Monitoring the 2030 Agenda in Mexico: Institutional Coordination and the Integration of Information
Mexico is one of only two countries in the world, together with Brazil, where the National Statistical Office and the National Mapping Agency have been integrated into a single organisation. Established in 1983 and granted constitutional autonomy in 2008, the National Institute of Statistics and Geography (INEGI, by its Spanish acronym) is the organisation in charge of the production and coordination of statistical and geographical information in Mexico, thus allowing the development of both disciplines in constant interaction.
Valuable feedback and benefits between producers of official statistics and geo-products, and the final users of such integrated data, allow for the development of better public policies, the monitoring of international goals and agreements, such as the SDGs, as well as swifter and more accurate decision-making during disaster management situations.
4.1 Institutional setting
In 2008, INEGI became the single public agency responsible for coordinating and regulating the newly-created National System of Statistical and Geographical Information (SNIEG), whose main function is to collect, process and publish information of national interest, in other words to generate, coordinate and disseminate the nation’s official data. The SNIEG provides the Mexican State, and society, with high quality, timely and freely available information that can aid in national development and other processes. It produces statistical and geographic information on all areas of sustainable development (economic, socio-demographic, environmental and on government and justice); disseminates it in a timely fashion; promotes the knowledgeable use of such information; and is responsible for storing and preserving this information.
With all the associated tools that this integration has allowed, it is possible to geo-reference many relevant statistics; determine the exact location of economic, social and environmental issues and needs, including the unveiling of otherwise hidden inequalities and other complex interactions; and monitor damage, rescue and recovery efforts deriving from natural disasters and other emergencies that help improve public programmes and maximize resources for the overall benefit of people and territory. The use of satellite imagery, as well as other EO-derived data, has been key in the geo-statistical integration process and several tools have been developed to aid in policy design and monitoring in all dimensions of sustainable development.
Geo-statistical integration has allowed for the development of a free and open online platform, known as the Digital Map of Mexico (MxSIG). This adaptable, user-specific geo-statistical information integration and visualization software features a built-in system of international standards, is free to download and use, and does not require additional commercial software licenses. It allows the visualization and analysis of geographic and geo-referenced statistical information offering 208 vector data layers, with more than 71 million geographic objects and 4 raster layers covering the whole country, including geographical limits, geodesy, water infrastructure, geographical names, hydrography, terrain data, geographical addresses and localities.
In addition to these institutional settings and integrative tools designed to fulfil national priorities, with the integration of statistics and geography at its core, Mexico has undertaken a state-wide effort for the monitoring and fulfilment of the Sustainable Development Goals (SDGs), through a National Council for the 2030 Agenda for Sustainable Development, coordinated at the highest level by the Office of the President and involving all relevant state units, including line Ministries, Congress, and state and municipal governments. This cross-sector initiative includes an online platform (www.agenda2030.mx) that includes information on national SDG measurement and monitoring progress. Currently, 25 SDG indicators are ready to be measured at a national level, with further additions and updates expected on a regular basis. According to a recent national crosscutting analysis, there is sufficient – and consistent – data and methodologies to adequately measure up to 94 SDG indicators (i.e., considered as belonging to Tier I according to the IAEG-SDG classification), compared to 81 globally according to the UN system. Also, upwards of 50 indicators have been identified at the national level that could either directly benefit from the contribution of geospatial information and/or Earth observations (GI/EO), or complement and enrich the information provided by statistics and administrative records.
Based on the IAEG-SDG Global Indicator Framework, a comprehensive analysis has also delivered a list whereby both geospatial and EO data can contribute to better measurements (including transitioning from a Tier III to a Tier II, or even a Tier I, classification), either directly or indirectly. A number of such examples are presented herewith.
This national effort follows Mexico’s international leadership on the 2030 Agenda follow-up and the use therein of GI/EO. This includes the country’s active participation in the multilateral negotiations at the United Nations leading to the 2030 Agenda and SDGs, as well as its current role, through INEGI, as co-chair of the IAEG-SDGs and of the IAEG-SDGs’ Working Group on Geospatial/EO information. In this regard, Mexico’s participation in the United Nations Committee of Experts on Global Geospatial Information Management (UN-GGIM), as well as in the Group on Earth Observations (GEO) through its initiative in support of the 2030 Agenda (EO4SDG), has been particularly fruitful.
Furthermore, a collaboration is currently underway between Mexico (through INEGI and the Environment Ministry SEMARNAT), the United Nations Statistics Division (UNSD) and UN Environment on the implementation of the System of Environmental Economic Accounting – Experimental Ecosystem Accounting (SEEA EEA), including the use of EO and geospatial information in support of the SEEA framework. A further article on this topic may be found in Part II of this Handbook.
Table 1: Mexico’s integrated use of geospatial/EO information and statistics to monitor national and global indicators.
4.2 Measurement of specific SDG Indicators using EO and GI
Indicator 9.1.1 – Proportion of the rural population who live within 2 km of an all-season road.
This indicator is derived using a combination of statistical (Census Data, ITER 2010) and geographic data (National Topographic Data Set, including transportation layers and validation using satellite imagery).
Indicator 15.1.1 – Forest area as a proportion of total land area
This indicator is derived entirely from geospatial and satellite data. It uses five datasets of land use and vegetation (derived from remote-sensing images). The classification system comprises 57 types of vegetation, including temperate and tropical forests, grasslands, shrubland, mangroves and other categories, such as agricultural and built-up/urban areas.
Indicator 15.3.1 – Proportion of land that is degraded over total land area
According to the UN Convention to Combat Desertification (UNCCD), this indicator is defined as the amount of land area that is degraded. Its measurement unit is the spatial extent expressed as the proportion of land that is degraded over total land area. Indicator 15.3.1 is derived by summing all those areas subject to change, whose conditions are considered negative by national authorities (i.e., land degradation) while using ‘good practice guidance’ in the measurement and evaluation of changes to each of the following three sub-indicators:
i. Land cover and land cover change, which can be derived from the land cover and vegetation time series, as described for indicator 15.1.1 (see above). In Mexico, these indices are already being calculated for national reports on carbon emissions due to land cover/use change, as well as on reports on deforestation by the FAO’s Global Forest Resources Assessments (FRA).
ii. Land productivity, which is calculated using the normalized difference vegetation index (NDVI), a simple graphical indicator that can be used to analyse remote-sensing measurements, typically from a space platform, and assess whether the target being observed contains live green vegetation or not. In Mexico, this index is calculated using MODIS, Landsat and Sentinel satellite imagery, which acquire data in visible and near-infrared in plant reflectance to determine spatial distribution.
iii. Carbon stocks above and below ground, calculated using digital mapping from organic carbon content in soil samples, together with field data from around 20,000 soil profiles in Mexico’s National Forest and Soil Inventory (INFyS) by the National Forestry Commission (CONAFOR).
All indicators related to land cover, land use, land degradation, agricultural area and the like benefit both from the Land Use and Vegetation Chart Series (scale 1:250,000) mentioned earlier and from the National Forest and Soil Inventory (www.cnf.gob.mx:8090/snif/portal/infys).
The INFyS is updated yearly (and completely every five years) using satellite imagery and field data, including GPS and photography, through the measurement of over 170 variables. Data collection in the field is the systematic stratification of over 26,000 conglomerates (from over 81,000 sampling sites), covering all climates and vegetation in the country. This information is combined with data on roads, watersheds, climate, soils, natural protected areas and various forest inventories. Forest monitoring involves the interpretation of MODIS satellite images by means of specialized software, and supported by the field work for the INFyS, to determine the dynamics of changes in vegetation every year.
4.3 EO/GI in the monitoring of other processes for the 2030 Agenda
Disaster risk reduction
When disaster strikes, geospatial information becomes a critical asset for actions that can mitigate its effects. This information should be timely, accessible and of adequate quality to offer the best response possible.
To ensure the availability of this information in Mexico, INEGI has put into operation a collaborative online platform for disaster response, the Collaborative Site for Disaster Response, where the relevant state agencies can exchange information to perform their respective functions in a more timely and efficient manner.
The collaborative site is a restricted access website for users at several government agencies ranging from those related to the production of disaster-related geospatial and statistical information to those directly in charge of the emergency response. These include the Interior, Transportation, Environment, Energy, Agriculture, Army and Navy ministries, among other entities, coordinated by the Disaster Prevention Centers and the Civil Protection System.
Once an authorized user gains access to the main page, the following sections are displayed: Recent Events, Historic Events, Available Information, News, and Contact Information.
The section on Recent Events contains information related to disaster events where the response is on-going or has occurred within the past year. Each event can be considered as a ‘sub-site’ within the main site. Access is given to relevant datasets, either through links to downloadable files or the URLs to Web Map Services. Examples are population (census) data at the street block level for towns or cities in the affected area, hydrographic networks, road networks and satellite imagery, both prior to the event and, whenever possible, in the hours or days after the event so that affected areas and features can be located.
Figure 1: Calculation of SDG indicator 9.1.1 (Proportion of the rural population who live within 2 km of an all-season road), using census, topographic, road and satellite data. Green: populated places within 2 km of an all-season road. Pink: populated places further than 2 km from an all-season road.
A specific message board is created for each event, so that multiple users can exchange comments, questions and experiences. There is also a section for data visualization.
The Historic Events section provides access to data sets related to events that happened in previous years or where the emergency phase has ended. The general structure of this section is the same as that for recent events.
As a disaster may occur anytime and anywhere in the country, the Available Information section gives permanent access to some basic – or framework – data sets. Access to this information is through downloadable links or URLs to Web Services: Web Map Services, Web Feature Services and Web Coverage Services.
This multi-user data-sharing platform relies on satellite optical and radar data, along with other EO sources. Different types of satellite data are acquired in consideration of the type of disaster and meteorological conditions. Optical data is used for fires, earthquakes, volcanoes, floods and landslides. Before/after images are mainly supplied by the Army and Navy, as well as by drones from the Disaster Prevention Center (CENAPRED), and supplemented by private providers, which are regulated through flying permits.
Radar data are used for floods, landslides and earthquakes, and for all of the above in case there are no conditions for optical imaging. Vertical displacements are identified using interferometry. Also, Global Navigation Satellite System (GNSS) data is used to quantify land displacements after earthquakes. Additionally, volunteered geographic information (VGI), in the form of geo-tagged photographs and other types of geo-referenced citizen data, is incorporated to the site after proper validation and can prove particularly valuable, especially in cases where communications have been affected or an affected site has been isolated after a disaster.
This platform has been instrumental during past emergencies, such as when hurricanes Ingrid and Manuel struck the Atlantic and Pacific coasts of Mexico within a 24-hour period in September 2013. More recently, it proved key during the response to hurricanes Franklin, Katia and José, as well as several powerful earthquakes affecting southern states and Mexico City in September 2017.
Figure 2: Overview of the national collaborative site for disaster response and preparedness, including coordinated data inputs from relevant agencies for recent and historic events.
4.4 National Gender Atlas
This is an online platform aimed at gathering, integrating and visualizing, in a geographic context, some of the most outstanding socio-demographic and economic indicators with a gender perspective, to make visible not only the gender differences but also the additional differences derived from their geographical location disaggregated at the state level of the national territory. Maps that show the behaviour of demographic, social, work, time use, entrepreneurship, poverty, decision-making and violence against women, related to human rights and with issues of public interest, are easily accessed on the portal (http://gaia.inegi.org.mx/atlas_genero).
The Gender Atlas derives from a collaborative agreement between INEGI, The National Women’s Institute (INMUJERES), UN Women and the UN Economic Commission for Latin America and the Caribbean (UN ECLAC). Launched in 2016, it is oriented towards policy analyses that derive in substantive gender and regional equality. It is presented as an online platform for easy access and visualization of the issues addressed. It contains both statistical data and references to the sources of the indicators that are presented on the maps.
Figure 3: Radarsat image acquired after Hurricane Patricia made landfall in the state of Colima, on October 24th 2015. The blue polygon shows a flooded area, mostly cropland, around the Marabasco river.
Currently, the site includes 78 national indicators related to gender statistics, including SDG 5 indicators on gender equality. Metadata include methodological aspects and geographic disaggregation. The information of the Gender Atlas will be updated and expanded on a permanent basis, considering new statistics as well as national planning and government programmes and policies and international agreements linked to the empowerment of women and equality between women and men. Efforts are underway to develop similar platforms in other Latin American countries, which would be linked and interoperable for cross-regional analyses. Its multi-dimensional nature will ensure that gender, as envisioned in the SDGs, will be addressed in a cross-cutting and integral way, considering its social, economic, political, administrative, environmental and geographical aspects.
Figure 4: Drone image over Juchitan, Oaxaca, showing collapsed buildings after the 8.1 magnitude earthquake on 7 September 2017.
4.5 Conclusions
– Geospatial Information, Earth Observations, Big Data and Statistics can and should be integrated in support of national policies and the implementation of international agreements. Efforts should be made at the national, regional and global levels to generate collect and curate these sources of information in a high-quality and consistent manner for their systematic use in complementing official statistics/information in a sustainable manner.
– Geospatial information facilitates the monitoring of social, economic and environmental indicators to support, design and monitor public policies.
– Integration facilitates location of needs, assessment of policy/global goals (such as the SDGs), as well as progress over time.
– Institutional capacity and inter-institutional coordination, including with non-state actors such as the private sector, academia and civil society, are key in order to focus skills and resources, avoid duplications and effectively use all pertinent tools to achieve priorities.
– Participation from all sectors of society is key, including academia, civil society and the private sector.
Figure 5: Mapping of affected areas in Oaxaca City, Mexico after the 8.1-magnitude earthquake on September 7 using satellite images from different sources (visualization within the Collaborative Site for Disaster Response).
Article Contributors
Rolando Ocampo, Francisco Jimenez-Nava, Eduardo de la Torre (Instituto Nacional de Estadística y Geografía, INEGI; Mexico)
