Indicator 11.3.1 Ratio of land consumption rate to population growth rate

Indicator 11.3.1: Ratio of land consumption rate to population growth rate

Target 11.3: By 2030, enhance inclusive and sustainable urbanization and capacity for participatory, integrated and sustainable human settlement planning and management in all countries

United Nations Human Settlements Programme (UN-Habitat)

Definitions:

The indicator is defined as the ratio of land consumption rate to population growth rate.

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 “consumption” of land since this may cover aspects of “consumed” or “preserved” or available for “development” for cases such as land occupied by wetlands. Secondly, there is not one unequivocal measure of whether land that is being developed is truly “newly-developed” (or vacant) land, or if it is at least partially “redeveloped”. 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.

Concepts:

City or urban area: 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.^[1] 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).

Population growth rate (PGR) 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.

Land consumption 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.

Land consumption rate 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.

Built up area within the context of indicator 11.3.1 is defined as all areas occupied by buildings.

For the two components used to compute of this indicator, i.e a) land consumption rate and b) population growth rate, the unit of measurement is a percentage value.

The resulting indicator is measured as a ratio of these two percentages making it unitless.

Sources and collection process:

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.

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.

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.

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 HERE.

UN-Habitat and other partners such as the Global Human Settlement Layer (GHSL) team, the German Aerospace Center (DLR), partners in the Group on Earth Observations (GEO) and ESRI among others will support various components for reporting on this indicator. The global responsibility of building the capacity of national governments and statistical agencies to report on this indicator will be led by UN-Habitat. National governments/national statistical agencies will have the primary responsibility of reporting on this indicator at national level with the support of UN-Habitat to ensure uniform standards in analysis and reporting.

The major limitation for this indicator lies in its interpretation. In each human settlement structure, there are many factors at play, that make it more difficult to generalize the implication of a single LCRPGR value to sustainable urbanization. For example, while a value less than 1 could be a good indicator of urban compactness and its associated benefits, intra-city analysis may reveal high levels of congestion and poor living environments, which is against the principles of sustainable development. On the other hand, a value of one may not mean an optimal balance between spatial growth of urban areas and their populations, since it would imply new developments with every unit increase in population. To help explain the values of the indicator, two secondary indicators have been proposed, which use the same inputs as the core indicator: built up area per capita and total change in built up area.

Another limitation in the indicator is where zero or negative growth get reported, such as where population over the analysis period decreases or a natural disaster results in loss of the built-up area mass. Without looking at the land consumption and population growth rates separately, it is difficult to correctly interpret the indicator and its meaning. To address this, it is recommended to understand the individual rates, and also use the proposed secondary indicators to explain the trends.

Aggregating the indicator values for more than one city may also make the interpretation ambiguous. For example, an average value for a country with two cities might be between 0 and 1 if both cities are record values within this range, or if one has a value above 1 and the other a value below 0. The use of the national sample of cities approach, which produces a representative sample for each country will help resolve this challenge.

In some cases, it is difficult to measure the urban expansion by conurbations of two or more urban areas that are in close proximity; to whom to attribute the urban growth and how to include it as one metric usually becomes a challenge. At the same time, data would not always coincide to administrative levels, boundaries and built-up areas. To resolve this, the use of a harmonized approach to defining urban areas and cities has been identified as helping to resolve this challenge.

In the absence of the GIS layers, this indicator may not be computed as defined. As a result, more alternative measures for land that is developed or consumed per year can be adequately used. Alternatively, one can monitor the efficient use of urban land by measuring how well we are achieving the densities in residential zones that any city plans or international guidance call for. Comparing achieved to planned densities is very useful at the city level. However, planned densities vary greatly from country to country, and at times from city to city. At the sub-regional or city levels, it is more appropriate to compare average densities achieved currently to those achieved in the recent past. While building more densely does use land more efficiently, high density neighborhoods, especially in and around urban centers, have a number of other advantages. They support more frequent public transportation, and more local stores and shops; they encourage pedestrian activity to and from local establishments; and they create lively (and sometimes safer) street life.

The method to compute ratio of land consumption rate to population growth rate follows five broad steps:

1. Deciding on the analysis period/years
2. Delimitation of the urban area or city which will act as the geographical scope for the analysis
3. Spatial analysis and computation of the land consumption rate
4. Spatial analysis and computation of the population growth rate
5. Computation of the ratio of land consumption rate to population growth rate
6. Computation of recommended secondary indicators
7. Deciding on the analysis period/years

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.

1. Delimitation of the urban area or city which will act as the spatial analysis scope

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.

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.

Following consultations with 86 member states, the United Nations Statistical Commission in its 51^st 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: https://unstats.un.org/unsd/statcom/51st-session/documents/BG-Item3j-Recommendation-E.pdf

1. Spatial analysis and computation of the land consumption rate

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:

1. From satellite imagery, extract data on built up areas for each analysis year
2. Calculate the total area covered by the built-up areas for each of the analysis years
3. Compute the (annual) land consumption rate using the formula:

$\mathbf{L}\mathbf{a}\mathbf{n}\mathbf{d}\mathbf{\ }\mathbf{C}\mathbf{o}\mathbf{n}\mathbf{s}\mathbf{u}\mathbf{m}\mathbf{p}\mathbf{t}\mathbf{i}\mathbf{o}\mathbf{n}\mathbf{\ }\mathbf{R}\mathbf{a}\mathbf{t}\mathbf{e}\mathbf{\ }\mathbf{i}.\mathbf{e}\mathbf{\ }\mathbf{L}\mathbf{C}\mathbf{R}=\frac{\mathrm{V}\mathrm{p}\mathrm{r}\mathrm{e}\mathrm{s}\mathrm{e}\mathrm{n}\mathrm{t}-\mathrm{V}\mathrm{p}\mathrm{a}\mathrm{s}\mathrm{t}}{\begin{array}{c}Vpast\mathrm{\ }\mathrm{\ }\\ \mathrm{\ }\end{array}}$ * $\frac{1}{\begin{array}{c}\left(t\right)\mathrm{\ }\mathrm{\ }\\ \mathrm{\ }\end{array}}$

Where: V_present is total built up area in current year

V_past is total built up area in past year

t is the number of years between V_present and V_past (or length in years of the period considered)

1. Spatial analysis and computation of the population growth rate

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.

The (annual) population growth rate is calculated using the total population within the urban area for the analysis period using the formula below:

Population Growth rate i.e. $\mathbf{\ }\mathbf{P}\mathbf{G}\mathbf{R}=\frac{\mathbf{L}\mathbf{N}\left({\mathbf{P}\mathbf{o}\mathbf{p}}_{\mathbf{t}+\mathbf{n}}/{\mathbf{P}\mathbf{o}\mathbf{p}}_{\mathbf{t}}\right)}{\left(\mathbf{y}\right)}$

Where

LN is the natural logarithm value

Pop_t is the total population within the urban area/city in the past/initial year

Pop_t+n is the total population within the urban area/city in the current/final year

y is the number of years between the two measurement periods

1. Computation of the ratio of land consumption rate to population growth rate

The ratio of land consumption rate (LCRPGR) to population growth rate is calculated using the formula:

$\mathbf{L}\mathbf{C}\mathbf{R}\mathbf{P}\mathbf{G}\mathbf{R}=\mathbf{\ }\left(\left(\frac{\mathbf{\ }\mathbf{L}\mathbf{a}\mathbf{n}\mathbf{d}\mathbf{\ }\mathbf{C}\mathbf{o}\mathbf{n}\mathbf{s}\mathbf{u}\mathbf{m}\mathbf{p}\mathbf{t}\mathbf{i}\mathbf{o}\mathbf{n}\mathbf{\ }\mathbf{r}\mathbf{a}\mathbf{t}\mathbf{e}}{\mathbf{\ }\mathbf{P}\mathbf{o}\mathbf{p}\mathbf{u}\mathbf{l}\mathbf{a}\mathbf{t}\mathbf{i}\mathbf{o}\mathbf{n}\mathbf{\ }\mathbf{g}\mathbf{r}\mathbf{o}\mathbf{w}\mathbf{t}\mathbf{h}\mathbf{\ }\mathbf{r}\mathbf{a}\mathbf{t}\mathbf{e}}\right)\right)$

The overall formula can be summarized as:

$\mathbf{L}\mathbf{C}\mathbf{R}\mathbf{P}\mathbf{G}\mathbf{R}=\raisebox{1ex}{$\left(\frac{\mathrm{V}\mathrm{p}\mathrm{r}\mathrm{e}\mathrm{s}\mathrm{e}\mathrm{n}\mathrm{t}-\mathrm{V}\mathrm{p}\mathrm{a}\mathrm{s}\mathrm{t}}{\begin{array}{c}Vpast\mathrm{\ }\mathrm{\ }\\ \mathrm{\ }\end{array}}\mathrm{\ }\mathrm{*}\mathrm{\ }\frac{1}{\begin{array}{c}T\mathrm{\ }\mathrm{\ }\\ \mathrm{\ }\end{array}}\right)$}\!\left/ \!\raisebox{-1ex}{$\left(\frac{\mathbf{L}\mathbf{N}\left(\frac{{\mathbf{P}\mathbf{o}\mathbf{p}}_{\mathbf{t}+\mathbf{n}}}{{\mathbf{P}\mathbf{o}\mathbf{p}}_{\mathbf{t}}}\right)}{\mathbf{y}}\right)$}\right.\mathbf{\ }$

The analysis years for both the land consumption rate and the population growth rate should be the same.

1. Computation of recommended secondary indicators

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:

1. Built-up area per capita – 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:

$\mathbf{B}\mathbf{u}\mathbf{i}\mathbf{l}\mathbf{t}-\mathbf{u}\mathbf{p}\mathbf{\ }\mathbf{a}\mathbf{r}\mathbf{e}\mathbf{a}\mathbf{\ }\mathbf{p}\mathbf{e}\mathbf{r}\mathbf{\ }\mathbf{c}\mathbf{a}\mathbf{p}\mathbf{i}\mathbf{t}\mathbf{a}\mathbf{\ }(\mathbf{m}2/\mathbf{p}\mathbf{e}\mathbf{r}\mathbf{s}\mathbf{o}\mathbf{n})\mathbf{\ }=\mathbf{\ }\left(\left(\frac{\mathbf{\ }{\mathbf{U}\mathbf{r}\mathbf{B}\mathbf{U}}_{\mathbf{t}}}{\mathbf{\ }{\mathbf{P}\mathbf{o}\mathbf{p}}_{\mathbf{t}}}\right)\right)$

Where

UrBU_t is the total built-up area/city in the urban area in time t (in square meters)

Pop_t is the population in the urban area in time t

1. Total change in built up area – 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:

$\mathbf{T}\mathbf{o}\mathbf{t}\mathbf{a}\mathbf{l}\mathbf{\ }\mathbf{c}\mathbf{h}\mathbf{a}\mathbf{n}\mathbf{g}\mathbf{e}\mathbf{\ }\mathbf{i}\mathbf{n}\mathbf{\ }\mathbf{b}\mathbf{u}\mathbf{i}\mathbf{l}\mathbf{t}\mathbf{\ }\mathbf{u}\mathbf{p}\mathbf{\ }\mathbf{a}\mathbf{r}\mathbf{e}\mathbf{a}\mathbf{\ }\left(\mathbf{\%}\right)\mathbf{\ }=\mathbf{\ }\frac{\left({\mathbf{U}\mathbf{r}\mathbf{B}\mathbf{U}}_{\mathbf{t}+\mathbf{n}}-\mathit{\ }{\mathbf{U}\mathbf{r}\mathbf{B}\mathbf{U}}_{\mathbf{t}}\right)}{{\mathbf{U}\mathbf{r}\mathbf{B}\mathbf{U}}_{\mathbf{t}}}$

Where

UrBU_{t +n} is the total built-up area in the urban area/city in time the current/final year

UrBU_t is the total built-up area in the urban area/city in time the past/initial year

Detailed steps for computation of the core indicator and the secondary indicators are available in the detailed training module for indicator 11.3.1: https://unhabitat.org/sites/default/files/2020/07/indicator_11.3.1_training_module_land_use_efficiency_french.pdf

2021-03-01

United Nations Human Settlements Programme (UN-Habitat)

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2