Integrating an Expert System, GIS, and Satellite Remote Sensing to Evaluate Land Suitability for Sustainable Tea Production in Bangladesh

被引:24
作者
Das, Animesh Chandra [1 ,2 ]
Noguchi, Ryozo [3 ]
Ahamed, Tofael [3 ]
机构
[1] Univ Tsukuba, Grad Sch Life & Environm Sci, Ibaraki 3058572, Japan
[2] Sylhet Agr Univ, Fac Agr, Sylhet 3100, Bangladesh
[3] Univ Tsukuba, Fac Life & Environm Sci, Ibaraki 3058572, Japan
关键词
tea; land evaluation; phenological indices; remote sensing; GIS; analytical hierarchy process; yield validation; DECISION; IMPACT; CROPS;
D O I
10.3390/rs12244136
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Land evaluation is important 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 images 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 used to generate the elevation layer. Other vector and raster layers of edaphic, climatic parameters, and vegetation indices were processed in ArcGIS 10.7.1(R) software. Finally, suitability classes were determined using weighted overlay of spatial analysis based on reclassified raster layers of all parameters along with the results from multicriteria 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. 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 one in a not suitable area. Yield estimation was performed with the NDVI (R-2 = 0.69, 0.66, and 0.67) and the LAI (R-2 = 0.68, 0.65, and 0.63) for 2017, 2018, and 2019, respectively. This research suggests that satellite remote sensing and GIS application with the analytical hierarchy process (AHP) could be used by agricultural land use planners and land policy makers to select suitable lands for increasing tea production.
引用
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页码:1 / 25
页数:24
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