Nighttime Lights Trends in Jordan

The purpose of this notebook is to conduct an examination of the spatial and temporal distribution of nighttime lights, using NASA Black Marble, nationally and across districts in Jordan.

Data

Define Region of Interest

Define region of interest for which NASA Black Marble will be retrieved and aggregated. We use GADM.

Jordan

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JOR_0 = geopandas.read_file(
    "https://geodata.ucdavis.edu/gadm/gadm4.1/json/gadm41_JOR_0.json.zip"
)
JOR_0.explore()

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Districts of Jordan (ألوية)

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JOR_2 = geopandas.read_file(
    "https://geodata.ucdavis.edu/gadm/gadm4.1/json/gadm41_JOR_2.json.zip"
)
JOR_2.explore()

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Black Marble

NASA’s Black Marble represents a remarkable advancement in our ability to monitor and understand nocturnal light emissions on a global scale. By utilizing cutting-edge satellite technology and image processing techniques, the Black Marble dataset offers a comprehensive and high-resolution view of the Earth’s nighttime illumination patterns. To obtain the raster data conveniently and calculate zonal statistics, we use the BlackMarblePy [1] package developed by the World Bank.

Downloading VNP46A2 (Daily)

VNP46A2 = bm_extract(
    JOR_2,
    product_id="VNP46A2",
    date_range=pd.date_range("2023-01-01", "2024-02-15", freq="D"),
    bearer=bearer,
    aggfunc=["mean", "sum", "min", "max"],
)

Downloading VNP46A3 (Monthly)

VNP46A3 = bm_extract(
    JOR_2,
    product_id="VNP46A3",
    date_range=pd.date_range("2012-01-01", "2024-02-01", freq="MS"),
    bearer=bearer,
    aggfunc=["mean", "sum"],
)
VNP46A3_JOR_0 = bm_extract(
    JOR_0,
    product_id="VNP46A3",
    date_range=pd.date_range("2012-01-01", "2024-02-01", freq="MS"),
    bearer=bearer,
    aggfunc=["mean", "sum"],
)

The latest update date available from NASA’s Black Marble:

'08 February 2024 (Week 06)'

Important

The VNP46A2 Daily Moonlight-adjusted Nighttime Lights (NTL) Product is available daily. However, due data quality, cloud cover or other factors, the data may not be available always at a specific location.

Methodology

Creating a time series of weekly radiance using NASA’s Black Marble data involves several steps, including data acquisition, pre-processing, zonal statistics calculation, and time series generation. Below is a general methodology for this process.

Time Series Generation

Organize the zonal statistics results in a tabular format, where each column corresponds to a specific zone, and rows represent the daily radiance values. Next, we aggregate the data on a weekly basis, computing the desired statistical metric (e.g., mean or sum) for each zone for each week. Finally, we will visualize the time series data to observe trends, patterns, and anomalies over time.

Weekly

In this step, we compute a weekly aggregation of the zonal statistics by for each second-level administrative division and for each week. In this case, we W-SUN and mean as aggregate function.

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JO_2 = (
    VNP46A2.pivot_table(index="date", columns=["NAME_2"], values=[VAR])
    .resample("W")
    .mean()
)

JO_1 = (
    VNP46A2.pivot_table(index="date", columns=["NAME_1"], values=[VAR], aggfunc="mean")
    .resample("W-SUN", label="right")
    .mean()
)
JO_1

	ntl_mean
NAME_1	Ajlun	Amman	Aqaba	Balqa	Irbid	Jarash	Karak	Ma`an	Madaba	Mafraq	Tafilah	Zarqa
date
2023-01-01	6.553614	17.089626	1.337942	10.305475	15.036081	7.813278	1.182889	1.453644	3.091715	4.293278	0.516340	5.350969
2023-01-08	6.925726	16.851504	1.192398	13.652451	12.620506	6.193007	3.136338	1.442617	2.733074	4.487028	1.702175	7.120635
2023-01-15	7.014564	21.282728	1.179323	12.933054	14.062798	8.195653	3.717354	1.602577	3.134586	4.777348	2.034798	9.049575
2023-01-22	7.204723	20.469381	1.356341	12.043415	15.794291	7.917225	3.518542	1.921608	2.797661	5.420961	2.279622	8.663176
2023-01-29	8.780910	18.185698	1.133468	11.839344	16.362963	10.615097	3.555318	1.788156	3.056815	4.997560	2.280131	7.647737
2023-02-05	7.023463	14.807090	1.252475	10.034234	14.974453	7.312657	3.219223	1.848303	3.406766	4.326514	1.926031	7.371080
2023-02-12	8.318564	18.118729	1.184232	11.724532	12.786302	7.250184	2.652394	1.676834	2.809271	4.740587	1.677896	7.991622
2023-02-19	7.171500	20.389868	1.313050	12.389357	15.807822	7.938092	3.216915	1.803367	3.116871	5.345709	2.174536	8.657893
2023-02-26	7.573780	21.958042	1.378766	13.224041	16.343245	8.588145	3.903232	2.049574	3.393519	5.752626	2.396570	9.079799
2023-03-05	8.014141	22.074569	1.260965	13.546127	17.560595	8.883459	3.782953	1.953754	3.090220	5.721044	2.389548	9.246531
2023-03-12	7.557208	19.787281	1.116344	12.194766	15.682060	7.649423	3.381873	1.670901	2.795376	5.584482	2.042827	8.522241
2023-03-19	6.665508	12.158870	1.048582	9.234016	14.417531	5.612315	3.077479	1.551485	2.329972	4.175126	1.693649	7.431360
2023-03-26	7.434890	8.717388	0.800920	8.432571	11.163462	12.079061	2.562035	0.913057	1.956043	2.731027	1.057532	4.814900
2023-04-02	6.574686	20.861471	1.140732	12.024210	14.529601	7.910909	3.285034	1.802680	2.967938	4.914102	2.031900	9.293596
2023-04-09	7.326884	17.319678	1.165424	13.640539	17.665023	8.095854	2.853101	1.352534	2.977836	4.355196	1.698427	7.741399
2023-04-16	7.889825	24.887262	1.348776	14.070664	15.972971	7.509497	3.096332	1.925139	2.692917	4.992247	2.270459	9.868858
2023-04-23	8.558882	22.896442	1.499092	11.829104	18.172011	8.446800	3.048397	1.788419	2.627472	5.723006	1.921935	10.157876
2023-04-30	7.899432	22.874692	1.539177	13.680517	16.222887	7.936313	3.758394	2.020738	3.307109	5.928257	2.311702	8.697650
2023-05-07	7.982337	22.601721	1.033899	13.516930	18.344870	8.670102	3.885742	1.778918	3.441294	6.002452	2.236492	9.854427
2023-05-14	7.772844	21.851723	1.405304	13.170719	17.261466	8.679282	3.880688	2.036877	3.373683	5.914200	2.576136	9.715557
2023-05-21	8.939603	16.796040	1.275589	12.201684	15.319001	7.948092	3.803280	1.964169	3.617117	5.062599	2.116043	8.853832
2023-05-28	8.801076	17.224096	1.203578	11.154665	18.607510	8.296881	3.821440	1.424412	8.872302	6.479573	1.853927	14.516472
2023-06-04	8.172181	15.387304	1.441433	12.689785	18.568036	7.463718	3.081639	1.679680	3.234259	5.004378	1.815386	7.165242
2023-06-11	7.113150	14.603541	0.972269	11.408844	16.883187	8.550189	3.114113	1.808878	2.852778	4.972402	2.185785	6.735259
2023-06-18	7.669387	21.200813	1.349253	12.931719	17.841189	8.541935	3.891227	2.110864	3.290445	5.662483	2.400559	9.627447
2023-06-25	8.307181	24.225970	1.425167	14.599924	19.900998	9.354145	4.443062	2.411512	3.841191	6.358227	2.900355	10.347527
2023-07-02	8.011186	24.607739	1.352764	14.267570	20.224072	9.213605	4.350074	2.198869	3.837411	6.192990	2.695749	10.252297
2023-07-09	7.862403	23.594522	0.983204	14.112334	19.332294	9.004011	4.103980	1.952790	3.725700	5.990913	2.435325	9.930953
2023-07-16	8.212797	24.246511	1.415287	14.501791	20.373905	9.639081	4.542126	2.260104	4.000981	6.503189	2.791092	10.468213
2023-07-23	7.904835	23.493397	1.252254	14.258070	20.073049	9.247895	4.446398	2.263003	3.787536	6.055776	2.795497	9.777270
2023-07-30	7.775163	21.657060	1.225693	13.558004	18.925947	8.902467	4.215789	2.078058	3.762702	5.622017	2.554455	8.548337
2023-08-06	7.979066	24.608087	1.088537	14.642612	20.290297	9.458233	4.271531	2.036089	3.978651	6.138712	2.493140	10.148771
2023-08-13	7.794103	23.022145	1.226908	14.248380	18.559759	9.201307	4.392461	2.059791	4.137162	6.081089	2.735196	9.555307
2023-08-20	7.864048	20.404061	1.444041	12.750299	10.979055	8.359712	4.445966	2.005059	3.766656	5.042963	2.836460	10.148782
2023-08-27	8.204490	23.980610	1.390753	14.439368	19.083684	9.208852	4.833363	2.296364	4.333596	6.304918	3.044219	10.202704
2023-09-03	7.636809	22.606137	1.078973	13.355498	18.183366	8.347787	4.244322	1.845214	3.930025	5.845762	2.535126	9.452122
2023-09-10	7.865827	22.605973	1.262006	14.154798	18.693676	8.715887	4.421432	2.119020	4.182523	6.013685	2.815362	9.534347
2023-09-17	7.732312	22.255352	1.493893	13.788303	18.618095	8.714697	4.753989	2.296897	4.066721	6.127536	3.062951	9.558284
2023-09-24	8.308977	23.883825	1.471181	14.505443	18.799702	9.170241	4.826404	2.389610	4.334535	6.575271	3.169624	10.150605
2023-10-01	7.855340	26.386223	1.292625	13.776799	15.625671	8.483750	4.988369	1.632651	3.891433	5.690511	3.334503	11.908721
2023-10-08	8.269542	16.668704	1.077456	13.816568	13.580138	7.233172	3.229418	1.464934	4.254577	4.612727	2.352224	7.768185
2023-10-15	7.475188	26.809686	1.558039	11.700221	17.023449	8.046034	4.611878	2.216917	3.769920	5.920211	2.878260	7.840910
2023-10-22	7.774611	21.972477	1.585803	13.017458	18.101572	8.869439	4.282855	2.349022	3.821007	6.073596	3.115314	10.451683
2023-10-29	9.788059	24.729888	1.410979	14.837356	21.147902	9.348636	4.317457	2.455011	4.773784	5.575718	3.134979	10.644845
2023-11-05	8.636695	21.806738	1.420556	14.887323	19.191005	9.409041	4.856956	2.202097	5.722046	6.751051	2.844641	10.832408
2023-11-12	7.922564	21.442736	1.389055	13.545763	16.844445	8.756429	4.333543	2.206856	5.188855	5.594353	3.118133	8.380319
2023-11-19	7.480286	18.695148	1.494026	10.963753	18.442322	8.774380	3.695956	2.102390	4.054361	5.308693	2.454161	8.017294
2023-11-26	6.861697	19.395793	1.353484	13.157533	18.219133	7.167230	3.897891	1.588863	4.418614	5.090993	2.570587	7.003433
2023-12-03	7.461221	20.722550	2.329026	13.057442	17.393860	7.720167	3.746143	1.885457	4.102386	5.644296	2.607277	9.004224
2023-12-10	6.681664	17.893838	1.383928	11.566957	13.587801	6.283298	3.515919	1.843646	2.999329	5.435706	2.178366	8.346085
2023-12-17	7.447806	17.550542	1.112721	11.738803	14.610322	6.650827	3.319307	1.699108	3.271925	5.382364	1.963749	8.064997
2023-12-24	6.339929	15.993737	1.454995	13.273185	16.051027	6.425750	3.203037	1.882359	4.134357	3.450228	2.352680	6.547154
2023-12-31	6.552213	20.643292	1.083800	12.194779	14.728168	6.982223	3.837785	1.689556	3.402771	4.797841	2.465967	7.489126
2024-01-07	7.155472	15.330091	1.404368	12.232883	14.322415	7.479134	3.727843	2.047969	3.137475	5.187520	2.649125	6.490157
2024-01-14	6.044978	16.222327	1.379840	10.919437	11.433778	6.354409	4.276449	2.100772	3.290307	4.449964	2.267988	7.245366
2024-01-21	5.995695	15.131319	1.273858	10.030166	15.861356	6.117911	3.092834	2.009539	4.208126	6.031729	2.083615	7.506417
2024-01-28	8.296833	16.189207	0.982500	11.921734	13.485584	9.709556	2.761093	1.732280	3.207788	3.664505	2.147136	7.969058
2024-02-04	7.041361	14.315559	1.113992	12.715988	14.829829	7.342199	2.562630	1.891801	3.241188	3.429573	2.872636	6.504966
2024-02-11	7.073317	16.995336	1.132566	12.161524	15.262148	6.569613	3.005733	1.747079	2.878806	4.823398	1.747239	8.061008

Now, we visualize,

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p = figure(
    title="Jordan: Weekly Nighttime Lights",
    width=800,
    height=700,
    x_axis_label="Date",
    x_axis_type="datetime",
    y_axis_label=r"Radiance [nW $$cm^{-2}$$ $$sr^{-1}$$]",
    tools="pan,wheel_zoom,box_zoom,reset,save,box_select",
)
p.add_layout(
    Title(
        text="Weekly Average Radiance since 2023",
        text_font_size="12pt",
        text_font_style="italic",
    ),
    "above",
)
p.add_layout(
    Title(
        text=f"Data Source: NASA Black Marble. Creation date: {datetime.today().strftime('%d %B %Y')}. Feedback: datalab@worldbank.org.",
        text_font_size="10pt",
        text_font_style="italic",
    ),
    "below",
)
p.add_layout(Legend(), "right")

p.add_tools(
    HoverTool(
        tooltips=[
            ("Week", "@x{%W} (@x{%F})"),
            ("Radiance", "@y{0.00}"),
        ],
        formatters={"@x": "datetime"},
    )
)
renderers = []
for column, color in zip(data.columns, cc.b_glasbey_category10):
    try:
        r = p.line(
            data.index,
            data[column],
            legend_label=column[1],
            line_color=color,
            line_width=2,
        )
        r.muted = True
        renderers.append(r)
    except Exception:
        pass

renderers[0].muted = False

p.legend.location = "bottom_left"
p.legend.click_policy = "mute"
p.title.text_font_size = "16pt"
p.sizing_mode = "scale_both"

output_notebook()
show(p)

Loading BokehJS ...

Fig. 18 Weekly average zonal statistics (i.e., mean) for each second-level administrative division derived from NASA Black Marble.

Monthly

In this step, we compute a monthy aggregation of the zonal statistics by for each second-level administrative division and for each month. Additionally, we add the VNP46A3 monthly composite (when available) in grey.

Loading BokehJS ...

Findings

Percent Change in NTL Radiance

Baseline Comparison

In this exploratory analysis, we conducted analysis of NTL radiance trends, comparing the observed average radiance levels to a 6-month baseline (Jan-Jun 2023) for each second-level administrative division.

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data = 100 * (
    JO_1 / JO_1[(JO_1.index >= "2023-01-01") & (JO_1.index < "2023-06-30")].mean()
    - 1  # scale by 2022 baseline
)

pd.set_option("display.max_rows", None)
data[data.index >= "2023-01-01"].style.map(
    lambda x: "background-color: #DF4661" if x < 0 else "background-color: white"
)

	ntl_mean
NAME_1	Ajlun	Amman	Aqaba	Balqa	Irbid	Jarash	Karak	Ma`an	Madaba	Mafraq	Tafilah	Zarqa
date
2023-01-01 00:00:00	-14.480629	-10.167625	7.516717	-15.866455	-6.451951	-4.828312	-64.595991	-17.443942	-5.216051	-16.524670	-74.424382	-37.757903
2023-01-08 00:00:00	-9.624880	-11.419320	-4.179212	11.458138	-21.480619	-24.564439	-6.129012	-18.070162	-16.211049	-12.757538	-15.686957	-17.173275
2023-01-15 00:00:00	-8.465611	11.873603	-5.229873	5.585003	-12.507300	-0.170682	11.260878	-8.985642	-3.901734	-7.112775	0.788698	5.264030
2023-01-22 00:00:00	-5.984184	7.598207	8.995282	-1.677976	-1.734691	-3.562151	5.310397	9.132923	-14.230996	5.401162	12.915434	0.769456
2023-01-29 00:00:00	14.583784	-4.406069	-8.914784	-3.344008	1.803341	29.299992	6.411108	1.553853	-6.285992	-2.831120	12.940653	-11.042057
2023-02-05 00:00:00	-8.349491	-22.165872	0.648608	-18.080858	-6.835373	-10.926256	-3.648252	4.969719	4.442592	-15.878456	-4.598810	-14.260110
2023-02-12 00:00:00	8.550540	-4.758095	-4.835366	-4.281324	-20.449108	-11.687216	-20.613503	-4.768417	-13.875047	-7.827513	-16.889557	-7.042010
2023-02-19 00:00:00	-6.417728	7.180244	5.516355	1.146279	-1.650509	-3.307977	-3.717336	2.417688	-4.444823	3.938022	7.710252	0.708004
2023-02-26 00:00:00	-1.168298	15.423425	10.797285	7.960613	1.680666	4.610171	16.824230	16.400428	4.036467	11.849826	18.708147	5.615593
2023-03-05 00:00:00	4.578058	16.035951	1.330886	10.590109	9.254494	8.207313	13.224265	10.958555	-5.261883	11.235757	18.360362	7.555002
2023-03-12 00:00:00	-1.384551	4.012718	-10.290823	-0.442353	-2.432946	-6.824190	1.219901	-5.105342	-14.301027	8.580550	1.186360	-0.869885
2023-03-19 00:00:00	-13.020505	-36.086360	-15.736235	-24.613811	-10.300302	-31.637720	-7.890660	-11.887290	-28.569123	-18.821924	-16.109284	-13.558933
2023-03-26 00:00:00	-2.980696	-54.176664	-35.638220	-31.156785	-30.545726	47.132184	-23.317972	-48.145239	-40.032801	-46.899917	-47.617777	-43.993422
2023-04-02 00:00:00	-14.205665	9.659250	-8.331024	-1.834765	-9.603053	-3.639086	-1.678511	2.378676	-9.010735	-4.453834	0.645156	8.102464
2023-04-09 00:00:00	-4.390092	-8.958347	-6.346761	11.360889	9.904200	-1.386317	-14.606314	-23.186197	-8.707270	-15.320776	-15.872641	-9.952591
2023-04-16 00:00:00	2.955833	30.820995	8.387291	14.872413	-0.623020	-8.528596	-7.326401	9.333425	-17.442167	-2.934425	12.461573	14.793866
2023-04-23 00:00:00	11.686495	20.356162	20.466713	-3.427603	13.058462	2.888477	-8.761082	1.568800	-19.448523	11.273904	-4.801691	18.155709
2023-04-30 00:00:00	3.081205	20.241832	23.687899	11.687271	0.931846	-3.329647	12.489209	14.762766	1.387356	15.264652	14.504438	1.170455
2023-05-07 00:00:00	4.163051	18.806948	-16.916145	10.351751	14.133915	5.608459	16.300743	1.029207	5.501142	16.707259	10.779105	14.626012
2023-05-14 00:00:00	1.429335	14.864550	12.929900	7.525298	7.393443	5.720285	16.149486	15.679316	3.428362	14.991352	27.602511	13.010684
2023-05-21 00:00:00	16.654594	-11.710869	2.506040	-0.385877	-4.691740	-3.186166	13.832665	11.550078	10.891418	-1.566556	4.812947	2.987159
2023-05-28 00:00:00	14.846929	-9.460774	-3.280753	-8.933705	15.767949	1.062341	14.376191	-19.104116	172.001737	25.984048	-8.170332	68.854592
2023-06-04 00:00:00	6.640355	-19.115953	15.833205	3.598966	15.522359	-9.086217	-7.766157	-4.606779	-0.846031	-2.698557	-10.079328	-16.654402
2023-06-11 00:00:00	-7.179140	-23.235840	-21.868712	-6.858590	5.039953	4.147828	-6.794199	2.730692	-12.541247	-3.320289	8.267476	-21.655940
2023-06-18 00:00:00	0.079295	11.443014	8.425655	5.574107	11.000232	4.047296	16.464909	19.881222	0.876480	10.097136	18.905759	11.985790
2023-06-25 00:00:00	8.401993	27.344887	14.526073	19.193271	23.815477	13.940625	32.981407	36.955775	17.760944	23.624683	43.661888	20.361713
2023-07-02 00:00:00	4.539498	29.351674	8.707783	16.479951	25.825507	12.228747	30.198261	24.879270	17.645047	20.411936	33.527246	19.254009
2023-07-09 00:00:00	2.598008	24.025654	-20.989924	15.212609	20.277248	9.675726	22.832656	10.903818	14.220290	16.482897	20.627802	15.516156
2023-07-16 00:00:00	7.170361	27.452861	13.732107	18.392123	26.757704	17.411363	35.946405	28.356932	22.659690	26.443211	38.249841	21.765522
2023-07-23 00:00:00	3.151709	23.494083	0.630821	16.402389	24.885908	12.646422	33.081265	28.521573	16.116008	17.744033	38.468042	13.728525
2023-07-30 00:00:00	1.459598	13.841298	-1.503590	10.687072	17.749127	8.438848	26.179090	18.018112	15.354673	9.310359	26.528614	-0.566338
2023-08-06 00:00:00	4.120365	29.353500	-12.525418	19.541776	26.237531	15.208504	27.847460	15.634567	21.975089	19.356598	23.491525	18.049800
2023-08-13 00:00:00	1.706748	21.016928	-1.405928	16.323283	15.470862	12.078948	31.466917	16.980684	26.834630	18.236202	35.481170	11.146669
2023-08-20 00:00:00	2.619470	7.254852	16.042789	4.092998	-31.693023	1.827682	33.068330	13.872304	15.475878	-1.948352	40.497012	18.049930
2023-08-27 00:00:00	7.061958	26.055142	11.760606	17.882505	18.730502	12.170857	44.663170	30.416229	32.856795	22.588167	50.787869	18.677143
2023-09-03 00:00:00	-0.345814	18.830165	-13.293977	9.033826	13.129108	1.682422	27.033095	4.794306	20.484359	13.660694	25.571176	9.946422
2023-09-10 00:00:00	2.642681	18.829298	1.414500	15.559279	16.304036	6.166162	32.334033	20.344422	28.225297	16.925655	39.452002	10.902861
2023-09-17 00:00:00	0.900419	16.986247	20.048884	12.567227	15.833807	6.151664	42.287510	30.446530	24.675102	19.139282	51.715711	11.181292
2023-09-24 00:00:00	8.425436	25.546386	18.223776	18.421937	16.963687	11.700538	44.454885	35.711893	32.885593	27.844719	56.999459	18.071124
2023-10-01 00:00:00	2.505838	38.700353	3.875066	12.473310	-2.783771	3.338553	49.302534	-7.277660	19.301233	10.642092	65.166344	38.521416
2023-10-08 00:00:00	7.910844	-12.380216	-13.415850	12.797981	-15.510203	-11.894437	-3.343097	-16.802728	30.434274	-10.313541	16.511606	-9.641008
2023-10-15 00:00:00	-2.454835	40.926306	25.203688	-4.479803	5.912604	-1.993158	38.034106	25.904263	15.575950	15.108213	42.567481	-8.795084
2023-10-22 00:00:00	1.452392	15.499301	27.434775	6.274078	12.620225	8.036538	28.186390	33.406837	17.142146	18.090519	54.309387	21.573243
2023-10-29 00:00:00	27.726254	29.993756	13.385958	21.131664	31.573184	13.873523	29.222025	39.426196	46.351810	8.410142	55.283438	23.820100
2023-11-05 00:00:00	12.701891	14.628087	14.155586	21.539588	19.398205	14.609307	45.369318	25.062588	75.423060	31.262448	40.902277	26.001814
2023-11-12 00:00:00	3.383060	12.714694	11.624150	10.587138	4.798914	6.659987	29.703495	25.332846	59.076822	8.772471	54.449012	-2.520713
2023-11-19 00:00:00	-2.388316	-1.728124	20.059551	-10.492297	14.740225	6.878649	10.620424	19.399987	24.296160	3.218318	21.560803	-6.743396
2023-11-26 00:00:00	-10.460406	1.954845	8.765686	7.417646	13.351634	-12.697667	16.664363	-9.764531	35.463212	-1.014495	27.327662	-18.536550
2023-12-03 00:00:00	-2.637096	8.929002	87.159979	6.600504	8.217141	-5.962466	12.122533	7.079810	25.768489	9.743520	29.145013	4.736506
2023-12-10 00:00:00	-12.809691	-5.940244	11.212098	-5.567766	-15.462529	-23.464637	5.231902	4.705284	-8.048375	5.687858	7.899994	-2.918915
2023-12-17 00:00:00	-2.812152	-7.744797	-10.582034	-4.164819	-9.100840	-18.987846	-0.652715	-3.503433	0.308733	4.650711	-2.730571	-6.188516
2023-12-24 00:00:00	-17.269051	-15.928212	16.923073	8.361823	-0.137388	-21.729462	-4.132693	6.903880	26.748656	-32.916307	16.534172	-23.843958
2023-12-31 00:00:00	-14.498914	8.512381	-12.906071	-0.442243	-8.367650	-14.951192	14.865403	-4.045911	4.320110	-6.714321	22.145591	-12.887011
2024-01-07 00:00:00	-6.626870	-19.416694	12.854687	-0.131166	-10.892075	-8.898436	11.574830	16.309264	-3.813163	0.862316	31.217860	-24.506951
2024-01-14 00:00:00	-21.117924	-14.726618	10.883595	-10.854097	-28.863935	-22.598447	27.994664	19.308093	0.872270	-13.478190	12.339180	-15.722406
2024-01-21 00:00:00	-21.761022	-20.461548	2.366894	-18.114076	-1.317442	-25.479174	-7.431081	14.126723	29.010219	17.276498	3.206732	-12.685878
2024-01-28 00:00:00	8.266964	-14.900713	-21.046533	-2.671374	-16.098480	18.269806	-17.360120	-1.619478	-1.657552	-28.750074	6.353070	-7.304477
2024-02-04 00:00:00	-8.115935	-24.749628	-10.479851	3.812884	-7.735160	-10.566402	-23.300170	7.440072	-0.633604	-33.317915	42.288929	-24.334685
2024-02-11 00:00:00	-7.698925	-10.663263	-8.987248	-0.713741	-5.045457	-19.977097	-10.038029	-0.779039	-11.743284	-6.217416	-13.454828	-6.234919

Fig. 19 Percent change compared to a 2022 baseline. Values in red indicate a negative percent change.

Show code cell source

Hide code cell source

p = figure(
    title="Jordan: Percent Change in Nighttime Lights Radiance",
    width=800,
    height=800,
    x_axis_label="Date",
    x_axis_type="datetime",
    y_axis_label="Radiance Percent Change (%)",
    tools="pan,wheel_zoom,box_zoom,reset,save,box_select",
)
p.xaxis.major_label_orientation = math.pi / 4
p.add_layout(
    Title(
        text="Percent change (compared to 2022) in NTL radiance for each second-level administrative division",
        text_font_size="12pt",
        text_font_style="italic",
    ),
    "above",
)
p.add_layout(
    Title(
        text=f"Source: NASA Black Marble. Creation date: {datetime.today().strftime('%d %B %Y')}. Feedback: datalab@worldbank.org.",
        text_font_size="10pt",
        text_font_style="italic",
    ),
    "below",
)
p.add_layout(Legend(), "right")
p.renderers.extend(
    [
        Span(
            location=datetime(2023, 10, 7),
            dimension="height",
            line_color="gray",
            line_width=1.5,
            line_dash=(4, 4),
        ),
    ]
)
p.add_tools(
    HoverTool(
        tooltips=[
            ("Week", "@x{%W} (@x{%F})"),
            ("Percent Change", "@y{0.00}% (2022 baseline)"),
        ],
        formatters={"@x": "datetime"},
    )
)
renderers = []
for column, color in zip(data.columns, cc.b_glasbey_category10):
    r = p.line(
        data.index,
        data[column],
        legend_label=str(column[1]),
        line_color=color,
        line_width=2,
    )
    r.visible = False
    renderers.append(r)

renderers[0].visible = True

p.legend.location = "bottom_left"
p.legend.click_policy = "hide"
p.title.text_font_size = "12pt"
p.sizing_mode = "scale_both"

show(p)

Fig. 20 Percent change in average Nighttime Lights (NTL) radiance over time compared to a 2022 baseline average, with a dashed line indicating October 7th.

Week over Week Comparison

In this exploratory analysis, we conducted analysis of NTL radiance trends, comparing the observed average radiance levels week over week (WOW) for each second-level administrative division.

Show code cell source

Hide code cell source

p = figure(
    title="Jordan: Percent Change in Nighttime Lights Radiance",
    width=800,
    height=800,
    x_axis_label="Date",
    x_axis_type="datetime",
    y_axis_label="Radiance Percent Change (%)",
    tools="pan,wheel_zoom,box_zoom,reset,save,box_select",
)
p.xaxis.major_label_orientation = math.pi / 4
p.add_layout(
    Title(
        text="Percent change week over week in NTL radiance for each second-level administrative division",
        text_font_size="12pt",
        text_font_style="italic",
    ),
    "above",
)
p.add_layout(
    Title(
        text=f"Source: NASA Black Marble. Creation date: {datetime.today().strftime('%d %B %Y')}. Feedback: datalab@worldbank.org.",
        text_font_size="10pt",
        text_font_style="italic",
    ),
    "below",
)
p.add_layout(Legend(), "right")
p.renderers.extend(
    [
        Span(
            location=datetime(2023, 10, 7),
            dimension="height",
            line_color="gray",
            line_width=1.5,
            line_dash=(4, 4),
        ),
    ]
)
p.add_tools(
    HoverTool(
        tooltips=[
            ("Week", "@x{%W} (@x{%F})"),
            ("Percent Change", "@y{0.00}% (WOW)"),
        ],
        formatters={"@x": "datetime"},
    )
)
renderers = []
for column, color in zip(data.columns, cc.b_glasbey_category10):
    r = p.line(
        data.index,
        data[column],
        legend_label=str(column[1]),
        line_color=color,
        line_width=2,
    )
    r.visible = False
    renderers.append(r)

renderers[0].visible = True

p.legend.location = "bottom_left"
p.legend.click_policy = "hide"
p.title.text_font_size = "12pt"
p.sizing_mode = "scale_both"

show(p)

Fig. 21 Percent change in average Nighttime Lights (NTL) radiance week over week, with a dashed line indicating October 7th.

National Weekly Sum of Lights

Limitations

See also

Limitations

References

1

Gabriel Stefanini Vicente and Robert Marty. BlackMarblePy: Georeferenced Rasters and Statistics of Nighttime Lights from NASA Black Marble. February 2024. URL: https://doi.org/10.5281/zenodo.10667925, doi:10.5281/zenodo.10667925.