The document analyzes how topography has affected urban sprawl in Beijing over 20 years from 1993 to 2012. It finds that the flat central and eastern parts of Beijing experienced the most development, while the mountainous western and northern areas saw slower growth. Urban areas and nighttime lights expanded fastest towards the flatter land, closely following the development of transportation networks. Topography is thus shown to be a major factor influencing the uneven pattern of Beijing's urbanization.
Urban sprawl in india and smart growth modelJigar Pandya
Policies responsible for Urban Sprawl in India. Smart Growth Models. TDR and other programs when combined with focused policy can work for intensive community development. Community empowerment through land equity.
Urban sprawl in india and smart growth modelJigar Pandya
Policies responsible for Urban Sprawl in India. Smart Growth Models. TDR and other programs when combined with focused policy can work for intensive community development. Community empowerment through land equity.
Research on the characteristics and evaluation of nightscape along the LRT lineIJERA Editor
With people's increasing demand of nightlife activities, the nightscape has become more important than ever to
enhance the image of city. In this study, we tried to analyze the effects and influence of the landscape lighting
that produced the nightscape and pointed out that the optimal nightscapes along the LRT (Light Rail Transit)
line. We selected the urban landscapes along the LRT wayside as the research objects, used the SD (Semantic
Differential) technique to compare the difference between the daytime and the nighttime landscapes by the
vision engineering and measurement psychology. As a result, it became clear as follows: 1) image evaluation of
the nightscapes got higher estimation than that of daytime landscapes. The importance of the nightscape has been
recognized once again; 2) landscape lighting played the important role in the charming nightscape; 3) the
optimal nightscapes along the LRT routes could be chosen with the results of factor analysis.
Counterfactual Planning: What if there had been no Greenbelt in Seoul?Prabal Dahal
This article uses a specific and long-established planning policy, Seoul’s greenbelt, to explore the concept of counterfactual planning. Suppose the greenbelt had never existed
Article by Chang-Hee Christine Bae & Myung-Jin Jun
2003
An Empirical Study of the Environmental Kuznets Curve for Environment Quality...ijceronline
This paper attempts to examine the determinants of environmental degradation within the framework of Environment Kuznets Curve (EKC) hypothesis using China's city-level panel data from 2003 to 2012. The population agglomeration as well as three types of cities such as municipalities, sub-provincial city and prefecture-level city are considered in our paper. Our empirical results with the whole sample data verified the theory of the EKC hypothesis, which shows a reverse "U" shape between economic growth and environmental pollution. In addition, the effect of population on environmental pollution is quite different among the various types of cities. The results of this study can serve as a useful reference for policy makers in terms of achieving economic and environmental sustainability.
Liveability Dimensions in New Town Developments: An Overview of Senri New Town and Purbachal New Town
* 1 M. Eng. Tahmina Rahman Image result for research orcid , 2 Dr. Md. Nawrose Fatemi Image result for research orcid
1 Division of Global Architecture, Osaka University, Osaka, Japan
2 Department of Architecture, University of Asia Pacific, Dhaka, Bangladesh
E-mail 1: ar.tahminarahman@gmail.com , E-mail 2: nawrose@uap-bd.edu
ARTICLE INFO:
Article History:
Received 20 April 2021
Accepted 10 August 2021
Available online 15 August 2021
Keywords:
Dimensions of Liveability;
New Town Development;
Satellite Townships;
Osaka;
Dhaka.
ABSTRACT
Since the 1960s, new town developments within large metropolises have been widely adopted to decongest the city centres, especially in Asian cities. This paper provides a brief account of the liveability dimensions of two new townships developed in large metropolitan areas: Senri New Town in Osaka and Purbachal New Town in Dhaka. The study primarily draws on master plans of the two developments to identify how the components of the plans reflect the physical, social, functional and safety dimensions of a proposed liveability framework. The methodology combines a review of masters plans with scholarly and grey literature on the two new town developments. The findings show while the social and functional dimensions are integrated with Senri New Town; Purbachal New Town, though more recent, appears to have missed opportunities for diversifying density, social mix and mass transit. The paper concludes that the comparative case, Senri-New Town provides insights on how public-private people participation can leverage citizen-centred design for more liveable residential living environments in developing cities.
JOURNAL OF CONTEMPORARY URBAN AFFAIRS (2021), 5(2), 221-233.
Research on the characteristics and evaluation of nightscape along the LRT lineIJERA Editor
With people's increasing demand of nightlife activities, the nightscape has become more important than ever to
enhance the image of city. In this study, we tried to analyze the effects and influence of the landscape lighting
that produced the nightscape and pointed out that the optimal nightscapes along the LRT (Light Rail Transit)
line. We selected the urban landscapes along the LRT wayside as the research objects, used the SD (Semantic
Differential) technique to compare the difference between the daytime and the nighttime landscapes by the
vision engineering and measurement psychology. As a result, it became clear as follows: 1) image evaluation of
the nightscapes got higher estimation than that of daytime landscapes. The importance of the nightscape has been
recognized once again; 2) landscape lighting played the important role in the charming nightscape; 3) the
optimal nightscapes along the LRT routes could be chosen with the results of factor analysis.
Counterfactual Planning: What if there had been no Greenbelt in Seoul?Prabal Dahal
This article uses a specific and long-established planning policy, Seoul’s greenbelt, to explore the concept of counterfactual planning. Suppose the greenbelt had never existed
Article by Chang-Hee Christine Bae & Myung-Jin Jun
2003
An Empirical Study of the Environmental Kuznets Curve for Environment Quality...ijceronline
This paper attempts to examine the determinants of environmental degradation within the framework of Environment Kuznets Curve (EKC) hypothesis using China's city-level panel data from 2003 to 2012. The population agglomeration as well as three types of cities such as municipalities, sub-provincial city and prefecture-level city are considered in our paper. Our empirical results with the whole sample data verified the theory of the EKC hypothesis, which shows a reverse "U" shape between economic growth and environmental pollution. In addition, the effect of population on environmental pollution is quite different among the various types of cities. The results of this study can serve as a useful reference for policy makers in terms of achieving economic and environmental sustainability.
Liveability Dimensions in New Town Developments: An Overview of Senri New Town and Purbachal New Town
* 1 M. Eng. Tahmina Rahman Image result for research orcid , 2 Dr. Md. Nawrose Fatemi Image result for research orcid
1 Division of Global Architecture, Osaka University, Osaka, Japan
2 Department of Architecture, University of Asia Pacific, Dhaka, Bangladesh
E-mail 1: ar.tahminarahman@gmail.com , E-mail 2: nawrose@uap-bd.edu
ARTICLE INFO:
Article History:
Received 20 April 2021
Accepted 10 August 2021
Available online 15 August 2021
Keywords:
Dimensions of Liveability;
New Town Development;
Satellite Townships;
Osaka;
Dhaka.
ABSTRACT
Since the 1960s, new town developments within large metropolises have been widely adopted to decongest the city centres, especially in Asian cities. This paper provides a brief account of the liveability dimensions of two new townships developed in large metropolitan areas: Senri New Town in Osaka and Purbachal New Town in Dhaka. The study primarily draws on master plans of the two developments to identify how the components of the plans reflect the physical, social, functional and safety dimensions of a proposed liveability framework. The methodology combines a review of masters plans with scholarly and grey literature on the two new town developments. The findings show while the social and functional dimensions are integrated with Senri New Town; Purbachal New Town, though more recent, appears to have missed opportunities for diversifying density, social mix and mass transit. The paper concludes that the comparative case, Senri-New Town provides insights on how public-private people participation can leverage citizen-centred design for more liveable residential living environments in developing cities.
JOURNAL OF CONTEMPORARY URBAN AFFAIRS (2021), 5(2), 221-233.
Park, Chaerin: Tracking the Nature of Urban Carbon Cycle – the Introduction o...
Zhao,Jianting_EE
1. How Topography Has Affected Beijing on Its Urban Sprawl | LARP 743 Midterm Project | Jianting Zhao | Oct. 24th 2016
10 km 20 km 30km 40km n
How Topography Has Affected Beijing on Its Urban Sprawl
Interest in This Topic
Growing up in Beijing, it is always been the most
important city in my mind. Its civic development
matters to millions citizens.
In recent years, Beijing is growing exponentially.
But the growth in uneven. Where has grown the
fastest, and where the slowest? We will find out in
this project.
Topography of Beijing
From the Digital Elevation Model (DEM) we can see that the northeast, north, northwest, west and southwest
parts of Beijing are higher in elevation and the central, southern and eastern parts are flat. The urban core of
Beijing is developed in the flat area.
Developed
area
Medium
Developed
area
Less
Developed
area
Under
Developed
area
2. How Topography Has Affected Beijing on Its Urban Sprawl | LARP 743 Midterm Project | Jianting Zhao | Oct. 24th 2016
Urban Development Over 2 Decades
The shapefiles of the urban sprawl from 1993 to 2012 and the Night Lighting from the same time span are displayed. There is a close relationship between urban
sprawl and stable lights. However, the shapefiles are able to show urban development beyond Beijing as well, whereas their counterparts in lighting are clipped.
Annual Urban Sprawl Annual Stable Lighting
1993 1994 1995 1996 1993 1994 1995 1996
1997 1998 1999 2000 1997 1998 1999 2000
2001 2002 2003 2004 2001 2002 2003 2004
2005 2006 2007 2008 2005 2006 2007 2008
2009 2010 2011 2012 2009 2010 2011 2012
3. How Topography Has Affected Beijing on Its Urban Sprawl | LARP 743 Midterm Project | Jianting Zhao | Oct. 24th 2016
Overlay Comparison
Urban Sprawl Overlay from 1993-2012
It is apparent that the flatter area are occupied by people and development.
More importantly, the urban sprawl also goes beyond Beijing’s municipal
boundary towards east, southeast and south.
Stable Lights Overlay from 1993-2012
The lighting overlay almost fills up the low elevation area in Beijing. The
pattern is very similar to that of urban sprawl. It is easy to see a correlation
between these two properties.
4. How Topography Has Affected Beijing on Its Urban Sprawl | LARP 743 Midterm Project | Jianting Zhao | Oct. 24th 2016
Rate of Urbanization
After confirming the close relationship between
urban sprawl shapefiles and stable lights images,
I used the image collection to conduct further
analysis, because there are more methods available
to work with image collection in Google Earth
Engine.
Rate of Urbanization is calculated by adding the
pixel values of each year and reducing to an image
with the sum of all pixel values over time span (as
shown below). The darker green indicates higher
pixel value, and hence longer time of stable lights.
Afterward, I reprojected this sum image to
EPSG:3857 -- WGS84 Web Mercator (Auxiliary
Sphere) projection. By doing this projection, I was
able to use ee.Terrain.slope to calculate the slope
of that sum image, such that I can get the rate of
urbanization over 2 decades (Right Image). The
slope is calculated such that the steeper slope
(darker blue) represents less sprawl over unit time,
versus flatter slope (lighter blue) indicates more
sprawl over unit time.
More Stable Light
Faster Sprawl
Less Stable Light
Slower Sprawl
The area in the mountain region has darker colors, indicating slow urban sprawl. In contrast, the area on plain has
bigger urban sprawl.
5. How Topography Has Affected Beijing on Its Urban Sprawl | LARP 743 Midterm Project | Jianting Zhao | Oct. 24th 2016
Other Approaches of Analysis on Urbanization
Summarizing Urban Sprawl by Standard Deviation
Over 2 decades, the lighting has changed a lot, and it is in general, from low
light intensity to high intensity. Therefore, one way to measure the urban sprawl
is to measure how unstable the light intensity is over the years. If it is big, that
means it’s been developing and vice versa. The central urban core has small
number, because it is lit up throughout the time span, whereas the mountain
area has small number because there isn’t much development.
Summarizing Urban Sprawl by Mean
This method produces similar result to the sum image. In this mean image,
each pixel represents the mean value of stable light intensity over the time
span. The urban core, where is always lit up, has the highest mean value, and
the less development the less pixel value in the rest of the area.
More Change In
Light Intensity More Stable Light
Less Change In
Light Intensity
Less Stable Light
6. How Topography Has Affected Beijing on Its Urban Sprawl | LARP 743 Midterm Project | Jianting Zhao | Oct. 24th 2016
/////////// Load Data /////////////////
var BJdem1 = ee.Image(“users/zhaojianting/MidTerm/ASTGTM2_N39E116_dem”),
BJdem2 = ee.Image(“users/zhaojianting/MidTerm/ASTGTM2_N40E116_dem”),
BJdem3 = ee.Image(“users/zhaojianting/MidTerm/ASTGTM2_N39E115_dem”),
BJdem4 = ee.Image(“users/zhaojianting/MidTerm/ASTGTM2_N39E117_dem”),
BJdem5 = ee.Image(“users/zhaojianting/MidTerm/ASTGTM2_N40E115_dem”),
BJdem6 = ee.Image(“users/zhaojianting/MidTerm/ASTGTM2_N40E117_dem”),
BJdem7 = ee.Image(“users/zhaojianting/MidTerm/ASTGTM2_N41E116_dem”),
BJ = ee.FeatureCollection(“ft:1y1yODcot22kvYzeKKuZllMro1fkzSQf2ozfF0Qnw”),
BJ1993 = ee.FeatureCollection(“ft:1Gr-KhI32ffFCDLgBKIIF9y2rkWQIMDp-zDqp8At4”),
BJ1994 = ee.FeatureCollection(“ft:1oQeiBQIRoNgPEKeDZ1u8qCQP5I657fsOMecSZ0l-”),
BJ1995 = ee.FeatureCollection(“ft:1Wf6L2ZbhZ1c3UQM95RVZzMsr8-ZHk1GmpSmN5OMd”),
BJ1996 = ee.FeatureCollection(“ft:1us8xnLuzbc71qHphrL1lz-9_mSq_FSFLpxMNrKJz”),
BJ1997 = ee.FeatureCollection(“ft:1sbnsmOV5Kb2fA5fXdB8Vq-Jr2NJRa0tCkNtdnPR4”),
BJ1998 = ee.FeatureCollection(“ft:1r3DcuFbra-HMUOT8KzJgMfViYDmDC7St1PzFt-A8”),
BJ1999 = ee.FeatureCollection(“ft:1DFfQ51IyxddakAXHQBg4uNsZobwRUDl-6G8sSuj_”),
BJ2000 = ee.FeatureCollection(“ft:1LJIlkDNa3Xq4gH9ivO_8kWNVpKHZgsU5WLCfaI2u”),
BJ2001 = ee.FeatureCollection(“ft:1fdungkkXjF4Qr-MQhAIfAMOME39-5GizAQeHqVZT”),
BJ2002 = ee.FeatureCollection(“ft:1m2Qk089MtdxU3v6zk7fNQCvv0WpYstFKqapvrTEW”),
BJ2003 = ee.FeatureCollection(“ft:1VnZiXbcHAeIu_aY1awpGCDIJWGD1-mgo8Op_gfjr”),
BJ2004 = ee.FeatureCollection(“ft:17hXweCxsqYgqLt65MLWAzRMphpg61PBRrMPrljZy”),
BJ2005 = ee.FeatureCollection(“ft:1dSrFSQNFnXZptJ8ilOepJ3yRDFEKO9gj9UFK1fcW”),
BJ2006 = ee.FeatureCollection(“ft:1D7ALNyY8c6PIDGy_a15Tc6wb2y-77ZMArmI8EUuy”),
BJ2007 = ee.FeatureCollection(“ft:15CCzRn4XCa0dRUgXlyvPMGwylF02DaCaw54ydRvr”),
BJ2008 = ee.FeatureCollection(“ft:1D9OxIv6-nXzJ2idPHPX2lBuBZP8ZhyE-Y_6ekff8”),
BJ2009 = ee.FeatureCollection(“ft:15Nfkm2ADzgduaPsE3iwMdiZZ6Zjuq9avoQerXgz0”),
BJ2010 = ee.FeatureCollection(“ft:1lyLAs2x4JiyQCThmqbpbBq6whfuAAF0Jt17ogQpW”),
BJ2011 = ee.FeatureCollection(“ft:13MPSOxUqk9hcm12kLa3sTHoJTapF2a4hrXqQdjb-”),
BJ2012 = ee.FeatureCollection(“ft:1bXJ0xyWwGbM48KAQm6HdtDAPD5lzCN2CIVtg5I0n”),
Lt1993 = ee.Image(“NOAA/DMSP-OLS/NIGHTTIME_LIGHTS/F101993”),
Lt1994 = ee.Image(“NOAA/DMSP-OLS/NIGHTTIME_LIGHTS/F101994”),
Lt1995 = ee.Image(“NOAA/DMSP-OLS/NIGHTTIME_LIGHTS/F121995”),
Lt1996 = ee.Image(“NOAA/DMSP-OLS/NIGHTTIME_LIGHTS/F121996”),
Lt1997 = ee.Image(“NOAA/DMSP-OLS/NIGHTTIME_LIGHTS/F121997”),
Lt1998 = ee.Image(“NOAA/DMSP-OLS/NIGHTTIME_LIGHTS/F121998”),
Lt1999 = ee.Image(“NOAA/DMSP-OLS/NIGHTTIME_LIGHTS/F121999”),
Lt2000 = ee.Image(“NOAA/DMSP-OLS/NIGHTTIME_LIGHTS/F142000”),
Lt2001 = ee.Image(“NOAA/DMSP-OLS/NIGHTTIME_LIGHTS/F142001”),
Lt2002 = ee.Image(“NOAA/DMSP-OLS/NIGHTTIME_LIGHTS/F142002”),
Lt2003 = ee.Image(“NOAA/DMSP-OLS/NIGHTTIME_LIGHTS/F142003”),
Lt2004 = ee.Image(“NOAA/DMSP-OLS/NIGHTTIME_LIGHTS/F152004”),
Lt2005 = ee.Image(“NOAA/DMSP-OLS/NIGHTTIME_LIGHTS/F152005”),
Lt2006 = ee.Image(“NOAA/DMSP-OLS/NIGHTTIME_LIGHTS/F152006”),
Lt2007 = ee.Image(“NOAA/DMSP-OLS/NIGHTTIME_LIGHTS/F152007”),
Lt2008 = ee.Image(“NOAA/DMSP-OLS/NIGHTTIME_LIGHTS/F152008”),
Lt2009 = ee.Image(“NOAA/DMSP-OLS/NIGHTTIME_LIGHTS/F162009”),
Lt2010 = ee.Image(“NOAA/DMSP-OLS/NIGHTTIME_LIGHTS/F182010”),
Lt2011 = ee.Image(“NOAA/DMSP-OLS/NIGHTTIME_LIGHTS/F182011”),
Lt2012 = ee.Image(“NOAA/DMSP-OLS/NIGHTTIME_LIGHTS/F182012”);
Google Earth Engine Code --->
Conclusion
From the comparisons of topography and urban
sprawl images, we can see a relationship between
them. More mountains hinders urban sprawl. This
makes sense because uneven topography makes
urban development harder. People tend to gather
on flat topography.
For Beijing specifically, it is growing eastard
and connecting with other larger cities such as
Tangshan and Tianjin. If the sprawl keeps its pace,
Beijing will become a giant metropolitan area
expanding all the way to the Bohai Sea.
7. How Topography Has Affected Beijing on Its Urban Sprawl | LARP 743 Midterm Project | Jianting Zhao | Oct. 24th 2016
//////////////// Locate the map to Beijing /////////////////////////
Map.setCenter(116.4056, 39.9083,9);
/////////////// Creating an Image Collection for DEM ////////////////
var DEM_collection = ee.ImageCollection([BJdem1,BJdem2,BJdem3,BJdem4,BJdem5,BJdem6,BJdem7]);
/////////////// Clip Global DEM to only Beijing //////////////////
function ShowElv(DemImage){
return DemImage.clip(BJ);
}
var topoBJ = DEM_collection.map(ShowElv);
////////////// Creating Elevation for elevation higher than 150m and within Beijing //////////
function ShowHighElv(DemImage){
var dem_mask = DemImage.gt(150);
var high_elev = DemImage.mask(dem_mask);
var high_elev_bj = high_elev.clip(BJ);
return high_elev_bj;
}
var HIGHDEM_col = DEM_collection.map(ShowHighElv);
//////// Clip night lighting to Beijing and mask out area without stable lighting or intensity less than 15 ///
var NightLight = ee.ImageCollection([Lt1993,Lt1994,Lt1995,Lt1996,Lt1997,Lt1998,Lt1999,Lt2000,
Lt2001,Lt2002,Lt2003,Lt2004,Lt2005,Lt2006,Lt2007,Lt2008,Lt2009,Lt2010,Lt2011,Lt2012]);
print(‘night light’,NightLight);
function LightBJ(LightImage){
var light_mask = LightImage.select([‘stable_lights’]).gt(15);
var lightOn = LightImage.mask(light_mask);
var lightOnBJ = lightOn.clip(BJ);
return lightOnBJ;
}
var light_clip = NightLight.map(LightBJ);
////////////// Calculate Rate of Growth in Urban Area based on Night Lighting ///////////////
function LightBJAll(LightImage){
var lightBJall = LightImage.clip(BJ);
return lightBJall;
}
var lights_BJ = NightLight.map(LightBJAll)
var light_sd = lights_BJ.select(‘stable_lights’).reduce(ee.Reducer.stdDev());
var light_mean = lights_BJ.select(‘stable_lights’).mean();
var light_sum = lights_BJ.select(‘stable_lights’).sum();
var light_sum_proj = light_sum.reproject(‘EPSG:3857’,null,1000);
var urban_rate = ee.Terrain.slope(light_sum_proj);
print(‘urban rate’, urban_rate);
Google Earth Engine Code - continued
8. How Topography Has Affected Beijing on Its Urban Sprawl | LARP 743 Midterm Project | Jianting Zhao | Oct. 24th 2016
//////////// urban area shapefile bounded to BEIJING //////
var BJ1993_bound = BJ1993.filterBounds(BJ);
var BJ1994_bound = BJ1994.filterBounds(BJ);
var BJ1995_bound = BJ1995.filterBounds(BJ);
var BJ1996_bound = BJ1996.filterBounds(BJ);
var BJ1997_bound = BJ1997.filterBounds(BJ);
var BJ1998_bound = BJ1998.filterBounds(BJ);
var BJ1999_bound = BJ1999.filterBounds(BJ);
var BJ2000_bound = BJ2000.filterBounds(BJ);
var BJ2001_bound = BJ2001.filterBounds(BJ);
var BJ2002_bound = BJ2002.filterBounds(BJ);
var BJ2003_bound = BJ2003.filterBounds(BJ);
var BJ2004_bound = BJ2004.filterBounds(BJ);
var BJ2005_bound = BJ2005.filterBounds(BJ);
var BJ2006_bound = BJ2006.filterBounds(BJ);
var BJ2007_bound = BJ2007.filterBounds(BJ);
var BJ2008_bound = BJ2008.filterBounds(BJ);
var BJ2009_bound = BJ2009.filterBounds(BJ);
var BJ2010_bound = BJ2010.filterBounds(BJ);
var BJ2011_bound = BJ2011.filterBounds(BJ);
var BJ2012_bound = BJ2012.filterBounds(BJ);
////////////// Show Beijing Topography ///////////////////////////////////////////
Map.addLayer(topoBJ,{min:0, max: 2200,palette:[‘e6ffe6’,’006622’]},’BJ Topo’)
////////////// Present lighting for each year //////////////////
Map.addLayer(light_clip.filterDate(‘1993-01-01’,’1993-12-31’),
{min:0,max:65,palette:[‘000000’,’ffffb3’], bands:’stable_lights’},’nightlights1993’);
Map.addLayer(light_clip.filterDate(‘1994-01-01’,’1994-12-31’),
{min:0,max:65,palette:[‘000000’,’ffffb3’], bands:’stable_lights’},’nightlights1994’);
Map.addLayer(light_clip.filterDate(‘1995-01-01’,’1995-12-31’),
{min:0,max:65,palette:[‘000000’,’ffffb3’], bands:’stable_lights’},’nightlights1995’);
Map.addLayer(light_clip.filterDate(‘1996-01-01’,’1996-12-31’),
{min:0,max:65,palette:[‘000000’,’ffffb3’], bands:’stable_lights’},’nightlights1996’);
Map.addLayer(light_clip.filterDate(‘1997-01-01’,’1997-12-31’),
{min:0,max:65,palette:[‘000000’,’ffffb3’], bands:’stable_lights’},’nightlights1997’);
Map.addLayer(light_clip.filterDate(‘1998-01-01’,’1998-12-31’),
{min:0,max:65,palette:[‘000000’,’ffffb3’], bands:’stable_lights’},’nightlights1998’);
Map.addLayer(light_clip.filterDate(‘1999-01-01’,’1999-12-31’),
{min:0,max:65,palette:[‘000000’,’ffffb3’], bands:’stable_lights’},’nightlights1999’);
Map.addLayer(light_clip.filterDate(‘2000-01-01’,’2000-12-31’),
{min:0,max:65,palette:[‘000000’,’ffffb3’], bands:’stable_lights’},’nightlights2000’);
Map.addLayer(light_clip.filterDate(‘2001-01-01’,’2001-12-31’),
{min:0,max:65,palette:[‘000000’,’ffffb3’], bands:’stable_lights’},’nightlights2001’);
Google Earth Engine Code - continued
10. How Topography Has Affected Beijing on Its Urban Sprawl | LARP 743 Midterm Project | Jianting Zhao | Oct. 24th 2016
////////////// Show Urbanization Rate, darker color means slower sprawl, vice versa /////////
Map.addLayer(urban_rate,{min:0,max:20,palette:[‘e6f9ff’,’0099cc’] },’Urbanization Rate’);
///////////// Show Mountains of Beijing //////////////////////////
Map.addLayer(HIGHDEM_col,{min:150, max: 2200,palette:[‘e6ffe6’,’006622’]},’BJ mountain’)
///////////// Show other statistics measuring of lights over 2 decades //////////////
Map.addLayer(light_sd,{min:0,max:20,palette:[‘ecffb3’,’739900’]},’light value sd’);
Map.addLayer(light_mean,{min:0,max:65,palette:[‘ecffb3’,’739900’]},’Light mean value’);
Map.addLayer(light_sum,{min:0,max:1500,palette:[‘ecffb3’,’739900’]},’Light sum value’);
///////////// Show other statistics measuring of lights over 2 decades //////////////
Map.addLayer(light_sd,{min:0,max:20,palette:[‘ecffb3’,’739900’]},’light value sd’);
Map.addLayer(light_mean,{min:0,max:65,palette:[‘ecffb3’,’739900’]},’Light mean value’);
Map.addLayer(light_sum,{min:0,max:1500,palette:[‘ecffb3’,’739900’]},’Light sum value’);
Google Earth Engine Code - continued
11. How Topography Has Affected Beijing on Its Urban Sprawl | LARP 743 Midterm Project | Jianting Zhao | Oct. 24th 2016
Data Sources:
USGS Earth Explorer: http://earthexplorer.usgs.gov/
Beijing City Lab: http://www.beijingcitylab.com/data-released-1/
NOAA Night Light: https://code.earthengine.google.com/
ArcGIS tutorial: http://desktop.arcgis.com/en/arcmap/10.3/tools/spatial-analyst-toolbox/slope.htm
Spatial Reference: http://spatialreference.org/ref/sr-org/7483/
Google Earth Engine Tutorial: https://developers.google.com/earth-engine
Thank to Professor Dana Tomlin and Jill Kelly for technical support.
Reference and Notes