A Method for Classified Correction of Stable DMSP/OLS Nighttime Light Imagery Across China

Ziyang CAO; Zhifeng WU; Sujuan MI; Ke YANG

doi:10.12082/dqxxkx.2020.190253

Journals >Journal of Geo-information Science >Volume 22 >Issue 2 >Page 246 > Article

Journal of Geo-information Science
Vol. 22, Issue 2, 246 (2020)

A Method for Classified Correction of Stable DMSP/OLS Nighttime Light Imagery Across China

Ziyang CAO^{1、1、2、2、3、3、*}, Zhifeng WU^4、4, Sujuan MI^{1、1、2、2}, and Ke YANG^1、1

Author Affiliations

¹China Transport Telecommunications & Information Center, Beijing 100011, China

¹中国交通通信信息中心交通运输遥感中心,北京 100011

²China Transport Infocom Technologies Co., Ltd., Beijing 100000, China

²北京国交信通科技发展有限公司,北京 100000

³School of Geological and Surveying Engineering of Chang'an University, Xi'an 710061, China

³长安大学地质工程与测绘学院,西安 710061

⁴School of Geographical Sciences of Guangzhou University, Guangzhou 510006, China

⁴广州大学地理科学学院,广州 510006

show less

DOI: 10.12082/dqxxkx.2020.190253 Cite this Article

Ziyang CAO, Zhifeng WU, Sujuan MI, Ke YANG. A Method for Classified Correction of Stable DMSP/OLS Nighttime Light Imagery Across China[J]. Journal of Geo-information Science, 2020, 22(2): 246 Copy Citation Text

show less

Fig. 1. Comparison of scatter distribution of DNs between SNL images and reference images in 2006

Download full size | View in the Article

Fig. 2. Sum of the DNs of bright pixels with DN value ≤55 in SNL images obtained from different satellites

Download full size | View in the Article

Fig. 3. Relationship (and coefficients) of unsaturated pixel DNs between NSL images

Download full size | View in the Article

Fig. 4. NDLI values of the stable nighttime light image of the same year obtained by different satellites before and after the classified correction

Download full size | View in the Article

Fig. 5. Sum of bright pixel values obtained from different satellites after correction by different methods

Download full size | View in the Article

Fig. 6. Comparison of different types of NTL images for some Chinese urban agglomerations in 2006

Download full size | View in the Article

Fig. 7. Latitudinal transects of different types of NTL index for Jing-Jin-Tang urban agglomerations in 2006

Download full size | View in the Article

Fig. 8. Correlation of GDP and electricity consumption with 4 types of NTL images for Chinese cities from 1999 to 2013

Download full size | View in the Article

城市	R²	城市	R²	城市	R²	城市	R²
拉萨市	0.9673	德宏州	0.9347	宁波市	0.9185	台州市	0.9103
延安市	0.9580	黄山市	0.9335	迪庆州	0.9178	梧州市	0.9091
克孜州	0.9541	甘南州	0.9309	威海市	0.9176	苏州市	0.9089
凉山州	0.9538	临沧市	0.9300	绍兴市	0.9171	普洱市	0.9088
怒江州	0.9503	遂宁市	0.9298	重庆市	0.9169	贺州市	0.9080
舟山市	0.9469	海南州	0.9280	银川市	0.9162	南充市	0.9078
金华市	0.9434	杭州市	0.9279	资阳市	0.9157	抚州市	0.9071
长沙市	0.9422	和田地区	0.9271	固原市	0.9147	上饶市	0.9068
喀什地区	0.9422	保山市	0.9261	中卫市	0.9141	西双版纳州	0.9068
成都市	0.9392	博尔塔拉州	0.9246	铜仁地区	0.9124	赣州市	0.9060
文山州	0.9385	昌都地区	0.9242	惠州市	0.9119	嘉兴市	0.9043
石河子市	0.9371	丽水市	0.9220	嘉峪关市	0.9113	河源市	0.9017
西宁市	0.9349	锡林郭勒盟	0.9194	永州市	0.9111	桂林市	0.9016
甘孜州	0.9348	丽江市	0.9190	厦门市	0.9109	酒泉市	0.9010

Table 1. Chinese cities with the index correlation coefficient between the total DN value of unsaturated pixels in the SNL images and years over 0.9

辐射校准的灯光影像	混合的稳定灯光影像	待校正稳定灯光影像
F12_1996	F12_1997	F10_1992-1994, F12_1994-1999
F12_1999	F14_1999	F14_1997-2003
F12-F15_2000	F15_2000	F15_2000-2007 ^a
F14-F15_2003	F15_2003
F14_2004	F15_2004
F16_2006	F16_2006	F16_2004-2009
F16_2010	F18_2010	F18_2010-2013 ^b
F16_2010-2011	F18_2010	F18_2010-2013 ^b

Table 2. Representative reference images for raw SNL images

稳定灯光影像	d	e	R²	稳定灯光影像	d	e	R²
F101992	1.6058	0.7209	0.8261	F152001	1.7151	0.6638	0.8790
F101993	1.4223	0.7706	0.8892	F152002	1.6428	0.7099	0.8848
F101994	1.2326	0.8284	0.8861	F152003	0.9146	0.8068	0.9204
F121994	1.5814	0.8405	0.8629	F152004	0.8386	0.8766	0.9392
F121995	1.3788	0.8840	0.9129	F152005	0.9129	0.8569	0.9092
F121996	1.2844	0.8915	0.9372	F152006	0.9378	0.8610	0.9028
F121997	1.2981	0.9312	0.9462	F152007	1.1294	0.8048	0.8898
F121998	1.4016	0.9209	0.9180	F162004	1.2520	0.8496	0.9036
F121999	1.3058	0.9414	0.8496	F162005	1.1273	0.8424	0.9204
F141997	1.2187	0.7903	0.8974	F162006	1.2374	0.8664	0.9290
F141998	1.2622	0.7917	0.9084	F162007	1.3602	0.8881	0.9109
F141999	1.0184	0.8740	0.9254	F162008	1.3228	0.8969	0.8708
F142000	1.1412	0.8477	0.9055	F162009	1.8805	0.7539	0.8342
F142001	1.3947	0.8358	0.8642	F182010	1.9359	0.8480	0.8960
F142002	1.1143	0.9249	0.8493	F182011	1.3247	0.9173	0.8207
F142003	1.1901	0.9357	0.8088	F182012	1.9522	0.8100	0.8483
F152000	1.7378	0.6493	0.8707	F182013	1.8153	0.8430	0.7392

Table 3. Calibration model coefficients for saturated pixels of each stable nighttime light image

辐射校准的灯光影像	C₀	C₁	R²
F12_1996	4.336	0.915	0.971
F12_1999	1.423	0.780	0.980
F12-F15_2000	3.658	0.710	0.980
F14-F15_2002	3.736	0.797	0.980
F14_2004	1.062	0.761	0.984
F16_2006	0.000	1.000	1.000
F16_2010	2.196	1.195	0.981
F16_2010-2011	-1.987	1.246	0.981

Table 4. Coefficients adopted for intercalibration of RC NTL dataset

不连续稳定灯光影像	a	b	c	R²
F101994	0.000 10	0.9158	0.7429	0.9456
F121996	-0.002 40	1.1846	-0.6158	0.9481
F121999	-0.000 10	0.8944	0.8090	0.9299
F141998	-0.000 60	0.9030	0.5025	0.9026
F162005	-0.003 50	1.1887	0.0175	0.9198
F162006	-0.005 20	1.3614	-1.1588	0.9671
F162008	-0.000 08	0.9654	0.3562	0.9698
F162009	-0.006 60	1.3758	-1.7220	0.8883
F182010	-0.000 09	0.9353	-0.4345	0.8884
F182013	-0.006 40	1.1823	-0.0691	0.8417

Table 5. Coefficients adopted for intercalibration of unsaturated pixels in discontinuous images

Ziyang CAO, Zhifeng WU, Sujuan MI, Ke YANG. A Method for Classified Correction of Stable DMSP/OLS Nighttime Light Imagery Across China[J]. Journal of Geo-information Science, 2020, 22(2): 246

Download Citation

Tools

Save the article for my favorites

Paper Information