25:["$","title",null,{"children":"Etude de l'évolution de la production et de la récolte de bois commercialisé en France métropolitaine | Thomas | Observable"}] 49:T4f9,Le placement des arbres dans le zoom de la région sélectionnée repose sur une logique combinant le centre de la zone et la distance aux bords. On cherche à ce que ces arbres restent à l'intérieur de la région et ne se chevauchent pas. Tout d’abord, on identifie le point le plus à l’intérieur de la région, c'est-à-dire le plus éloigné des frontières, sous forme de test de chaque carré d'une grille 9*9. Ensuite, on définit 3 secteurs angulaires depuis le centre : vers le Nord, vers Sud-Ouest et vers le Sud-Est. On cherche ensuite le meilleur point dans chaque secteur. On teste plusieurs positions en combinant 8 directions et 6 rayons différents, et on vérifie pour chaque position si on est toujours dans la région, si on est pas trop proche d'un groupe déjà placé et si on est pas trop près des bords. Un score est calculé en fonction de la distance aux bords et au centre, on garde la position ayant le meilleur score. Enfin, on place les 3 groupes dans l'ordre grumes vers le Nord, Bois d'industrie vers le Sud-Ouest et bois d'énergie vers le Sud-Est, et on dessine les arbres avec une taille proportionnelle à leur quantité, mais en respectant une taille minimale, afin qu'ils soient toujours visible même dans les petites zones.4a:T54b,## Résultats - On distingue avant tout 4 grandes régions de récolte de bois en France (Nouvelle-Aquitaine, Auvergne-Rhône-Alpes, Bourgogne-Franche-Comté et Grand Est), où la majorité de récolte de bois français a lieu. - Au contraire, la Corse se distingue par sa quasi absence de récolte en bois au cours de l'année 2023. En regardant les détails, on observe que seuls 16 000 m^3 ont été récolté sur l'année (soit près d'un millième de la récolte totale en Nouvelle-Aquitaine, et un centième en termes de densité), dont les 3 quarts étant des bois d'énergie. - Dû à son important urbanisme, l'Île de France est également moins performante en récoltes de bois, et se concentre principalement sur la récolte de bois d'énergie. - Les Hauts-de-France se placent en doyens de forêts durables, avec près de 70% de bois certifiés (provenant de forêts gérées durablement). - L'évolution de la récolte des types de bois en France entre 2018 et 2023 montre globalement une constance des récoltes pour tout type de bois au cours de ces 6 années. Cependant, une distingue tout de même une baisse de régime en 2020 (diminution de l'ordre de 5% de la récolte totale) lors du confinement avec un léger rattrapage en 2021. - La récolte de grumes feuillus n'a quant à elle quasiment pas été affectée par le Covid19.4b:T843,// On crée un tableau de fusion des données enrichedRegions = { const features = regions.features.map(region => { const code = region.properties.code; let nom = region.properties.nom; // Normaliser les accents if (nom === "Île-de-France") { nom = "Ile-de-France"; } if (nom === "Bourgogne-Franche-Comté") { nom = "Bourgogne-Franche-Comte"; } if (nom === "Auvergne-Rhône-Alpes") { nom = "Auvergne-Rhone-Alpes"; } if (nom === "Provence-Alpes-Côte d'Azur") { nom = "Provence-Alpes-Cote d'Azur"; } const data = dataRecolte.find(d => { const regionCode = Object.entries(regionMapping).find( ([name, c]) => c === code ); return regionCode && d.region.includes(regionCode[0].split('-')[0]); }) || dataRecolte.find(d => d.region.toLowerCase().includes(nom.toLowerCase().split('-')[0]) ); const superficie = superficiesRegions[nom] || 1; // 1 pour éviter division par zéro // Calculer les densités (en milliers m³ / km²) const totalRecolte = data ? data.totalRecolte : 0; const grumes = data ? data.grumes : 0; const boisIndustrie = data ? data.boisIndustrie : 0; const boisEnergie = data ? data.boisEnergie : 0; const boisCertifies = data ? data.boisCertifies : 0; return { type: "Feature", geometry: region.geometry, properties: { ...region.properties, superficie: superficie, // Valeurs absolues de stockage totalRecolteAbs: totalRecolte, grumesAbs: grumes, boisIndustrieAbs: boisIndustrie, boisEnergieAbs: boisEnergie, boisCertifiesAbs: boisCertifies, // Densités pour faire une vraie carte choroplèthe totalRecolte: totalRecolte / superficie *1000, grumes: grumes / superficie *1000, boisIndustrie: boisIndustrie / superficie *1000, boisEnergie: boisEnergie / superficie *1000, boisCertifies: boisCertifies / superficie*1000 } }; }); return { type: "FeatureCollection", features: features }; }4c:T232a,viewof carteRecolte = { const container = d3.create("div") .style("position", "relative") .style("width", `${width}px`) .style("height", `${height}px`); // svg const svg = container.append("svg") .attr("width", width) .attr("height", height) .attr("viewBox", [0, 0, width, height]) .style("max-width", "100%") .style("height", "auto"); const g = svg.append("g"); // tooltip const tooltip = container.append("div") .style("position", "absolute") .style("display", "none") .style("background-color", "white") .style("border", "2px solid #333") .style("border-radius", "4px") .style("padding", "10px") .style("pointer-events", "none") .style("box-shadow", "0 2px 8px rgba(0,0,0,0.2)") .style("font-size", "13px") .style("line-height", "1.5") .style("z-index", "1000"); // Dessin des régions const paths = g.selectAll("path") .data(enrichedRegions.features) .join("path") .attr("d", path) .attr("fill", d => { const value = d.properties[typeBoisSelectionne]; return value > 0 ? colorScaleRecolte(value) : "#e0e0e0"; // Couleur de la région selon la récolte }) .attr("stroke", d => { // Si c'est la région sélectionnée, on épaissit la bordure return regionSelectionnee && regionSelectionnee.properties.code === d.properties.code ? "black" : "black" }) .attr("stroke-width", d => { return regionSelectionnee && regionSelectionnee.properties.code === d.properties.code ? 2 : 1; }) .style("opacity", d => { // On atténue les autres régions si une est sélectionnée if (!regionSelectionnee) return 1; return regionSelectionnee.properties.code === d.properties.code ? 1 : 0.5; }) .style("cursor", "pointer") .on("mouseover", function(event, d) { if (!regionSelectionnee || regionSelectionnee.properties.code !== d.properties.code) { d3.select(this) .attr("stroke", "#666") .attr("stroke-width", 3); } // Données de la région const nom = d.properties.nom; const total = d.properties.totalRecolteAbs; const grumes = d.properties.grumesAbs; const industrie = d.properties.boisIndustrieAbs; const energie = d.properties.boisEnergieAbs; const certifies = d.properties.boisCertifiesAbs; const valeurSelectionnee = d.properties[typeBoisSelectionne]; const superficie = d.properties.superficie; // Densités const totalDensite = d.properties.totalRecolte; const grumesDensite = d.properties.grumes; const industrieDensite = d.properties.boisIndustrie; const energieDensite = d.properties.boisEnergie; const certifiesDensite = d.properties.boisCertifies; // Pourcentage de bois certifié const pctCertifies = total > 0 ? ((certifies / total) * 100).toFixed(1) : 0; // Affichage du tooltip tooltip .style("display", "block") .style("left", (event.offsetX + 15) + "px") .style("top", (event.offsetY - 100) + "px") .html(`

${nom}

Superficie : ${superficie.toLocaleString()} km²

Densité récolte totale : ${totalDensite.toLocaleString()} m³/km²

• Densité grumes : ${grumesDensite.toLocaleString()} m³/km²

• Densité bois d'industrie : ${industrieDensite.toLocaleString()} m³/km²

• Densité bois énergie : ${energieDensite.toLocaleString()} m³/km²

Densité bois certifiés : ${certifiesDensite.toLocaleString()} m³/km² (${pctCertifies}%)

Cliquez pour voir les détails

`); }) .on("mousemove", function(event) { tooltip .style("left", (event.offsetX + 15) + "px") .style("top", (event.offsetY - 100) + "px"); }) .on("mouseout", function(event, d) { // Retour à la normale si ce n'est pas la région sélectionnée if (!regionSelectionnee || regionSelectionnee.properties.code !== d.properties.code) { d3.select(this) .attr("stroke", "black") .attr("stroke-width", 1); } tooltip.style("display", "none"); }) .on("click", function(event, d) { viewof regionSelectionnee.value = d; viewof regionSelectionnee.dispatchEvent(new CustomEvent("input")); }); // RAJOUT DES ARBRES // Calcul des seuils pour afficher de 1 à 5 arbres const maxRecolte = d3.max(enrichedRegions.features, d => d.properties[typeBoisSelectionne]); const seuil1Arbre = maxRecolte * 0.15; // < 15% = 1 arbre const seuil2Arbres = maxRecolte * 0.30; // 15-30% = 2 arbres const seuil3Arbres = maxRecolte * 0.50; // 30-50% = 3 arbres const seuil4Arbres = maxRecolte * 0.70; // 50-70% = 4 arbres // > 70% = 5 arbres function dessinerArbre(x, y, taille) { const groupe = g.append("g") .attr("transform", `translate(${x}, ${y})`) .attr("pointer-events", "none"); // Rajout d'un outline autour des arbres pour qu'on puisse les distinguer même dans les régions à forte densité de récoltes // Contour tronc groupe.append("rect") .attr("x", -taille * 0.15) .attr("y", 0) .attr("width", taille * 0.3) .attr("height", taille * 0.5) .attr("fill", "none") .attr("stroke", "white") .attr("stroke-width", 2); // Contour du feuillage const triangles = [ { y: -taille * 0.3, size: 0.8 }, { y: -taille * 0.5, size: 0.7 }, { y: -taille * 0.65, size: 0.6 } ]; triangles.forEach(t => { groupe.append("polygon") .attr("points", ` 0,${t.y} ${-taille * t.size},${t.y + taille * 0.4} ${taille * t.size},${t.y + taille * 0.4} `) .attr("fill", "none") .attr("stroke", "white") .attr("stroke-width", 2) .attr("stroke-linejoin", "round"); }); // Dessin des arbres // Tronc rempli groupe.append("rect") .attr("x", -taille * 0.15) .attr("y", 0) .attr("width", taille * 0.3) .attr("height", taille * 0.5) .attr("fill", "#8B4513") .attr("stroke", "none"); // Feuillage rempli triangles.forEach(t => { groupe.append("polygon") .attr("points", ` 0,${t.y} ${-taille * t.size},${t.y + taille * 0.4} ${taille * t.size},${t.y + taille * 0.4} `) .attr("fill", "#2d5016") .attr("stroke", "none"); }); return groupe; } // Ajout des arbres sur chaque région enrichedRegions.features.forEach(d => { const recolte = d.properties[typeBoisSelectionne]; if (recolte === 0) return; const centroid = path.centroid(d); const cx = centroid[0]; const cy = centroid[1]; let nbArbres = 1; if (recolte > seuil4Arbres) { nbArbres = 5; } else if (recolte > seuil3Arbres) { nbArbres = 4; } else if (recolte > seuil2Arbres) { nbArbres = 3; } else if (recolte > seuil1Arbre) { nbArbres = 2; } const tailleBase = 14; const espacement = tailleBase * 0.9; // Positionnement des arbres selon leur nombre if (nbArbres === 1) { dessinerArbre(cx, cy, tailleBase); } else if (nbArbres === 2) { dessinerArbre(cx - espacement, cy, tailleBase); dessinerArbre(cx + espacement, cy, tailleBase); } else if (nbArbres === 3) { dessinerArbre(cx, cy - espacement * 0.5, tailleBase); dessinerArbre(cx - espacement, cy + espacement * 0.3, tailleBase); dessinerArbre(cx + espacement, cy + espacement * 0.3, tailleBase); } else if (nbArbres === 4) { dessinerArbre(cx, cy - espacement * 0.8, tailleBase); dessinerArbre(cx - espacement, cy, tailleBase); dessinerArbre(cx + espacement, cy, tailleBase); dessinerArbre(cx, cy + espacement * 0.8, tailleBase); } else if (nbArbres === 5) { dessinerArbre(cx, cy, tailleBase); dessinerArbre(cx - espacement, cy - espacement * 0.8, tailleBase * 0.9); dessinerArbre(cx + espacement, cy - espacement * 0.8, tailleBase * 0.9); dessinerArbre(cx - espacement, cy + espacement * 0.8, tailleBase * 0.9); dessinerArbre(cx + espacement, cy + espacement * 0.8, tailleBase * 0.9); } }); container.value = regionSelectionnee; return container.node(); }4d:T733,legendeRecolte = { //légende carte choroplèthe couleurs const legendWidth = 300; const legendHeight = 50; const svg = d3.create("svg") .attr("width", legendWidth + 100) .attr("height", legendHeight + 40) .style("display", "block") .style("margin", "20px auto"); // Titre const titres = { totalRecolte: "Densité de récolte totale", grumes: "Densité de grumes", boisIndustrie: "Densité de bois d'industrie", boisEnergie: "Densité de bois énergie", boisCertifies: "Densité de bois certifiés" }; svg.append("text") .attr("x", (legendWidth + 100) / 2) .attr("y", 15) .attr("text-anchor", "middle") .attr("font-weight", "bold") .attr("font-size", "14px") .text(`${titres[typeBoisSelectionne]} (milliers m³/km²) - 2023`); // Gradient const defs = svg.append("defs"); const gradient = defs.append("linearGradient") .attr("id", "legend-gradient-recolte"); const numStops = 10; for (let i = 0; i <= numStops; i++) { const t = i / numStops; gradient.append("stop") .attr("offset", `${t * 100}%`) .attr("stop-color", colorScaleRecolte(domainRecolte[0] + t * (domainRecolte[1] - domainRecolte[0]))); } // Rectangle du gradient svg.append("rect") .attr("x", 50) .attr("y", 25) .attr("width", legendWidth) .attr("height", 20) .style("fill", "url(#legend-gradient-recolte)") .attr("stroke", "#ccc") .attr("stroke-width", 1); // Labels svg.append("text") .attr("x", 50) .attr("y", 60) .attr("text-anchor", "start") .attr("font-size", "12px") .text("0"); svg.append("text") .attr("x", 350) .attr("y", 60) .attr("text-anchor", "end") .attr("font-size", "12px") .text(Math.round(domainRecolte[1].toFixed(2))); return svg.node(); }4e:T4f6,legendeArbres = html`

🌲 Niveau de production

🌲 Très faible (< 15%)

🌲🌲 Faible (15-30%)

🌲🌲🌲 Moyenne (30-50%)

🌲🌲🌲🌲 Élevée (50-70%)

🌲🌲🌲🌲🌲 Très élevée (> 70%)

`;4f:Tee3,legendeCombinee = { const container = d3.create("div") .style("background", "white") .style("padding", "15px") .style("border-radius", "8px") .style("margin-top", "10px") .style("box-shadow", "0 2px 4px rgba(0,0,0,0.1)") .style("display", "flex") .style("gap", "20px") .style("align-items", "flex-start"); //Gradient vertical const svgWidth = 80; const svgHeight = 220; const gradientWidth = 30; const gradientHeight = 150; const svg = d3.create("svg") .attr("width", svgWidth) .attr("height", svgHeight); const titres = { totalRecolte: "Récolte", grumes: "Grumes", boisIndustrie: "Bois industrie", boisEnergie: "Bois énergie", boisCertifies: "Bois certifiés" }; svg.append("text") .attr("x", svgWidth / 2) .attr("y", 15) .attr("text-anchor", "middle") .attr("font-weight", "bold") .attr("font-size", "16px") .attr("fill", "#2d5016") .text("Densité"); const defs = svg.append("defs"); const gradient = defs.append("linearGradient") .attr("id", "legend-gradient-vertical") .attr("x1", "0%") .attr("y1", "100%") .attr("x2", "0%") .attr("y2", "0%"); const numStops = 10; for (let i = 0; i <= numStops; i++) { const t = i / numStops; gradient.append("stop") .attr("offset", `${t * 100}%`) .attr("stop-color", colorScaleRecolte(domainRecolte[0] + t * (domainRecolte[1] - domainRecolte[0]))); } // Rectangle vertical du gradient const rectX = (svgWidth - gradientWidth) / 2; const rectY = 38; svg.append("rect") .attr("x", rectX) .attr("y", rectY) .attr("width", gradientWidth) .attr("height", gradientHeight) .style("fill", "url(#legend-gradient-vertical)") .attr("stroke", "#ccc") .attr("stroke-width", 1); // Labels svg.append("text") .attr("x", svgWidth / 2) .attr("y", rectY + gradientHeight + 15) .attr("text-anchor", "middle") .attr("font-size", "10px") .text("0"); svg.append("text") .attr("x", svgWidth / 2) .attr("y", rectY-5) .attr("text-anchor", "middle") .attr("font-size", "13px") .text(Math.round(domainRecolte[1])); container.node().appendChild(svg.node()); // Légende des arbres const legendeArbres = document.createElement("div"); legendeArbres.style.flex = "1"; legendeArbres.innerHTML = `

${titres[typeBoisSelectionne]}

🌲🌲🌲🌲🌲 Très élevée (> 70%)

🌲🌲🌲🌲 Élevée (50-70%)

🌲🌲🌲 Moyenne (30-50%)

🌲🌲 Faible (15-30%)

🌲 Très faible (< 15%)

`; container.node().appendChild(legendeArbres); return container.node(); }50:T212e,detailsRegion = { if (!regionSelectionnee) { return html`

Cliquez sur une région pour voir ses détails

`; } const d = regionSelectionnee; const miniWidth = 400, miniHeight = 240; const miniProjection = d3.geoMercator().fitSize([miniWidth, miniHeight], d); const miniPath = d3.geoPath().projection(miniProjection); const total = d.properties.totalRecolte; const grumes = d.properties.grumesAbs; const industrie = d.properties.boisIndustrieAbs; const energie = d.properties.boisEnergieAbs; const UNITE=200; const allCategories = [ { name: "Grumes", value : grumes, color: "#8B4513", darkColor: "#5C2D0A" }, { name: "Bois d'industrie", value : industrie, color: "#D2691E", darkColor: "#8B4210" }, { name: "Bois énergie", value : energie, color: "#FF6347", darkColor: "#B22000" }, ].filter(c => c.value > 0); const n = allCategories.length; const SCALE = 5; const gW = Math.ceil(miniWidth / SCALE); const gH = Math.ceil(miniHeight / SCALE); const offCanvas = document.createElement("canvas"); offCanvas.width = gW; offCanvas.height = gH; const offCtx = offCanvas.getContext("2d"); offCtx.scale(1 / SCALE, 1 / SCALE); offCtx.fill(new Path2D(miniPath(d))); const pixels = offCtx.getImageData(0, 0, gW, gH).data; function isInside(px, py) { const gx = Math.round(px / SCALE), gy = Math.round(py / SCALE); if (gx < 0 || gx >= gW || gy < 0 || gy >= gH) return false; return pixels[(gy * gW + gx) * 4 + 3] > 128; } function borderDist(px, py) { let minD = Infinity; for (let a = 0; a < Math.PI * 2; a += Math.PI / 4) { for (let r = SCALE; r < 120; r += SCALE) { if (!isInside(px + Math.cos(a) * r, py + Math.sin(a) * r)) { minD = Math.min(minD, r); break; } } } return minD; } // Pôle d'inaccessibilité : grille 9×9 autour du centroïde const [cxReal, cyReal] = miniPath.centroid(d); function findDeepestPoint(startX, startY) { let bestX = startX, bestY = startY, bestDist = 0; const searchR = 60, step = SCALE * 2; for (let dx = -searchR; dx <= searchR; dx += step) { for (let dy = -searchR; dy <= searchR; dy += step) { const px = startX + dx, py = startY + dy; if (!isInside(px, py)) continue; const dist = borderDist(px, py); if (dist > bestDist) { bestDist = dist; bestX = px; bestY = py; } } } return { x: bestX, y: bestY, safeR: bestDist }; } const pole = findDeepestPoint(cxReal, cyReal); const cx = pole.x, cy = pole.y; // Meilleur point dans un secteur avec distance minimale aux autres groupes function findBestInSector(centerAngle, spreadAngle, already = [], minSep = 50) { const maxR = Math.max(pole.safeR * 2.0, 55); let bestX = cx, bestY = cy, bestScore = -Infinity; for (let ai = 0; ai < 8; ai++) { const a = centerAngle - spreadAngle / 2 + ai * (spreadAngle / 7); for (let fi = 2; fi <= 7; fi++) { const r = maxR * (fi / 7); const px = cx + Math.cos(a) * r; const py = cy + Math.sin(a) * r; if (!isInside(px, py)) continue; const tooClose = already.some(p => Math.hypot(px - p.x, py - p.y) < minSep); if (tooClose) continue; const dist = borderDist(px, py); const score = dist + Math.hypot(px - cx, py - cy) * 0.35; if (score > bestScore) { bestScore = score; bestX = px; bestY = py; } } } return { x: bestX, y: bestY }; } const [[x0,y0],[x1,y1]] = miniPath.bounds(d); const regionW = x1-x0, regionH = y1-y0; // La distance minimale entre groupes est proportionnelle à la taille de la région const minSep = Math.min(regionW, regionH) * 0.30; let groupPositions; if (n === 1) { groupPositions = [{ x: cx, y: cy }]; } else if (n === 2) { const p1 = findBestInSector(-Math.PI / 2, Math.PI * 0.9, [], minSep); const p2 = findBestInSector( Math.PI / 2, Math.PI * 0.9, [p1], minSep); groupPositions = [p1, p2]; } else { const p1 = findBestInSector(-Math.PI / 2, Math.PI * 0.7, [], minSep); const p2 = findBestInSector( Math.PI * 5 / 6, Math.PI * 0.7, [p1], minSep); const p3 = findBestInSector(-Math.PI / 6, Math.PI * 0.7, [p1,p2], minSep); groupPositions = [p1, p2, p3]; } // Dessin d'arbre function drawTree(parent, x, y, size, fillColor, darkColor) { const scale = 0.82 + Math.abs(Math.sin(x * 4.1 + y * 2.7)) * 0.36; const s = size * scale; const grp = parent.append("g") .attr("transform", `translate(${x},${y})`) .attr("pointer-events", "none"); grp.append("ellipse") .attr("cx", s * 0.1).attr("cy", s * 0.08) .attr("rx", s * 0.38).attr("ry", s * 0.1) .attr("fill", "rgba(0,0,0,0.12)"); grp.append("rect") .attr("x", - s * 0.13).attr("y", 0) .attr("width", s * 0.26).attr("height", s * 0.5) .attr("fill", "#7B4F2E"); [ { dy: -s * 0.20, w: 0.74 }, { dy: -s * 0.42, w: 0.58 }, { dy: -s * 0.60, w: 0.44 }, ].forEach(t => { grp.append("polygon") .attr("points", `0,${t.dy} ${-s*t.w},${t.dy+s*0.37} ${s*t.w},${t.dy+s*0.37}`) .attr("fill", fillColor) .attr("stroke", darkColor) .attr("stroke-width", 0.4); }); } function drawGroup(parent, centerX, centerY, cat, nbTrees, treeSize) { const spacingX = treeSize * 1.55; const spacingY = treeSize * 1.80; const cols = Math.max(1, Math.ceil(Math.sqrt(nbTrees * 1.4))); const rows = Math.ceil(nbTrees / cols); const gridW = (cols - 1) * spacingX; const gridH = (rows - 1) * spacingY; let count = 0; for (let row = 0; row < rows && count < nbTrees; row++) { const offsetX = (row % 2 === 1) ? spacingX * 0.5 : 0; const colsThisRow = (row === rows - 1) ? (nbTrees - row * cols) : cols; for (let col = 0; col < colsThisRow && count < nbTrees; col++) { const jx = Math.sin(count * 6.1 + centerX) * 1.8; const jy = Math.cos(count * 4.3 + centerY) * 1.2; const tx = centerX - gridW / 2 + col * spacingX + offsetX + jx; const ty = centerY - gridH / 2 + row * spacingY + jy; drawTree(parent, tx, ty, treeSize, cat.color, cat.darkColor); count++; } } } //svg const svg = d3.create("svg") .attr("width", miniWidth).attr("height", miniHeight) .style("display", "block").style("margin", "0 auto") .style("border-radius", "6px"); const defs = svg.append("defs"); const skyGrad = defs.append("linearGradient") .attr("id","sky2").attr("x1","0").attr("y1","0").attr("x2","0").attr("y2","1"); skyGrad.append("stop").attr("offset","0%").attr("stop-color","#c8dff0"); skyGrad.append("stop").attr("offset","100%").attr("stop-color","#e8f4f8"); svg.append("rect").attr("width",miniWidth).attr("height",miniHeight).attr("fill","url(#sky2)"); const g = svg.append("g"); g.append("path") .attr("d", miniPath(d)) .attr("fill", "#c8dba0") .attr("stroke", "#FF6B35") .attr("stroke-width", 2); defs.append("clipPath").attr("id","region-clip-detail") .append("path").attr("d", miniPath(d)); const forestG = g.append("g").attr("clip-path","url(#region-clip-detail)"); const treeSize = Math.max(8, Math.min(16, Math.min(regionW, regionH) * 0.055)); allCategories.forEach((cat, i) => { const pos = groupPositions[i]; const nbTrees = Math.max(1, Math.round(cat.value / UNITE)); drawGroup(forestG, pos.x, pos.y, cat, nbTrees, treeSize); }); g.append("path") .attr("d", miniPath(d)) .attr("fill", "none") .attr("stroke", "#FF6B35") .attr("stroke-width", 2.5); return html`

${d.properties.nom} — ${total.toLocaleString()} milliers m³ total

${svg.node()}

🌲 1 arbre = ${UNITE} milliers m³ | ${n} groupe${n>1?"s":""} de catégories

`; }51:Tfa4,tableauRegion = { if (! regionSelectionnee) { return html`

Répartition de la production

${data.map((d, i) => html` `)}

Catégorie	Volume (milliers m³)	% du total	Visualisation
${d.categorie}	${d.valeur.toLocaleString()}	${d.pct}%
TOTAL	${total.toLocaleString()}

`; }52:Taf2,camembertRegion = { if (! regionSelectionnee) { return html`

`; } const region = regionSelectionnee; const total = region.properties.totalRecolteAbs; const grumes = region.properties.grumesAbs; const industrie = region.properties.boisIndustrieAbs; const energie = region.properties.boisEnergieAbs; const autres = total - grumes - industrie - energie; const data = [ { name: "Grumes", value: grumes, color: "#8B4513" }, { name: "Bois d'industrie", value: industrie, color: "#D2691E" }, { name: "Bois énergie", value: energie, color: "#FF6347" }, { name: "Autres bois", value: autres, color: "#8CCC89" } ].filter(d => d.value > 0); const width = 400; const height = 300; const radius = Math.min(width, height) / 2 - 40; const svg = d3.create("svg") .attr("width", width) .attr("height", height) .attr("viewBox", [0, 0, width, height]) .style("max-width", "100%") .style("height", "auto"); const g = svg.append("g") .attr("transform", `translate(${width / 2 + 75}, ${height / 2})`); const pie = d3.pie() .value(d => d.value) .sort(null); const arc = d3.arc() .innerRadius(0) .outerRadius(radius); const arcHover = d3.arc() .innerRadius(0) .outerRadius(radius + 10); const arcs = g.selectAll("arc") .data(pie(data)) .join("g") .attr("class", "arc"); arcs.append("path") .attr("d", arc) .attr("fill", d => d.data.color) .attr("stroke", "white") .attr("stroke-width", 2) .style("cursor", "pointer") .on("mouseover", function(event, d) { d3.select(this) .transition() .duration(200) .attr("d", arcHover); }) .on("mouseout", function() { d3.select(this) .transition() .duration(200) .attr("d", arc); }); arcs.append("text") .attr("transform", d => `translate(${arc.centroid(d)})`) .attr("text-anchor", "middle") .attr("fill", "white") .attr("font-weight", "bold") .attr("font-size", "12px") .attr("pointer-events", "none") .text(d => { const pct = ((d.data.value / d3.sum(data, v => v.value)) * 100).toFixed(0); return pct > 5 ? `${pct}%` : ""; }); // Légende const legend = svg.append("g") .attr("transform", `translate(10, 10)`); data.forEach((d, i) => { const legendRow = legend.append("g") .attr("transform", `translate(0, ${i * 25})`); legendRow.append("rect") .attr("width", 18) .attr("height", 18) .attr("fill", d.color) .attr("rx", 3); legendRow.append("text") .attr("x", 25) .attr("y", 13) .attr("font-size", "12px") .text(`${d.name}: ${d.value.toLocaleString()}k m³`); }); return svg.node(); }53:T5d9,dataEvolution = { // On parse le csv const parsed = recoltes.map(row => { const values = row["LIBELLE;2018;2019;2020;2021;2022;2023"].split(";"); return { libelle: values[0], 2018: parseFloat(values[1]?.replace(/\s/g, '')), 2019: parseFloat(values[2]?.replace(/\s/g, '')), 2020: parseFloat(values[3]?.replace(/\s/g, '')), 2021: parseFloat(values[4]?.replace(/\s/g, '')), 2022: parseFloat(values[5]?.replace(/\s/g, '')), 2023: parseFloat(values[6]?.replace(/\s/g, '')) }; }); // Extraction des données utilisées par la suite const grumesFeuillusRow = parsed.find(d => d.libelle === "Feuillus" && parsed.indexOf(d) === 4); const autresGrumesRow = parsed.find(d => d.libelle === "Coniferes"); const boisIndustrieRow = parsed.find(d => d.libelle === "Bois d'industrie"); const boisEnergieRow = parsed.find(d => d.libelle === "Bois energie"); //const boisCertifiesRow = parsed.find(d => d.libelle === "dont bois certifie*"); // correspond bien aux données de 2023 à 3m^2 près const annees = [2018, 2019, 2020, 2021, 2022, 2023]; return annees.map(annee => ({ annee: annee, grumesFeuilllus: grumesFeuillusRow ? grumesFeuillusRow[annee] : 0, autresGrumes: autresGrumesRow ? autresGrumesRow[annee] : 0, boisIndustrie: boisIndustrieRow ? boisIndustrieRow[annee] : 0, boisEnergie: boisEnergieRow ? boisEnergieRow[annee] : 0, //boisCertifies: boisCertifiesRow ? boisCertifiesRow[annee] : 0 })); }54:Td67,graphiqueEvolution = { const width = 960; const height = 500; const marginTop = 40; const marginRight = 180; const marginBottom = 60; const marginLeft = 80; const svg = d3.create("svg") .attr("width", width) .attr("height", height) .attr("viewBox", [0, 0, width, height]) .style("max-width", "100%") .style("height", "auto"); const x = d3.scaleLinear() .domain(d3.extent(dataEvolution, d => d.annee)) .range([marginLeft, width - marginRight]); const y = d3.scaleLinear() .domain([0, d3.max(dataEvolution, d => d.grumesFeuilllus + d.autresGrumes + d.boisIndustrie + d.boisEnergie //+ d.boisCertifies )]) .nice() .range([height - marginBottom, marginTop]); // aires empilées const stack = d3.stack() .keys(categoriesEvolution.map(c => c.key)) .order(d3.stackOrderNone) .offset(d3.stackOffsetNone); const series = stack(dataEvolution); // Générateur d'aire const area = d3.area() .x(d => x(d.data.annee)) .y0(d => y(d[0])) .y1(d => y(d[1])) .curve(d3.curveMonotoneX); // Dessiner les aires svg.selectAll("path") .data(series) .join("path") .attr("fill", (d, i) => categoriesEvolution[i].couleur) .attr("d", area) .style("opacity", 0.8) .on("mouseover", function() { d3.select(this).style("opacity", 1); }) .on("mouseout", function() { d3.select(this).style("opacity", 0.8); }) .append("title") .text((d, i) => categoriesEvolution[i].nom); svg.append("g") .attr("transform", `translate(0,${height - marginBottom})`) .call(d3.axisBottom(x).tickFormat(d3.format("d")).ticks(6)) .call(g => g.select(".domain").remove()) .call(g => g.selectAll(".tick line").clone() .attr("y2", -height + marginTop + marginBottom) .attr("stroke-opacity", 0.1)) .call(g => g.append("text") .attr("x", width - marginRight) .attr("y", 35) .attr("fill", "currentColor") .attr("text-anchor", "end") .attr("font-weight", "bold") .text("Année")); svg.append("g") .attr("transform", `translate(${marginLeft},0)`) .call(d3.axisLeft(y).ticks(10)) .call(g => g.select(".domain").remove()) .call(g => g.selectAll(".tick line").clone() .attr("x2", width - marginLeft - marginRight) .attr("stroke-opacity", 0.1)) .call(g => g.append("text") .attr("x", -marginLeft) .attr("y", 20) .attr("fill", "currentColor") .attr("text-anchor", "start") .attr("font-weight", "bold") .text("Récolte (milliers m³)")); svg.append("text") .attr("x", width / 2) .attr("y", 20) .attr("text-anchor", "middle") .attr("font-size", "22px") .attr("font-weight", "bold") .attr("fill", "#2d5016") .text("Évolution de la récolte de bois en France 2018-2023"); const legend = svg.append("g") .attr("transform", `translate(${width - marginRight + 20}, ${marginTop})`); categoriesEvolution.forEach((cat, i) => { const legendRow = legend.append("g") .attr("transform", `translate(0, ${i * 25})`); legendRow.append("rect") .attr("width", 18) .attr("height", 18) .attr("fill", cat.couleur) .style("opacity", 0.8); legendRow.append("text") .attr("x", 25) .attr("y", 13) .attr("font-size", "12px") .text(cat.nom); }); return svg.node(); 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29:{"id":"d960fe6f50c56419","slug":null,"title":"Etude de l'évolution de la production et de la récolte de bois commercialisé en France métropolitaine","thumbnail":"50b5cc2e0244ff54d307a575f2804e0e0d0bbfdd6dff740dc18a6b7747ef6900","access_level":"public","create_time":"$D2026-01-26T08:20:44.527Z","update_time":"$D2026-03-09T14:13:46.181Z","view_time":null,"first_public_time":"$D2026-01-26T09:26:54.941Z","has_unpublished_edits":null,"fork":false,"stars":0,"starred":false,"owner":{"type":"team","id":"3874ede34560a245","login":"thomas31","name":"Thomas","avatar_url":"https://avatars-next.observableusercontent.com/b4665a07c0af05c7e35458c4b3f163df23d96d43d3ccc44be2a74895e9a3e761","tier":"starter_2024","bio":"","followed_by_you":false,"follows_you":false},"version":831,"publish_version":null,"role":null,"authored":false,"authors":[{"type":"individual","id":"179b3f857fafed12","login":"thomas14","name":"Thomas","avatar_url":"https://avatars-next.observableusercontent.com/bac0b2ec6257d07a0a81e0c9ab1a164f205bcd130ba06fea682f9064cd9c6680","tier":null,"bio":"","followed_by_you":false,"follows_you":false}],"members":[{"type":"individual","id":"179b3f857fafed12","login":"thomas14","name":"Thomas","avatar_url":"https://avatars-next.observableusercontent.com/bac0b2ec6257d07a0a81e0c9ab1a164f205bcd130ba06fea682f9064cd9c6680","tier":null,"role":"editor"},{"type":"team","id":"3874ede34560a245","login":"thomas31","name":"Thomas","avatar_url":"https://avatars-next.observableusercontent.com/b4665a07c0af05c7e35458c4b3f163df23d96d43d3ccc44be2a74895e9a3e761","tier":"starter_2024","role":"editor"}],"comments":[],"custom_thumbnail":false,"trashed":false,"lapsed":null,"subscribed":null,"forks":5,"collection":null,"type":"notebook","body":{"titling":"auto","title":"Etude de l'évolution de la production et de la récolte de bois commercialisé en France métropolitaine","cells":[{"id":0,"value":"# Etude de l'évolution de la production et de la récolte de bois commercialisé en France métropolitaine ","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":812,"value":" Hugo Eberschweiler et Thomas Papon.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":5,"value":"### Description\n\nCe projet cherche à réaliser analyse spatio-temporelle de l’évolution de la récolte et de la production de bois en France métropolitaine entre 2018 et 2023, en mettant en évidence les disparités régionales et les tendances temporelles selon les types de produits bois.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":8,"value":"### Visualisations principales\n\n- Carte \"choroplèthe\" interactive avec des arbres en plus des couleurs pour visualiser la densité de récolte de bois en 2023 par région.\n\n- Détails de récolte (en quantité absolue cette fois) d'une région en 2023 : zoom sur le région, tableau de données, camembert de répartition des récoltes.\n\n- Graphique de récolte de bois en France au cours du temps, entre 2018 et 2023.\n\n### Interactions\n\n- Sélection de la région affichant les détails sous différents formats\n\n- Filtrage par type de bois récolté \n\n- Tooltip affichant les valeurs exactes par région lorsque l'on passe la souris dessus\n","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":795,"value":"### Origine des données\n\nLa base de données provient d'une enquête sur les exploitations forestières et scieries par le Service de la statistique et de la prospective (SSP) du ministère en charge de l’agriculture. Nous avons pu accéder à ces données depuis le site internet de l'Agreste agriculture (https://agreste.agriculture.gouv.fr/agreste-web/disaron/Chd2501/detail/). \n\nAvant d'ouvrir ces données sur ce notebook, nous les avons formattées à la main en effaçant les lignes de titre, description ou explication du tableau, et en effaçant les accents et autres caractères non utf-8. ","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":15,"value":"## Prototype du projet","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":13,"value":"FileAttachment(\"prototype.jpg\").image()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":475,"value":"viewof typeBoisSelectionne = Inputs.select(\n [\"totalRecolte\", \"grumes\", \"boisIndustrie\", \"boisEnergie\", \"boisCertifies\"],\n {\n label: \"Type de bois affiché\",\n format: x => ({\n totalRecolte: \"Récolte totale\",\n grumes: \"Grumes\",\n boisIndustrie: \"Bois d'industrie\",\n boisEnergie: \"Bois énergie\",\n boisCertifies: \"Bois certifiés\"\n }[x]),\n value: \"totalRecolte\"\n }\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":458,"value":"

Récolte de bois en France métropolitaine en 2023

\n ${viewof typeBoisSelectionne}\n ${viewof carteRecolte}\n ${legendeCombinee}\n

\n\n\n\n\n \n

Détails de la région

\n ${detailsRegion}\n ${tableauRegion}\n

\n ${camembertRegion}\n

\n ${graphiqueEvolution}\n

","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":499,"value":"*Un bois certifié est un bois provenant de forêts gérées durablement.\t\t\t\n","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":817,"value":"$49","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":656,"value":"========================================================================================================================================================================================================================================================================================","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":780,"value":"$4a","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":660,"value":"========================================================================================================================================================================================================================================================================================","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":27,"value":"data2 = d3.dsv(\";\", await FileAttachment(\"recolte_bois_par_region_de_provenance_2023.csv\").url(), d3.autoType)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":37,"value":"regions = FileAttachment(\"regions.geojson\").json()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":707,"value":"superficiesRegions = { // superficie des régions en km^2\n return {\n \"Nouvelle-Aquitaine\": 84102,\n \"Occitanie\": 72723,\n \"Auvergne-Rhone-Alpes\": 69711,\n \"Grand Est\": 57433,\n \"Bourgogne-Franche-Comte\": 47784,\n \"Centre-Val de Loire\": 39151,\n \"Pays de la Loire\": 32082,\n \"Provence-Alpes-Cote d'Azur\": 31400,\n \"Hauts-de-France\": 31813,\n \"Normandie\": 29906,\n \"Bretagne\": 27208,\n \"Ile-de-France\": 12012,\n \"Corse\": 8680\n };\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":44,"value":"md`**Régions chargées :** ${regions.features.length} régions\n \n**Liste des régions :**\n${regions.features.map(d => `- ${d.properties.nom} (${d.properties.code})`).join('\\n')}\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":38,"value":"height = 600","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":40,"value":"width = 550","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":47,"value":"projection = {\n const proj = d3.geoConicConformal()\n .center([2.454071, 46.279229])\n .scale(2800)\n .translate([width / 2, height / 2]);\n \n return proj;\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":49,"value":"path = d3.geoPath().projection(projection)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":55,"value":"{\n const svg = d3.create(\"svg\")\n .attr(\"width\", width)\n .attr(\"height\", height);\n \n const path = d3.geoPath().projection(projection);\n \n svg.selectAll(\"path\")\n .data(regions.features)\n .enter()\n .append(\"path\")\n .attr(\"d\", path)\n .attr(\"class\", \"department\");\n \n return svg.node();\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":62,"value":"dataRecolte = {\n // On enlève la ligne d'en-tête et de résumé sur la France entière\n const filtered = data2.filter(d => \n d.Recolte && \n d.Recolte !== \"France\" && \n d[\"Total recolte\"] !== null\n );\n \n // Nettoyage des données\n return filtered.map(d => ({\n region: d.Recolte,\n grumes: parseFloat(String(d.Grumes || 0).replace(/\\s/g, '')),\n autres: parseFloat(String(d[\"\"] || 0).replace(/\\s/g, '')),\n boisIndustrie: parseFloat(String(d[\"Bois d'industrie\"] || 0).replace(/\\s/g, '')),\n boisEnergie: parseFloat(String(d[\"Bois energie\"] || 0).replace(/\\s/g, '')),\n totalRecolte: parseFloat(String(d[\"Total recolte\"] || 0).replace(/\\s/g, '')),\n boisCertifies: parseFloat(String(d[\"Dont bois certifies\"] || 0).replace(/\\s/g, ''))\n }));\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":64,"value":"// Table de correspondance nom/code de la région \nregionMapping = {\n return {\n \"Auvergne-Rhone-Alpes\": \"84\",\n \"Bourgogne-Franche-Comte\": \"27\",\n \"Bretagne\": \"53\",\n \"Centre-Val de Loire\": \"24\",\n \"Grand Est\": \"44\",\n \"Hauts-de-France\": \"32\",\n \"Île-de-France\": \"11\",\n \"Normandie\": \"28\",\n \"Nouvelle-Aquitaine\": \"75\",\n \"Occitanie\": \"76\",\n \"Pays de la Loire\": \"52\",\n \"Provence-Alpes-Cote d'Azur\": \"93\",\n \"Corse\": \"94\"\n };\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":67,"value":"$4b","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":69,"value":"domainRecolte = {\n const values = enrichedRegions.features\n .map(d => d.properties[typeBoisSelectionne])\n .filter(v => v > 0);\n \n if (values.length === 0) return [0, 2000];\n \n return [0, d3.max(values)];\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":71,"value":"colorScaleRecolte = d3.scaleSequential()\n .interpolator(d3.interpolateGreens)\n .domain(domainRecolte)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":130,"value":"viewof regionSelectionnee = Inputs.input(null)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":664,"value":"Carte récolte","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":73,"value":"$4c","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":76,"value":"$4d","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":376,"value":"$4e","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":667,"value":"légende combinée","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":517,"value":"$4f","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":669,"value":"Détails région","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":137,"value":"$50","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":672,"value":"Tableau régions","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":139,"value":"$51","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":674,"value":"Camembert","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":141,"value":"$52","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":223,"value":"// isotypes pour exemples de pictogrammes --> couleurs\n// Remettre les pictos des arbres sur le graphe temporel\n// On voit pas très bien la différence entre 4 et 5\n// Rajouter une frontière\n// Bois certifiés, décrorreler les couleurs\n// --> Tout ça fait ✓\n\n// retours Théo :\n// Combiner les 2 légendes redondantes pour mettre en valeur leur correspondance ✓\n\n// Rajouter données Ile de France ✓\n// Rajouter données grumes conifères ?\n// Manque une réactualisation des frontières après hover si aucune région n'est sélectionnée ✓\n// Il faut diviser le stock par la superficie pour pouvoir faire une carte choroplèthe ✓\n// Modifier le texte d'intro ✓\n// Dire comment on a modifié les données : à la main, pas un script python ✓\n\n// retours de Romain et Théo : \n// Améliorer les unités sur la carte ✓\n// décrire quelque part la construction des pictogrammes (si auto ou manuels) ✓\n// Mettre un outline sur les pictos pour faciliter le contraste avec la carte ✓","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":93,"value":"statsRecolte = {\n const total = d3.sum(dataRecolte, d => d.totalRecolte);\n const totalGrumes = d3.sum(dataRecolte, d => d.grumes);\n const totalIndustrie = d3.sum(dataRecolte, d => d.boisIndustrie);\n const totalEnergie = d3.sum(dataRecolte, d => d.boisEnergie);\n const totalCertifies = d3.sum(dataRecolte, d => d.boisCertifies);\n \n // Région la plus productive\n const topRegion = dataRecolte.reduce((max, d) => \n d.totalRecolte > max.totalRecolte ? d : max\n );\n \n const pctCertifies = ((totalCertifies / total) * 100).toFixed(1);\n \n return 0\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":306,"value":"recoltes = FileAttachment(\"recolte_de_bois_en_france_metropolitaine_de_2018_2023.csv\").csv()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":311,"value":"$53","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":313,"value":"categoriesEvolution = [\n { key: \"grumesFeuilllus\", nom: \"Grumes feuillus\", couleur: \"#66320C\" }, //correspondent à l'ensemble des grumes sur la carte\n { key: \"autresGrumes\", nom: \"Autres grumes\", couleur: \"#A0522D\" },\n { key: \"boisIndustrie\", nom: \"Bois d'industrie\", couleur: \"#D2691E\" },\n { key: \"boisEnergie\", nom: \"Bois énergie\", couleur: \"#FF6347\" },\n //{ key: \"boisCertifies\", nom: \"Bois certifiés\", couleur: \"#228B22\" }\n]","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":315,"value":"$54","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"}],"files":"$W55","stdlib":"1"}} 24:null