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Last remote commit Merge pull request #289 from weblate/weblate-sdg-metadata-1-1-1a da8a3e7076
User avatar jenpark9 authored 16 hours ago
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Translation file translations/fr/6-6-1a.po
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Resource update

SDG Metadata / 6-6-1aFrench

Resource update 3 weeks ago
User avatar mirigaj

New translation

SDG Metadata / 6-6-1aFrench

<h1>References</h1>
<h2>URL: </h2>
<p><a href="http://www.sdg6monitoring.org/indicators/target-66/indicators661/">http://www.sdg6monitoring.org/indicators/target-66/indicators661/</a></p>
<h1>Additional information</h1>
<p>The methodology was tested in two pilot phases. The first of these involved designing the methodology in consultation with countries resulting in a first draft of the methodology which was reviewed and strengthened by the Target Team. In early 2016, the draft methodology was pilot tested in five countries between April and November 2016 through workshops: Jordan, the Netherlands, Peru, Senegal, and Uganda. In each of these countries, various participants from national entities and government sectors were engaged to obtain wide feedback on the technical feasibility of the draft methodology. </p>
<p>During the 2016 country pilots of the draft methodology, the NSO from each of the 5 countries was consulted and engaged in the process. During the 2017 pilot methodology data drive, the initial request for data was communicated to all NSOs. In addition, in October 2017 national data on spatial extent of open water (derived from earth observations) was shared with 188 countries, directly via their NSOs (see further details above).</p>
<h1>Références</h1>
<h2>URL : </h2>
<p><a href="http://www.sdg6monitoring.org/indicators/target-66/indicators661/">http://www.sdg6monitoring.org/indicators/target-66/indicators661/</a></p>
<h1>Information supplémentaire</h1>
<p>La méthodologie a été testée en deux phases pilotes. La première consistait à concevoir la méthodologie en consultation avec les pays, ce qui a donné lieu à une première ébauche de la méthodologie qui a été revue et renforcée par l'équipe cible. Au début de 2016, le projet de méthodologie a été testé dans cinq pays entre avril et novembre 2016 dans le cadre d'ateliers : Jordanie, Pays-Bas, Pérou, Sénégal et Ouganda. Dans chacun de ces pays, divers participants des entités nationales et des secteurs gouvernementaux ont été engagés pour obtenir un large retour d'information sur la faisabilité technique du projet de méthodologie. </p>
<p>Lors des essais pilotes de 2016 du projet de méthodologie, l'INS de chacun des 5 pays a été consulté et a participé au processus. Lors de la campagne de collecte de données de la méthodologie pilote de 2017, la demande initiale de données a été communiquée à toutes les OSN. De plus, en octobre 2017, les données nationales sur l'étendue spatiale des eaux libres (dérivées des observations de la terre) ont été partagées avec 188 pays, directement via leurs OSN (voir plus de détails ci-dessus). </p>
3 weeks ago
User avatar mirigaj

New translation

SDG Metadata / 6-6-1aFrench

<h2>Sources of discrepancies:</h2>
<p>NA</p>
<h2>Sources des divergences : </h2>
<p>NA</p>
3 weeks ago
User avatar mirigaj

New translation

SDG Metadata / 6-6-1aFrench

<h1>Data availability</h1>
<h2>Description:</h2>
<p>The data for Sub-Indicators 1 and 2 is available annually. For Sub-Indicators 3, 4, and 5, data is already available from some countries and national authorities should strengthen their monitoring and report efforts to expand data availability for these three sub-indicators.</p>
<p>Data collection for all Sub-Indicators was included in a 2017 data drive to countries; however, the data is still being validated. In addition, national spatial extent data for 188 countries has been collected from 2001-2015 to support Sub-Indicator 1. Data for all 5 Sub-Indicators is reported to UNSD every 5 years.</p>
<h2>Time series:</h2>
<p>The reporting on this indicator will follow an annual cycle. </p>
<h2>Disaggregation:</h2>
<p>Indicator 6.6.1 can be disaggregated by each Sub-Indicator. All Sub-Indicators can also be disaggregated at different spatial scales i.e.. National, basin, and ecosystem type.</p>
<h1>Disponibilité des données </h1>
<h2>Description : </h2>
<p>Les données des sous-indicateurs 1 et 2 sont disponibles chaque année. Pour les sous-indicateurs 3, 4 et 5, des données sont déjà disponibles dans certains pays et les autorités nationales devraient renforcer leurs efforts de surveillance et de notification pour accroître la disponibilité des données pour ces trois sous-indicateurs</p>.
<p>La collecte de données pour tous les sous-indicateurs a été incluse dans une campagne de collecte de données de 2017 auprès des pays ; cependant, les données sont encore en cours de validation. En outre, des données sur l'étendue spatiale nationale pour 188 pays ont été collectées de 2001 à 2015 pour soutenir le sous-indicateur 1. Les données pour les 5 sous-indicateurs sont communiquées à la DSNU tous les 5 ans. </p>
<h2>Séries chronologiques : </h2>
<p>Les rapports sur cet indicateur suivront un cycle annuel. </p>
<h2>Désagrégation:</h2>
<p>L'indicateur 6.6.1 peut être désagrégé par sous-indicateur. Tous les sous-indicateurs peuvent également être désagrégés à différentes échelles spatiales, c'est-à-dire Type de pays, de bassin et d'écosystème. </p>
3 weeks ago
User avatar mirigaj

New translation

SDG Metadata / 6-6-1aFrench

<h2>Regional aggregates:</h2>
<p>For the aggregation methods, please see: </p>
<p><a href="http://pre-uneplive.unep.org/media/docs/graphs/aggregation_methods.pdf">http://pre-uneplive.unep.org/media/docs/graphs/aggregation_methods.pdf</a></p>
<h2>Agrégats régionaux : </h2>
<p>Pour les méthodes d'agrégation, voir : </p>
<p><a href="http://pre-uneplive.unep.org/media/docs/graphs/aggregation_methods.pdf">http://pre-uneplive.unep.org/media/docs/graphs/aggregation_methods.pdf</a></p>
3 weeks ago
User avatar mirigaj

New translation

SDG Metadata / 6-6-1aFrench

<h2>Treatment of missing values:</h2>
<ul>
<li><strong><em>At country level:</em></strong></li>
</ul>
<p>Due to the use of satellite data for some sub-indicators, it is not expected to have missing data for these sub-indicators. For all other sub-indicators, missing values are not imputed. </p>
<ul>
<li><strong><em>At regional and global levels:</em></strong></li>
</ul>
<p>Missing values are not imputed.</p>
<h2>Traitement des valeurs manquantes : </h2>
<ul>
<li><strong><em>Au niveau national : </em></strong></li>
</ul>
<p>En raison de l'utilisation de données satellitaires pour certains sous-indicateurs, il ne devrait pas y avoir de données manquantes pour ces sous-indicateurs. Pour tous les autres sous-indicateurs, les valeurs manquantes ne sont pas imputées. </p>
<ul>
<li><strong><em>Aux niveaux régional et mondial : </em></strong></li>
</ul>
<p>Les valeurs manquantes ne sont pas imputées.</p>
3 weeks ago
User avatar mirigaj

New translation

SDG Metadata / 6-6-1aFrench

<h1>Methodology</h1>
<h2>Computation method:</h2>
<p>The 5 Sub-Indicators are computed separately and thus Indicator 6.6.1 is comprised of 5 stand-alone methodologies. </p>
<p><strong><em>Sub-Indicator 1: Spatial Extent of Water-related Ecosystems</em></strong></p>
<p>The methodology for this Sub-Indicator describes how Earth observations are generated and processed into a global spatial extent of water-related ecosystems dataset. The basic premise of this approach is that different land covers, such as snow, bare rock, vegetation, and water, reflect different wavelengths of light. Satellites continually circulate our earth, capturing images and wavelengths reflected from every location on the globe. For any one location on earth, thousands of images can be combined to classify the site&#x2019;s land cover. Advanced computing technology can be programmed to digest all of these images and split the earth into land cover type pixels, one of which is open water. Open water is defined as any area of surface water unobstructed by aquatic vegetation. Thus, changes in the spatial extent of open water locations over a long period of time can be discerned including new and lost waterbodies or seasonal changes. </p>
<p>To distinguish one water-related ecosystem type from another, further processing of this open water data is required in conjunction with other datasets. The data generated on open water is further distinguished into lakes, rivers and estuaries versus artificial waterbodies. In addition, vegetated wetlands are discerned through further processing. The method to detect vegetated wetlands from Earth observations is based on an approach which detects the physical properties of wetland areas (e.g. soil moisture and vegetation water content) from multi-temporal SAR (Synthetic Aperture Radar) and optical satellite imagery, combined with other geospatial datasets related to the topography of the area, the hydrography of the watershed and its drainage network, and the soil types. The resulting datasets obtained from earth observations on the spatial extent of vegetated wetlands and artificial waterbodies are excluded from the calculation of spatial extent values for lakes, rivers and estuaries, to prevent duplication of spatial extent estimations. </p>
<p>Thus, three global datasets are generated through this methodology annually: spatial extent of lakes, rivers, and estuaries; spatial extent of artificial waterbodies; and spatial extent of vegetated wetlands. These national spatial extent datasets are provided to countries to validate. Once validated, the annual datasets are used to calculate percentage change of spatial extent over time, using a 2001-2005 baseline period. Subsequent five year averages are compared to this baseline. </p>
<p><img src="data:image/png;base64,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"></p>
<p>Where &#x3B2; = the average national spatial extent from 2001-2005 </p>
<p>Where &#x3B3; = the average national spatial extent of any other 5 year period</p>
<p><strong><em>Sub-Indicator 2: Water Quality of Lakes and artificial water bodies</em></strong></p>
<p>The methodology for this Sub-Indicator describes how Earth observations are generated and processed into two datasets of chlorophyll a (Chl) and total suspended solids (TSS) within lakes globally. Earth observations can only provide information on concentrations of in-water materials that affect the colour of water. These materials include Chl, which is the primary pigment in phytoplankton (the primary source of food on the food-chain), and TSS. The concentrations of Chl and TSS can be used as proxies to infer other important waterbody characteristics.</p>
<p>Chl and TSS results are derived using empirical algorithms, generated for each individual pixel to ensure the spatial variability within each lake is fully captured. Results are averaged over a year for each lake to produce lake-wide Chl and TSS concentrations and small localized fluctuations in concentration of these two parameters are not shown. On any one day, the pixels representing each concentration of Chl or TSS are quantified and a lake-wide average is determined for that day. </p>
<p>The change in concentration of both Chl and TSS can be determined from comparing an annual average against the baseline. This annual average Chl and TSS will be averaged every 5 years, which will be compared to the Chl and TSS baselines to generate a percentage change. The locations where percentage change is excessive can be targeted for increased water quality monitoring and management. </p>
<p><strong><em>Sub-Indicator 3: Quantity (Discharge) of Water in Rivers and Estuaries</em></strong></p>
<p>The methodology for this Sub-Indicator describes different techniques for countries to implement to monitor river and estuary discharge. These techniques can include gauging stations or discharge meters. The methodology does not prescribe the type of discharge measurement technique because selection should be based on the size and type of the waterbody, terrain and velocity of water flow, the desired accuracy of measurement, as well as finances available. However, any discharge data collected by countries must adhere to the following minimum criteria:</p>
<ul>
<li>Discharge data from each river/estuary monitored should be collected at least once per month. This data should then be averaged to obtain an annual average discharge per river/estuary monitored. </li>
<li>Each basin should have at minimum of one sampling location, at the point where its water exits into another basin or crosses a national boundary. </li>
</ul>
<p>Countries will submit 5 years of data on annual average discharges per basin to the custodian agencies. The data from these 5 years will be averaged to smooth short-term variability. To generate national percentage change of discharge over time, a common reference period for all basins must be established. This baseline period will be used to calculate percentage change of discharge for any subsequent 5-year period. To calculate percentage change in discharge for each five year period following the reference period, the following formula is used:</p>
<p><img src="data:image/png;base64,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"></p>
<p>Where &#x3B2; = historical 5 year reference discharge </p>
<p>Where &#x3B3; = the average discharge of 5 year period of interest</p>
<p><strong><em>Sub-Indicator 4: Quality of Water-related Ecosystems</em></strong></p>
<p>The methodology for this Sub-Indicator is described in SDG Indicator 6.3.2. The data collected for Indicator 6.3.2 is utilized for Sub-Indicator 4 to inform a calculation of percentage change over time in waterbodies with good ambient water quality. </p>
<p><strong>Sub-Indicator 5: Quantity of Groundwater within Aquifers</strong></p>
<p>The methodology for this Sub-Indicator describes a simplified technique for countries to monitor groundwater quantity within aquifers. The volume of groundwater stored in an aquifer is most traditionally estimated using a combination of parameters but for the purposes of Indicator 6.6.1 monitoring, the &#x2018;head&#x2019; or level of groundwater within an aquifer can solely be measured as a proxy for groundwater volume within an aquifer. Measuring the level of groundwater within an aquifer is done through the use of boreholes. The methodology does not prescribe the number of boreholes to be monitored per aquifer because the distribution of groundwater can be variable depending on the location and characteristics of aquifers. However, any groundwater level data collected by countries must adhere to the following minimum criteria:</p>
<ul>
<li>Point measurements of groundwater level within aquifers should be collected at least twice per year. This data should then be averaged to obtain an annual average groundwater level per aquifer monitored. Understanding the seasonal and other short term changes is a necessary aspect of management of groundwater but should only be considered as part of the local management of the groundwater.</li>
<li>Each aquifer monitored should have at minimum one borehole that can be used for groundwater level measurements.</li>
</ul>
<p>Countries will submit 5 years of data on annual average groundwater level per basin to the custodian agencies, which will be averaged to smooth short-term variability. To generate national percentage change of discharge over time, a common reference period for all basins must be established. This baseline period will be used to calculate percentage change of groundwater quantity for any subsequent 5-year period. To calculate percentage change in quantity for each five year period following the reference period, the following formula is used.</p>
<p><img src="data:image/png;base64,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"></p>
<p>Where &#x3B2; =historical 5 year reference groundwater level </p>
<p>Where &#x3B3; = the average groundwater level of 5 year period of interest</p>
<h1>Méthodologie</h1>
<h2>Méthode de calcul:</h2>
<p>Les 5 sous-indicateurs sont calculés séparément et, par conséquent, l’indicateur 6.6.1 est composé de 5 méthodologies autonomes.</p>
<p><strong><em>Sub-Indicateur 1 : Étendue spatiale des écosystèmes liés à l’eau</em></strong></p>
<p>La méthodologie de ce sous-indicateur décrit comment les observations de la Terre sont générées et traitées dans une étendue spatiale mondiale de l’ensemble de données sur les écosystèmes liés à l’eau. La prémisse de base de cette approche est que différentes couvertures terrestres, telles que la neige, la roche nue, la végétation et l’eau, reflètent différentes longueurs d’onde de lumière. Les satellites font circuler continuellement notre terre, capturant des images et des longueurs d’onde réfléchies de tous les emplacements du globe. Pour n’importe quel endroit sur terre, des milliers d’images peuvent être combinées pour classer le site et #x2019 la couverture terrestre. La technologie informatique de pointe peut être programmée pour digérer toutes ces images et diviser la terre en pixels de type couverture terrestre, dont l’eau libre. L’eau libre est définie comme n’importe quelle zone d’eau de surface dégagée par la végétation aquatique. Ainsi, des changements dans l’étendue spatiale des emplacements en eau libre sur une longue période de temps peuvent être discernés, y compris des corps d’eau nouveaux et perdus ou des changements saisonniers. </p>
<p> Pour distinguer un type d’écosystème lié à l’eau d’un autre, un traitement ultérieur de ces données sur l’eau libre est nécessaire conjointement avec d’autres ensembles de données. Les données générées en eau libre se distinguent davantage par les lacs, les rivières et les estuaires que par les corps aquatiques artificiels. De plus, les milieux humides végétalisé sont discernés par un traitement plus ultérieur. La méthode de détection des milieux humides végétalisées à partir des observations de la Terre est fondée sur une approche qui détecte les propriétés physiques des zones humides (p. ex. humidité du sol et teneur en eau végétale) à partir de sar multitemporels (radar d’ouverture synthétique) et d’imagerie satellite optique, combinée à d’autres ensembles de données géospatiales liés à la topographie de la région, à l’hydrographie du bassin versant et de son réseau de drainage, ainsi qu’aux types de sol. Les ensembles de données obtenus à partir d’observations terrestres sur l’étendue spatiale des zones humides végétalisées et des corps aquatiques artificiels sont exclus du calcul des valeurs d’étendue spatiale pour les lacs, les rivières et les estuaires, afin d’éviter la duplication des estimations de l’étendue spatiale. </p>
<p>Ainsi, trois ensembles de données mondiaux sont générés par cette méthodologie chaque année : l’étendue spatiale des lacs, des rivières et des estuaires; l’étendue spatiale des corps aquatiques artificiels; et l’étendue spatiale des zones humides végétalisées. Ces ensembles nationaux de données sur l’étendue spatiale sont fournis aux pays pour validation. Une fois validés, les ensembles de données annuels sont utilisés pour calculer le changement en pourcentage de l’étendue spatiale au fil du temps, à l’aide d’une période de référence 2001-2005. Les moyennes subséquentes sur cinq ans sont comparées à cette base de référence. </p>
<p><img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAeEAAABCCAMAAABXa57IAAAAAXNSR0IArs4c6QAAAARnQU1BAACxjwv8YQUAAAI6UExURf////7+/v39/fPz8+7u7vz8/Orq6vj4+NjY2JKSkpmZmfv7+9ra2uvr68rKyo2Njampqebm5r29vW5ubpaWlt7e3u/v76ysrIGBgX5+fnNzc7y8vPf398/Pz4CAgIWFhfr6+sLCwm1tbaOjo2dnZ7a2tuLi4tTU1IaGhl5eXrq6uoqKin19feXl5eTk5Hp6esvLy1VVVZOTk/Hx8cTExFhYWHV1dezs7NDQ0I6OjvLy8rOzs19fX6urq0RERLi4uFlZWfT09FpaWvX19XBwcEZGRszMzLCwsFJSUpWVlZ6enpqamqenp1ZWVqampvn5+WNjY4uLi4+Pj09PT8bGxnZ2doODg+fn56Ghobu7u0lJSYKCglBQUJubm/b29sjIyGVlZWZmZpSUlFFRUcDAwHJycunp6bm5udfX152dnW9vb7+/v6+vr8nJyaioqGxsbGhoaGtra9bW1pCQkHFxcaWlpeDg4GBgYNnZ2ePj46qqqvDw8NPT06SkpFNTU3h4eImJiejo6JGRkU1NTdLS0l1dXbS0tGRkZH9/f0dHR7W1tVRUVMPDw5+fn+Hh4aCgoGlpaZiYmGFhYXR0dK2traKiopycnMHBwbGxsbKysre3t8XFxdXV1e3t7VxcXNvb293d3YiIiFtbW76+voeHh5eXl9zc3Hx8fK6urt/f31dXV2pqaoSEhExMTHd3d8fHx87Ozs3NzWJiYnl5eYyMjHt7e9HR0U5OTkpKSktLS0hISEVFRUJCQgAAACnMincAAAC+dFJOU////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////wCTsNOGAAAACXBIWXMAACHVAAAh1QEEnLSdAAALBElEQVR4Xu2cy3UjKxCGZ8GKbDoBLcmBZadBNJAAEdzg7vdX0Q95ZFu2Nce2Dr896m6aR0G9QZ4/ExMTExMTExMTExMTExMTE/8EYVzvRfhog4lvRW3ROBZqvZNzqZXJ49+DvMbKJZTe15697D2k3tVm4jcgr6aPIa451LbcyeLQ+tTi34Ham7EqLTLVaVnvZFxavd3ET0dZXWvLf7rez+EQlzRuJ3402moONcT/xLByiXq6iZCj2fMazW/npVjxxM9GWJrftEsNIQ+TfRM1drPk+WKV6jLN9G9AMKaBtqTU1/HwCuoqhY8Xt+t3G/SJ70S5uK0NbakoqcfVes7lwO5wC6F2Wt2Qh3Vy+Ddg96boMFyLm+klG1qVH9vvrtlYZrKrwfDuHnziZ6McHBa/ 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
3 weeks ago
User avatar mirigaj

New translation

SDG Metadata / 6-6-1aFrench

<h2>Comments and limitations:</h2>
<p>This methodology mobilizes the collection of widely available earth observation data on spatial extent and some water quality parameters which will be validated by countries. The data itself in the form of images and numbers is straightforward to understand. However, the methodologies used to generate this data are technical in nature and some countries may wish understand these better. The methodology employs internationally recognized methods, from expert communities such as the Group on Earth Observation (GEO) and international space agencies, to derive statistically sound and the most technologically advanced earth observation datasets for Sub-Indicators 1 and 2. These organizations will also be engaged to provided tools and training to support countries. Sub-Indicator 2 only measures two water quality parameters, while it is recognized that to determine good water quality requires measuring multiple parameters. However, globally available data can indicate potential hot spots of pollution or human disturbance allowing countries to undertake more local assessments of water quality.</p>
<p>The Indicator is designed in a way to generate data to allow informed decision making towards protecting and restoring water-related ecosystems. It does not measure how many water-related ecosystems have been protected and restored. It is assumed that countries would use the data to actively make decisions, but these actions are not currently being measured. The data generated should be considered alongside other data such as land use change to enable decision-makers to protect and restore water-related ecosystems.</p>
<h2>Commentaires et limitations : </h2>
<p>Cette méthodologie mobilise la collecte de données d'observation de la terre largement disponibles sur l'étendue spatiale et certains paramètres de qualité de l'eau qui seront validés par les pays. Les données elles-mêmes, sous forme d'images et de chiffres, sont faciles à comprendre. Cependant, les méthodologies utilisées pour générer ces données sont de nature technique et certains pays souhaiteront peut-être mieux les comprendre. La méthodologie utilise des méthodes reconnues au niveau international, provenant de communautés d'experts telles que le Groupe sur l'observation de la Terre (GEO) et les agences spatiales internationales, pour obtenir des ensembles de données d'observation de la Terre statistiquement solides et les plus avancés technologiquement pour les sous-indicateurs 1 et 2. Ces organisations seront également engagées à fournir des outils et des formations pour aider les pays. Le sous-indicateur 2 ne mesure que deux paramètres de qualité de l'eau, alors qu'il est reconnu que pour déterminer la bonne qualité de l'eau, il faut mesurer plusieurs paramètres. Cependant, les données disponibles au niveau mondial peuvent indiquer des points chauds potentiels de pollution ou de perturbation humaine, ce qui permet aux pays d'entreprendre des évaluations plus locales de la qualité de l'eau. </p>
<p>L'indicateur est conçu de manière à générer des données permettant une prise de décision éclairée en vue de protéger et de restaurer les écosystèmes liés à l'eau. Il ne mesure pas le nombre d'écosystèmes liés à l'eau qui ont été protégés et restaurés. On suppose que les pays utiliseraient les données pour prendre des décisions actives, mais ces actions ne sont pas mesurées actuellement. Les données générées doivent être prises en compte parallèlement à d'autres données telles que le changement d'utilisation des terres pour permettre aux décideurs de protéger et de restaurer les écosystèmes liés à l'eau. </p>
3 weeks ago
User avatar mirigaj

New translation

SDG Metadata / 6-6-1aFrench

<h2>Rationale:</h2>
<p>Target 6.6 aims to &#x201C;protect and restore water-related ecosystems, including mountains, forests, wetlands, rivers, aquifers and lakes&#x201D; through Indicator 6.6.1 which aims to understand how and why these ecosystems are changing in extent over time. All of the different components of Indicator 6.6.1 are important to form a comprehensive picture that enables informed decisions towards the protection and restoration of water-related ecosystems. However, a lack of data within countries to support Indicator 6.6.1 has become clear through the 2017 pilot testing and thus a combination of national data and data based on satellite images is proposed. All data generated is processed using internationally recognized methodologies, resulting in high quality global datasets with extensive spatial and temporal scale.</p>
<h2>Raison d'être :</h2>
<p>La cible 6.6 vise à &#x201C; protéger et restaurer les écosystèmes liés à l'eau, notamment les montagnes, les forêts, les zones humides, les rivières, les aquifères et les lacs&#x201D; grâce à l'indicateur 6.6.1 qui vise à comprendre comment et pourquoi ces écosystèmes changent d'étendue au fil du temps. Toutes les différentes composantes de l'indicateur 6.6.1 sont importantes pour former un tableau complet qui permet de prendre des décisions éclairées en vue de la protection et de la restauration des écosystèmes liés à l'eau. Cependant, le manque de données dans les pays pour soutenir l'Indicateur 6.6.1 est devenu évident lors de l'essai pilote de 2017 et c'est pourquoi une combinaison de données nationales et de données basées sur des images satellites est proposée. Toutes les données générées sont traitées selon des méthodologies reconnues au niveau international, ce qui permet d'obtenir des ensembles de données mondiales de haute qualité à grande échelle spatiale et temporelle. </p>
3 weeks ago
User avatar mirigaj

New translation

SDG Metadata / 6-6-1aFrench

<h1>Data compilers</h1>
<ol>
<li> UN Environment (United Nations Environment Programme) </li>
</ol>
<h1>Compilateurs de données </h1>
<ol>
<li>NU Environnement (Programme des Nations unies pour l'environnement) </li>
</ol>
3 weeks ago
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Last change Dec. 23, 2020, 6:28 p.m.
Last author Diada Mirindi

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