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<li><a href="#fast-and-flexible-cartogram-equal-density-map-production" id="toc-fast-and-flexible-cartogram-equal-density-map-production" class="nav-link active" data-scroll-target="#fast-and-flexible-cartogram-equal-density-map-production">Fast and Flexible Cartogram (equal-density map) Production</a></li>

<li><a href="#geoai-models-for-object-detection-in-urban-environment" id="toc-geoai-models-for-object-detection-in-urban-environment" class="nav-link" data-scroll-target="#geoai-models-for-object-detection-in-urban-environment">GeoAI Models for Object Detection in Urban Environment</a></li>

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<h1 class="title">Download</h1>

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</header>

<p>Programs, code, visuals, and data for downloading. Some are shared through GitHub and ObservableHQ.<br>

</p>

<h3 class="anchored" data-anchor-id="fast-and-flexible-cartogram-equal-density-map-production">Fast and Flexible Cartogram (equal-density map) Production</h3>

<h4 class="anchored" data-anchor-id="f4carto-the-recommended-new-version">F4Carto, the recommended new version </h4>

<p><a href="http://www.sunsp.net/download/programs/F4CartoInstaller.msi" title="F4Carto Cartogram production program">Installer for Windows 64 bit Program</a> <br>

<a href="http://www.sunsp.net/download/programs/F4Carto_Package.zip" title="F4Carto Cartogram production program">Zipped package, no installation needed</a> <br>

<a href="http://www.sunsp.net/download/programs/F4Carto_Documentation.pdf" title="F4Carto Documentation">Documentation</a></p>

</section>

<h4 class="anchored" data-anchor-id="carto3f-the-older-version">Carto3F, the older version </h4>

<p><a href="http://www.sunsp.net/download/programs/Carto3F_Setup.msi" title="Carto3F Setup - A Fast, Free-From Cartogram production program">Installer for Windows 32bit Program</a> <br>

<a href="http://www.sunsp.net/download/programs/Carto3F_Documentation.pdf" title="Carto3F Documentation">Documentation</a></p>

</section>

<h3 class="anchored" data-anchor-id="geoai-models-for-object-detection-in-urban-environment">GeoAI Models for Object Detection in Urban Environment</h3>

<p>Supported by PSC-CUNY, Center for Advanced Research on Spatial Information (CARSI, led by Prof. Sean Ahearn), and the MS in GeoInformatics (MGEOi) program, this project explores the application of advanced deep learning models for detecting small urban objects using high-resolution (6-inch) aerial imagery.</p>

<p>The current training phase is exploratory, utilizing a limited subset of the full dataset—merely 500 images—and 100 training epochs. Each image consists of a 1024 × 1024 pixels with oriented bounding boxes for three target feature types: water tanks, cooling towers/AC units, and curb cuts.</p>

<p>Six customized models have been successfully implemented and tested across two leading frameworks—<strong>MMDetection</strong> and <strong>Ultralytics YOLO</strong>—within multiple Python computational environments (Windows, macOS, and WSL/Ubuntu). The models demonstrate flexibility and compatibility across diverse GPU configurations, providing a strong foundation for future large-scale experimentation and refinement.</p>

<p>The preliminary results are as follows, and represented in <a href="https://www.dropbox.com/scl/fi/1x8poks2dfvhsttuqxtgx/GeoAI_Poster_V_1.4.pdf?rlkey=4iaupfgjsja0yki94bcn1y1bk&dl=0">this poster</a>. Pre-trained PyTorch models that can predict these three features are available upon request.</p>

<thead>

<th>Base Model</th>

</tr>

</thead>

<tbody>

<td>Overall</td>

<td>Water Tank</td>

<td>Cooling Tower</td>

</tr>

<td><a href="https://www.dropbox.com/scl/fi/ppk8jqyixhtczxq2876n5/rotated-faster-rcnn.pth?rlkey=smoipn6dm3xqkisff0ugw6ogx&dl=0">Rotated Faster R-CNN</a> *</td>

</tr>

<td>RoI (Regions of Interest) Transformer</td>

</tr>

<td><a href="https://www.dropbox.com/scl/fi/rudvozdflq9itrox9umjx/lsk.pth?rlkey=5v1mp1ht0q3fekr6iek3kx9bs&dl=0">LSKNet (Large Selective Kernel)</a> *</td>

</tr>

<td>Strip R-CNN</td>

</tr>

</tr>

<td>M3 Ultra/MPS</td>

</tr>

</tr>

</tr>

</tbody>

</table>

<p>*: Models trained with MMDetection and MMRotate frameworks by applying transfer learning techniques.</p>

<p>†: This Yolo v12 model does not use any pre-trained parameters like other models. It was trained using 500 NYC images with 1,600 epochs. Other models use parameters pre-trained from the DOTA V1 dataset, by default.</p>

<p>‡: This model uses pre-trained model parameters that are based on 5,000 NYC images of 1024 by 1024. The pre-training was accomplished by this project with a self-supervised learning (SSL) framework.</p>

</section>

</main>

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}

// Inspect non-navigation links and adorn them if external

var links = window.document.querySelectorAll('a[href]:not(.nav-link):not(.navbar-brand):not(.toc-action):not(.sidebar-link):not(.sidebar-item-toggle):not(.pagination-link):not(.no-external):not([aria-hidden]):not(.dropdown-item):not(.quarto-navigation-tool):not(.about-link)');

for (var i=0; i<links.length; i++) {

const link = links[i];

if (!isInternal(link.href)) {

// undo the damage that might have been done by quarto-nav.js in the case of

// links that we want to consider external

if (link.dataset.originalHref !== undefined) {

link.href = link.dataset.originalHref;

}

// target, if specified

link.setAttribute("target", "_blank");

if (link.getAttribute("rel") === null) {

link.setAttribute("rel", "noopener");

}

// default icon

link.classList.add("external");

}

function tippyHover(el, contentFn, onTriggerFn, onUntriggerFn) {

const config = {

allowHTML: true,

maxWidth: 500,

delay: 100,

arrow: false,

appendTo: function(el) {

return el.parentElement;

interactive: true,

interactiveBorder: 10,

theme: 'quarto',

placement: 'bottom-start',

};

if (contentFn) {

config.content = contentFn;

}

if (onTriggerFn) {

config.onTrigger = onTriggerFn;

}

if (onUntriggerFn) {

config.onUntrigger = onUntriggerFn;

}

window.tippy(el, config);

}

const noterefs = window.document.querySelectorAll('a[role="doc-noteref"]');

for (var i=0; i<noterefs.length; i++) {

const ref = noterefs[i];

tippyHover(ref, function() {

// use id or data attribute instead here

let href = ref.getAttribute('data-footnote-href') || ref.getAttribute('href');

try { href = new URL(href).hash; } catch {}

const id = href.replace(/^#\/?/, "");

const note = window.document.getElementById(id);

if (note) {

return note.innerHTML;

} else {

return "";

}

});

}

const xrefs = window.document.querySelectorAll('a.quarto-xref');

const processXRef = (id, note) => {

// Strip column container classes

const stripColumnClz = (el) => {

el.classList.remove("page-full", "page-columns");

if (el.children) {

for (const child of el.children) {

stripColumnClz(child);

}

stripColumnClz(note)

if (id === null || id.startsWith('sec-')) {

// Special case sections, only their first couple elements

const container = document.createElement("div");

if (note.children && note.children.length > 2) {

container.appendChild(note.children[0].cloneNode(true));

for (let i = 1; i < note.children.length; i++) {

const child = note.children[i];

if (child.tagName === "P" && child.innerText === "") {

continue;

} else {

container.appendChild(child.cloneNode(true));

break;

}

if (window.Quarto?.typesetMath) {

window.Quarto.typesetMath(container);

}

return container.innerHTML

} else {

if (window.Quarto?.typesetMath) {

window.Quarto.typesetMath(note);

}

return note.innerHTML;

}

} else {

// Remove any anchor links if they are present

const anchorLink = note.querySelector('a.anchorjs-link');

if (anchorLink) {

anchorLink.remove();

}

if (window.Quarto?.typesetMath) {

window.Quarto.typesetMath(note);

}

if (note.classList.contains("callout")) {

return note.outerHTML;

} else {

return note.innerHTML;

}

for (var i=0; i<xrefs.length; i++) {

const xref = xrefs[i];

tippyHover(xref, undefined, function(instance) {

instance.disable();

let url = xref.getAttribute('href');

let hash = undefined;

if (url.startsWith('#')) {

hash = url;

} else {

try { hash = new URL(url).hash; } catch {}

}

if (hash) {

const id = hash.replace(/^#\/?/, "");

const note = window.document.getElementById(id);

if (note !== null) {

try {

const html = processXRef(id, note.cloneNode(true));

instance.setContent(html);

} finally {

instance.enable();

instance.show();

}

} else {

// See if we can fetch this

fetch(url.split('#')[0])

.then(res => res.text())

.then(html => {

const parser = new DOMParser();

const htmlDoc = parser.parseFromString(html, "text/html");

const note = htmlDoc.getElementById(id);

if (note !== null) {

const html = processXRef(id, note);

instance.setContent(html);

}

}).finally(() => {

instance.enable();

instance.show();

});

}

} else {

// See if we can fetch a full url (with no hash to target)

// This is a special case and we should probably do some content thinning / targeting

fetch(url)

.then(res => res.text())

.then(html => {

const parser = new DOMParser();

const htmlDoc = parser.parseFromString(html, "text/html");

const note = htmlDoc.querySelector('main.content');

if (note !== null) {

// This should only happen for chapter cross references

// (since there is no id in the URL)

// remove the first header

if (note.children.length > 0 && note.children[0].tagName === "HEADER") {

note.children[0].remove();

}

const html = processXRef(null, note);

instance.setContent(html);

}

}).finally(() => {

instance.enable();

instance.show();

});

}

}, function(instance) {

});

}

let selectedAnnoteEl;

const selectorForAnnotation = ( cell, annotation) => {

let cellAttr = 'data-code-cell="' + cell + '"';

let lineAttr = 'data-code-annotation="' + annotation + '"';

const selector = 'span[' + cellAttr + '][' + lineAttr + ']';

return selector;

}

const selectCodeLines = (annoteEl) => {

const doc = window.document;

const targetCell = annoteEl.getAttribute("data-target-cell");

const targetAnnotation = annoteEl.getAttribute("data-target-annotation");

const annoteSpan = window.document.querySelector(selectorForAnnotation(targetCell, targetAnnotation));

const lines = annoteSpan.getAttribute("data-code-lines").split(",");

const lineIds = lines.map((line) => {

return targetCell + "-" + line;

})

let top = null;

let height = null;

let parent = null;

if (lineIds.length > 0) {

//compute the position of the single el (top and bottom and make a div)

const el = window.document.getElementById(lineIds[0]);

top = el.offsetTop;

height = el.offsetHeight;

parent = el.parentElement.parentElement;

if (lineIds.length > 1) {

const lastEl = window.document.getElementById(lineIds[lineIds.length - 1]);

const bottom = lastEl.offsetTop + lastEl.offsetHeight;

height = bottom - top;

}

if (top !== null && height !== null && parent !== null) {

// cook up a div (if necessary) and position it

let div = window.document.getElementById("code-annotation-line-highlight");

if (div === null) {

div = window.document.createElement("div");

div.setAttribute("id", "code-annotation-line-highlight");

div.style.position = 'absolute';

parent.appendChild(div);

}

div.style.top = top - 2 + "px";

div.style.height = height + 4 + "px";

div.style.left = 0;

let gutterDiv = window.document.getElementById("code-annotation-line-highlight-gutter");

if (gutterDiv === null) {

gutterDiv = window.document.createElement("div");

gutterDiv.setAttribute("id", "code-annotation-line-highlight-gutter");

gutterDiv.style.position = 'absolute';

const codeCell = window.document.getElementById(targetCell);

const gutter = codeCell.querySelector('.code-annotation-gutter');

gutter.appendChild(gutterDiv);

}

gutterDiv.style.top = top - 2 + "px";

gutterDiv.style.height = height + 4 + "px";

}

selectedAnnoteEl = annoteEl;

}

};

const unselectCodeLines = () => {

const elementsIds = ["code-annotation-line-highlight", "code-annotation-line-highlight-gutter"];

elementsIds.forEach((elId) => {

const div = window.document.getElementById(elId);

if (div) {

div.remove();

}

});

selectedAnnoteEl = undefined;

};

// Handle positioning of the toggle

window.addEventListener(

"resize",

throttle(() => {

elRect = undefined;

if (selectedAnnoteEl) {

selectCodeLines(selectedAnnoteEl);

}

}, 10)

);

function throttle(fn, ms) {

let throttle = false;

let timer;

return (...args) => {

if(!throttle) { // first call gets through

fn.apply(this, args);

throttle = true;

} else { // all the others get throttled

if(timer) clearTimeout(timer); // cancel #2

timer = setTimeout(() => {

fn.apply(this, args);

timer = throttle = false;

}, ms);

}

};

}

// Attach click handler to the DT

const annoteDls = window.document.querySelectorAll('dt[data-target-cell]');

for (const annoteDlNode of annoteDls) {

annoteDlNode.addEventListener('click', (event) => {

const clickedEl = event.target;

if (clickedEl !== selectedAnnoteEl) {

unselectCodeLines();

const activeEl = window.document.querySelector('dt[data-target-cell].code-annotation-active');

if (activeEl) {

activeEl.classList.remove('code-annotation-active');

}

selectCodeLines(clickedEl);

clickedEl.classList.add('code-annotation-active');

} else {

// Unselect the line

unselectCodeLines();

clickedEl.classList.remove('code-annotation-active');

}

});

}

const findCites = (el) => {

const parentEl = el.parentElement;

if (parentEl) {

const cites = parentEl.dataset.cites;

if (cites) {

return {

el,

cites: cites.split(' ')

};

} else {

return findCites(el.parentElement)

}

} else {

return undefined;

}

};

var bibliorefs = window.document.querySelectorAll('a[role="doc-biblioref"]');

for (var i=0; i<bibliorefs.length; i++) {

const ref = bibliorefs[i];

const citeInfo = findCites(ref);

if (citeInfo) {

tippyHover(citeInfo.el, function() {

var popup = window.document.createElement('div');

citeInfo.cites.forEach(function(cite) {

var citeDiv = window.document.createElement('div');

citeDiv.classList.add('hanging-indent');

citeDiv.classList.add('csl-entry');

var biblioDiv = window.document.getElementById('ref-' + cite);

if (biblioDiv) {

citeDiv.innerHTML = biblioDiv.innerHTML;

}

popup.appendChild(citeDiv);

});

return popup.innerHTML;

});

}

});

</script>

</div>

</i>

</a>

</li>

</i>

</a>

</li>

</i>

</a>

</li>

</ul>

</div>

</div>

<p>Last updated: March 12, 2026</p>

</div>

</footer>

</body></html>

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