{"id":44358,"date":"2025-10-06T12:02:39","date_gmt":"2025-10-06T10:02:39","guid":{"rendered":"https:\/\/www.tygron.com\/nl\/?p=44358"},"modified":"2025-10-09T16:51:29","modified_gmt":"2025-10-09T14:51:29","slug":"mapping-green-spaces-with-ai-and-tygron-research-on-mapping-hedges-in-ede","status":"publish","type":"post","link":"https:\/\/www.tygron.net\/en\/blog\/2025\/10\/06\/mapping-green-spaces-with-ai-and-tygron-research-on-mapping-hedges-in-ede\/","title":{"rendered":"Mapping Green Spaces with AI and Tygron: Research on Mapping Hedges in Ede"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-post\" data-elementor-id=\"44358\" class=\"elementor elementor-44358\" data-elementor-post-type=\"post\">\n\t\t\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-dbc1ead elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"dbc1ead\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-thegem\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-50 elementor-top-column elementor-element elementor-element-2d698dd\" data-id=\"2d698dd\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-1a94eca flex-horizontal-align-default flex-horizontal-align-tablet-default flex-horizontal-align-mobile-default flex-vertical-align-default flex-vertical-align-tablet-default flex-vertical-align-mobile-default elementor-widget elementor-widget-text-editor\" data-id=\"1a94eca\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.20.0 - 26-03-2024 *\/\n.elementor-widget-text-editor.elementor-drop-cap-view-stacked .elementor-drop-cap{background-color:#69727d;color:#fff}.elementor-widget-text-editor.elementor-drop-cap-view-framed .elementor-drop-cap{color:#69727d;border:3px solid;background-color:transparent}.elementor-widget-text-editor:not(.elementor-drop-cap-view-default) .elementor-drop-cap{margin-top:8px}.elementor-widget-text-editor:not(.elementor-drop-cap-view-default) .elementor-drop-cap-letter{width:1em;height:1em}.elementor-widget-text-editor .elementor-drop-cap{float:left;text-align:center;line-height:1;font-size:50px}.elementor-widget-text-editor .elementor-drop-cap-letter{display:inline-block}<\/style>\t\t\t\t<p><strong>Written by Frank Bouw as part of an internship project at Aveco de Bondt.<\/strong><\/p><p>Mapping green spaces in cities is crucial for biodiversity, climate adaptation, and creating a healthy living environment. However, mapping greenery is easier said than done. So what role can AI play in accelerating and automating this process?<\/p><p>During my research internship at Aveco de Bondt, I explored how AI within the Tygron platform can help. The focus of the research was to develop an AI model that can automatically recognize hedges in aerial photographs.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<div class=\"elementor-column elementor-col-50 elementor-top-column elementor-element elementor-element-1ea74d1\" data-id=\"1ea74d1\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-6e8b4c2 flex-horizontal-align-default flex-horizontal-align-tablet-default flex-horizontal-align-mobile-default flex-vertical-align-default flex-vertical-align-tablet-default flex-vertical-align-mobile-default elementor-widget elementor-widget-image\" data-id=\"6e8b4c2\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.20.0 - 26-03-2024 *\/\n.elementor-widget-image{text-align:center}.elementor-widget-image a{display:inline-block}.elementor-widget-image a img[src$=\".svg\"]{width:48px}.elementor-widget-image img{vertical-align:middle;display:inline-block}<\/style>\t\t\t\t\t\t\t\t\t\t<img fetchpriority=\"high\" decoding=\"async\" width=\"723\" height=\"651\" src=\"https:\/\/www.tygron.net\/wp-content\/uploads\/2025\/10\/frank_b.jpg\" class=\"attachment-large size-large wp-image-44360\" alt=\"\" srcset=\"https:\/\/www.tygron.net\/wp-content\/uploads\/2025\/10\/frank_b.jpg 723w, https:\/\/www.tygron.net\/wp-content\/uploads\/2025\/10\/frank_b-300x270.jpg 300w, https:\/\/www.tygron.net\/wp-content\/uploads\/2025\/10\/frank_b-13x12.jpg 13w\" sizes=\"(max-width: 723px) 100vw, 723px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-9c50448 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"9c50448\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-thegem\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-d48abec\" data-id=\"d48abec\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-a0f9666 flex-horizontal-align-default flex-horizontal-align-tablet-default flex-horizontal-align-mobile-default flex-vertical-align-default flex-vertical-align-tablet-default flex-vertical-align-mobile-default elementor-widget elementor-widget-text-editor\" data-id=\"a0f9666\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>My background is in environmental and climate sciences, with some experience in GIS. During my internship, I learned that it is possible to build AI models using Tygron even without an ICT background. Although this study focused on hedges, the same approach can be applied to many other themes.<\/p><ul><li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"7\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;multilevel&quot;}\" data-aria-posinset=\"4\" data-aria-level=\"1\"><strong>Internship research (PDF): <\/strong><a href=\"https:\/\/www.tygron.com\/wp-content\/uploads\/2025\/10\/Eindverslag_Onderzoeksstage_Frank_Bouw.pdf\" target=\"_blank\" rel=\"noopener\">https:\/\/www.tygron.com\/wp-content\/uploads\/2025\/10\/Eindverslag_Onderzoeksstage_Frank_Bouw.pdf<\/a><\/li><li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"7\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;multilevel&quot;}\" data-aria-posinset=\"4\" data-aria-level=\"1\"><strong>Final presentation (PDF): <\/strong><a href=\"https:\/\/www.tygron.com\/wp-content\/uploads\/2025\/10\/Eindpresentatie_Onderzoeksstage_Frank_Bouw.pdf\" target=\"_blank\" rel=\"noopener\">https:\/\/www.tygron.com\/wp-content\/uploads\/2025\/10\/Eindpresentatie_Onderzoeksstage_Frank_Bouw.pdf<\/a><\/li><\/ul>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-3cc6e23 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"3cc6e23\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-thegem\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-be4bd87\" data-id=\"be4bd87\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-686d36a flex-horizontal-align-default flex-horizontal-align-tablet-default flex-horizontal-align-mobile-default flex-vertical-align-default flex-vertical-align-tablet-default flex-vertical-align-mobile-default elementor-widget elementor-widget-text-editor\" data-id=\"686d36a\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<h4>Why Hedges?<\/h4><p>Hedges are more than just boundaries. They are vital habitats for species such as hedgehogs and house sparrows, and they contribute to the green appearance of urban areas. With better data on hedges, we can improve models that assess biodiversity or heat stress.<\/p><p>Aveco de Bondt, for example, uses a <em>biodiversity stress test, <\/em>a GIS tool that maps habitat suitability by combining various input layers. As with that tool, better data leads to more accurate results. However, hedges are often missing from existing datasets: trees are usually well-registered, but lower vegetation is not.<\/p><p>An AI model can make a difference by automatically detecting such elements. Moreover, since AI models analyze aerial imagery, they can also identify greenery in private gardens, providing a more complete picture that includes both public and private green space.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-5edb74b elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"5edb74b\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-thegem\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-82efb6b\" data-id=\"82efb6b\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-cccfcc4 flex-horizontal-align-default flex-horizontal-align-tablet-default flex-horizontal-align-mobile-default flex-vertical-align-default flex-vertical-align-tablet-default flex-vertical-align-mobile-default elementor-widget elementor-widget-text-editor\" data-id=\"cccfcc4\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<h4>Training Your Own AI Model with Tygron<\/h4>\n<p>Tygron recently introduced an AI feature that allows users to build their own object recognition models. For my research, I followed a five-step process:<\/p>\n<ol>\n<li><strong>Creating Training Data<\/strong><br>In QGIS, I selected five training areas in Ede and manually mapped over 1,900 hedges.<figure id=\"attachment_44361\" aria-describedby=\"caption-attachment-44361\" style=\"width: 1385px\" class=\"wp-caption alignleft\"><img decoding=\"async\" class=\"size-full wp-image-44361\" src=\"https:\/\/www.tygron.com\/wp-content\/uploads\/2025\/10\/Groen-in-kaart-met-AI-en-Tygron-input-FW-1.jpg\" alt=\"\" width=\"1385\" height=\"559\" srcset=\"https:\/\/www.tygron.net\/wp-content\/uploads\/2025\/10\/Groen-in-kaart-met-AI-en-Tygron-input-FW-1.jpg 1385w, https:\/\/www.tygron.net\/wp-content\/uploads\/2025\/10\/Groen-in-kaart-met-AI-en-Tygron-input-FW-1-300x121.jpg 300w, https:\/\/www.tygron.net\/wp-content\/uploads\/2025\/10\/Groen-in-kaart-met-AI-en-Tygron-input-FW-1-1024x413.jpg 1024w, https:\/\/www.tygron.net\/wp-content\/uploads\/2025\/10\/Groen-in-kaart-met-AI-en-Tygron-input-FW-1-768x310.jpg 768w, https:\/\/www.tygron.net\/wp-content\/uploads\/2025\/10\/Groen-in-kaart-met-AI-en-Tygron-input-FW-1-18x7.jpg 18w\" sizes=\"(max-width: 1385px) 100vw, 1385px\" \/><figcaption id=\"caption-attachment-44361\" class=\"wp-caption-text\">Visualization of drawing hedges. On the left is an image where the hedges haven&#8217;t yet been drawn, and on the right is an image where the hedges have been drawn.<\/figcaption><\/figure><br><br><\/li>\n<li><strong>Preparing the Data in Tygron<\/strong><br>The aerial photos and drawn hedges were imported into Tygron and exported as training and test data to be used for model training.<\/li>\n<li><strong>Training the Model<\/strong><br>Using Tygron\u2019s open-source repository, I trained a Mask R-CNN model\u2014a type of AI that can not only recognize but also outline objects. Various settings and iteration counts (epochs) were tested to find the right balance between precision and generalization.<\/li>\n<li><strong>Testing the Model<\/strong><br>The trained model was applied to aerial imagery of Ede. Results were compared to the manually mapped hedges to evaluate accuracy. Precision and recall metrics were used: precision measures how many of the detected hedges are correct, while recall measures how many actual hedges were detected.<\/li>\n<li><strong>Validating the Model<\/strong><br>Validation was conducted using fieldwork data from two neighborhoods\u2014one with many trees and one with few. It turned out that many hedges were not visible in aerial photos due to several limitations:\n<ul>\n<li><strong>Tilt effect:<\/strong> Buildings obscure nearby hedges due to the camera angle.<\/li>\n<li><strong>Shadow effect:<\/strong> Sunlight causes dark areas that hide vegetation.<\/li>\n<li><strong>Overhang effect:<\/strong> Trees or structures can cover hedges from view.<\/li>\n<\/ul>\n<\/li>\n<\/ol>\n<p>In the tree-dense neighborhood, about 50% of the hedges were not visible at all.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-2c8474f elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"2c8474f\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-thegem\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-50 elementor-top-column elementor-element elementor-element-a405b00\" data-id=\"a405b00\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-8aa90f2 flex-horizontal-align-default flex-horizontal-align-tablet-default flex-horizontal-align-mobile-default flex-vertical-align-default flex-vertical-align-tablet-default flex-vertical-align-mobile-default elementor-widget elementor-widget-image\" data-id=\"8aa90f2\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"462\" height=\"473\" src=\"https:\/\/www.tygron.net\/wp-content\/uploads\/2025\/10\/Groen-in-kaart-met-AI-en-Tygron-input-FW-3.jpg\" class=\"attachment-large size-large wp-image-44362\" alt=\"\" srcset=\"https:\/\/www.tygron.net\/wp-content\/uploads\/2025\/10\/Groen-in-kaart-met-AI-en-Tygron-input-FW-3.jpg 462w, https:\/\/www.tygron.net\/wp-content\/uploads\/2025\/10\/Groen-in-kaart-met-AI-en-Tygron-input-FW-3-293x300.jpg 293w, https:\/\/www.tygron.net\/wp-content\/uploads\/2025\/10\/Groen-in-kaart-met-AI-en-Tygron-input-FW-3-12x12.jpg 12w, https:\/\/www.tygron.net\/wp-content\/uploads\/2025\/10\/Groen-in-kaart-met-AI-en-Tygron-input-FW-3-45x45.jpg 45w\" sizes=\"(max-width: 462px) 100vw, 462px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<div class=\"elementor-column elementor-col-50 elementor-top-column elementor-element elementor-element-4beac64\" data-id=\"4beac64\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-4a751e7 flex-horizontal-align-default flex-horizontal-align-tablet-default flex-horizontal-align-mobile-default flex-vertical-align-default flex-vertical-align-tablet-default flex-vertical-align-mobile-default elementor-widget elementor-widget-image\" data-id=\"4a751e7\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"463\" height=\"479\" src=\"https:\/\/www.tygron.net\/wp-content\/uploads\/2025\/10\/Groen-in-kaart-met-AI-en-Tygron-input-FW-4.jpg\" class=\"attachment-large size-large wp-image-44363\" alt=\"\" srcset=\"https:\/\/www.tygron.net\/wp-content\/uploads\/2025\/10\/Groen-in-kaart-met-AI-en-Tygron-input-FW-4.jpg 463w, https:\/\/www.tygron.net\/wp-content\/uploads\/2025\/10\/Groen-in-kaart-met-AI-en-Tygron-input-FW-4-290x300.jpg 290w, https:\/\/www.tygron.net\/wp-content\/uploads\/2025\/10\/Groen-in-kaart-met-AI-en-Tygron-input-FW-4-12x12.jpg 12w\" sizes=\"(max-width: 463px) 100vw, 463px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-e523587 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"e523587\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-thegem\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-a35c223\" data-id=\"a35c223\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-35fb3ba flex-horizontal-align-default flex-horizontal-align-tablet-default flex-horizontal-align-mobile-default flex-vertical-align-default flex-vertical-align-tablet-default flex-vertical-align-mobile-default elementor-widget elementor-widget-text-editor\" data-id=\"35fb3ba\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><em>Visualization of the slope effect, the shadow effect, and the effect of overhanging trees on the aerial photograph from 2024 (left, cloudy) and 2023 (right, sunny). The red areas indicate the BAG registration of buildings, which indicates the location of the building at ground level. This clearly shows that part of the building&#8217;s surroundings is obscured by the angle at which the aerial photograph was taken. Much is also obscured by the overhanging trees, and the aerial photograph on the right also provides a clear image of the shadow effect.<\/em><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-7fadd47 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"7fadd47\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-thegem\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-76c2f6c\" data-id=\"76c2f6c\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-c10c37a flex-horizontal-align-default flex-horizontal-align-tablet-default flex-horizontal-align-mobile-default flex-vertical-align-default flex-vertical-align-tablet-default flex-vertical-align-mobile-default elementor-widget elementor-widget-image\" data-id=\"c10c37a\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"800\" height=\"390\" src=\"https:\/\/www.tygron.net\/wp-content\/uploads\/2025\/10\/Groen-in-kaart-met-AI-en-Tygron-input-FW-6-1024x499.jpg\" class=\"attachment-large size-large wp-image-44364\" alt=\"\" srcset=\"https:\/\/www.tygron.net\/wp-content\/uploads\/2025\/10\/Groen-in-kaart-met-AI-en-Tygron-input-FW-6-1024x499.jpg 1024w, https:\/\/www.tygron.net\/wp-content\/uploads\/2025\/10\/Groen-in-kaart-met-AI-en-Tygron-input-FW-6-300x146.jpg 300w, https:\/\/www.tygron.net\/wp-content\/uploads\/2025\/10\/Groen-in-kaart-met-AI-en-Tygron-input-FW-6-768x374.jpg 768w, https:\/\/www.tygron.net\/wp-content\/uploads\/2025\/10\/Groen-in-kaart-met-AI-en-Tygron-input-FW-6-18x9.jpg 18w, https:\/\/www.tygron.net\/wp-content\/uploads\/2025\/10\/Groen-in-kaart-met-AI-en-Tygron-input-FW-6.jpg 1231w\" sizes=\"(max-width: 800px) 100vw, 800px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-c2b695e elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"c2b695e\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-thegem\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-f63e473\" data-id=\"f63e473\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-6d54220 flex-horizontal-align-default flex-horizontal-align-tablet-default flex-horizontal-align-mobile-default flex-vertical-align-default flex-vertical-align-tablet-default flex-vertical-align-mobile-default elementor-widget elementor-widget-text-editor\" data-id=\"6d54220\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><em>Visualization of the model output compared to the hedgerows mapped during fieldwork.<\/em><br \/><em>The blue areas represent the model output and the green outlines represent the plotted hedgerows.<\/em><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-a5ba202 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"a5ba202\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-thegem\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-f6aa3b3\" data-id=\"f6aa3b3\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-409e408 flex-horizontal-align-default flex-horizontal-align-tablet-default flex-horizontal-align-mobile-default flex-vertical-align-default flex-vertical-align-tablet-default flex-vertical-align-mobile-default elementor-widget elementor-widget-text-editor\" data-id=\"409e408\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<h4>Results<\/h4><p>In the neighborhood with few trees, precision and recall were both about 50%; in the tree-dense area, around 25%. This is not yet accurate enough for precise hedge mapping. <br \/><br \/>The neural network trained in this study is therefore not yet suitable for use in Aveco de Bondt\u2019s analyses. <br \/>However, an important result is that it was possible to build and apply an AI model without an ICT background. This shows the potential for collecting new data and enriching existing datasets using Tygron\u2019s AI tools.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-aa962e3 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"aa962e3\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-thegem\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-5857575\" data-id=\"5857575\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-c69c2f6 flex-horizontal-align-default flex-horizontal-align-tablet-default flex-horizontal-align-mobile-default flex-vertical-align-default flex-vertical-align-tablet-default flex-vertical-align-mobile-default elementor-widget elementor-widget-text-editor\" data-id=\"c69c2f6\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<h4>Lessons Learned<\/h4><p>This research demonstrates that creating and applying an AI model in Tygron is feasible for non-programmers. A key lesson is to carefully consider the source data and the goal beforehand. In this case, many hedges were simply invisible in the aerial imagery.<\/p><p>Therefore, one should always assess whether the available data sources (aerial or satellite) are suitable for the intended goal.<\/p><p>For clearer objects such as solar panels, better results have already been achieved. Tygron\u2019s own Foliage AI model, for example, already performs quite well.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-1f50324 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"1f50324\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-thegem\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-4a13ed9\" data-id=\"4a13ed9\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-0e67976 flex-horizontal-align-default flex-horizontal-align-tablet-default flex-horizontal-align-mobile-default flex-vertical-align-default flex-vertical-align-tablet-default flex-vertical-align-mobile-default elementor-widget elementor-widget-text-editor\" data-id=\"0e67976\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<h4>What Is the Tygron AI Suite?<\/h4><p><strong>The Tygron AI Suite<\/strong> is a collection of powerful tools that allow urban planners and GIS specialists to train and deploy neural networks directly within the Tygron Platform. <br \/>It enables automatic recognition of objects such as trees, shrubs, or other features in satellite or aerial imagery using machine learning. The computations are performed at high speed using GPU supercomputers directly connected to the platform.<\/p><p>The goal of the AI Suite is to make advanced AI technology accessible to users without deep programming knowledge. Tygron emphasizes open source and accessibility: users can use existing open models or upload their own trained neural networks in ONNX format for seamless integration.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-34acda7 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"34acda7\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-thegem\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-1528764\" data-id=\"1528764\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-1a7141d flex-horizontal-align-default flex-horizontal-align-tablet-default flex-horizontal-align-mobile-default flex-vertical-align-default flex-vertical-align-tablet-default flex-vertical-align-mobile-default elementor-widget elementor-widget-text-editor\" data-id=\"1a7141d\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<h4>Getting Started: Useful Links\u00a0<\/h4><ul><li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"7\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;multilevel&quot;}\" data-aria-posinset=\"1\" data-aria-level=\"1\"><b><span data-contrast=\"auto\">Introduction and overview:<\/span><\/b> <span style=\"text-decoration: underline;\"><a href=\"https:\/\/www.tygron.com\/nl\/ai\/\" target=\"_blank\" rel=\"noopener\">https:\/\/www.tygron.com\/nl\/ai\/<\/a>\u00a0<\/span><\/li><\/ul><ul><li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"7\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;multilevel&quot;}\" data-aria-posinset=\"2\" data-aria-level=\"1\"><b><span data-contrast=\"auto\">Step-by-step guide and scripts:<\/span><\/b> <span style=\"text-decoration: underline;\"><a href=\"https:\/\/previewsupport.tygron.com\/wiki\/How_to_train_your_own_AI_model_for_an_Inference_Overlay\" target=\"_blank\" rel=\"noopener\">https:\/\/previewsupport.tygron.com\/wiki\/How_to_train_your_own_AI_model_for_an_Inference_Overlay<\/a>\u00a0<\/span><\/li><\/ul><ul><li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"7\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;multilevel&quot;}\" data-aria-posinset=\"3\" data-aria-level=\"1\"><b><span data-contrast=\"auto\">Open-source repository &amp; scripts:<\/span><\/b> <span style=\"text-decoration: underline;\"><a href=\"https:\/\/github.com\/Tygron\/tygron-ai-suite\" target=\"_blank\" rel=\"noopener\">https:\/\/github.com\/Tygron\/tygron-ai-suite<\/a>\u00a0<\/span><\/li><\/ul><ul><li aria-setsize=\"-1\" data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"7\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;multilevel&quot;}\" data-aria-posinset=\"4\" data-aria-level=\"1\"><b><span data-contrast=\"auto\">Technical session (PDF):<\/span><\/b> <span style=\"text-decoration: underline;\"><span style=\"text-decoration: underline;\"><a href=\"https:\/\/www.tygron.com\/wp-content\/uploads\/2024\/11\/AI-aan-de-slag.pdf\" target=\"_blank\" rel=\"noopener\">https:\/\/www.tygron.com\/wp-content\/uploads\/2024\/11\/AI-aan-de-slag.pdf<\/a><\/span><\/span><\/li><\/ul><p><span data-contrast=\"auto\">These resources make it easy to start identifying green data from imagery on the Tygron platform\u2014or even train and apply your own AI models.<\/span><span data-ccp-props=\"{&quot;134233117&quot;:true,&quot;134233118&quot;:true,&quot;201341983&quot;:0,&quot;335559740&quot;:240}\">\u00a0<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"<p>Mapping green spaces in cities is crucial for biodiversity, climate adaptation, and creating a healthy living environment. However, mapping greenery is easier said than done. So what role can AI play in accelerating and automating this process?<\/p>\n","protected":false},"author":2,"featured_media":44368,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[173],"tags":[172],"class_list":["post-44358","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-relevant","tag-relevant"],"_links":{"self":[{"href":"https:\/\/www.tygron.net\/en\/wp-json\/wp\/v2\/posts\/44358","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.tygron.net\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.tygron.net\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.tygron.net\/en\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.tygron.net\/en\/wp-json\/wp\/v2\/comments?post=44358"}],"version-history":[{"count":20,"href":"https:\/\/www.tygron.net\/en\/wp-json\/wp\/v2\/posts\/44358\/revisions"}],"predecessor-version":[{"id":44419,"href":"https:\/\/www.tygron.net\/en\/wp-json\/wp\/v2\/posts\/44358\/revisions\/44419"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.tygron.net\/en\/wp-json\/wp\/v2\/media\/44368"}],"wp:attachment":[{"href":"https:\/\/www.tygron.net\/en\/wp-json\/wp\/v2\/media?parent=44358"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.tygron.net\/en\/wp-json\/wp\/v2\/categories?post=44358"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.tygron.net\/en\/wp-json\/wp\/v2\/tags?post=44358"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}