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  • The vector dataset portrays poverty rates at the country level. The data for the poverty dataset comes from: the Tajikistan Living Standard Measurement Survey 2009 (TLSS) collected by the State Statistical Agency of Tajikistan in collaboration with the World Bank, and the 2010 Census of Tajikistan. The TLSS provides information on food and non-food expenditure, labor activities, migration, agriculture, education, dwelling, utilities, and durable goods. The Census of Tajikistan covers approximately 1.6 million households and 8 million individuals. This dataset has been produced based on the data provided in the "Poverty Mapping in Tajikistan: Method and Key Findings" report. This report is the joint product of the World Bank Group (WBG) and the Agency of Statistics under the President of Tajikistan (TajStat).

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    The 500m raster dataset represents selected top location score areas filtered by exclusive criteria: access to finance, distance to major roads, access to IT and distance to urban areas. The layer was produced under the scope of FAO’s Hand-in-Hand Initiative, Geographical Information Systems - Multicriteria Decision Analysis for value chain infrastructure location. The location score is achieved by processing sub-model outputs characterizing logistical factors dairy processing (UHT/milk powder) facilities siting: Supply, demand, Infrastructure/accessibility. The top 99th percentile is selected/clipped using the exclusive criteria. Access to finance, distance to roads and urban areas are defined using a linear distance threshold: • Banks - approx. 20km (0.18 degree) buffer radius. • Major roads - approx. 2km (0.018 degree) buffer radius. Access to IT is characterized applying the mobile broadband coverage map.

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    The raster dataset consists of a 500m score grid for vegetable storage location achieved by processing sub-model outputs that characterize logistical factors for selected crop warehouse location: • Supply: Vegetables. • Demand: Human population density, Major cities population (national and bordering countries). • Infrastructure/accessibility: main transportation infrastructure. It consists of an arithmetic weighted sum of normalized grids (0 to 100): ("Crop Production" * 0.4) + ("Human Population Density" * 0.2) + ("Major Cities Accessibility" * 0.2) + (“Poverty” * 0.1) + (”Regional Cities Weighted Accessibility” * 0.1) This 500m resolution raster dataset is part of FAO’s Hand-in-Hand Initiative, Geographical Information Systems - Multicriteria Decision Analysis (GIS-MCDA) aimed at the identification of value chain infrastructure sites (optimal location).

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    Accessibility to major cities dataset is modelled as raster-based travel time/cost analysis, computed for the 11 largest cities (>40k habitants) in the country. The following cities are included: City - Population Dushanbe - 831,400 Hissar - 293,900 Khujand - 179,900 Bokhtar - 109,100 Kulob - 104,400 Istaravshan - 63,500 Tursunzade - 53,100 Konibodom - 51,600 Isfara - 49,700 Vahdat - 42,500 Panjakent - 42,300 This 500m resolution raster dataset is part of FAO’s Hand-in-Hand Initiative, Geographical Information Systems - Multicriteria Decision Analysis (GIS-MCDA) aimed at the identification of value chain infrastructure sites (or optimal location).

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    The raster dataset consists of a 500m score grid for dairy processing industry (UHT and milk powder) facilities siting, produced under the scope of FAO’s Hand-in-Hand Initiative, Geographical Information Systems - Multicriteria Decision Analysis for value chain infrastructure location. The analysis is based on cattle dairy production intensification potential, defined using crop production, livestock production systems and cattle distribution. The score is achieved by processing sub-model outputs that characterize logistical factors: 1. Supply - Feed, livestock production systems, cattle distribution. 2. Demand - Human population density, large cities, urban areas. 3. Infrastructure - Transportation network (accessibility) 4. Poverty. It consists of an arithmetic weighted sum of normalized grids (0 to 100): ("Crop Production" * 0.3) + ("Human Population Density" * 0.1) + (“Major Cities Accessibility” * 0.1) + ( "Poverty" * 0.1)+(”dairyIntensification” * 0.4)

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    The raster dataset represents top location score areas suitable for fruits storage filtered by exclusive criteria: access to finance, distance to major roads and access to IT (mobile broadband connection). Access to finance and roads are defined using a linear distance threshold: • Banks - approx. 20km (0.18 degree) buffer radius. • Major roads - approx. 2km (0.018 degree) buffer radius. Access to IT is characterized applying the mobile broadband coverage map. The location score is achieved by processing sub-model outputs characterizing logistical factors for crop warehouse siting: Supply, demand, Infrastructure/accessibility. The location score from 0 to 100 is then obtained through a simple arithmetic weighted sum of the normalized/scaled grids. The top 99th percentile is selected/clipped using the exclusive criteria. This 500m resolution raster dataset is part of FAO’s Hand-in-Hand Initiative, Geographical Information Systems - Multicriteria Decision Analysis (GIS-MCDA) aimed at the identification of value chain infrastructure sites (optimal location).

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    The 500m raster dataset represents selected top location score areas filtered by exclusive criteria: access to finance, distance to major roads, access to IT and distance to urban areas. The layer was produced under the scope of FAO’s Hand-in-Hand Initiative, Geographical Information Systems - Multicriteria Decision Analysis for value chain infrastructure location. The location score is achieved by processing sub-model outputs characterizing logistical factors for the slaughterhouse facilities siting: Demand, Supply, Infrastructure/accessibility. The top 99th percentile is selected/clipped using the exclusive criteria. Access to finance, distance to roads and urban areas are defined using a linear distance threshold: • Banks - approx. 20km (0.18 degree) buffer radius. • Major roads - approx. 2km (0.018 degree) buffer radius. • Access to IT is characterized by applying the mobile broadband coverage map.

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    The raster dataset consists of a 500m score grid for fruits storage location achieved by processing sub-model outputs that characterize logistical factors for selected crop warehouse location: • Supply: Fruits. • Demand: Human population density, Major cities population (national and bordering countries). • Infrastructure/accessibility: main transportation infrastructure. It consists of an arithmetic weighted sum of normalized grids (0 to 100): ("Crop Production" * 0.4) + ("Human Population Density" * 0.2) + ("Major Cities Accessibility" * 0.2) + (“Poverty” * 0.1) + (”Regional Cities Weighted Accessibility” * 0.1). This 500m resolution raster dataset is part of FAO’s Hand-in-Hand Initiative, Geographical Information Systems - Multicriteria Decision Analysis (GIS-MCDA) aimed at the identification of value chain infrastructure sites (optimal location).

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    A combination of cattle livestock intensification potential and poverty rates. The resulting dataset enables location analysis for dairy value chain potential investment. - Cattle livestock intensification layer is a combination of the cattle density/distribution and the selected livestock production system (MR Mixed RainfedArid+ MR Mixed Rainfed Humid + MR Mixed Rainfed Temperate + MI Mixed Irrigated Hyperarid + MI Mixed Irrigated Arid + MI Mixed Irrigated Humid+MI Mixed Irrigated Temperate+Urban). Livestock Production System used as 1/0 layer. - Poverty rates vary from 12.7 to 76.2 percent, higher percentage representing areas of higher poverty incidence.

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    The regional cities accessibility dataset is modelled as raster-based travel time/cost analysis. Individual cumulative travel time/cost maps were produced for major regional cities (>170k habitants) less than 100 km from the border. The following values were assumed: City - Country Namangan - UZB - 626,120 Samarkand - UZB - 546,303 Tashkent - UZB - 2,571,668 Mazar i sharif - AFG - 484,500 Fergana - UZB - 288,850 Kokand - UZB - 252,730 Altiarik - UZB - 210,515 Kunduz - AFG - 189,300 Termez - UZB - 179,572 Jizzax - UZB - 177,447 This 500m resolution raster dataset is part of FAO’s Hand-in-Hand Initiative, Geographical Information Systems - Multicriteria Decision Analysis (GIS-MCDA) aimed at the identification of value chain infrastructure sites (optimal location).