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Overview

Project website github.com/worldbank/sdg-metadata
Instructions for translators

This project is limited to Russian translation only, for now.

More detailed instructions to come.
Project maintainers User avatar brockfanning
Translation license MIT License
Translation process
  • Translations can be made directly.
  • Translation suggestions are turned off.
  • Translations are reviewed by dedicated reviewers.
  • Any authenticated user can contribute.
  • The translation uses monolingual files.
  • The translation base language can not be edited.
Source code repository https://github.com/worldbank/sdg-metadata
Repository branch master
Last remote commit Merge pull request #542 from weblate/weblate-sdg-metadata-1-1-1a 85d59a4a6e9
User avatar brockfanning authored 2 weeks ago
Last commit in Weblate Translated using Weblate (French) fec624aacd3
User avatar deblsyl authored 2 years ago
Weblate repository https://hosted.weblate.org/git/sdg-metadata/1-1-1a/
File mask translations-metadata/*/11-3-1.yml
Monolingual base language file translations-metadata/en/11-3-1.yml
Translation file Download translations-metadata/fr/11-3-1.yml
Last change Feb. 17, 2022, 3:25 p.m.
Last author Sylvie DeBlois
3 weeks ago

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Waiting for review 9% 3 1% 13 1% 141
Translated 9% 3 1% 13 1% 141
Needs editing 0% 0 0% 0 0% 0
Read-only 0% 0 0% 0 0% 0
Failing checks 0% 0 0% 0 0% 0
Strings with suggestions 0% 0 0% 0 0% 0
Untranslated strings 90% 28 99% 6,400 99% 57,801
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  1. SDG Metadata
  2. 11-3-1
  3. French
<p>2021-03-01</p>
<p>Mars 2022021-03-01</p>
2 years ago
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Resource updated

  1. SDG Metadata
  2. 11-3-1
  3. French
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  1. SDG Metadata
  2. 11-3-1
  3. French
<p><strong>Sources of discrepancies:</strong></p>
<p>Significant variations between global and national figures are anticipated where globally produced built-up layers are used to compute the indicator. This is largely due to the uniqueness of some local contexts and variations in image reflectance and land cover types, which make it difficult to accurately capture built up areas consistently. While the national figures will be used for reporting &#x2013; resulting in less differences being observed, some countries may opt to use the globally available products, which may create some variations as locally generated data becomes available. UN-Habitat will be responsible for checking all figures to ensure that no inconsistencies are reported. </p>
<p>The second likely source of differences between figures is the approach used to define urban areas and cities for the purpose of the indicator computation. To resolve this, the use of the degree of urbanization approach to definition of urban and rural areas and production of comparable data is recommended. This approach was endorsed by the UN Statistical Commission in March 2020, and its incremental adoption by countries is likely to reduce any differences in the figures reported in future. </p>
 
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  1. SDG Metadata
  2. 11-3-1
  3. French
<p><strong>Data availability:</strong></p>
<p>This indicator is categorized under Tier II, meaning the indicator is conceptually clear and an established methodology exists but data on many countries is not yet available. The indicator&#x2019;s rapid adoption by countries since 2015 has resulted in increased production of data at the local level, while activities of UN-Habitat and partners in the earth observation field are significantly contributing to availability of baseline data for the indicator. For example, using global datasets such as the Global Human Settlement Layer (GHSL), the World Settlement Footprint (WSF), the Gridded Population of the World (GPW), WorldPop dataset, the High Resolution Settlement Layer (HRSL) among others can help attain global estimates for the indicator. While some of these datasets have limitations in their application to track city level trends, their wide coverage provides a useful resource for the indicator computation. Higher resolution data is continuously being produced by countries, which are supported by organizations working in the earth observation and geospatial information field of expertise. More than 1,500 cities from more than 80 countries have data at the right resolution required for the indicator computation.</p>
<p><strong>Time series:</strong></p>
<p>Available time series runs at the city and national level for selected countries</p>
<p><strong>Disaggregation:</strong></p>
<p>Potential Disaggregation:</p>
<ul>
<li>Disaggregation by location (operational urban area vs administratively defined urban area, urban wide vs intra-urban growth trends)</li>
<li>Disaggregation by type of growth<strong> </strong>(infill, expansion, leapfrogging)</li>
<li>Disaggregation by city type (large vs medium sized vs small)</li>
<li>Disaggregation by type of land use consumed by the urbanization process </li>
</ul>
 
2 years ago
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  1. SDG Metadata
  2. 11-3-1
  3. French
<p><strong>&#x2022; At country level</strong></p>
<p><strong>&#x2022; At regional and global levels</strong></p>
<p>All countries are expected to fully report on this indicator more consistently starting in 2020 with few challenges where missing values will be reported due to missing base map files. Only limited cases of missing values are anticipated, which can emanate from situations where population growth figures are unavailable or where land consumption rates are inestimable due to lack or poor quality of multi-temporal coverage of satellite imagery. Because the values will be aggregated at the national levels from a national sample of cities, missing values will be less observed at national and global levels</p>
 
2 years ago
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  1. SDG Metadata
  2. 11-3-1
  3. French
<p>The method to compute ratio of land consumption rate to population growth rate follows five broad steps:</p>
<ol>
<li>Deciding on the analysis period/years</li>
<li>Delimitation of the urban area or city which will act as the geographical scope for the analysis</li>
<li>Spatial analysis and computation of the land consumption rate</li>
<li>Spatial analysis and computation of the population growth rate</li>
<li>Computation of the ratio of land consumption rate to population growth rate</li>
<li>Computation of recommended secondary indicators</li>
<li><strong>Deciding on the analysis period/years</strong></li>
</ol>
<p>This step involves selecting the time period during which the measurement of the indicator will be undertaken. Since this indicator considers historical growth of urban areas, analysis can be done annually, in 5-year cycles or 10-year cycles. Cycles of 5 or 10 years are commended, especially where use of mid-to-high resolution satellite imagery is used to extract data on built up areas, which is used to compute the land consumption rate component of the indicator. UN-Habitat and partners have been creating a repository of some data on this indicator using 1990 as the baseline year. Countries can however compute the indicator as far as back as satellite imagery is available (1975 for Landsat free imagery) and can maintain the current/most recent year as the final reporting year. </p>
<ol>
<li><strong>Delimitation of the urban area or city which will act as the spatial analysis scope</strong></li>
</ol>
<p>Urban areas and cities grow in different ways, the most common of which include infill (new developments within existing urban areas resulting in densification), extension (new developments at the edge of existing urban areas), leapfrogging (new urban threshold developments which are not attached to the urban area but which are functionally linked) and inclusion (engulfing of outlying urban clusters or leapfrog developments into the urban area, often forming urban conurbations). Key to note also is that growth of urban areas is not always positive. Sometimes, negative growth can be recorded, such as where disasters (e.gs floods, earthquakes) result in collapse of buildings and/or reduction in the built-up area mass. </p>
<p>Understanding the spatial growth of urban areas requires two important pre-requisites: a) delimitation of an appropriate spatial analysis scope which captures the entire urban fabric (as opposed to just the administratively defined boundaries), and b) use of a growth tracking measurement that helps understand when both positive and negative growth happen. For the former, a harmonized urban area/city definition approach which allows for consistent analysis is recommended, while the use of built up areas is recommended for the latter since it allows for measurement of both positive and negative urban growth. </p>
<p>Following consultations with 86 member states, the United Nations Statistical Commission in its 51<sup>st</sup> Session (March 2020) endorsed the Degree of Urbanisation (DEGURBA) as a workable method to delineate cities, urban and rural areas for international statistical comparisons. Countries are thus encouraged to adopt this approach, which will help them produce data that is comparable across urban areas within their territories, as well as with urban areas and cities in other countries. More details on DEGURBA are available here: <a href="https://unstats.un.org/unsd/statcom/51st-session/documents/BG-Item3j-Recommendation-E.pdf">https://unstats.un.org/unsd/statcom/51st-session/documents/BG-Item3j-Recommendation-E.pdf</a></p>
<ol>
<li><strong>Spatial analysis and computation of the land consumption rate</strong></li>
</ol>
<p>Using the urban boundaries defined in step (b), spatial analysis is undertaken to determine the land consumption rate. To implement this, the three steps below are followed:</p>
<ol>
<li>From satellite imagery, extract data on built up areas for each analysis year </li>
<li>Calculate the total area covered by the built-up areas for each of the analysis years </li>
<li>Compute the (annual) land consumption rate using the formula:</li>
</ol>
<p></p>
<p><math xmlns="http://www.w3.org/1998/Math/MathML">
<mi mathvariant="bold">L</mi>
<mi mathvariant="bold">a</mi>
<mi mathvariant="bold">n</mi>
<mi mathvariant="bold">d</mi>
<mi mathvariant="bold">&amp;nbsp;</mi>
<mi mathvariant="bold">C</mi>
<mi mathvariant="bold">o</mi>
<mi mathvariant="bold">n</mi>
<mi mathvariant="bold">s</mi>
<mi mathvariant="bold">u</mi>
<mi mathvariant="bold">m</mi>
<mi mathvariant="bold">p</mi>
<mi mathvariant="bold">t</mi>
<mi mathvariant="bold">i</mi>
<mi mathvariant="bold">o</mi>
<mi mathvariant="bold">n</mi>
<mi mathvariant="bold">&amp;nbsp;</mi>
<mi mathvariant="bold">R</mi>
<mi mathvariant="bold">a</mi>
<mi mathvariant="bold">t</mi>
<mi mathvariant="bold">e</mi>
<mi mathvariant="bold">&amp;nbsp;</mi>
<mi mathvariant="bold">i</mi>
<mo>.</mo>
<mi mathvariant="bold">e</mi>
<mi mathvariant="bold">&amp;nbsp;</mi>
<mi mathvariant="bold">L</mi>
<mi mathvariant="bold">C</mi>
<mi mathvariant="bold">R</mi>
<mo>=</mo>
<mfrac>
<mrow>
<mi mathvariant="normal">V</mi>
<mi mathvariant="normal">p</mi>
<mi mathvariant="normal">r</mi>
<mi mathvariant="normal">e</mi>
<mi mathvariant="normal">s</mi>
<mi mathvariant="normal">e</mi>
<mi mathvariant="normal">n</mi>
<mi mathvariant="normal">t</mi>
<mo>-</mo>
<mi mathvariant="normal">V</mi>
<mi mathvariant="normal">p</mi>
<mi mathvariant="normal">a</mi>
<mi mathvariant="normal">s</mi>
<mi mathvariant="normal">t</mi>
</mrow>
<mrow>
<mtable>
<mtr>
<mtd>
<mrow>
<maligngroup></maligngroup>
<mi>V</mi>
<mi>p</mi>
<mi>a</mi>
<mi>s</mi>
<mi>t</mi>
<mi>&amp;nbsp;</mi>
<mi>&amp;nbsp;</mi>
</mrow>
</mtd>
</mtr>
<mtr>
<mtd>
<mrow>
<maligngroup></maligngroup>
<mi>&amp;nbsp;</mi>
</mrow>
</mtd>
</mtr>
</mtable>
</mrow>
</mfrac>
</math> * <math xmlns="http://www.w3.org/1998/Math/MathML">
<mfrac>
<mrow>
<mn>1</mn>
</mrow>
<mrow>
<mtable>
<mtr>
<mtd>
<mrow>
<maligngroup></maligngroup>
<mo>(</mo>
<mi>t</mi>
<mo>)</mo>
<mi>&amp;nbsp;</mi>
<mi>&amp;nbsp;</mi>
</mrow>
</mtd>
</mtr>
<mtr>
<mtd>
<mrow>
<maligngroup></maligngroup>
<mi>&amp;nbsp;</mi>
</mrow>
</mtd>
</mtr>
</mtable>
</mrow>
</mfrac>
</math></p>
<p>Where: V<sub>present</sub> is total built up area in current year</p>
<p>V<sub>pas</sub>t is total built up area in past year</p>
<p>t is the number of years between V<sub>present</sub> and V<sub>past</sub> (or length in years of the period considered)</p>
<ol>
<li><strong>Spatial analysis and computation of the population growth rate</strong></li>
</ol>
<p>Using the urban boundaries defined in step (b), calculate the total population within the urban area in each of the analysis years where the land consumption rate is computed. Population data collected by National Statistical Offices through censuses and other surveys should be used for this analysis. Where this type of population data is not available, or where data is released at large population units which exceed the defined urban area, countries are encouraged to create population grids, which can help disaggregate the data from large and different sized census/ population data release units to smaller uniform sized grids. </p>
<p>The (annual) population growth rate is calculated using the total population within the urban area for the analysis period using the formula below:</p>
<p><strong>Population Growth rate i.e. </strong><math xmlns="http://www.w3.org/1998/Math/MathML">
<mi mathvariant="bold">&amp;nbsp;</mi>
<mi mathvariant="bold">P</mi>
<mi mathvariant="bold">G</mi>
<mi mathvariant="bold">R</mi>
<mo>=</mo>
<mfrac>
<mrow>
<mi mathvariant="bold">L</mi>
<mi mathvariant="bold">N</mi>
<mfenced separators="|">
<mrow>
<msub>
<mrow>
<mi mathvariant="bold">P</mi>
<mi mathvariant="bold">o</mi>
<mi mathvariant="bold">p</mi>
</mrow>
<mrow>
<mi mathvariant="bold">t</mi>
<mo>+</mo>
<mi mathvariant="bold">n</mi>
</mrow>
</msub>
<mo>/</mo>
<msub>
<mrow>
<mi mathvariant="bold">P</mi>
<mi mathvariant="bold">o</mi>
<mi mathvariant="bold">p</mi>
</mrow>
<mrow>
<mi mathvariant="bold">t</mi>
</mrow>
</msub>
</mrow>
</mfenced>
</mrow>
<mrow>
<mo>(</mo>
<mi mathvariant="bold">y</mi>
<mo>)</mo>
</mrow>
</mfrac>
</math></p>
<p>Where </p>
<p>LN is the natural logarithm value</p>
<p>Pop<sub>t </sub>is the total population within the urban area/city in the past/initial year</p>
<p>Pop<sub>t+n</sub> is the total population within the urban area/city in the current/final year</p>
<p>y is the number of years between the two measurement periods</p>
<ol>
<li><strong>Computation of the ratio of land consumption rate to population growth rate</strong></li>
</ol>
<p>The ratio of land consumption rate (LCRPGR) to population growth rate is calculated using the formula: </p>
<p><math xmlns="http://www.w3.org/1998/Math/MathML">
<mi mathvariant="bold">L</mi>
<mi mathvariant="bold">C</mi>
<mi mathvariant="bold">R</mi>
<mi mathvariant="bold">P</mi>
<mi mathvariant="bold">G</mi>
<mi mathvariant="bold">R</mi>
<mo>=</mo>
<mi mathvariant="bold">&amp;nbsp;</mi>
<mfenced separators="|">
<mrow>
<mfenced separators="|">
<mrow>
<mfrac>
<mrow>
<mi mathvariant="bold">&amp;nbsp;</mi>
<mi mathvariant="bold">L</mi>
<mi mathvariant="bold">a</mi>
<mi mathvariant="bold">n</mi>
<mi mathvariant="bold">d</mi>
<mi mathvariant="bold">&amp;nbsp;</mi>
<mi mathvariant="bold">C</mi>
<mi mathvariant="bold">o</mi>
<mi mathvariant="bold">n</mi>
<mi mathvariant="bold">s</mi>
<mi mathvariant="bold">u</mi>
<mi mathvariant="bold">m</mi>
<mi mathvariant="bold">p</mi>
<mi mathvariant="bold">t</mi>
<mi mathvariant="bold">i</mi>
<mi mathvariant="bold">o</mi>
<mi mathvariant="bold">n</mi>
<mi mathvariant="bold">&amp;nbsp;</mi>
<mi mathvariant="bold">r</mi>
<mi mathvariant="bold">a</mi>
<mi mathvariant="bold">t</mi>
<mi mathvariant="bold">e</mi>
</mrow>
<mrow>
<mi mathvariant="bold">&amp;nbsp;</mi>
<mi mathvariant="bold">P</mi>
<mi mathvariant="bold">o</mi>
<mi mathvariant="bold">p</mi>
<mi mathvariant="bold">u</mi>
<mi mathvariant="bold">l</mi>
<mi mathvariant="bold">a</mi>
<mi mathvariant="bold">t</mi>
<mi mathvariant="bold">i</mi>
<mi mathvariant="bold">o</mi>
<mi mathvariant="bold">n</mi>
<mi mathvariant="bold">&amp;nbsp;</mi>
<mi mathvariant="bold">g</mi>
<mi mathvariant="bold">r</mi>
<mi mathvariant="bold">o</mi>
<mi mathvariant="bold">w</mi>
<mi mathvariant="bold">t</mi>
<mi mathvariant="bold">h</mi>
<mi mathvariant="bold">&amp;nbsp;</mi>
<mi mathvariant="bold">r</mi>
<mi mathvariant="bold">a</mi>
<mi mathvariant="bold">t</mi>
<mi mathvariant="bold">e</mi>
</mrow>
</mfrac>
</mrow>
</mfenced>
</mrow>
</mfenced>
</math></p>
<p>The overall formula can be summarized as:</p>
<p><math xmlns="http://www.w3.org/1998/Math/MathML">
<mi mathvariant="bold">L</mi>
<mi mathvariant="bold">C</mi>
<mi mathvariant="bold">R</mi>
<mi mathvariant="bold">P</mi>
<mi mathvariant="bold">G</mi>
<mi mathvariant="bold">R</mi>
<mo>=</mo>
<mfrac bevelled="true">
<mrow>
<mfenced separators="|">
<mrow>
<mfrac>
<mrow>
<mi mathvariant="normal">V</mi>
<mi mathvariant="normal">p</mi>
<mi mathvariant="normal">r</mi>
<mi mathvariant="normal">e</mi>
<mi mathvariant="normal">s</mi>
<mi mathvariant="normal">e</mi>
<mi mathvariant="normal">n</mi>
<mi mathvariant="normal">t</mi>
<mo>-</mo>
<mi mathvariant="normal">V</mi>
<mi mathvariant="normal">p</mi>
<mi mathvariant="normal">a</mi>
<mi mathvariant="normal">s</mi>
<mi mathvariant="normal">t</mi>
</mrow>
<mrow>
<mtable>
<mtr>
<mtd>
<mrow>
<maligngroup></maligngroup>
<mi>V</mi>
<mi>p</mi>
<mi>a</mi>
<mi>s</mi>
<mi>t</mi>
<mi>&amp;nbsp;</mi>
<mi>&amp;nbsp;</mi>
</mrow>
</mtd>
</mtr>
<mtr>
<mtd>
<mrow>
<maligngroup></maligngroup>
<mi>&amp;nbsp;</mi>
</mrow>
</mtd>
</mtr>
</mtable>
</mrow>
</mfrac>
<mi mathvariant="normal">&amp;nbsp;</mi>
<mi mathvariant="normal">*</mi>
<mi mathvariant="normal">&amp;nbsp;</mi>
<mfrac>
<mrow>
<mn>1</mn>
</mrow>
<mrow>
<mtable>
<mtr>
<mtd>
<mrow>
<maligngroup></maligngroup>
<mi>T</mi>
<mi>&amp;nbsp;</mi>
<mi>&amp;nbsp;</mi>
</mrow>
</mtd>
</mtr>
<mtr>
<mtd>
<mrow>
<maligngroup></maligngroup>
<mi>&amp;nbsp;</mi>
</mrow>
</mtd>
</mtr>
</mtable>
</mrow>
</mfrac>
</mrow>
</mfenced>
</mrow>
<mrow>
<mfenced separators="|">
<mrow>
<mfrac>
<mrow>
<mi mathvariant="bold">L</mi>
<mi mathvariant="bold">N</mi>
<mfenced separators="|">
<mrow>
<mfrac>
<mrow>
<msub>
<mrow>
<mi mathvariant="bold">P</mi>
<mi mathvariant="bold">o</mi>
<mi mathvariant="bold">p</mi>
</mrow>
<mrow>
<mi mathvariant="bold">t</mi>
<mo>+</mo>
<mi mathvariant="bold">n</mi>
</mrow>
</msub>
</mrow>
<mrow>
<msub>
<mrow>
<mi mathvariant="bold">P</mi>
<mi mathvariant="bold">o</mi>
<mi mathvariant="bold">p</mi>
</mrow>
<mrow>
<mi mathvariant="bold">t</mi>
</mrow>
</msub>
</mrow>
</mfrac>
</mrow>
</mfenced>
</mrow>
<mrow>
<mi mathvariant="bold">y</mi>
</mrow>
</mfrac>
</mrow>
</mfenced>
</mrow>
</mfrac>
<mi mathvariant="bold">&amp;nbsp;</mi>
</math></p>
<p>The analysis years for both the land consumption rate and the population growth rate should be the same. </p>
<ol>
<li><strong>Computation of recommended secondary indicators</strong></li>
</ol>
<p>There are two important secondary indicators which help interpret the value of the main indicator - LGRPGR, thus helping in better understanding the nature of urban growth in each urban area. Both indicators use the same input data as the LCRPGR and will thus not require additional work by countries. These are: </p>
<ol>
<li><strong>Built-up area per capita</strong> &#x2013; which is a measure of the average amount of built-up area available to each person in an urban area during each analysis year. This indicator can help identify when urban areas become too dense and/or when they become too sparsely populated. It is computed by dividing the total built-up area by the total urban population within the urban area/city at a given year, using the formula below:</li>
</ol>
<p><math xmlns="http://www.w3.org/1998/Math/MathML">
<mi mathvariant="bold">B</mi>
<mi mathvariant="bold">u</mi>
<mi mathvariant="bold">i</mi>
<mi mathvariant="bold">l</mi>
<mi mathvariant="bold">t</mi>
<mo>-</mo>
<mi mathvariant="bold">u</mi>
<mi mathvariant="bold">p</mi>
<mi mathvariant="bold">&amp;nbsp;</mi>
<mi mathvariant="bold">a</mi>
<mi mathvariant="bold">r</mi>
<mi mathvariant="bold">e</mi>
<mi mathvariant="bold">a</mi>
<mi mathvariant="bold">&amp;nbsp;</mi>
<mi mathvariant="bold">p</mi>
<mi mathvariant="bold">e</mi>
<mi mathvariant="bold">r</mi>
<mi mathvariant="bold">&amp;nbsp;</mi>
<mi mathvariant="bold">c</mi>
<mi mathvariant="bold">a</mi>
<mi mathvariant="bold">p</mi>
<mi mathvariant="bold">i</mi>
<mi mathvariant="bold">t</mi>
<mi mathvariant="bold">a</mi>
<mi mathvariant="bold">&amp;nbsp;</mi>
<mo>(</mo>
<mi mathvariant="bold">m</mi>
<mn>2</mn>
<mo>/</mo>
<mi mathvariant="bold">p</mi>
<mi mathvariant="bold">e</mi>
<mi mathvariant="bold">r</mi>
<mi mathvariant="bold">s</mi>
<mi mathvariant="bold">o</mi>
<mi mathvariant="bold">n</mi>
<mo>)</mo>
<mi mathvariant="bold">&amp;nbsp;</mi>
<mo>=</mo>
<mi mathvariant="bold">&amp;nbsp;</mi>
<mfenced separators="|">
<mrow>
<mfenced separators="|">
<mrow>
<mfrac>
<mrow>
<mi mathvariant="bold">&amp;nbsp;</mi>
<msub>
<mrow>
<mi mathvariant="bold">U</mi>
<mi mathvariant="bold">r</mi>
<mi mathvariant="bold">B</mi>
<mi mathvariant="bold">U</mi>
</mrow>
<mrow>
<mi mathvariant="bold">t</mi>
</mrow>
</msub>
</mrow>
<mrow>
<mi mathvariant="bold">&amp;nbsp;</mi>
<msub>
<mrow>
<mi mathvariant="bold">P</mi>
<mi mathvariant="bold">o</mi>
<mi mathvariant="bold">p</mi>
</mrow>
<mrow>
<mi mathvariant="bold">t</mi>
</mrow>
</msub>
</mrow>
</mfrac>
</mrow>
</mfenced>
</mrow>
</mfenced>
</math></p>
<p>Where</p>
<p>UrBU<sub>t </sub>is the total built-up area/city in the urban area in time t (in square meters) </p>
<p>Pop<sub>t</sub> is the population in the urban area in time t</p>
<ol>
<li><strong>Total change in built up area</strong> &#x2013; which is a measure of the total increase in built up areas within the urban area over time. When applied to a small part of an urban area, such as the core city (or old part of the urban area), this indicator can be used to understand densification trends in urban areas. It is measured using the same inputs as the land consumption rate for the different analysis years, based on the below formula: </li>
</ol>
<p><math xmlns="http://www.w3.org/1998/Math/MathML">
<mi mathvariant="bold">T</mi>
<mi mathvariant="bold">o</mi>
<mi mathvariant="bold">t</mi>
<mi mathvariant="bold">a</mi>
<mi mathvariant="bold">l</mi>
<mi mathvariant="bold">&amp;nbsp;</mi>
<mi mathvariant="bold">c</mi>
<mi mathvariant="bold">h</mi>
<mi mathvariant="bold">a</mi>
<mi mathvariant="bold">n</mi>
<mi mathvariant="bold">g</mi>
<mi mathvariant="bold">e</mi>
<mi mathvariant="bold">&amp;nbsp;</mi>
<mi mathvariant="bold">i</mi>
<mi mathvariant="bold">n</mi>
<mi mathvariant="bold">&amp;nbsp;</mi>
<mi mathvariant="bold">b</mi>
<mi mathvariant="bold">u</mi>
<mi mathvariant="bold">i</mi>
<mi mathvariant="bold">l</mi>
<mi mathvariant="bold">t</mi>
<mi mathvariant="bold">&amp;nbsp;</mi>
<mi mathvariant="bold">u</mi>
<mi mathvariant="bold">p</mi>
<mi mathvariant="bold">&amp;nbsp;</mi>
<mi mathvariant="bold">a</mi>
<mi mathvariant="bold">r</mi>
<mi mathvariant="bold">e</mi>
<mi mathvariant="bold">a</mi>
<mi mathvariant="bold">&amp;nbsp;</mi>
<mo>(</mo>
<mi mathvariant="bold">%</mi>
<mo>)</mo>
<mi mathvariant="bold">&amp;nbsp;</mi>
<mo>=</mo>
<mi mathvariant="bold">&amp;nbsp;</mi>
<mfrac>
<mrow>
<mfenced separators="|">
<mrow>
<msub>
<mrow>
<mi mathvariant="bold">U</mi>
<mi mathvariant="bold">r</mi>
<mi mathvariant="bold">B</mi>
<mi mathvariant="bold">U</mi>
</mrow>
<mrow>
<mi mathvariant="bold">t</mi>
<mo>+</mo>
<mi mathvariant="bold">n</mi>
</mrow>
</msub>
<mo>-</mo>
<mi mathvariant="bold-italic">&amp;nbsp;</mi>
<msub>
<mrow>
<mi mathvariant="bold">U</mi>
<mi mathvariant="bold">r</mi>
<mi mathvariant="bold">B</mi>
<mi mathvariant="bold">U</mi>
</mrow>
<mrow>
<mi mathvariant="bold">t</mi>
</mrow>
</msub>
</mrow>
</mfenced>
</mrow>
<mrow>
<msub>
<mrow>
<mi mathvariant="bold">U</mi>
<mi mathvariant="bold">r</mi>
<mi mathvariant="bold">B</mi>
<mi mathvariant="bold">U</mi>
</mrow>
<mrow>
<mi mathvariant="bold">t</mi>
</mrow>
</msub>
</mrow>
</mfrac>
</math></p>
<p>Where</p>
<p>UrBU<sub>t +n </sub>is the total built-up area in the urban area/city in time the current/final year </p>
<p>UrBU<sub>t </sub>is the total built-up area in the urban area/city in time the past/initial year </p>
<p>Detailed steps for computation of the core indicator and the secondary indicators are available in the detailed training module for indicator 11.3.1: <a href="https://unhabitat.org/sites/default/files/2020/07/indicator_11.3.1_training_module_land_use_efficiency_french.pdf">https://unhabitat.org/sites/default/files/2020/07/indicator_11.3.1_training_module_land_use_efficiency_french.pdf</a> </p>
 
2 years ago
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  1. SDG Metadata
  2. 11-3-1
  3. French
<p><strong>Sources and collection process:</strong></p>
<p>Population data required for this indicator is available from National Statistical Offices, UNDESA as well as through newly emerging multi-temporal gridded population datasets for the world. Historical built-up area data can also be generated for most countries and cities using mid-to-high resolution satellite imagery from the Landsat and Sentinel missions. Higher resolution data is available for several countries which have a rich repository of earth observation missions or partnerships with commercial providers of high to very high-resolution imagery. Other sources of data for this indicator include urban planning authorities and multi-temporal analytical databases on built-up area at the global level produced by organizations working in the earth observation field. </p>
<p>The production of data for this indicator requires some level of understanding of geospatial analysis techniques at the country level. Several tools have been developed to help with the indicator computation, including systems that allow for on-the-cloud analysis, but users still require some good level of understanding of the process and geospatial analysis to efficiently utilize these tools. Equally, access to internet is needed either to download the free satellite imagery or undertake analysis using existing cloud-based architecture. </p>
<p>National level capacity building initiatives will aim to balance the knowledge and understanding of the analysis, compilation and reporting of this indicator. Global reporting will rely on the estimates that come from the national statistical agencies, who should work collaboratively with mapping agencies and city data producers. With uniform standards in computation at the national level, few errors of omission or bias will be observed at the global/regional level. A rigorous analysis routine will be used to re-assess the quality and accuracy of the data at the regional and global levels. This will involve cross-comparisons with expected ranges of the values reported for cities.</p>
<p>UN-Habitat has developed a simple reporting template that allows countries to input data on the intermediate products (built-up area and population) then get the computed values for each analysis city and period. The template, which will be send to countries every year to report any new data is appended to this metadata and can also be accessed <a href="https://data.unhabitat.org/datasets/template-for-compilation-of-sdg-indicator-11-3-1">HERE</a>.</p>
 
2 years ago
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  1. SDG Metadata
  2. 11-3-1
  3. French
<p><strong>Definitions:</strong></p>
<p>The indicator is defined as the ratio of land consumption rate to population growth rate.</p>
<p>This indicator requires defining the two components of population growth and land consumption rate. Computing the population growth rate is more straightforward and more readily available, while land consumption rate is slightly challenging, and requires the use of new techniques. In estimating the land consumption rate, one needs to define what constitutes &#x201C;consumption&#x201D; of land since this may cover aspects of &#x201C;consumed&#x201D; or &#x201C;preserved&#x201D; or available for &#x201C;development&#x201D; for cases such as land occupied by wetlands. Secondly, there is not one unequivocal measure of whether land that is being developed is truly &#x201C;newly-developed&#x201D; (or vacant) land, or if it is at least partially &#x201C;redeveloped&#x201D;. As a result, the percentage of current total urban land that was newly developed (consumed) will be used as a measure of the land consumption rate. The fully developed area is also sometimes referred to as built up area.</p>
<p><strong>Concepts:</strong></p>
<p><strong>City or urban area</strong>: Since 2016 UN-Habitat and partners organized global consultations and discussions to narrow down the set of meaningful definitions that would be helpful for the global monitoring and reporting process. Following consultations with 86 member states, the United Nations Statistical Commission, in its 51st Session (March 2020) endorsed the Degree of Urbanisation (DEGURBA) as a workable method to delineate cities, urban and rural areas for international statistical comparisons.<sup><sup><a href="#footnote-2" id="footnote-ref-2">[1]</a></sup> </sup>This definition combines population size and population density thresholds to classify the entire territory of a country along the urban-rural continuum, and captures the full extent of a city, including the dense neighbourhoods beyond the boundary of the central municipality. DEGURBA is applied in a two-step process: First, 1 km2 grid cells are classified based on population density, contiguity and population size. Subsequently, local units are classified as urban or rural based on the type of grid cells in which majority of their population resides. For the computation of indicator 11.3.1, countries are encouraged to adopt the degree of urbanisation to define the analysis area (city or urban area).</p>
<p><strong>Population growth rate (PGR)</strong> is the change of a population in a defined area (country, city, etc) during a period, usually one year, expressed as a percentage of the population at the start of that period. It reflects the number of births and deaths during a period and the number of people migrating to and from the focus area. In SDG 11.3.1, this is computed at the area defined as urban/city. </p>
<p><strong>Land consumption</strong> within the context of indicator 11.3.1 is defined as the uptake of land by urbanized land uses, which often involves conversion of land from non-urban to urban functions. </p>
<p><strong>Land consumption rate</strong> is the rate at which urbanized land or land occupied by a city/urban area changes during a period of time (usually one year), expressed as a percentage of the land occupied by the city/urban area at the start of that time. </p>
<p><strong>Built up area </strong>within the context of indicator 11.3.1 is defined as all areas occupied by buildings. </p><div class="footnotes"><div><sup class="footnote-number" id="footnote-2">1</sup><p> A recommendation on the method to delineate cities, urban and rural areas for international statistical comparisons. <a href="https://unstats.un.org/unsd/statcom/51st-session/documents/BG-Item3j-Recommendation-E.pdf">https://unstats.un.org/unsd/statcom/51st-session/documents/BG-Item3j-Recommendation-E.pdf</a> <a href="#footnote-ref-2">&#x2191;</a></p></div></div>
 
2 years ago
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  1. SDG Metadata
  2. 11-3-1
  3. French
<p>2021-03-01</p>
<p>Mars 2021</p>
2 years ago
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  1. SDG Metadata
  2. 11-3-1
  3. French
<p>March 2022021-03-01</p>
2 years ago
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