Procedural Urban Forestry

Abstract

The placement of vegetation plays a central role in the realism of virtual scenes. We introduce procedural placement models (PPMs) for vegetation in urban layouts. PPMs are environmentally sensitive to city geometry and allow identifying plausible plant positions based on structural and functional zones in an urban layout. PPMs can either be directly used by defining their parameters or learned from satellite images and land register data. This allows us to populate urban landscapes with complex 3D vegetation and enhance existing approaches for generating urban landscapes. Our framework’s effectiveness is shown through examples of large-scale city scenes and close-ups of individually grown tree models. We validate the results generated with our framework with a perceptual user study and its usability based on urban scene design sessions with expert users.

Ecoclimates

“…Plant Ecosystems. Methods for generating models of plant ecosystems aim to jointly compute plausible distributions of plants and to represent plants with an appropriate level of geometric detail [Deussen et al 1998;Lane and Prusinkiewicz 2002;Niese et al 2022]. A number of approaches exists that represent plant ecosystems as layers [Argudo et al 2017], voxels [Jaeger and Teng 2003], volumetric textures [Bruneton and Neyret 2012], through more principled level of detail strategies [Neubert et al 2011], or based on simulating erosion feedback with vegetation ].…”

Text2City: One-Stage Text-Driven Urban Layout Regeneration

“…Professional designers visualize the urban layout based on the white papers, and create the urban layout map by hand or with the aid of computer-assisted tools. Previous computer-assisted city modeling methods (Parish and Müller 2001;Chen et al 2008;Groenewegen et al 2009;Niese et al 2022) generate urban layouts by employing complex hand-crafted rules. Users have to carefully adjust the control parameters, such as the number of roads, patterns, longest length, to obtain the desirable urban layout.…”

“…For example, while roads should bypass historic buildings that need to be preserved, building footprints should generally align with existing roads. However, existing city modeling methods take a two-stage approach (Parish and Müller 2001;Chen et al 2008;Groenewegen et al 2009;Vanegas et al 2010;Benes et al 2021;Niese et al 2022).…”

TreeDetector: Using Deep Learning for the Localization and Reconstruction of Urban Trees from High-Resolution Remote Sensing Images

“…These methods have high requirements on the gaps between tree crowns in remote sensing images when generating edge maps, and they perform poorly when dealing with dense tree crowns. The second category of methods [11,12] first obtains a tree crown coverage map of the input image and then uses a generative algorithm to generate the distribution of trees for the covered areas. These methods treat all tree crowns as a whole and generate the distribution of trees, which can result in some isolated tree crowns being generated as multiple trees.…”

“…We referenced the design concept of [13], and proposed an urban tree generation algorithm based on planting rules to make the generated results closer to the real distribution. Like the method of Till et al [11], we used tree location to describe the distribution of trees. This method is not affected by the fuzzy boundaries of tree crowns and provides seamless integration for subsequent 3D reconstruction visualization due to its sparse representation.…”