顧芩 Ku, Chin Work & Internship Taipei City, Taiwan
Assistant Urban Planner | JiaCheng Planning Consultant Studied the existing situation of tourism industry in Tainan and came up with a model of accomodation choice.
Assistant Urban Planner | Visionary International Design & Planning Consultant
Email: kuchin9402@gmail.com
2017.9-2017.12 2016.7-2016.12
Work as assistant urban planner helping making infor graphs and conducting GIS analysis.
Phone: +886 0986896685
Intern | Department of Urban Development, Taipei City Government
2014.8-2014.9
Deal with individual rezoning projects.
Info
Education Academic activity
Nationality Born Gender Language
Teacher assistant | epartment of Urban Development, Taipei City Government
Taiwan February 17th, 1994 at Taipei Female Taiwan Mandarin (native) | English (fluent) | Japanese (basic)
Software & Skill
MSc. Urban Planning | National Cheng Kung University, Tainan, Taiwan
2016.9 - 2018.6
BSc. Urban Planning|National Cheng Kung University, Tainan, Taiwan
2012.9 - 2016.6
Academic conference Oral presenter | The Forum on Land Use and Planning | Tainan, Taiwan “Exploring and visualizing the relationship of the composing for urban landscape”
Oral presenter | 20th International Conference on Sustainable Urban Planning | Amsterdam, Netherland
AutoCAD
Spatial statistic, Network analysis, Land suitability analysis, Terrain analysis, Landscape ecology analysis, 3D analysis, Model builder
CityEngine (ESRI)
2018.2
depthmapX
Analysis of connectivity, global and local integration value
SketchUp 2018.1
Visited disaster-related institutions in Japan and participated a workshop with Japanese students. Integrated social design and environment design skill to deal with local problem.
ArcGIS pro (ESRI)
3d city modeling, 3d simulation, City information model (CIM)
International workshop
Participant| Sichuan transnational workshop | China
Graphic Design
2018.3
“3D Visualization for the Relationship of the Urban Rule and Building Form by Using CityEngine”
Participant| Japan-Taiwan students and youths study and exchange tour on disaster prevention | Tokyo, Japan
Spatial Analysis & 3D Modeling
2015.7
Adobe Illustrator Adobe Photoshop Adobe InDesign Data Analysis Data Mining (Python) Data wrangling, data analysis,data visualization
SPSS
Unmanned Aerial Vehicle
Data analysis
Pix4D, PhotoScan
Others Microsoft office
Manipulating UAV (Mavic pro/Hexacopter)
2D/3D point cloud modeling
(Word, Power point, Excel)
SQL
2016.9-2018.6
Visualizing and Parameterizing the Urban Landscape
Map layers Graguate thesis (2018)
This model presents the 3d visualization for the LANDSCAPE, STREETS, and BUILDINGS by using CityEngine. In the interface of CityEngine, we can rapidly adjust the parameters of urban landscape and zoning code, such as street width, floor area ratio, building coverage ratio, setback distance and other regulations, and then the model will immediately show the different 3d scenes.
In CityEngine, it is the Computer generate architecture(CGA) rule to create a dynamic city layout and customize different parameters of city environment . Therefore, we can build up a city within hours.
CityEngine is a procedural modeling tool which can visualize a large scale landscape through the parameterizing and programming process. It is a useful and professional tool for the field of urban planning and urban design.
Natural environment
Scope Taichung City, Taiwan
Street network
3.5 km2 Existing building volume
Zoning regulation & urban design guildline
Keyword: ArcGIS, CityEngine, CGA,Parametric modeling, Procedural modeling, 3d simulation Urban land consolidation VII high-rise building and commercial building Taichung new city hall/ 新市政中心
Urban Rule
Building volume Urban land consolidation II & III & V town house, detached house, apartment
Mayuantou River/麻園頭溪
Near to old Taichung downtown town house, detached house, apartment, high-rise building
Parameterizing
Programming
set(buildingArea, geometry.area()) splitArea(x){~1 : GreenSpace | (buildingArea*BCR) : SetBuildingHeight} #splitArea(z1) parcel_z1 --> setback(setbackDistance){ street.front : NIL | remainder : preFootprint_z1 } preFootprint_z1 --> set(buildingArea, geometry.area()) splitArea(z){(buildingArea*BCR) : SetBuildingHeight | ~1 : GreenSpace} #splitArea(z2) parcel_z2 --> setback(setbackDistance){ street.front : NIL | remainder : preFootprint_z2 } preFootprint_z2 --> set(buildingArea, geometry.area()) splitArea(z){~1 : GreenSpace|(buildingArea*BCR) : SetBuildingHeight } GreenSpace --> Open_Space.ParkShape SetBuildingHeight --> case buildingType == "1.0" : set(buildingHeight,rand(16,40)*UFheight + 1.5) Footprint case buildingType == "2.0" : set(buildingHeight, rand(2,7)*UFheight + 1.5) Footprint ase buildingType == "3.0" : set(buildingHeight,rand(2,4)*UFheight + 1.5) Footprint case buildingType == "4.0" : set(building eight,rand(2,7)*UFheight + 1.5) Footprint case buildingType == "5.0" : comp(f) {horizontal : NIL | all : NoHorizontalFaces.} else :set(material.opacity,Opacity)comp(f) {all : NIL} Reporting --> report("Parcel Area",parcelArea) report("Foorprint Area",footprintArea) report("Floor Area",floors*footprintArea) report("Zoning", zoning) /** report("Parcel Area (m2)",parcelArea) report("Max Footprint Area (m2)",footprintArea) report("potential GFA",geometry.volume/floorHeight) report("potential FAR",geometry.volume/-
More application...
This model can be used to conduct other simulation, such as flooding, wind, shadow, viewshed and solar radiation simulations which prove the process of urban design and 3D analysis. Moreover, the model can be redering in the game engine sofeware.
Calligraphy Greenway/草悟道
Flooding / VR/Microclimate/...
Facade modeling
STEP 1 Facade Liabary: photoes taking by my self STEP 2 Facade Wizard
STEP 3 Facade texturing: “Baking ” the facade images on building Aerial view of 3d city model
Diversity of roof types (solar panel, green roof, flat roof and pitched roof)
River and stream system simulation
Street layout and pedestrian space simulation
Landscape modeling
Street layout and pedestrian space simulation
View corridor analysis
Full video
Parametric Street Layout
Street Layout
Bicycle lane-Lane-Buffer tree-Bicycle lane
Parametric Building
Building Modeling
屋頂形式 (Flat, Hip, Gable, Pyramid, Shed)
Lane-Bus lane-Median lane-Bus lane-Lane Scrolling bar
Bus lane-Lane
Building form
Street View
Building Design
UV Texturing UV-set Texture Layer 0 colomap 1 bumpmap 2 dirtmap 3 specularmap 4 opacitymap 5 normalmap
Original Brick Wall
Brick Wall + Dirty map
+
Brick Wall + Graffiti
+
Building modeling
Farmland Suitability Analysis
(Shingang Township, Taiwan)
The result map shows the agricultural land classification after considering social and economical indicators. It separates the farmland into three classes and finding out the opportunities and limitations in each blocks. ArcGIS is used to analyze and process information by Model Builder.
Farmland Agricultural District I
Agricultural District IV
Model Builder in ArcGIS
Indicators Include soil, humidity, slop, minimum area, urban development and industrial land, cropping suitability, irrigation area, land suitable for agriculture and animal husbandry purpose, etc.
Land suitable for agriculture or animal husbandry purpose
Important Agricultural Development area
Cropping Suitability
Irrigation area
Highway interference
Minimum area>25ha
Urban Development and Industrial land
(Course work,2017)
Agricultural District III
Agricultural District II
Functional Zones in Spatial Planning
(Course work,2017)
Background: Spatial Planning Act Since 2016, Taiwan has passed legislation to implement Spatial Planning Act which specifically establishes guidelines concerning measures to be taken to cope with climate change, assure land use safety, conserve the natural environment and cultural assets, promote the reasonable allocation of resources and industries, strengthen land consolidation and management mechanisms, and restore sensitive areas and damaged land in pursuit sustainable development.
The result map of Chiayi city in Taiwan illustrates the distribution of four zones. 1. 2. 3. 4.
environmental conservation zones marine resource zones agricultural development zones urban-rural development zones
Network Analysis
(Taichung City, Taiwan)
(Course work,2017)
This project aims to calculate the accessibility of public facilities and communities through network distance.
Primary School
College
Step1: Build Netword dataset Step1: Build Netword dataset
Taichung road map
Calculate geometry: Length
High School
Playground
Park and Plaza
Amenity
Government Agency
Health Care
Cost: network distance
Step2: Build OD cost matrix
Minimum Spatial Units for communities
Step3: Calculate the value of accessibility
Point of interest (POI)
Analysis Settings Impedance：Cost (Meter) → Network distance Default Cutoff Value：1200m →Service area Destination To Find：146 →The amount of amenity
The result of network analysis of POI and minimum spatial units for communities.
Hotspot Analysis of Residential burglary
(Taipei City, Taiwan)
Data Source : Open data provided by Taipei City Year : 2015~2018
Keyword: ArcGIS pro, Hotspot analysis, Residential burglary, Google Earth, QGIS Address → KML → Point Shapefile
Point Data
Data processing
Data Analysis
GeoCoding
Hotspot
Interpolation
Analyzing and Simulating the Building Volume
(Course work,2018)
The aim of this project is to visualize the outcome of zoning code and find out difference between existing buildng volume and the predicted one. It starts with tracing back the history of Hu-Wei-Liao area and studying the zoning regulations, and then uses CityEngine and ArcGIS to visualize the 3d outcome of future urban landscape. This project reveals the key factor which significantly influence the building volume, and explores different way to simulate the outcome of zoning code.
Floors : 11 Actural BCR : 20%
(a) Existing Building
Keyword: ArcGIS, CityEngine, CGA, Zoning simulation, 3d visualization
(b) Simulate by BCR and FAR Floors : 9 Actural BCR : 20%
(Year 1898)
(Year 1944)
Existing Buildings
(Year 1996) Front view
(c) a+b Diagram
Simulate by BCR and FAR
Existing situation Existing situation
Zoning regulation
Simulation 1 simulate the building height by “Block” which is the unit of zoning regulation.
Simulation 2 simulate the building height by “Block” which is the unit of zoning regulation.
Existing building footprint
Street network
Digital elevation model (DEM)
Residential Area 1
3d zoning Residential Area 2
Residential Area 3
South Tainan Sub-city certer | 南台南永續副都心
Tainan cultural center/台南文化中心
(Course work,2014)
Ecological community/生態社區
南台南永續副都心是位於台南市東區，鄰近南區交界處，現為 素地。本規畫設計案首先透過”地方把脈” ，了解周遭的商業 活動情形、大型公共設施分布、藍綠帶現況以及都市紋理特徵 ，將副都心周遭分為四個生活圈，並使南台南永續副都心扮演 地方領頭羊的角色，串聯現有資源，以及自然環境之潛力，發 展以永續為基礎之新型態社區。
Existing community/ 現有社區 Road system/道路系統
Tainan hospital/台南醫院
Pedestrian and bike system/行人及自行車系統
Ecological environment/永續環境
Older Train Station/ 舊火車站 South Tainan Train Station/ 南台南火車站
Ecological economy/永續經濟
Elderly-friendly community/ 銀髮友善社區 Ecological community/ 生態社區
Ecological society/永續社會
Building types/建物類型配置
High-rise building
Apartment
Ecological community/永續社區 Town house
Detached house
Office of Taiwan sugar corporation/ 台糖行政中心
Art museum/美術館
Research park of Taiwan sugar corporation/ 台糖研究園區
全區配置圖 三大軸線： -永續環境 -永續社會 -永續社區
Backyard Entertainment Complex Development Implementation Planning (Course work,2016)
This Project is separated into two parts: site planning and development planning, including financial feasible analysis, architecture design, marketing and urban design.
Site Location
Master Plan
Planning Concept
開發基地北側及東側臨公園，並向北 、向西銜接人行徒步區，因此將建築 量體切割出主要軸線。
內部人行動線 與切割量體。
利用開放空間縫 合各棟量體。
Building Design Concept
Floor Plan
A Research of Predicting Building Types
Graguate thesis (2018)
Low-rise Bulding Type 6
1 story, bungalow, model house, supermarket, restaurant etc. Building footprint is probably surrounded by the remainder of plot.
Mid-rise Bulding
Type 3
2~6 stories, detached house, small-sized commercial building.
Type 2
Type 7
Type 4
2~6 stories, semi-detached with potential retail. Building footprint is next to their neighbor and the remainder of plots is probably side yard and front yard or back yard.
2~6 stories, town house with potential retail. Building footprint is next to other footprints and the remainder of plots is probably front yard or back yard.
2~6 stories, apartment, medium-sized commercial building. Building footprint is probably surrounded by the remainder of plots.
The aim of this research is to find out the relationship between urban planning condition and building types. There are four stages in here, including exploring the indicators represented planning condition, deciding the way building classified, applying KNN algorithm to find out the relationship, and verifing it.
Global Integration Value
Local Integration Value
Street Width
Step 1
The original indicators are GIV, LIV, street widith, block shape and area, plot shape and area, building coverage ratio and floor area ratio. However, the indicator will be test by box plot later to find the suitable one.
Block Shape Block Area Plot Shape Plot Area
Building Coverage Ratio Floor Area Ratio
Area A
Area B
Area C
The association test (Pearson correlation coefficient) of each indicators in different areas.
Red- High value Blue- Low value Red- High value Blue- Low value
High-rise Bulding
Super High-rise Bulding
7~15 stories, office or high-rise apartment with potential groundfloor retail, department store, shopping mall, entertainment place. Building footprint is probably surrounded by the remainder of plots.
16+ stories, office or high-rise apartment with potential groundfloor retail, department store, shopping mall, entertainment place. Building footprint is probably surrounded by the remainder of plots.
Type 5
Black- Wide road Grey- Narrow road Square
Large Square
Type 1
Irregular
Small
Classifing different building types
Irregular
Large
Small
Large
Small
Large
Small
Original 9 indicators which represent planning condition
Step 2
The way I classify different building types is according to its numbers of floor and the types of open space. Therefore, there are 7 building types for following research.
Step 3
Type 1
Type 2
Type 3
Type 4
Type 5
Type 6
Type 7
Type 1
Type 2
Type 3
Type 4
Type 5
Type 6
Type 7
Type 1
Type 2
Type 3
Type 4
Type 5
Type 6
Type 7
Type 1
Type 2
Type 3
Type 4
Type 5
Type 6
Type 7
Type 1
Type 2
Type 3
Type 4
Type 5
Type 6
Type 7
Type 1
Type 2
Type 3
Type 4
Type 5
Type 6
Type 7
Type 1
Type 1
Type 2
Type 2
Type 3
Type 3
Type 4
Type 4
Type 5
Type 5
Type 6
Type 6
Type 7
Type 7
Type 1
Type 1
Type 1
Type 1
Type 2
Type 2
Type 2
Type 2
Type 3
Type 3
Type 3
Type 3
Type 4
Type 4
Type 4
Type 4
Type 5
Type 5
Type 5
Type 5
Type 6
Type 6
Type 6
Type 6
Type 7
Type 7
Type 7
Type 7
Type 1
Type 1
Type 2
Type 2
Type 3
Type 3
Type 4
Type 4
Type 5
Type 5
Type 6
Type 6
Make use of KNN algorithm to predict building types. The result shows that it is more successful to predict building types by 7 indicators than BCR and FAR.
Type 7
Scenario 1 Predicting building types by building coverage ratio (BCR) and floor area ratio (FAR)
Type 7
Type 1
Type 2
Type 3
Type 4
Type 5
Type 6
Type 7
Type 1
Type 2
Type 3
Type 4
Type 5
Type 6
Type 7
Scenario 2 Predicting building types by seven indicators
Type 1
Type 2
Type 3
Type 4
Type 5
Type 6
Type 7
Type 1
Type 2
Type 3
Type 4
Type 5
Type 6
Type 7
Step 4
The box plots which illustrate the descriptive statistic of different building types.
Cross table analysis reveals that every prdicting successful rate of different building type.
Cross analysis of original building types and predicted one
UAV & 3D Point Cloud Modeling
Still more 3D polint cloud modeling
Space Syntax : Integration Value
Global integration value (RRAn)
(Taichung City, Taiwan)
Local integration value (RRA3)