. The aim of this research was to determine the suitable lands for sustainable tea production in the northeastern part of Bangladesh using phenological datasets from remote sensing, geospatial datasets of soil-plant biophysical properties, and expert opinions. Sentinel-2 satellite image datasets were processed to obtain layers for land use and land cover (LULC) as well as the normalized difference vegetation index (NDVI). Data from the Shuttle Radar Topography Mission (SRTM) were processed to generate the elevation layer. Other vector layers of edaphic and climatic parameters were processed in ArcGIS 10.7.1® software for the respective raster layers. Finally, land suitability classes were obtained from the reclassified raster layers of all parameters along with the results from multicriteria analysis using spatial analysis. The results of the study showed that only 41,460 hectares of land (3.37% of the total land) were in the highly suitable category in the Sylhet region of Bangladesh. The proportions of moderately suitable, marginally suitable, and not suitable land categories for tea cultivation in the Sylhet division were 9.01%, 49.87% and 37.75%, respectively. Thirty-one tea estates were located in highly suitable areas, 79 in moderately suitable areas, 24 in marginally suitable areas, and only 1 in a not suitable area. Yield estimation was performed with the NDVI (R2 = 0.69, 0.66, and 0.67) and the LAI (R2 = 0.68, 0.65, and 0.63) for 2017, 2018, and 2019. This research suggests that satellite remote sensing and GIS applications with the analytical hierarchy process (AHP) could be used by land policy makers and agricultural land use planners to select suitable lands for increasing tea production.