Abstract: Machine learning systems and methods are described in regard to automating and acting upon evaluations of hypothetical composite project sites of 2+ disparate land parcels so as to allow a developer, owner, or other stakeholder to see and act upon potential land uses that are not reflected in conventional valuations. Some variants include a feature augmentation protocol for speciating one or more detailed structures feasible for development, a pattern matching protocol for identifying viable composite project sites that might suit a developer's requirements, technologies for accommodating latent preferences, proactive virtual development of co-owned disparate parcels, a notification protocol implementing offers to numerous potential sellers whose responses might affect project viability, wise virtual development and prioritization, or other such innovative configurations.

Abstract: Machine learning systems and methods are described in regard to automating and acting upon evaluations of hypothetical composite project sites of 2+ disparate land parcels so as to allow a developer, owner, or other stakeholder to see and act upon potential land uses that are not reflected in conventional valuations. Some variants include a feature augmentation protocol for speciating one or more detailed structures feasible for development, a pattern matching protocol for identifying viable composite project sites that might suit a developer's requirements, technologies for accommodating latent preferences, proactive virtual development of co-owned disparate parcels, a notification protocol implementing offers to numerous potential sellers whose responses might affect project viability, wise virtual development and prioritization, or other such innovative configurations.

Abstract: Machine learning systems and methods are described in regard to automating and acting upon evaluations of hypothetical composite project sites of 2+ disparate land parcels so as to allow a developer, owner, or other stakeholder to see and act upon potential land uses that are not reflected in conventional valuations. Some variants include a feature augmentation protocol for speciating one or more detailed structures feasible for development, a pattern matching protocol for identifying viable composite project sites that might suit a developer's requirements, technologies for accommodating latent preferences, proactive virtual development of co-owned disparate parcels, a notification protocol implementing offers to numerous potential sellers whose responses might affect project viability, wise virtual development and prioritization, or other such innovative configurations.

Abstract: Machine learning systems and methods are described in regard to automating and acting upon evaluations of hypothetical assemblages of adjacent land parcels so as to allow a developer, owner, or other investor to see and act upon potential land uses that are not reflected in conventional valuations. Some variants include a feature augmentation protocol for speciating one or more detailed structures feasible for an assemblage, a pattern matching protocol for identifying viable assemblages that might suit a developer's requirements or implementing numerous simultaneous offers to numerous potential sellers whose decisions might affect project viability.

Abstract: Machine learning systems and methods are described in regard to automating and acting upon evaluations of hypothetical composite project sites of 2+ disparate land parcels so as to allow a developer, owner, or other stakeholder to see and act upon potential land uses that are not reflected in conventional valuations. Some variants include a feature augmentation protocol for speciating one or more detailed structures feasible for development, a pattern matching protocol for identifying viable composite project sites that might suit a developer's requirements, technologies for accommodating latent preferences, proactive virtual development of co-owned disparate parcels, a notification protocol implementing offers to numerous potential sellers whose responses might affect project viability, wise virtual development and prioritization, or other such innovative configurations.

Abstract: Machine learning systems and methods are described in regard to automating and acting upon evaluations of hypothetical composite project sites of 2+ disparate land parcels so as to allow a developer, owner, or other stakeholder to see and act upon potential land uses that are not reflected in conventional valuations. Some variants include a feature augmentation protocol for speciating one or more detailed structures feasible for development, a pattern matching protocol for identifying viable composite project sites that might suit a developer's requirements, technologies for accommodating latent preferences, proactive virtual development of co-owned disparate parcels, a notification protocol implementing offers to numerous potential sellers whose responses might affect project viability, wise virtual development and prioritization, or other such innovative configurations.