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19/11/2018 1 P1 P2 Engineering Perspective of Geo-Spatial Intelligence in Smart City Huang Qian 19 November 2018

Engineering Perspective of Geo-Spatial Intelligence in ...ggim.un.org/unwgic/presentations/3.1_Mr. Huang_Qian.pdf · Engineering Perspective of Geo-Spatial Intelligence in Smart City

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Page 1: Engineering Perspective of Geo-Spatial Intelligence in ...ggim.un.org/unwgic/presentations/3.1_Mr. Huang_Qian.pdf · Engineering Perspective of Geo-Spatial Intelligence in Smart City

19/11/2018

1

P1

P2

Engineering Perspective of Geo-Spatial

Intelligence in Smart City

Huang Qian

19 November 2018

Page 2: Engineering Perspective of Geo-Spatial Intelligence in ...ggim.un.org/unwgic/presentations/3.1_Mr. Huang_Qian.pdf · Engineering Perspective of Geo-Spatial Intelligence in Smart City

19/11/2018

2

P3

What is a Smarter City?

Physical

Energy

Information

Emission reduction

GreenGreen

Biodiversity

Livable

Networking

Digitization

Intelligent

SensorSensorControllerController

ControllerController

SensorSensor

Ecology

Wisdom

P4

What Computers Do: Model, Connect, and Engage

参与(Engage)

联结(Connect)

建模(Model)

Butler LampsonA.M. Turing Award Laureate

Technical Fellow at Microsoft

Corporation

Adjunct Professor of Computer

Science and Electrical

Engineering at MIT

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���������������!��� ��#��"��$%

�&'(�*)'(�+,-�� .���/ 2 ��,0 ��� .���/%

AI

Big

Data

5G

IoT

Digital

Twins

Page 3: Engineering Perspective of Geo-Spatial Intelligence in ...ggim.un.org/unwgic/presentations/3.1_Mr. Huang_Qian.pdf · Engineering Perspective of Geo-Spatial Intelligence in Smart City

19/11/2018

3

P5

Real World

Information World

People

Internet of

People things

Internet of

things

Object

ID

Virtual

Represent

Control

Mathematical

Model

Mathematical

Model

Connection, more and faster

202513456789:;<=53.8>?@A5G56789:<=39.3>B ——C20181A45GDEFGHIJKLMNOP

P6

Engage, interactive and automatic

Depth perception

Edge calculation

Time-space migration

Collaborative control network

Page 4: Engineering Perspective of Geo-Spatial Intelligence in ...ggim.un.org/unwgic/presentations/3.1_Mr. Huang_Qian.pdf · Engineering Perspective of Geo-Spatial Intelligence in Smart City

19/11/2018

4

P7

Model, Geo-Spatial Big Data

Point

Q0-DR

Line

Q1-DR

Polygon

Q2-DR

Body

Q3-DR

Mutil-D

Temporal

Spatio

static

dynamic

MacroMicro

Simple

Complex

transportatio

n network

underground

pipe network

Function

Zoning

Land use

BIM

Mutil-

Domain

Intgeration

City

General

Indicator

Small

Big

Agent Based

Discrete Event Simulation

System dynamics

P8

Geo System

Geo-Spatial

TechnologyGeoControlGeoMonitor

GeoModelingGeoModeling

Data

Model

Math

Model

GeoDesign

sensor controller

IoT

BIM

Cooperative object

network

Earth Observation

Network

Evolution of new Geo-Spatial Technology

Page 5: Engineering Perspective of Geo-Spatial Intelligence in ...ggim.un.org/unwgic/presentations/3.1_Mr. Huang_Qian.pdf · Engineering Perspective of Geo-Spatial Intelligence in Smart City

19/11/2018

5

P9

Geo-Spatial

Intelligence

ST(discover)

UV(foresight)

WX(insight)

YZ(organization)

[\(tools)

]^(process)

_`abcdefghiffjdkilmfn

T

op(system)

qr(E

nv)

Geo-Spatial Intelligence Structure and Mechanism

st(fusion)

u�v

w ����

xyzy{|}~�|������|{y��

�}��������{y�z

��

��{����{�

P10

�|z �� ��|� �|y�{��|����|�|z����{

xy��y��}{y�� y� �yz��|�����{���{y�� �|�|z����{

�|�� ����y{y�� y� �y�}�y����{yz|{y��

������������� �� ����  ��

¡�|¢ £|�y� �� ��|�¤y�����|{y¥|{y��

¦§�§������ �� ¨�©�§ ª§«� �

Can we reform traditional transportation?

Page 6: Engineering Perspective of Geo-Spatial Intelligence in ...ggim.un.org/unwgic/presentations/3.1_Mr. Huang_Qian.pdf · Engineering Perspective of Geo-Spatial Intelligence in Smart City

19/11/2018

6

P11

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°±²³´µ¶·¸)

¹º»¼½¾¿ÀÁÂÿÄ

QÅÆÇÈÉÇODÇÊËÌR

ÍÎÏнÑÒÓÔÕÖ×ÔÕÂ×ÕÔ¿Ä

(ØÙÇÚÛÜÝÞÇßàáR

âã�äå� �0%(æç´èé)

Ëê

ë¿ìíîÔïÃðñòó

ôê

õíï×ÁïÃ

ö÷øù

úû

üà

ï××ÔÁýÕ׿þÿ��

System Analysis

P12

Big Data Processing and Sharing Platform

Scientific

Support

Industry

Revolution

Smart Operation

& Maintenance

Community

Service

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������� �������������� �����

Transformation

& Upgrading

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�$)�""�*%%�")$+ ($%*,"

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0�*"&$"�")$ 0�"�,$'$"&

12$.�&*�"�30�"�,$'$"&

0�.4$& -.$ *&

Data

Layer

Tech

Layer

App

Layer

Tech Stack

Page 7: Engineering Perspective of Geo-Spatial Intelligence in ...ggim.un.org/unwgic/presentations/3.1_Mr. Huang_Qian.pdf · Engineering Perspective of Geo-Spatial Intelligence in Smart City

19/11/2018

7

P13

Case 1,Remote Sensing Recognition

P14

Algorithm, Generative Adversarial Networks

567689:;8

<=>?8=@=79:;8 A;8BC

DEFG

HIFG

� 生成器:生成以假乱真的图像� 鉴别器:尽可能鉴别真假� 当鉴别器无法区分真假时,模型训练完毕。

JKDE

Page 8: Engineering Perspective of Geo-Spatial Intelligence in ...ggim.un.org/unwgic/presentations/3.1_Mr. Huang_Qian.pdf · Engineering Perspective of Geo-Spatial Intelligence in Smart City

19/11/2018

8

P15

Model Fusing

Multi-scale fusing

多框架︑多参数︑多模型

噪声少、连续性好

LM

LM

LM

NL

P16

Post-treatment, Rattlesnake

利用自动生长、“响尾蛇”等算法,实现路网的自动连接

OPHQ

RSTUV

OPHQ

Page 9: Engineering Perspective of Geo-Spatial Intelligence in ...ggim.un.org/unwgic/presentations/3.1_Mr. Huang_Qian.pdf · Engineering Perspective of Geo-Spatial Intelligence in Smart City

19/11/2018

9

P17

Building Recognition

P18

Xiamen

Page 10: Engineering Perspective of Geo-Spatial Intelligence in ...ggim.un.org/unwgic/presentations/3.1_Mr. Huang_Qian.pdf · Engineering Perspective of Geo-Spatial Intelligence in Smart City

19/11/2018

10

P19

Faster

以25平方公里的区域为例,人工勾画路网需8小时/人,利用机器学习自动提取,

结合半自动化的后处理,仅需半小时/人

W

X

Y

Z

[

\

]

^

_

`abc defg

hijkhl

P20

mnopqr

stqr

Better

Page 11: Engineering Perspective of Geo-Spatial Intelligence in ...ggim.un.org/unwgic/presentations/3.1_Mr. Huang_Qian.pdf · Engineering Perspective of Geo-Spatial Intelligence in Smart City

19/11/2018

11

P21

养护 uvwx uvyz

Algorithm in Smart Maintenance

P22

Traffic Volume Forecast

{|à}~����

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�����

���� ����

���� ����� ������ ��������� ���� ������ �� ������

�����

���� ����

���� ����� ������ ��������� ���� ������ �� ������

�����

���� ����

��������

� ¡¢£¤{¥

¦§¨©ª«

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¢£¯ÚÉ°

±²ÝÞ¬¦¹³ÝÞ

´µ¢£¶·¸¹

Page 12: Engineering Perspective of Geo-Spatial Intelligence in ...ggim.un.org/unwgic/presentations/3.1_Mr. Huang_Qian.pdf · Engineering Perspective of Geo-Spatial Intelligence in Smart City

19/11/2018

12

P23

º»�¼ º»�¼ º»�¼ º»�¼ º»�¼ º»�¼

½¾¿¾ ½¾¿¿ ½¾¿½

½¾¿À ½¾¿Á ½¾¿Â

交通量影响因子

交通量

recurrent neural network(RNN)

Synthetic control method

P24

山西省全路网交通量预测 福建省拟建高速公路交通量预测

Traffic Volume Forecast Platform

Page 13: Engineering Perspective of Geo-Spatial Intelligence in ...ggim.un.org/unwgic/presentations/3.1_Mr. Huang_Qian.pdf · Engineering Perspective of Geo-Spatial Intelligence in Smart City

19/11/2018

13

P25

主体(subjects)

工具(tools)

ÃÄ(algorithm)

Åã(software)

ÆÇ(system)

ÈÉ(customer)

ÆÇÊIË(developer)

ÌÍÎÏ(domain expert)

:ÐÑÒÏ(data scientist)

ÓÔÕÖË(tools provider)

:ÐÕÖË(data provider)×Ø

(individual)

ÙØ(group)

ÚØ(ensemble)

�������%

ÛÜ(Information)

(entity-semantic-structure)

ÝÞ(Knowledge)

(relation-rule-pattern)

ßàáâ(individual

portrait)

ãä(heterogeneo

us)

åàáâ(group

portrait)

æäçä(classificatio

n;

clustering)

èàáâ(ensemble

portrait)

éÚêë(aggregation

structure)

:ÐìÝ(data

sense)

ÛÜÕí(information

extraction)

ÝÞîïKnowledge

condense

客体(objects)

Computer

Engineer

Urban

Planning/

Smart CityArtificial

Intelligence/

IoT….

Engineer Framework for Smart City

P26

ðñòóGeo-System

ôõö

Controler

÷øö

Sensor

ùúûüSystem Output

ýþûüMeasured Output

ùúûÿSystem Input

ýü��Measured Error

�����

Reference

GIS

GeoModeling

GeoDesign

GeoControlGeoMonito

r

Feedback

Geospatial Intelligence Helps City Smarter