Description: <div style="text-align:justify;"><span style="font-family:Arial, sans-serif; font-size:11pt;">This dataset shows the global distribution of
seamounts and knolls identified using global bathymetric data at 30 arc-sec
resolution. A total of 33,452 seamounts and 138,412 knolls were identified,
representing the largest global set of identified seamounts and knolls to date.
Seamount habitat was found to constitute approximately 4.7% of the ocean floor,
whilst knolls covered 16.3%. The research leading to these results received
funding from the European Community’s Seventh Framework Programme, and from the
International Union for Conservation of Nature (IUCN)</span></div>
Service Item Id: 4fbb2af154c74d2e8b1b24bd8bc69458
Copyright Text: Yesson C, Clark MR, Taylor M, Rogers AD (2011). The global distribution of seamounts based on 30-second bathymetry data. Deep Sea Research Part I: Oceanographic Research Papers 58: 442-453. DOI: http://dx.doi.org/10.1016/j.dsr.2011.02.004. Data DOI: http://doi.pangaea.de/10.1594/PANGAEA.757564.
Description: <div style="text-align:justify;">This dataset shows the global distribution of seamounts and knolls identified using global bathymetric data at 30 arc-sec resolution. A total of 33,452 seamounts and 138,412 knolls were identified, representing the largest global set of identified seamounts and knolls to date. Seamount habitat was found to constitute approximately 4.7% of the ocean floor, whilst knolls covered 16.3%. The research leading to these results received funding from the European Community’s Seventh Framework Programme, and from the International Union for Conservation of</div><div style="text-align:justify;">Nature (IUCN).</div>
Service Item Id: 4fbb2af154c74d2e8b1b24bd8bc69458
Copyright Text: Yesson C, Clark MR, Taylor M, Rogers AD (2011). The global distribution of
seamounts based on 30-second bathymetry data. Deep Sea Research Part I:
Oceanographic Research Papers 58: 442-453. DOI:
http://dx.doi.org/10.1016/j.dsr.2011.02.004. Data DOI:
http://doi.pangaea.de/10.1594/PANGAEA.757564.
Description: <p style="text-align:justify;"><span style="font-family:"Palatino Linotype", serif;"><font size="4">Il s’agit de la base de données des agglomérations de
l’Afrique de l’Ouest, tirée de la grande base d’Africapolis portant sur
l’ensemble du territoire africain. C’est une base de données standardisée et
géospatiale indispensable sur la dynamique de l'urbanisation en Afrique, dans
le but de rendre les données urbaines en Afrique comparables d'un pays à
l'autre et dans le temps. Cette base de données sur les agglomérations de
l’Afrique de l’Ouest concerne les petites villes et villes intermédiaires entre
10 000 et 300 000 habitants. Cependant, la base d’Africapolis n’intègre
pas certaines villes et villages de moins de 10 000 habitants, qui peuvent
néanmoins constituer des zones de bâti non négligeables pour caractériser
l’organisation et les dynamiques d’extension urbaine du littoral de l’Afrique
de l’ouest. Sur l’ensemble des 11 pays de la MOLOA, 271 agglomérations ont été
ajoutées dans le buffer de 25 km par rapport au trait de côte, qui a été élargi
pour le Sénégal, la Gambie et la Guinée Bissau le long des fleuves Gambie,
Gambie et Rio Cacheu. Ces agglomérations correspondent à des villages
présentant une densité de bâti qui le rend identifiable en parcourant les
images à la volée. L’identification sur les images à très haute résolution
s’est concentrée sur les villages se trouvant sur la côte, dans les zones de
mangrove, sur les bras des principaux fleuves, ou encore les villages
satellites des agglomérations. On a aussi cherché à identifier tous les noyaux carrefours
des principales voies de communication, en croisant les images à haute
résolution et la couche vectorisée et hiérarchisée du réseau routier de la
région. </font></span></p><p style="text-align:justify;"></p><p style="margin-right:11.25pt; text-align:justify;"><font size="4"><b><span style="font-family:"Palatino Linotype", serif;">Limites ou contraintes : </span></b><span style="font-family:"Palatino Linotype", serif;">Pas d’informations</span></font></p>
<p style="margin-bottom:8.0pt;"><font size="4"><b><span style="font-family:"Palatino Linotype", serif;">Projections cartographiques : </span></b><span style="font-family:"Palatino Linotype", serif;">WGS
1984</span></font></p>
<p style="margin-right:22.5pt; text-align:justify;"><b><span style="font-family:"Palatino Linotype", serif;"><font size="4">Liens en rapport avec les données : </font></span></b></p>
<p style="margin-right:22.5pt; text-align:justify; background:white;"><font size="4"><span style="font-family:"Palatino Linotype", serif; color:black;">Éclairer les politiques pour
l'avenir urbain de l'Afrique : </span><span style="color:black;"><a href="https://www.africapolis.org/home"><span style="font-family:"Palatino Linotype", serif;">https://www.africapolis.org/home</span></a></span><span style="font-family:"Palatino Linotype", serif; color:black;"> </span></font></p>
<p style><font size="4"><b><span style="font-family:"Palatino Linotype", serif;">Attributs</span></b></font></p>
<p style="margin-right:22.5pt;"><font size="4"><b><span style="font-family:"Palatino Linotype", serif;">ID</span></b><span style="font-family:"Palatino Linotype", serif;"> : Identifiant unique des agglomérations</span></font></p>
<p style="margin-right:22.5pt;"><font size="4"><b><span style="font-family:"Palatino Linotype", serif;">NOM</span></b><span style="font-family:"Palatino Linotype", serif;"> : Nom de l’agglomération</span></font></p>
<p style="margin-right:22.5pt;"><font size="4"><b><span style="font-family:"Palatino Linotype", serif;">PAYS</span></b><span style="font-family:"Palatino Linotype", serif;"> : Nom du pays dans lequel se trouve l’agglomération</span></font></p>
<p><font size="4"><b><span style="font-family:"Palatino Linotype", serif;">NIV_TOPO</span></b><span style="font-family:"Palatino Linotype", serif;"> : C’est le niveau d’hiérarchisation des agglomérations : ville principale,
ville secondaire, village et campement.</span></font></p><span style="font-size:10.0pt; font-family:"Palatino Linotype",serif;"></span>
Description: <p><span style="font-family:"Arial",sans-serif; color:#4C4C4C; background:white;">This dataset shows the known locations of sea
turtle nesting sites, for all seven species: hawksbill turtle (Eretmochelys
imbricata), Kemp's ridley turtle (Lepidochelys kempii), leatherback turtle
(Dermochelys coriacea), green turtle (Chelonia mydas), loggerhead turtle (Caretta
caretta), olive ridley turtle (Lepidochelys olivacea), and flatback turtle
(Natator depressus).</span></p>
Service Item Id: 4fbb2af154c74d2e8b1b24bd8bc69458
Copyright Text: UNEP-WCMC (1999). Global distribution of sea turtle nesting sites (version 1.1). Cambridge (UK): UNEP World Conservation Monitoring Centre. URL: http://data.unep-wcmc.org/datasets/22.
Description: <p style="text-align:justify; background:white;"></p><p style="text-align:justify; background:white;"><span style="font-family:"Palatino Linotype", serif; color:rgb(34, 34, 34);"><font size="4">La version initiale du Schéma
Directeur du Littoral d’Afrique de l’Ouest (SDLAO) avait été publiée et validé
en 2011. La rapidité du développement de l’occupation des littoraux qui avait
été constatée en 2011 impliquait d’une part la mise en place d’un mécanisme
régional d’observation, et d’autre part la planification d’une actualisation de
ce schéma directeur. Un an après la validation du SDLAO, la Mission
d’Observation du Littoral Ouest Africain (MOLOA) a été établie, comprenant une
coordination régionale et des antennes nationales au niveau de chacun des onze
pays partie prenant de l’initiative.</font></span></p>
<p style="text-align:justify; background:white;"><span style="font-family:"Palatino Linotype", serif; color:rgb(34, 34, 34);"><font size="4">L’ensemble du travail de suivi qui a été mis en œuvre
dans le cadre de ce dispositif est livré ici au travers de deux documents : une
actualisation du schéma directeur général, et une actualisation du schéma
directeur détaillé accompagnée d’une cartographie actualisée du SDLAO à
l’échelle du 1/500 000ème. Dans le cadre de cette actualisation, les priorités
qui avaient été initialement fixées pour l’intervention en matière de défense
des côtes et de réduction des risques côtiers et en matière de suivi et
d’observation ont été largement amendées en fonction des évolutions constatées.</font></span></p>
<p style="text-align:justify; background:white;"><span style="font-family:"Palatino Linotype", serif; color:rgb(34, 34, 34);"><font size="4">Le présent SDLAO est une version actualisée de celle de
2016, qui décrit les évolutions observées depuis 2011 et les niveaux de
criticité. Cette mise à jour est réalisée en rapport avec les antennes
nationales de la MOLOA (11 états côtiers de l’Afrique de l’Ouest, depuis la
Mauritanie jusqu’au Bénin, plus Sao Tomé et Principe) et le comité scientifique
régional.</font></span></p>
<p style="text-align:justify; background:white;"><span style="font-family:"Palatino Linotype", serif; color:rgb(34, 34, 34);"><font size="4">Ce Schéma Directeur Détaillé vise à
caractériser un territoire et mettre en exergue les problématiques majeures de
celui-ci en prenant en compte notamment l’impact du changement climatique sur
le littoral. À ce stade, le pays identifie la nécessité de mettre en place des
actions, mais ne les définit pas et ne les situe pas dans le temps. Ce travail
de définition et de priorisation est un travail interne à chaque territoire qui
pourrait être facilité par l’adhésion des territoires à l’Observatoire Régional
du Littoral Ouest Africain (ORLOA). À ce jour, il revient à chaque territoire,
avec l’appui de ses structures dédiées et de ses experts de définir celle-ci à
l’issue de l’analyse des éléments présentés dans le rapport à l’échelle d’un
territoire ou d’une problématique et au regard des ressources matérielles,
humaines et économiques disponibles.</font></span></p>
<p style="text-align:justify; background:white;"><font size="4"><b><span style="font-family:"Palatino Linotype", serif; color:rgb(34, 34, 34);">Limites : </span></b><span style="font-family:"Palatino Linotype", serif; color:rgb(34, 34, 34);">No informations</span></font></p>
<p style="text-align:justify; background:white;"><font size="4"><b><span style="font-family:"Palatino Linotype", serif; color:rgb(34, 34, 34);">Projection cartographique : </span></b><span style="font-family:"Palatino Linotype", serif; color:rgb(34, 34, 34);">WGS 1984</span></font></p>
<p style="text-align:justify; background:white;"><b><span style="font-family:"Palatino Linotype", serif; color:rgb(34, 34, 34);"><font size="4">Liens en rapport avec la couche d’information
géographique</font></span></b></p>
<p style="margin-top:0cm; margin-right:0cm; margin-bottom:8.0pt; margin-left:36.0pt; text-align:justify; text-indent:-18.0pt; background:white;"><font size="4">><span style="color:black;"><a href="https://www.iucn.org/fr/regions/afrique-centrale-et-occidentale/notre-travail/les-programme-thematiques-regionaux-dans-la-zone-du-paco/projets-acheves/developpement-du-mecanisme-dobservation-du-littoral-ouest-africain" target="_blank"><span style="font-family:"Palatino Linotype", serif; color:rgb(5, 99, 193);">https://www.iucn.org/fr/regions/afrique-centrale-et-occidentale/notre-travail/les-programme-thematiques-regionaux-dans-la-zone-du-paco/projets-acheves/developpement-du-mecanisme-dobservation-du-littoral-ouest-africain</span></a></span></font></p>
<p style="margin-top:0cm; margin-right:0cm; margin-bottom:8.0pt; margin-left:36.0pt; text-align:justify; text-indent:-18.0pt; background:white;"><font size="4">><span style="color:black;"><a href="https://www.wacaprogram.org/sites/waca/files/knowdoc/Littoraux%20d%27Afrique%20de%20l%27Ouest%20document%20general%20Version%20Francaise.pdf" target="_blank"><span style="font-family:"Palatino Linotype", serif; color:rgb(5, 99, 193);">https://www.wacaprogram.org/sites/waca/files/knowdoc/Littoraux%20d%27Afrique%20de%20l%27Ouest%20document%20general%20Version%20Francaise.pdf</span></a></span></font></p>
<p style="text-align:justify; background:white;"><font size="4"><b><span style="font-family:"Palatino Linotype", serif; color:rgb(34, 34, 34);">Date de création de la couche :</span></b><span style="color:rgb(34, 34, 34);"> </span><span style="font-family:"Palatino Linotype", serif; color:rgb(34, 34, 34);">2010</span></font></p>
<p style="text-align:justify; background:white;"><font size="4"><b><span style="font-family:"Palatino Linotype", serif; color:rgb(34, 34, 34);">Date de mise à jour de la couche :
</span></b><span style="color:rgb(34, 34, 34);"> </span><span style="font-family:"Palatino Linotype", serif; color:rgb(34, 34, 34);">02 décembre 2020</span></font></p><p style="text-align:justify; background:white;"></p><p style><font size="4"><b><span style="font-family:"Palatino Linotype", serif;">Attributs</span></b></font></p>
<p style="margin-top:0cm; margin-right:22.5pt; margin-bottom:0cm; margin-left:0cm; text-align:justify;"><font size="4"><b><span style="font-family:"Palatino Linotype", serif; color:black;">FID_1</span></b><span style="font-family:"Palatino Linotype", serif; color:black;"> : </span><span style="font-family:"Palatino Linotype", serif;">C’est l’identifiant unique d’un secteur donné. </span></font></p>
<p style="margin-top:0cm; margin-right:22.5pt; margin-bottom:0cm; margin-left:0cm; text-align:justify;"><font size="4"><b><span style="font-family:"Palatino Linotype", serif;">ZONE</span></b><span style="font-family:"Palatino Linotype", serif;"> : </span><span style="font-family:"Palatino Linotype", serif;">C’est le code de la zone à laquelle
appartient un secteur donné. Il est construit selon le code du pays (TCP ISO
3166), suivi d’un incrément numérique égal au nombre de zone dans un pays.</span></font></p>
<p style="margin-top:0cm; margin-right:22.5pt; margin-bottom:0cm; margin-left:0cm; text-align:justify;"><font size="4"><b><span style="font-family:"Palatino Linotype", serif;">PAYS</span></b><span style="font-family:"Palatino Linotype", serif;"> : Nom du pays auquel une zone ou un secteur appartient.</span></font></p>
<p style="margin-top:0cm; margin-right:22.5pt; margin-bottom:0cm; margin-left:0cm; text-align:justify;"><font size="4"><b><span style="font-family:"Palatino Linotype", serif;">REF</span></b><span style="font-family:"Palatino Linotype", serif;"> : </span><span style="font-family:"Palatino Linotype", serif;">C’est le code d’un secteur donné.
Il est construit en se basant du code de la zone plus un incrément alphabétique
égal au nombre de secteur présent dans une zone.</span></font></p>
<p style="margin-top:0cm; margin-right:22.5pt; margin-bottom:0cm; margin-left:0cm; text-align:justify;"><font size="4"><b><span style="font-family:"Palatino Linotype", serif;">SEGMENTS</span></b><span style="font-family:"Palatino Linotype", serif;"> : C’est la délimitation des secteurs suivant des repères
différents : les villes, les villages, les aires naturelles, etc.</span></font></p>
<p style="margin-top:0cm; margin-right:22.5pt; margin-bottom:0cm; margin-left:0cm; text-align:justify;"><font size="4"><b><span style="font-family:"Palatino Linotype", serif;">NOM ZONE</span></b><span style="font-family:"Palatino Linotype", serif;"> : </span><span style="font-family:"Palatino Linotype", serif;">Le nom de la zone.</span></font></p>
<p style="margin-top:0cm; margin-right:22.5pt; margin-bottom:0cm; margin-left:0cm; text-align:justify;"><font size="4"><b><span style="font-family:"Palatino Linotype", serif;">N</span></b><span style="font-family:"Palatino Linotype", serif;">° : C’est le numéro du secteur. Il est créé partant du nord vers
le sud. </span></font></p>
<p style="margin-top:0cm; margin-right:22.5pt; margin-bottom:0cm; margin-left:0cm; text-align:justify;"><font size="4"><b><span style="font-family:"Palatino Linotype", serif;">Type</span></b><span style="font-family:"Palatino Linotype", serif;"> : La cartographie porte sur l’échelle la plus fine et qui
concerne les secteurs. </span></font></p>
<p style="margin-top:0cm; margin-right:22.5pt; margin-bottom:0cm; margin-left:0cm; text-align:justify;"><font size="4"><b><span style="font-family:"Palatino Linotype", serif;">Dénominat</span></b><span style="font-family:"Palatino Linotype", serif;"> : Nom associé à un secteur donné. </span></font></p>
<p style="margin-top:0cm; margin-right:22.5pt; margin-bottom:0cm; margin-left:0cm; text-align:justify;"><font size="4"><b><span style="font-family:"Palatino Linotype", serif;">HABITAT</span></b><span style="font-family:"Palatino Linotype", serif;"> : Il s’agit des principales formes d’habitats naturels ou
artificiels notés dans un secteur donné. Ils concernent surtout les espaces
urbains, rurbains, rural, campement, petit village, mangrove zones humides et les
zones désertiques.</span></font></p>
<p style="margin-top:0cm; margin-right:22.5pt; margin-bottom:0cm; margin-left:0cm; text-align:justify;"><font size="4"><b><span style="font-family:"Palatino Linotype", serif;">ENJEUX</span></b><span style="font-family:"Palatino Linotype", serif;"> : Ce sont les différentes formes d’enjeux notés dans un secteur.</span></font></p>
<p style="margin-top:0cm; margin-right:22.5pt; margin-bottom:0cm; margin-left:0cm; text-align:justify;"><font size="4"><b><span style="font-family:"Palatino Linotype", serif;">ALEAS</span></b><span style="font-family:"Palatino Linotype", serif;"> : Ce sont les différentes formes d’aléas rencontrés dans un
secteur donné.</span></font></p>
<p style="margin-top:0cm; margin-right:22.5pt; margin-bottom:0cm; margin-left:0cm; text-align:justify;"><font size="4"><b><span style="font-family:"Palatino Linotype", serif;">Criti_2011</span></b><span style="font-family:"Palatino Linotype", serif;"> : </span><span style="font-family:"Palatino Linotype", serif;">Il s’agit du
niveau de criticité en 2011, c’est-à-dire l’impact des risques littoraux
(érosion côtière, inondations, les submersions marines, etc.) sur les personnes
et les biens. La criticité peut être aussi plus élevée pour le compartiment
« environnement » et avoir un impact notable sur la biodiversité, les
services écosystémiques, etc. l’échelle de criticité adoptée ici comporte 04
niveaux : faible, moyenne, élevée et très élevée. </span></font></p>
<p style="margin-top:0cm; margin-right:22.5pt; margin-bottom:0cm; margin-left:0cm; text-align:justify;"><font size="4"><b><span style="font-family:"Palatino Linotype", serif;">Criti_2016</span></b><span style="font-family:"Palatino Linotype", serif;"> : </span><span style="font-family:"Palatino Linotype", serif;">Il s’agit du
niveau de criticité en 2016. </span></font></p>
<p style="margin-top:0cm; margin-right:22.5pt; margin-bottom:0cm; margin-left:0cm; text-align:justify;"><font size="4"><b><span style="font-family:"Palatino Linotype", serif;">Criti_2020</span></b><span style="font-family:"Palatino Linotype", serif;"> : </span><span style="font-family:"Palatino Linotype", serif;">Il s’agit du
niveau de criticité en 2020.</span></font></p>
<p style="margin-top:0cm; margin-right:22.5pt; margin-bottom:0cm; margin-left:0cm; text-align:justify;"><font size="4"><b><span style="font-family:"Palatino Linotype", serif;">Evolu_Criti</span></b><span style="font-family:"Palatino Linotype", serif;"> : </span><span style="font-family:"Palatino Linotype", serif;">C’est l’évolution
du niveau de criticité entre 2016 et 2020. Il s’agit de voir si le niveau a
connu une baisse, hausse ou une stabilité.</span></font></p>
<p style="margin-top:0cm; margin-right:22.5pt; margin-bottom:0cm; margin-left:0cm; text-align:justify;"><font size="4"><b><span style="font-family:"Palatino Linotype", serif;">Suivi_2011</span></b><span style="font-family:"Palatino Linotype", serif;"> : </span><span style="font-family:"Palatino Linotype", serif;">Il s’agit de la
qualification de la nécessité d’une surveillance spatio-temporelle du secteur
axée sur les enjeux retenus. L’échelle de suivi comporte 04 niveaux : pas
de recommandation, veille, suivi régulier et léger et suivi régulier et
intensif. </span></font></p>
<p style="margin-top:0cm; margin-right:22.5pt; margin-bottom:0cm; margin-left:0cm; text-align:justify;"><font size="4"><b><span style="font-family:"Palatino Linotype", serif;">Suivi_2016</span></b><span style="font-family:"Palatino Linotype", serif;"> : </span><span style="font-family:"Palatino Linotype", serif;">Idem suivi 2011</span></font></p>
<p style="margin-top:0cm; margin-right:22.5pt; margin-bottom:0cm; margin-left:0cm; text-align:justify;"><font size="4"><b><span style="font-family:"Palatino Linotype", serif;">Suivi_2020</span></b><span style="font-family:"Palatino Linotype", serif;"> : </span><span style="font-family:"Palatino Linotype", serif;">Idem suivi 2011</span></font></p>
<p style="margin-top:0cm; margin-right:22.5pt; margin-bottom:0cm; margin-left:0cm; text-align:justify;"><font size="4"><b><span style="font-family:"Palatino Linotype", serif;">Evolu_Suiv</span></b><span style="font-family:"Palatino Linotype", serif;"> : </span><span style="font-family:"Palatino Linotype", serif;">C’est
l’évolution du niveau de suivi entre 2016 et 2020. Il s’agit de voir si le
niveau a connu une baisse, hausse ou une stabilité.</span></font></p>
<p style="margin-top:0cm; margin-right:22.5pt; margin-bottom:0cm; margin-left:0cm; text-align:justify;"><font size="4"><b><span style="font-family:"Palatino Linotype", serif;">AIRE_PROTG</span></b><span style="font-family:"Palatino Linotype", serif;"> : </span><span style="font-family:"Palatino Linotype", serif;">Il s’agit de la
présence d’une aire protégée dans le secteur.</span></font></p>
<p style="margin-top:0cm; margin-right:22.5pt; margin-bottom:0cm; margin-left:0cm; text-align:justify;"><font size="4"><b><span style="font-family:"Palatino Linotype", serif;">PROBLEMAT</span></b><span style="font-family:"Palatino Linotype", serif;"> : </span><span style="font-family:"Palatino Linotype", serif;">C’est la
problématique centrale rencontrée dans un secteur donné.</span></font></p>
<p style="margin-bottom:0cm; text-align:justify;"><font size="4"><b><span style="font-family:"Palatino Linotype", serif;">Long_km</span></b><span style="font-family:"Palatino Linotype", serif;"> :
</span><span style="font-family:"Palatino Linotype", serif;">C’est
la longueur d’un secteur donné en km.</span></font></p><span style="font-size:10.0pt; font-family:"Palatino Linotype",serif; color:#222222;"></span>
Description: <span style="color:rgb(106, 106, 106); font-family:Montserrat, "Helvetica Neue", Helvetica, Arial, sans-serif; font-size:18px;">The aim of this study is to assess the global occurrence of large submarine canyons to provide context and guidance for discussions regarding canyon occurrence, distribution, geological and oceanographic significance and conservation. Based on an analysis of the ETOPO1 data set, this study has compiled the first inventory of 5849 separate large submarine canyons in the world ocean. Active continental margins contain 15% more canyons (2586, equal to 44.2% of all canyons) than passive margins (2244, equal to 38.4%) and the canyons are steeper, shorter, more dendritic and more closely spaced on active than on passive continental margins. This study confirms observations of earlier workers that a relationship exists between canyon slope and canyon spacing (increased canyon slope correlates with closer canyon spacing).</span>
Service Item Id: 4fbb2af154c74d2e8b1b24bd8bc69458
Copyright Text: Harris and Whiteway 2011. Global distribution of large submarine canyons: Geomorphic differences
between active and passive continental margins. Marine Geology 285 (2011) 6986.
doi:10.1016/j.margeo.2011.05.008
Description: <p style="text-align:justify;"><span style="font-size:10.0pt; font-family:"Palatino Linotype",serif;">Il s’agit des contours
indiquant la profondeur des fonds marins au format vectoriel. Cette couche
d’information sur la profondeur des fonds marins est extraite de l’ensemble de
la base de données bathymétrique maillée de GEPCO (la grille GEPCO_2020). Elle
constitue un modèle de terrain global pour l’océan et la terre à des
intervalles de 15 secondes d’arc.</span></p>
Description: <div style="text-align:justify;"><span style="background-color:rgb(253, 253, 253); color:rgb(85, 85, 85); font-family:"Helvetica Nueue", Helvetica, Arial, Lato, "sans serif"; font-size:14px;">This is a portion of the data used to calculate 2008 and 2013 cumulative human impacts in: Halpern et al. 2015. Spatial and temporal changes in cumulative human impacts on the world's ocean. Seven data packages are available for this project: (1) supplementary data (habitat data and other files); (2) raw stressor data (2008 and 2013); (3) stressor data rescaled by one time period (2008 and 2013, scaled from 0-1); (4) stressor data rescaled by two time periods (2008 and 2013, scaled from 0-1); (5) pressure and cumulative impacts data (2013, all pressures); (6) pressure and cumulative impacts data (2008 and 2013, subset of pressures updated for both time periods); (7) change in pressures and cumulative impact (2008 to 2013). All raster files are .tif format and coordinate reference system is mollweide wgs84. Here is an overview of the calculations: Raw stressor data -> rescaled stressor data (values between 0-1) -> pressure data (stressor data after adjusting for habitat/pressure vulnerability) -> cumulative impact (sum of pressure data) -> difference between 2008 and 2013 pressure and cumulative impact data. This data package includes 2008 and 2013 raw stressor data. The 2008 data includes 18 raster files (preceeded by raw_2008_). The 2013 data includes 19 raster files (preceeded by raw_2013_). There is no sea level rise data for 2008.</span></div>
Description: <span style="color:rgb(85, 85, 85); font-family:"Helvetica Nueue", Helvetica, Arial, Lato, "sans serif"; font-size:14px; background-color:rgb(253, 253, 253);">This is a portion of the data used to calculate 2008 and 2013 cumulative human impacts in: Halpern et al. 2015. Spatial and temporal changes in cumulative human impacts on the world's ocean. Seven data packages are available for this project: (1) supplementary data (habitat data and other files); (2) raw stressor data (2008 and 2013); (3) stressor data rescaled by one time period (2008 and 2013, scaled from 0-1); (4) stressor data rescaled by two time periods (2008 and 2013, scaled from 0-1); (5) pressure and cumulative impacts data (2013, all pressures); (6) pressure and cumulative impacts data (2008 and 2013, subset of pressures updated for both time periods); (7) change in pressures and cumulative impact (2008 to 2013). All raster files are .tif format and coordinate reference system is mollweide wgs84. Here is an overview of the calculations: Raw stressor data -> rescaled stressor data (values between 0-1) -> pressure data (stressor data after adjusting for habitat/pressure vulnerability) -> cumulative impact (sum of pressure data) -> difference between 2008 and 2013 pressure and cumulative impact data. This data package includes 2008 and 2013 raw stressor data. The 2008 data includes 18 raster files (preceeded by raw_2008_). The 2013 data includes 19 raster files (preceeded by raw_2013_). There is no sea level rise data for 2008.</span>
Description: <p style="margin-top:0cm; margin-right:0cm; margin-bottom:7.5pt; margin-left:0cm; background:white;"><span style="font-family:"Arial",sans-serif; color:#555555;">This
dataset shows the known locations of sea turtle feeding sites, for five of the
seven species: hawksbill turtle (Eretmochelys imbricata), leatherback turtle
(Dermochelys coriacea), green turtle (Chelonia mydas), loggerhead turtle
(Caretta caretta), and olive ridley turtle (Lepidochelys olivacea).</span></p>
<p style="margin-top:0cm; margin-right:0cm; margin-bottom:7.5pt; margin-left:0cm; background:white; font-variant-ligatures:normal; font-variant-caps:normal; text-align:start; text-decoration-style:initial; text-decoration-color:initial; box-sizing:border-box; word-spacing:0px;"><span style="font-family:"Arial",sans-serif; color:#555555;">This dataset is no longer being maintained and must be used with
caution.</span></p>
Service Item Id: 4fbb2af154c74d2e8b1b24bd8bc69458
Copyright Text: UNEP-WCMC (1999). Global distribution of sea turtle feeding sites (ver. 1.1). Cambridge (UK): UNEP World Conservation Monitoring Centre. URL: http://data.unep-wcmc.org/datasets/21
Description: <span style="color:rgb(46, 46, 46); font-family:NexusSerif, Georgia, "Times New Roman", Times, STIXGeneral, "Cambria Math", "Lucida Sans Unicode", "Microsoft Sans Serif", "Segoe UI Symbol", "Arial Unicode MS", serif; font-size:18px;">Designing a representative network of high seas marine protected areas (MPAs) requires an acceptable scheme to classify the benthic (as well as the pelagic) bioregions of the oceans. Given the lack of sufficient biological information to accomplish this task, we used a multivariate statistical method with 6 biophysical variables (depth, seabed slope, sediment thickness, primary production, bottom water dissolved oxygen and bottom temperature) to objectively classify the ocean floor into 53,713 separate polygons comprising 11 different categories, that we have termed “seascapes”. A cross-check of the seascape classification was carried out by comparing the seascapes with existing maps of seafloor geomorphology and seabed sediment type and by GIS analysis of the number of separate polygons, polygon area and perimeter/area ratio. We conclude that seascapes, derived using a multivariate statistical approach, are biophysically meaningful subdivisions of the ocean floor and can be expected to contain different biological associations, in as much as different geomorphological units do the same. Less than 20% of some seascapes occur in the high seas while other seascapes are largely confined to the high seas, indicating specific types of environment whose protection and conservation will require international cooperation. Our study illustrates how the identification of potential sites for high seas marine protected areas can be accomplished by a simple GIS analysis of seafloor geomorphic and seascape classification maps. Using this approach, maps of seascape and geomorphic heterogeneity were generated in which heterogeneity hotspots identify themselves as MPA candidates. The use of computer-aided mapping tools removes subjectivity in the MPA design process and provides greater confidence to stakeholders that an unbiased result has been achieved.</span>
Service Item Id: 4fbb2af154c74d2e8b1b24bd8bc69458
Copyright Text: Harris and Whiteway 2009. High seas marine protected areas: Benthic environmental conservation
priorities from a GIS analysis of global ocean biophysical data.Ocean & Coastal Management
52 2238. doi:10.1016/j.ocecoaman.2008.09.009
Description: <span style="color:rgb(46, 46, 46); font-family:NexusSerif, Georgia, "Times New Roman", Times, STIXGeneral, "Cambria Math", "Lucida Sans Unicode", "Microsoft Sans Serif", "Segoe UI Symbol", "Arial Unicode MS", serif; font-size:18px;">Designing a representative network of high seas marine protected areas (MPAs) requires an acceptable scheme to classify the benthic (as well as the pelagic) bioregions of the oceans. Given the lack of sufficient biological information to accomplish this task, we used a multivariate statistical method with 6 biophysical variables (depth, seabed slope, sediment thickness, primary production, bottom water dissolved oxygen and bottom temperature) to objectively classify the ocean floor into 53,713 separate polygons comprising 11 different categories, that we have termed “seascapes”. A cross-check of the seascape classification was carried out by comparing the seascapes with existing maps of seafloor geomorphology and seabed sediment type and by GIS analysis of the number of separate polygons, polygon area and perimeter/area ratio. We conclude that seascapes, derived using a multivariate statistical approach, are biophysically meaningful subdivisions of the ocean floor and can be expected to contain different biological associations, in as much as different geomorphological units do the same. Less than 20% of some seascapes occur in the high seas while other seascapes are largely confined to the high seas, indicating specific types of environment whose protection and conservation will require international cooperation. Our study illustrates how the identification of potential sites for high seas marine protected areas can be accomplished by a simple GIS analysis of seafloor geomorphic and seascape classification maps. Using this approach, maps of seascape and geomorphic heterogeneity were generated in which heterogeneity hotspots identify themselves as MPA candidates. The use of computer-aided mapping tools removes subjectivity in the MPA design process and provides greater confidence to stakeholders that an unbiased result has been achieved.</span>
Service Item Id: 4fbb2af154c74d2e8b1b24bd8bc69458
Copyright Text: Harris and Whiteway 2009. High seas marine protected areas: Benthic environmental conservation
priorities from a GIS analysis of global ocean biophysical data.Ocean & Coastal Management
52 2238. doi:10.1016/j.ocecoaman.2008.09.009
Description: <span style="color:rgb(46, 46, 46); font-family:NexusSerif, Georgia, "Times New Roman", Times, STIXGeneral, "Cambria Math", "Lucida Sans Unicode", "Microsoft Sans Serif", "Segoe UI Symbol", "Arial Unicode MS", serif; font-size:18px;">Designing a representative network of high seas marine protected areas (MPAs) requires an acceptable scheme to classify the benthic (as well as the pelagic) bioregions of the oceans. Given the lack of sufficient biological information to accomplish this task, we used a multivariate statistical method with 6 biophysical variables (depth, seabed slope, sediment thickness, primary production, bottom water dissolved oxygen and bottom temperature) to objectively classify the ocean floor into 53,713 separate polygons comprising 11 different categories, that we have termed “seascapes”. A cross-check of the seascape classification was carried out by comparing the seascapes with existing maps of seafloor geomorphology and seabed sediment type and by GIS analysis of the number of separate polygons, polygon area and perimeter/area ratio. We conclude that seascapes, derived using a multivariate statistical approach, are biophysically meaningful subdivisions of the ocean floor and can be expected to contain different biological associations, in as much as different geomorphological units do the same. Less than 20% of some seascapes occur in the high seas while other seascapes are largely confined to the high seas, indicating specific types of environment whose protection and conservation will require international cooperation. Our study illustrates how the identification of potential sites for high seas marine protected areas can be accomplished by a simple GIS analysis of seafloor geomorphic and seascape classification maps. Using this approach, maps of seascape and geomorphic heterogeneity were generated in which heterogeneity hotspots identify themselves as MPA candidates. The use of computer-aided mapping tools removes subjectivity in the MPA design process and provides greater confidence to stakeholders that an unbiased result has been achieved.</span>
Service Item Id: 4fbb2af154c74d2e8b1b24bd8bc69458
Copyright Text: Harris and Whiteway 2009. High seas marine protected areas: Benthic environmental conservation
priorities from a GIS analysis of global ocean biophysical data.Ocean & Coastal Management
52 2238. doi:10.1016/j.ocecoaman.2008.09.009
Description: <div style="text-align:justify;"><span style="color:rgb(46, 46, 46); font-family:NexusSerif, Georgia, "Times New Roman", Times, STIXGeneral, "Cambria Math", "Lucida Sans Unicode", "Microsoft Sans Serif", "Segoe UI Symbol", "Arial Unicode MS", serif; font-size:18px;">Designing a representative network of high seas marine protected areas (MPAs) requires an acceptable scheme to classify the benthic (as well as the pelagic) bioregions of the oceans. Given the lack of sufficient biological information to accomplish this task, we used a multivariate statistical method with 6 biophysical variables (depth, seabed slope, sediment thickness, primary production, bottom water dissolved oxygen and bottom temperature) to objectively classify the ocean floor into 53,713 separate polygons comprising 11 different categories, that we have termed “seascapes”. A cross-check of the seascape classification was carried out by comparing the seascapes with existing maps of seafloor geomorphology and seabed sediment type and by GIS analysis of the number of separate polygons, polygon area and perimeter/area ratio. We conclude that seascapes, derived using a multivariate statistical approach, are biophysically meaningful subdivisions of the ocean floor and can be expected to contain different biological associations, in as much as different geomorphological units do the same. Less than 20% of some seascapes occur in the high seas while other seascapes are largely confined to the high seas, indicating specific types of environment whose protection and conservation will require international cooperation. Our study illustrates how the identification of potential sites for high seas marine protected areas can be accomplished by a simple GIS analysis of seafloor geomorphic and seascape classification maps. Using this approach, maps of seascape and geomorphic heterogeneity were generated in which heterogeneity hotspots identify themselves as MPA candidates. The use of computer-aided mapping tools removes subjectivity in the MPA design process and provides greater confidence to stakeholders that an unbiased result has been achieved.</span></div>
Service Item Id: 4fbb2af154c74d2e8b1b24bd8bc69458
Copyright Text: Harris and Whiteway 2009. High seas marine protected areas: Benthic environmental conservation
priorities from a GIS analysis of global ocean biophysical data.Ocean & Coastal Management
52 2238. doi:10.1016/j.ocecoaman.2008.09.009
Description: <span style="color:rgb(46, 46, 46); font-family:NexusSerif, Georgia, "Times New Roman", Times, STIXGeneral, "Cambria Math", "Lucida Sans Unicode", "Microsoft Sans Serif", "Segoe UI Symbol", "Arial Unicode MS", serif; font-size:18px;">Designing a representative network of high seas marine protected areas (MPAs) requires an acceptable scheme to classify the benthic (as well as the pelagic) bioregions of the oceans. Given the lack of sufficient biological information to accomplish this task, we used a multivariate statistical method with 6 biophysical variables (depth, seabed slope, sediment thickness, primary production, bottom water dissolved oxygen and bottom temperature) to objectively classify the ocean floor into 53,713 separate polygons comprising 11 different categories, that we have termed “seascapes”. A cross-check of the seascape classification was carried out by comparing the seascapes with existing maps of seafloor geomorphology and seabed sediment type and by GIS analysis of the number of separate polygons, polygon area and perimeter/area ratio. We conclude that seascapes, derived using a multivariate statistical approach, are biophysically meaningful subdivisions of the ocean floor and can be expected to contain different biological associations, in as much as different geomorphological units do the same. Less than 20% of some seascapes occur in the high seas while other seascapes are largely confined to the high seas, indicating specific types of environment whose protection and conservation will require international cooperation. Our study illustrates how the identification of potential sites for high seas marine protected areas can be accomplished by a simple GIS analysis of seafloor geomorphic and seascape classification maps. Using this approach, maps of seascape and geomorphic heterogeneity were generated in which heterogeneity hotspots identify themselves as MPA candidates. The use of computer-aided mapping tools removes subjectivity in the MPA design process and provides greater confidence to stakeholders that an unbiased result has been achieved.</span>
Service Item Id: 4fbb2af154c74d2e8b1b24bd8bc69458
Copyright Text: Harris and Whiteway 2009. High seas marine protected areas: Benthic environmental conservation
priorities from a GIS analysis of global ocean biophysical data.Ocean & Coastal Management
52 2238. doi:10.1016/j.ocecoaman.2008.09.009
Description: <span style="color:rgb(54, 54, 54); font-family:helvetica, arial, sans-serif; font-size:12px; text-align:justify;">A digital total-sediment-thickness database for the world's oceans and marginal seas has been compiled by the NOAA National Geophysical Data Center (NGDC) (now the National Centers for Environmental Information (NCEI)). The data were gridded with a grid spacing of 5 arc-minutes by 5 arc-minutes. Sediment-thickness data were compiled from three principle sources: (i) previously published isopach maps including Ludwig and Houtz [1979], Matthias et al. [1988], Divins and Rabinowitz [1990], Hayes and LaBrecque [1991], and Divins [2003]; (ii) ocean drilling results, both from the Ocean Drilling Program (ODP) and the Deep Sea Drilling Project (DSDP); and (iii) seismic reflection profiles archived here as well as seismic data and isopach maps available as part of the IOC's International Geological-Geophysical Atlas of the Pacific Ocean [Udinstev, 2003].</span>
Service Item Id: 4fbb2af154c74d2e8b1b24bd8bc69458
Copyright Text: Divins, D.L., Total Sediment Thickness of the World's Oceans & Marginal Seas, NOAA National Geophysical Data Center, Boulder, CO, 2003.
Description: <span style="color:rgb(54, 54, 54); font-family:helvetica, arial, sans-serif; font-size:12px; text-align:justify;">A digital total-sediment-thickness database for the world's oceans and marginal seas has been compiled by the NOAA National Geophysical Data Center (NGDC) (now the National Centers for Environmental Information (NCEI)). The data were gridded with a grid spacing of 5 arc-minutes by 5 arc-minutes. Sediment-thickness data were compiled from three principle sources: (i) previously published isopach maps including Ludwig and Houtz [1979], Matthias et al. [1988], Divins and Rabinowitz [1990], Hayes and LaBrecque [1991], and Divins [2003]; (ii) ocean drilling results, both from the Ocean Drilling Program (ODP) and the Deep Sea Drilling Project (DSDP); and (iii) seismic reflection profiles archived here as well as seismic data and isopach maps available as part of the IOC's International Geological-Geophysical Atlas of the Pacific Ocean [Udinstev, 2003]</span>
Service Item Id: 4fbb2af154c74d2e8b1b24bd8bc69458
Copyright Text: Divins, D.L., Total Sediment Thickness of the World's Oceans & Marginal Seas, NOAA National Geophysical Data Center, Boulder, CO, 2003.
Description: <span style="color:rgb(54, 54, 54); font-family:helvetica, arial, sans-serif; font-size:12px; text-align:justify;">A digital total-sediment-thickness database for the world's oceans and marginal seas has been compiled by the NOAA National Geophysical Data Center (NGDC) (now the National Centers for Environmental Information (NCEI)). The data were gridded with a grid spacing of 5 arc-minutes by 5 arc-minutes. Sediment-thickness data were compiled from three principle sources: (i) previously published isopach maps including Ludwig and Houtz [1979], Matthias et al. [1988], Divins and Rabinowitz [1990], Hayes and LaBrecque [1991], and Divins [2003]; (ii) ocean drilling results, both from the Ocean Drilling Program (ODP) and the Deep Sea Drilling Project (DSDP); and (iii) seismic reflection profiles archived here as well as seismic data and isopach maps available as part of the IOC's International Geological-Geophysical Atlas of the Pacific Ocean [Udinstev, 2003].</span>
Service Item Id: 4fbb2af154c74d2e8b1b24bd8bc69458
Copyright Text: Divins, D.L., Total Sediment Thickness of the World's Oceans & Marginal Seas, NOAA National Geophysical Data Center, Boulder, CO, 2003.
Description: <span style="color:rgb(54, 54, 54); font-family:helvetica, arial, sans-serif; font-size:12px; text-align:justify;">A digital total-sediment-thickness database for the world's oceans and marginal seas has been compiled by the NOAA National Geophysical Data Center (NGDC) (now the National Centers for Environmental Information (NCEI)). The data were gridded with a grid spacing of 5 arc-minutes by 5 arc-minutes. Sediment-thickness data were compiled from three principle sources: (i) previously published isopach maps including Ludwig and Houtz [1979], Matthias et al. [1988], Divins and Rabinowitz [1990], Hayes and LaBrecque [1991], and Divins [2003]; (ii) ocean drilling results, both from the Ocean Drilling Program (ODP) and the Deep Sea Drilling Project (DSDP); and (iii) seismic reflection profiles archived here as well as seismic data and isopach maps available as part of the IOC's International Geological-Geophysical Atlas of the Pacific Ocean [Udinstev, 2003].</span>
Service Item Id: 4fbb2af154c74d2e8b1b24bd8bc69458
Copyright Text: Divins, D.L., Total Sediment Thickness of the World's Oceans & Marginal Seas, NOAA National Geophysical Data Center, Boulder, CO, 2003.
Description: <span style="color:rgb(85, 85, 85); font-family:MuseoSans-300, Arial, sans-serif;">This dataset shows the global distribution of over 1,300 estuaries, including some lagoon systems and fjords. This dataset was developed as part of the “Sea Around Us” project</span><span style="color:rgb(85, 85, 85); font-family:MuseoSans-300, Arial, sans-serif;">.</span>
Service Item Id: 4fbb2af154c74d2e8b1b24bd8bc69458
Copyright Text: Alder J (2003). Putting the coast in the “Sea Around Us”. The Sea Around Us Newsletter 15: 1-2. URL: http://seaaroundus.org/newsletter/Issue15.pdf; http://data.unep-wcmc.org/datasets/23 (version 2.0)
Watson R, Alder J, Booth S, Christensen V, Kaschner K, Kitchingman A, Lai S, Palomares MLD, Valdez F, Pauly D (2004). Welcome to www.seaaroundus.org: launching our ‘product’ on the web. The Sea Around Us Newsletter 22: 1-8
Description: <span style="color:rgb(46, 46, 46); font-family:NexusSerif, Georgia, "Times New Roman", Times, STIXGeneral, "Cambria Math", "Lucida Sans Unicode", "Microsoft Sans Serif", "Segoe UI Symbol", "Arial Unicode MS", serif; font-size:18px;">Designing a representative network of high seas marine protected areas (MPAs) requires an acceptable scheme to classify the benthic (as well as the pelagic) bioregions of the oceans. Given the lack of sufficient biological information to accomplish this task, we used a multivariate statistical method with 6 biophysical variables (depth, seabed slope, sediment thickness, primary production, bottom water dissolved oxygen and bottom temperature) to objectively classify the ocean floor into 53,713 separate polygons comprising 11 different categories, that we have termed “seascapes”. A cross-check of the seascape classification was carried out by comparing the seascapes with existing maps of seafloor geomorphology and seabed sediment type and by GIS analysis of the number of separate polygons, polygon area and perimeter/area ratio. We conclude that seascapes, derived using a multivariate statistical approach, are biophysically meaningful subdivisions of the ocean floor and can be expected to contain different biological associations, in as much as different geomorphological units do the same. Less than 20% of some seascapes occur in the high seas while other seascapes are largely confined to the high seas, indicating specific types of environment whose protection and conservation will require international cooperation. Our study illustrates how the identification of potential sites for high seas marine protected areas can be accomplished by a simple GIS analysis of seafloor geomorphic and seascape classification maps. Using this approach, maps of seascape and geomorphic heterogeneity were generated in which heterogeneity hotspots identify themselves as MPA candidates. The use of computer-aided mapping tools removes subjectivity in the MPA design process and provides greater confidence to stakeholders that an unbiased result has been achieved.</span>
Service Item Id: 4fbb2af154c74d2e8b1b24bd8bc69458
Copyright Text: Harris and Whiteway 2009. High seas marine protected areas: Benthic environmental conservation
priorities from a GIS analysis of global ocean biophysical data.Ocean & Coastal Management
52 2238. doi:10.1016/j.ocecoaman.2008.09.009
Description: <p style="text-align:justify;"><span style="font-family:"Palatino Linotype", serif;"><font size="4">Couche SIG contenant les différentes informations sur
l’extension urbaine autour du littoral couvrant les pays de l’observatoire en
2010, 2016 et 2020. Cette couche a été créée en 2010 en utilisant les données
d’Africapolis comme socle de départ. Les agglomérations de plus de 10 000
habitants sont aussi prises en compte dans cette armature urbaine. L’échelle
géographique de cette couche est toute l’Afrique de l’ouest partant de la
Mauritanie jusqu’au Bénin, plus Sao Tomé et Principe. Tandis que, la profondeur
de l’information est de 25 km de la côte à l’intérieur des terres. </font></span></p><p style="text-align:justify;"></p><p style="margin-right:11.25pt; text-align:justify;"><font size="4"><b><span style="font-family:"Palatino Linotype", serif;">Limites : </span></b><span style="font-family:"Palatino Linotype", serif;">Pas
d’informations</span></font></p>
<p style="margin-bottom:8.0pt;"><font size="4"><b><span style="font-family:"Palatino Linotype", serif;">Projections cartographiques : </span></b><span style="font-family:"Palatino Linotype", serif;">WGS84. </span></font></p>
<p style><font size="4"><b><span style="font-family:"Palatino Linotype", serif;">Liens en rapport avec les données :
</span></b><span style="font-family:"Palatino Linotype", serif;">Pas d’informations;</span></font></p>
<p style="text-align:justify;"><font size="4"><b><span style="font-family:"Palatino Linotype", serif;">Source
des données</span></b><span style="font-family:"Palatino Linotype", serif;"> : </span><span style="font-family:"Palatino Linotype", serif;">Africapolis, Modifiées dans le cadre de la MOLOA.</span></font></p>
<p style="text-align:justify;"><font size="4"><b><span style="font-family:"Palatino Linotype", serif;">Date
de mise à jour de la couche</span></b><span style="font-family:"Palatino Linotype", serif;"> :
Octobre 2020.</span></font></p>
<p style="text-align:justify;"><font size="4"><b><span style="font-family:"Palatino Linotype", serif;">Source de données de mise à jour</span></b><span style="font-family:"Palatino Linotype", serif;"> : Google Earth 2019 / 2020.</span></font></p>
<p style="text-align:justify;"><font size="4"><b><span style="font-family:"Palatino Linotype", serif;">Producteur
de la mise à jour : </span></b><span style="font-family:"Palatino Linotype", serif;">Centre
de Suivi Ecologique (CSE).</span></font></p>
<p style="text-align:justify;"><b><span style="font-family:"Palatino Linotype", serif;"><font size="4">Attributs</font></span></b></p>
<p style="text-align:justify;"><font size="4"><b><span style="font-family:"Palatino Linotype", serif;">ID_DH</span></b><span style="font-family:"Palatino Linotype", serif;"> :
Clé primaire de la table : c’est l’identifiant unique du type de littoral.</span></font></p>
<p style="text-align:justify;"><font size="4"><b><span style="font-family:"Palatino Linotype", serif;">ID_PAYS : </span></b><span style="font-family:"Palatino Linotype", serif;">Clé
secondaire : c’est l’identifiant unique du pays auquel est rattaché un
type d’enjeu</span></font></p>
<p style="text-align:justify;"><font size="4"><b><span style="font-family:"Palatino Linotype", serif;">PAYS : </span></b><span style="font-family:"Palatino Linotype", serif;">Pays
concerné par la tache urbaine.</span></font></p>
<p style="text-align:justify;"><font size="4"><b><span style="font-family:"Palatino Linotype", serif;">ANNEE : </span></b><span style="font-family:"Palatino Linotype", serif;">Etat
de l’urbain à une année <i>t</i><b><span style="color:red;">1.</span></b></span></font></p>
<p style="text-align:justify;"><font size="4"><b><span style="font-family:"Palatino Linotype", serif;">TYPE_UR : </span></b><span style="font-family:"Palatino Linotype", serif;">Types
ou formes d’urbanisation </span><i>t</i><span style="font-family:"Palatino Linotype", serif;"><b><span style="color:red;">2.</span></b></span></font></p>
<p style="text-align:justify;"><font size="4"><b><span style="font-family:"Palatino Linotype", serif;">NOM : </span></b><span style="font-family:"Palatino Linotype", serif;">Nom
de la zone où l’extension est notée.</span></font></p>
<p style="text-align:justify;"><font size="4"><b><span style="font-family:"Palatino Linotype", serif;">SURFACE : </span></b><span style="font-family:"Palatino Linotype", serif;">Surface
en hectare (Ha)</span></font></p>
<p style="text-align:justify;"><font size="4"><b><span style="font-family:"Palatino Linotype", serif; color:red;">1 </span></b><b><span style="font-family:"Palatino Linotype", serif;">Année</span></b><span style="font-family:"Palatino Linotype", serif;"> :
2010 – 2015 – 2020.</span></font></p>
<p style="text-align:justify;"><font size="4"><b><span style="font-family:"Palatino Linotype", serif; color:red;">2 </span></b><b><span style="font-family:"Palatino Linotype", serif;">Formes d’urbanisation</span></b><span style="font-family:"Palatino Linotype", serif;"> : </span><span style="font-family:"Palatino Linotype", serif; color:black;">Urbain dense, Urbain lâche, Urbain très lâche, Espace non bâti, Tâches
urbaines non discriminées, Noyaux carrefour, </span><span style="font-family:"Palatino Linotype", serif;">Urbain très dense, Résidentiel, Zones en conquêtes,
Périurbain récent.</span></font></p><span style="font-size:10.0pt; font-family:"Palatino Linotype",serif;"></span>
Description: <p style="margin-right:11.25pt; text-align:justify;"><span style="font-family:"Palatino Linotype", serif;"><font size="4">We mapped Low Elevation Coastal Zones at or below 10m in elevation and
adjacent to the coastline for West Africa, from Senegal to Nigeria. This
analysis was conducted using MERIT DEM data, which was created by removing
multiple error types from SRTM3 v2.1 and AW3D-30m v1 to reduce vertical height
bias (Yamakzai et al. 2018). Given this increased vertical accuracy, MERIT DEM
can map 10-meter LECZs with an 89% accuracy (Gesch 2018). <o:p></o:p></font></span></p><p style="margin-right:11.25pt; text-align:justify;"><span style="font-family:"Palatino Linotype", serif;"><font size="4">To determine the 10-meter LECZ, we identified pixels that had a value less
than 10 and were adjacent to the coast or a coastal water body. We also masked
permanent water bodies from the zone to better visually represent the
surrounding land areas most at risk.</font></span></p><p style="margin-right:11.25pt; text-align:justify;"><b><span style="font-family:"Palatino Linotype", serif;"><font size="4">Limitations</font></span></b></p><p style="margin-bottom:8.0pt; text-align:justify;"><font size="4"><span style="font-family:"Palatino Linotype", serif; color:windowtext;">LIDAR derived Digital Elevation
Models (DEMs), along with current, bathymetric and storm surge data, is widely
acknowledged to be the most accurate way of modeling fine-scale SLR (Luger and
Gunduz 2015, Gesch 2018, Kulp and Strauss 2015). Although this is largely
recognized as the most accurate approach, LIDAR data is expensive to obtain,
often unavailable in many parts of the world, and would require a large amount
of processing power to analyze at the scale of the West African Coastline.
Remotely sensed, globally available DEMs are also commonly used to map SLR
vulnerability, although it has been shown that global DEMs are not suitable for
mapping fine scale sea-level rise over relatively short time horizons with any
acceptable amount of accuracy (Leon et al. 2014, Gesch 2018). Given these
accuracy and data availability issues, we were not able to model seal level
rise itself, but rather were able to identify 10-meter Low Elevation Coastal
Zones (LECZs) for the entire west coast of Africa (Senegal to Nigeria). We also
highlighted other key areas within the LECZ that are particularly vulnerable to
the impacts of sea level rise for information and planning purposes. </span></font></p><p style="margin-bottom:8.0pt; text-align:justify;"><font size="4"><b><span style="font-family:"Palatino Linotype", serif;">Map projection : </span></b><span style="font-family:"Palatino Linotype", serif;">It is currently Africa Albers Equal Area Conic
(WGS84).</span></font></p><p style><b><span style="font-family:"Palatino Linotype", serif;"><font size="4">Data links</font></span></b></p><p style="text-align:justify; text-indent:-18.0pt;"><font size="4"><span style="font-family:Symbol;">·<span style="font-variant-numeric:normal; font-variant-east-asian:normal; font-stretch:normal; font-family:"Times New Roman";"> </span></span><span style="font-family:"Palatino Linotype", serif;">MERIT DEM</span><b><span style="font-family:"Palatino Linotype", serif;"> :</span></b><span style="font-family:"Palatino Linotype", serif;"> <a href="https://hydro.iis.u-tokyo.ac.jp/~yamadai/MERIT_DEM/">https://hydro.iis.u-tokyo.ac.jp/~yamadai/MERIT_DEM/</a></span></font></p><p style="text-align:justify; text-indent:-18.0pt;"><font size="4"><!--<span style="font-family:Symbol;">·<span style="font-variant-numeric:normal; font-variant-east-asian:normal; font-stretch:normal; font-family:"Times New Roman";"> </span></span><span><a href="https://www.wabicc.org/mdocs-posts/mapping-west-africas-low-elevation-coastal-zones/"><span style="font-family:"Palatino Linotype", serif;">https://www.wabicc.org/mdocs-posts/mapping-west-africas-low-elevation-coastal-zones/</span></a></span><span style="font-family:"Palatino Linotype", serif;"> </span></font></p><p style="text-align:justify; text-indent:-18.0pt;"><font size="4"><span style="font-family:Symbol;">·<span style="font-variant-numeric:normal; font-variant-east-asian:normal; font-stretch:normal; font-family:"Times New Roman";"> </span></span><span><a href><span style="font-family:"Palatino Linotype", serif;">file:///C:/Users/ProDesk%20400/Downloads/Mapping%20West%20Africa&%23039%3Bs%20Low%20Elevation%20Coastal%20Zones.pdf</span></a></span><span style="font-family:"Palatino Linotype", serif;"> </span></font></p><p style="text-align:justify;"><b><span style="font-family:"Palatino Linotype", serif;"><font size="4">Data
source </font></span></b></p><p style="text-align:justify;"><font size="4"><span style="font-family:"Palatino Linotype", serif;">This data layer was developed using MERIT DEM
data, which is created </span><span style="font-family:"Palatino Linotype", serif;">by removing multiple error types from </span><span style="font-family:"Palatino Linotype", serif;">SRTM3
v2.1 and AW3D-30m v1 to reduce vertical height bias. This dataset was produced
by Yamakzai et al. 2018.<o:p></o:p></span></font></p><p style><b><span style="font-family:"Palatino Linotype",serif;"><font size="4">Citation
(s)</font></span></b></p><p style><span style="font-family:"Palatino Linotype", serif;"><font size="4">Cori G., 2019.
Mapping weest Africa’s low elevation costal zones. USAID, WA BiCC, Tetra Tech.</font></span></p><p style="text-align:justify;"><span style="font-family:"Palatino Linotype", serif;"><font size="4">Gesch,
D., 2018. Best Practices for Elevation-Based Assessments of Sea-Level Rise and
Coastal Flooding Exposure. Frontiers in Earth Science, 6.</font></span></p><p style="text-align:justify;"><span style="font-family:"Palatino Linotype", serif;"><font size="4">Gunduz,
Orhan & Tulger Kara, Gülşah. (2015). ‘Influence of DEM Resolution on
GIS-Based Inundation Analysis’. <i>9th World Congress of the European Water
Resources Association (EWRA</i>). İstanbul, Turkey. </font></span></p><p style="text-align:justify;"><span style="font-family:"Palatino Linotype", serif;"><font size="4">Kulp,
S. and Strauss, B., 2015. ‘The Effect Of DEM Quality On Sea Level Rise
Exposure Analysis’. AGU Fall Meeting. 2015. </font></span></p><p style="text-align:justify;"><span style="font-family:"Palatino Linotype", serif;"><font size="4">Leon,
J., Heuvelink, G. and Phinn, S., 2014. Incorporating DEM Uncertainty in Coastal
Inundation Mapping. PLoS ONE, 9(9), p.e108727.</font></span></p><p style><font size="4"><span style="font-family:"Palatino Linotype", serif;">Yamazaki D., D. Ikeshima, R. Tawatari,
T. Yamaguchi, F. O'Loughlin, J.C. Neal, C.C. Sampson, S. Kanae & P.D.
Bates. A high accuracy map of global terrain elevations. Geophysical Research
Letters, vol.44, pp.5844-5853, 2017 doi: 10.1002/2017GL072874.</span></font></p><p style="text-align:justify;"><font size="4"><b><span style="font-family:"Palatino Linotype", serif;">Geographic
coverage</span></b><span style="font-family:"Palatino Linotype", serif;">Senegal to
Nigeria<b>.</b></span></font></p><p style="text-align:justify;"><font size="4"><b><span style="font-family:"Palatino Linotype", serif;">Layer creation date</span></b><span style="font-family:"Palatino Linotype", serif;"> : 7/31/20.</span></font></p><p style="margin-right:11.25pt; text-align:justify;">
</p><p style="text-align:justify;"><font size="4"><b><span style="font-family:"Palatino Linotype", serif;">Contacts : </span></b><span style="font-family:"Palatino Linotype", serif;">Cori Grainger (</span><span><a href="mailto:cori.grainger@tetratech.com"><span style="font-family:"Palatino Linotype", serif;">cori.grainger@tetratech.com</span></a></span><span style="font-family:"Palatino Linotype", serif;">), Vaneska Litz (</span><span><a href="mailto:vaneska.litz@tetratech.com"><span style="font-family:"Palatino Linotype", serif;">vaneska.litz@tetratech.com</span></a></span><span style="font-family:"Palatino Linotype", serif;">), Stephen Kelleher (</span><span><a href="mailto:Stephen.Kelleher@wabicc.org"><span style="font-family:"Palatino Linotype", serif;">Stephen.Kelleher@wabicc.org</span></a></span><span style="font-family:"Palatino Linotype", serif;">).</span></font></p><p style="margin-right:11.25pt; text-align:justify;"><span style="font-size:10.0pt; font-family:"Palatino Linotype",serif;"></span></p>
Description: <span style="color:rgb(46, 46, 46); font-family:NexusSerif, Georgia, "Times New Roman", Times, STIXGeneral, "Cambria Math", "Lucida Sans Unicode", "Microsoft Sans Serif", "Segoe UI Symbol", "Arial Unicode MS", serif; font-size:18px;">Designing a representative network of high seas marine protected areas (MPAs) requires an acceptable scheme to classify the benthic (as well as the pelagic) bioregions of the oceans. Given the lack of sufficient biological information to accomplish this task, we used a multivariate statistical method with 6 biophysical variables (depth, seabed slope, sediment thickness, primary production, bottom water dissolved oxygen and bottom temperature) to objectively classify the ocean floor into 53,713 separate polygons comprising 11 different categories, that we have termed “seascapes”. A cross-check of the seascape classification was carried out by comparing the seascapes with existing maps of seafloor geomorphology and seabed sediment type and by GIS analysis of the number of separate polygons, polygon area and perimeter/area ratio. We conclude that seascapes, derived using a multivariate statistical approach, are biophysically meaningful subdivisions of the ocean floor and can be expected to contain different biological associations, in as much as different geomorphological units do the same. Less than 20% of some seascapes occur in the high seas while other seascapes are largely confined to the high seas, indicating specific types of environment whose protection and conservation will require international cooperation. Our study illustrates how the identification of potential sites for high seas marine protected areas can be accomplished by a simple GIS analysis of seafloor geomorphic and seascape classification maps. Using this approach, maps of seascape and geomorphic heterogeneity were generated in which heterogeneity hotspots identify themselves as MPA candidates. The use of computer-aided mapping tools removes subjectivity in the MPA design process and provides greater confidence to stakeholders that an unbiased result has been achieved.</span>
Service Item Id: 4fbb2af154c74d2e8b1b24bd8bc69458
Copyright Text: Harris and Whiteway 2009. High seas marine protected areas: Benthic environmental conservation
priorities from a GIS analysis of global ocean biophysical data.Ocean & Coastal Management
52 2238. doi:10.1016/j.ocecoaman.2008.09.009
Description: <p style="margin-right:11.25pt; text-align:justify;"><span style="font-size:10.0pt; font-family:"Palatino Linotype",serif;">La base de données sous régionale des aires protégées
est extraite de celle mondiale (WDPA), qui est la seule base de données
mondiale sur les aires protégées terrestres et marines disponibles </span><span style="font-size:10.0pt; font-family:"Palatino Linotype",serif;">et
constitue la base de Protected Planet. Protected Planet est un produit conjoint
de l'ONU Environnement et de l'UICN, géré par le PNUE-WCMC et l'UICN en
collaboration avec les gouvernements, les communautés et les partenaires
collaborateurs. </span></p>