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a/geographie-informatique.tex b/geographie-informatique.tex index fefb531..8debc2f 100644 --- a/geographie-informatique.tex +++ b/geographie-informatique.tex @@ -1591,6 +1591,48 @@ La pertinence de l'utilisation du positionnement relatif apparait rapidement qua Remarquez enfin que la carte de la figure \ref{figure:umap} a été réalisée avec un logiciel en ligne dédié à la création de cartes à usage collectif ou personnel à partir du fond cartographique d'OSM, nommé Umap\footnote{Voir~: \url{https://umap.openstreetmap.fr/fr/}}. La création de cartes avec celui-ci est décrite dans le corps du présent travail et nécessiterait une annexe approfondie à lui tout seul. Il est cependant très aisé de faire rapidement une carte avec umap et en apprendre l'usage des bases est certainement nécessaire. \section{Outils de positionnement}\label{section:outilsdepositionnement} +\subsection{Introduction} +Quand on fait de la cartographie, il est naturel à un moment où à un autre de s'intéresser à un positionnement absolu. Il s'agit d'une longue histoire qui passe par les méthodes de détermination de la latitude, puis évidemment du célèbre problème de la longitude. + +L'apparition du positionnement satellite nous intéresse ici dans le cadre de la cartographie. Or, dans ce cas, des problèmes spécifiques comme celui de l'évaluation de la précision, apparaissent et ils peuvent être à l'origine de découvertes qui peuvent intéresser des étudiants et mener à des expériences pratiques instructives. + +\subsection{Positionnement} +Pour poser le problème de manière très pragmatique, nous avons utilisé un smartphone (sous Fairphone OS) et trois applications, soit GPSTest, Here GPS Location et Phyphox, pour effectuer trois mesures de position au parc Gallet. L'idée est de se positionner précisément en un point connu et de faire les trois mesures sans en bouger. Ainsi, le kiosque à musique du parc, l'intersection de trois chemins et le coude de l'un d'eux ont été choisis pour cela. La figure \ref{figure:gpsmesurestout} montre en rouge les points choisis et en bleu les mesures. +\begin{figure}[c] + \centering + \begin{subfigure}{\textwidth} + \centering + \includegraphics[width=\textwidth]{images/GPS_Mesures_TOUT.eps} + \caption{L'ensemble des points.} + \label{figure:gpsmesurestout} + \end{subfigure} + + \begin{subfigure}{0.45\textwidth} + \centering + \includegraphics[width=\textwidth]{images/GPS_Mesures_Kiosque.eps} + \caption{Les mesures du kiosque.} + \label{figure:gpsmesureskiosque} + \end{subfigure} + \begin{subfigure}{0.5\textwidth} + \centering + \includegraphics[width=\textwidth]{images/GPS_Mesures_Centre.eps} + \caption{Les mesures des chemins.} + \label{figure:gpsmesurescentre} + \end{subfigure} + \caption{Mesures GPS avec GPSTest, Here GPS Location et Phyphox.} + \label{figure:mesuresgps} +\end{figure} +En premier lieu, il est intéressant de constater que les mesures sont assez éloignées des points cartographiés et que ces éloignements ne sont pas systématiquement dans une direction privilégiée. On a donc pas à faire à une erreur systématique du GPS. + +Ensuite, la figure \ref{figure:gpsmesureskiosque} montre les trois mesures réalisées en se trouvant exactement au centre du kiosque. La référence est donc un bâtiment dont la position devrait être précise, puisque probablement tracé à partir d'une image satellite de celui-ci. On remarque que la mesure la plus près de ce point est celle réalisée avec Phyphox. Nous y reviendrons. Pour les deux autres mesures, elles sont tout de même éloignées de plusieurs mètres. + +Enfin, la figure \ref{figure:gpsmesurescentre} montre deux point dont le positionnement cartographique est mal assuré, puisque il a été obtenu par estimation visuelle. Mais, on voit que les écarts sont importants et, à nouveau, que c'est Phyphox qui s'en sort le mieux. + +\medskip +La raison pour laquelle Phyphox s'en sort relativement bien semble être due au fait que dans les trois cas, la mesure effectuée avec lui a duré 300 secondes, soit cinq minutes, alors que pour les autres mesures, celles-ci ont duré moins de trente secondes. + +On peut comprendre cela en regardant les graphes de l'évolution des mesures faites avec Phyphox \dots + \section{Imagerie satellitaire} Cette section est une introduction à l'imagerie satellitaire. QGis est au centre de cette découverte qui a pour objectif de présenter ses possibilités de superposition d'information météorologique, océanographiques, \dots{} On peut ainsi imaginer faire travailler des élèves sur différentes situations météorologiques pour leur permettre d'apprendre à lire des cartes météo ou leur faire découvrir les fond océaniques pour étudier les plaques tectoniques. @@ -1740,6 +1782,51 @@ Image format: image/png Ces informations sont très intéressantes et exploitables par les étudiants. \subsubsection{Construction des cartes} +Comme nous l'avons montré dans la partie principale de ce document, une carte n'est pas une construction neutre. Au mieux, elle donne à voir certains aspects relativement objectifs de la réalité. On peut imaginer les images satellites plus objectives que les cartes symboliques. S'il n'en est en réalité rien en raison des déformations liées à l'imagerie elle-même (on sait que selon la focale, un objectif déforme plus ou moins l'image qu'il produit), certains type d'images satellites peut être très problématique à comprendre. C'est le cas, par exemple, des images de la canopées. En effet, des informations précises sur ce que ces images représentes sont nécessaires pour en saisir convenablement le sens. + +La figure \ref{figure:canopeechxfds} présente la canopée autour de la ville de la Chaux-de-Fonds. +\begin{figure}[c] + \centering + \includegraphics[width=\textwidth]{images/CanopeeChxFds.eps} + \caption{La canopée de la Chaux-de-Fonds} + \label{figure:canopeechxfds} +\end{figure} + +Deux couches sont présentes. Le fond est la carte d'OpenStreetMap et la couche supérieure vient des cartes de \emph{Glad Tree Canopy Height 2020}\footnote{Voir le site GLAD (Global Land Analysis \& Discovery)~: \url{https://glad.umd.edu/}}. Qgis, par l'intermédiaire de Search QMS, donne les informations suivantes sur cette couche~: +\begin{quotation} + \og \textbf{General info} + +Description: Global Forest Canopy Height, 2019 P. Potapov, X. Li, A. Hernandez-Serna, A. Tyukavina, M.C. Hansen, A. Kommareddy, A. Pickens, S. Turubanova, H. Tang, C. E. Silva, J. Armston, R. Dubayah, J. B. Blair, M. Hofton (2020). A new, 30-m spatial resolution global forest canopy height map was developed through the integration of the Global Ecosystem Dynamics Investigation (GEDI) lidar forest structure measurements and Landsat analysis-ready data time-series (Landsat ARD). The GEDI RH95 (relative height at 95%) metric was used to calibrate the model. The Landsat multi-temporal metrics that represent the surface phenology serve as the independent variables. The “moving window” locally calibrated and applied regression tree ensemble model was implemented to ensure high quality of forest height prediction and global map consistency. The model was extrapolated in the boreal regions (beyond the GEDI data range, 52°N to 52°S) to create the global forest height prototype map. GEDI: https://gedi.umd.edu Landsat ARD: https://glad.umd.edu/ard/home Data download: https://glad.umd.edu/dataset/gedi + +Type: WMS + +CRS: 4326 + +Submitter: glushkov2igor + +Source: Aucun(e) + +Date added: 15 septembre 2020 10:23 + +Last update: 17 septembre 2020 15:17 + +Service boundary: none + +Status: works \fg +\end{quotation} + +À part l'explication~: +\begin{quotation} + \og Une nouvelle carte de la hauteur de la canopée de 30 mètres de résolution spatiale a été développée par l'intégration de mesures lidar de la structure de la forêt du Global Ecosystem Dynamics Investigation (GEDI) et des séries de données temporelles prêtes pour l'analyse de Landsat (Landsat ARD).\fg +\end{quotation} + +aucune explication réelle n'est fournie. Pour obtenir une information plus détaillée, il est nécessaire de se rendre sur le site de GLAD\footnote{Voir~: \url{https://glad.umd.edu/}} et de choisir, parmi les multiples données qu'il fournit (onglet \emph{DATASET}), les \emph{GLAD Landsat ARD Tools}\footnote{Voir~: \url{https://glad.umd.edu/ard/home}}. Une section \emph{Landsat ARD Methodology} permet d'entrevoir comment la carte a pu être partiellement construite. Partiellement, car il s'agit de la partie \emph{Landsat ARD}, qui est utilisée parallèlement à l'analyse lidar du GEDI. Pour des renseignements à ce sujet, il faut se rendre sur le site éponyme du GEDI\footnote{Voir~: \url{https://gedi.umd.edu/}}. + +\medskip +La construction d'une carte de la canopée autour de la Chaux-de-Fonds est donc tributaire de recherches de documentation supplémentaire, ne serait-ce que pour obtenir une échelle de couleur permettant de \dots + +\subsection{Indice de végétation} +Évidemment, \subsection{Arcgisonline.com} diff --git a/images/CanopeeChxFds.eps b/images/CanopeeChxFds.eps new file mode 100644 index 0000000..8c92d81 --- /dev/null +++ b/images/CanopeeChxFds.eps @@ -0,0 +1,23014 @@ +%!PS-Adobe-3.0 EPSF-3.0 +%%Creator: GIMP PostScript file plug-in V 1.17 by Peter Kirchgessner +%%Title: CanopeeChxFds.eps +%%CreationDate: Thu Oct 22 23:49:54 2020 +%%DocumentData: Clean7Bit +%%LanguageLevel: 2 +%%Pages: 1 +%%BoundingBox: 14 14 988 562 +%%EndComments +%%BeginProlog +% Use own dictionary to avoid conflicts +10 dict begin +%%EndProlog +%%Page: 1 1 +% Translate for offset 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