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Lepsta

Lepsta is a collaboration platform for developers designed to help developers produce better quality software, faster! By running processes in parallel and by automating tasks that are normally executed manually, Lepsta is able to save companies 40% resources.

Thato Digital Solutions (Pty) Ltd

Thato Digital Solutions is a telecommunications and information technology-related company, offering logo designs, mobile applications development, publishing, etc.

Litabe Technologies

Litabe Technologies is an energy security company that specializes in electricity theft prevention and cable theft prevention.

GHS - Built-up Volume 1980 - 1 km

The GHS-BUILT-V R2023A dataset depicts the distribution of built-up volumes, expressed as number of cubic meters. This data reports about the total built-up volume. Data are spatial-temporal interpolated from 1975 to 2030 in 5 year intervals. Data were obtained by multiplying the GHS built-up surface versus the GHS building height (ANBH) part of the same GHS collection.

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GHS - Built-up Volume 1975 - 1 km

The GHS-BUILT-V R2023A dataset depicts the distribution of built-up volumes, expressed as number of cubic meters. This data reports about the total built-up volume. Data are spatial-temporal interpolated from 1975 to 2030 in 5 year intervals. Data were obtained by multiplying the GHS built-up surface versus the GHS building height (ANBH) part of the same GHS collection.

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GHS - Built-up Surface 1975 - 1 km

The GHS-BUILT-S spatial raster dataset depicts the distribution of the built-up (BU) surfaces estimates between 1975 and 2030 in 5 year intervals and two functional use components a) the total BU surface and b) the non-residential (NRES) BU surface. The data is made by spatial-temporal interpolation of five observed collections of multiple-sensor, multiple-platform satellite imageries: Landsat (MSS, TM, ETM sensor) data supports the 1975, 1990, 2000, and 2014 epochs, while a Sentinel-2 (S2) image composite (GHS-composite-S2 R2020A) supports the 2018 epoch.

This data represents the total BU

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GHS - Built-up Volume 2030 - 1 km

The GHS-BUILT-V R2023A dataset depicts the distribution of built-up volumes, expressed as number of cubic meters. This data reports about the total built-up volume. Data are spatial-temporal interpolated from 1975 to 2030 in 5 year intervals. Data were obtained by multiplying the GHS built-up surface versus the GHS building height (ANBH) part of the same GHS collection.

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GHS - Settlement Model

The GHS Settlement Model layers (GHS-SMOD) GHS-SMOD_GLOBE_R2023A delineate and classify settlement typologies via a logic of cell clusters population size, population and built-up area densities as defined by the stage I of the Degree of Urbanisation (European Commission & Statistical Office of the European Union, 2021) and recommended by the UN STAT COM. The raster dataset depicts the settlement classification per grid cell of 1 km².

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GHS - Population - 1 km

This GHS-POP spatial raster product (GHS-POP_GLOBE_R2023) depicts the distribution of human population, expressed as the number of people per cell. Residential population estimates at 5 years interval between 1975 and 2030 are derived from the raw global census data harmonized by CIESIN for the Gridded Population of the World, version 4.11 (GPWv4.11) at polygon level, and disaggregated from census or administrative units to grid cells, informed by the distribution, classification and volume of built-up as mapped in the GHSL global layers per corresponding epoch.

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GHS - Population - 100 m

This GHS-POP spatial raster product (GHS-POP_GLOBE_R2023) depicts the distribution of human population, expressed as the number of people per cell. Residential population estimates at 5 years interval between 1975 and 2030 are derived from the raw global census data harmonized by CIESIN for the Gridded Population of the World, version 4.11 (GPWv4.11) at polygon level, and disaggregated from census or administrative units to grid cells, informed by the distribution, classification and volume of built-up as mapped in the GHSL global layers per corresponding epoch.

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GHS - Built-up Surface 2025 - 100 m

The GHS-BUILT-S spatial raster dataset depicts the distribution of the built-up (BU) surfaces estimates between 1975 and 2030 in 5 year intervals and two functional use components a) the total BU surface and b) the non-residential (NRES) BU surface. The data is made by spatial-temporal interpolation of five observed collections of multiple-sensor, multiple-platform satellite imageries: Landsat (MSS, TM, ETM sensor) data supports the 1975, 1990, 2000, and 2014 epochs, while a Sentinel-2 (S2) image composite (GHS-composite-S2 R2020A) supports the 2018 epoch.

This data represents the total BU

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GHS - Built-up Surface 2015 - 100 m

The GHS-BUILT-S spatial raster dataset depicts the distribution of the built-up (BU) surfaces estimates between 1975 and 2030 in 5 year intervals and two functional use components a) the total BU surface and b) the non-residential (NRES) BU surface. The data is made by spatial-temporal interpolation of five observed collections of multiple-sensor, multiple-platform satellite imageries: Landsat (MSS, TM, ETM sensor) data supports the 1975, 1990, 2000, and 2014 epochs, while a Sentinel-2 (S2) image composite (GHS-composite-S2 R2020A) supports the 2018 epoch.

This data represents the total BU

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GHS - Built-up Surface 2010 - 100 m

The GHS-BUILT-S spatial raster dataset depicts the distribution of the built-up (BU) surfaces estimates between 1975 and 2030 in 5 year intervals and two functional use components a) the total BU surface and b) the non-residential (NRES) BU surface. The data is made by spatial-temporal interpolation of five observed collections of multiple-sensor, multiple-platform satellite imageries: Landsat (MSS, TM, ETM sensor) data supports the 1975, 1990, 2000, and 2014 epochs, while a Sentinel-2 (S2) image composite (GHS-composite-S2 R2020A) supports the 2018 epoch.

This data represents the total BU

Read More
GHS - Built-up Surface 2005 - 100 m

The GHS-BUILT-S spatial raster dataset depicts the distribution of the built-up (BU) surfaces estimates between 1975 and 2030 in 5 year intervals and two functional use components a) the total BU surface and b) the non-residential (NRES) BU surface. The data is made by spatial-temporal interpolation of five observed collections of multiple-sensor, multiple-platform satellite imageries: Landsat (MSS, TM, ETM sensor) data supports the 1975, 1990, 2000, and 2014 epochs, while a Sentinel-2 (S2) image composite (GHS-composite-S2 R2020A) supports the 2018 epoch.

This data represents the total BU

Read More
GHS - Built-up Surface 2000 - 100 m

The GHS-BUILT-S spatial raster dataset depicts the distribution of the built-up (BU) surfaces estimates between 1975 and 2030 in 5 year intervals and two functional use components a) the total BU surface and b) the non-residential (NRES) BU surface. The data is made by spatial-temporal interpolation of five observed collections of multiple-sensor, multiple-platform satellite imageries: Landsat (MSS, TM, ETM sensor) data supports the 1975, 1990, 2000, and 2014 epochs, while a Sentinel-2 (S2) image composite (GHS-composite-S2 R2020A) supports the 2018 epoch.

This data represents the total BU

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BamPro: A Bambara Nut Probiotic Beverage

BamPro is a natural, great tasting, lactose and cholesterol free yoghurt-like drink. It is naturally low in fat and rich in protein, fibre and antioxidants with added probiotics for maintaining good balance and composition of intestinal flora. BamPro is produced from whole milled Bambara fermented...

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