SDGSAT-1: the world’s first scientific satellite for Sustainable Development Goals

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Short Communication
SDGSAT-1: the world’s first scientific satellite for sustainable
development goals
Huadong Guo
a,b,c,
⇑
, Changyong Dou
a,b
, Hongyu Chen
a,d
, Jianbo Liu
a
, Bihong Fu
d
, Xiaoming Li
a,b
,
Ziming Zou
a,e
, Dong Liang
a,b
a
International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China
b
Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
c
University of Chinese Academy of Sciences, Beijing 100049, China
d
Innovation Academy for Microsatellites, Chinese Academy of Sciences, Shanghai 201304, China
e
National Space Science Center, Chinese Academy of Sciences, Beijing 100190, China
article info
Article history:
Received 30 August 2022
Received in revised form 1 December 2022
Accepted 2 December 2022
Available online 13 December 2022
Ó2022 Science China Press. Published by Elsevier B.V. and Science China Press. This is an open access
article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
The United Nations 2030 Agenda for Sustainable Development
(2030 Agenda) is facing several hurdles, e.g., lack of data, insuffi-
cient research methods, and uneven development, in achieving
the 17 Sustainable Development Goals (SDGs) by 2030 [1]. Aside
from global issues, such as food crises, climate change, and reverse
globalization, there are also many challenges in governance, capac-
ity, and a lack of comprehensive engagement of stakeholders that
all interplay to limit informed policies that could ensure sustain-
ability. The COVID-19 pandemic has further aggravated these lim-
itations, either diverting attention or slowing progress towards
these goals. Furthermore, monitoring progress towards the SDGs
is difficult due to unavailable or inaccessible data, as many devel-
oping countries lack basic health, social, and economic data [2].
The United Nations therefore actively advocates for investment
in data and promotes the adoption of science and technology to
facilitate implementation of the 2030 Agenda around the world.
The rapid development of science and technology has already led
to social changes, and the issues of development opportunities
and risks of new divides are now becoming the focus of discussion.
The United Nations Technology Facilitation Mechanism, therefore,
aims to improve international engagement through multistake-
holder collaboration and cooperation to advise policy and share
knowledge, information, experiences, and practices. ‘‘The
‘Space2030’ Agenda: space as a driver of sustainable development”
[3], a resolution adopted in 2021 by the United Nations General
Assembly, recognizes ‘‘space tools” to be highly relevant in accom-
plishing the 2030 Agenda for Sustainable Development. Earth
observation data from satellites provide spatial attributes relevant
to understanding essential issues of the Earth ecosystem, which are
immensely critical for solving sustainability challenges [4] and
additionally provide new opportunities to facilitate data-driven
policy and decision-making support [5].
To better fulfill the growing data needs and to improve global
data coverage for SDG applications, the Sustainable Development
Goals Science Satellite 1 (SDGSAT-1), developed and operated by
the International Research Center of Big Data for Sustainable
Development Goals (CBAS), was launched on 5 November 2021.
The satellite is specifically dedicated to collecting data related to
the SDGs [6]. Data from SDGSAT-1 will not only support scientific
applications but will also serve the UN Member States by filling in
data gaps and creating a reliable stream of information relevant to
achieving the SDGs. SDGSAT-1 is equipped with three advanced
sensors: a thermal infrared spectrometer, glimmer imager, and
multispectral imager. The technical specifications of SDGSAT-1 is
shown in Table 1. Aiming to precisely depict traces of anthropic
activity, SDGSAT-1 can acquire multitype, high-precision data
through its three sensors to maximize usage for a variety of SDG
applications, especially SDG indicators representing human-nature
interactions.
The thermal infrared spectrometer has the ability to detect tem-
perature differences with an accuracy of NEDT (noise equivalent
differential temperature) less than 0.041 K @ 300 K at a spatial res-
olution of 30 m, in contrast with 0.047 K @ 300 K at a spatial res-
olution of 100 m for Landsat, and 0.05 K @ 300 K at a spatial
resolution of 1000 m for the Moderate Resolution Imaging Spectro-
radiometer (MODIS). It is useful for detecting surface parameters,
such as thermal radiation intensity, temperature field distribution,
water temperature, and heat sources. Therefore, it has great advan-
tages in the observation of glacial variations, ecosystem changes,
https://doi.org/10.1016/j.scib.2022.12.014
2095-9273/Ó2022 Science China Press. Published by Elsevier B.V. and Science China Press.
This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
⇑
Corresponding author.
E-mail address: hdguo@radi.ac.cn (H. Guo).
Science Bulletin 68 (2023) 34–38
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journal homepage: www.elsevier.com/locate/scib

and port activity. The glimmer imager adopted an innovative
design employing color bands in addition to a panchromatic band,
a feature applied for the first time in spaceborne nighttime light
sensors. The spatial resolution of the color bands is 40 m, and that
of the panchromatic band is 10 m (vs 130 m for Luojia-1 and 750 m
for VIIRS onboard the Suomi NPP satellite). The glimmer imager
can pick up low-light data used in detecting nighttime urban pop-
ulation, human activity, spatial estimation of social and economic
development, power consumption assessment, as well as snow
and ice during polar nights. The multispectral imager specializes
in monitoring coastal and land environments, urban area function
identification, artificial construction, and the intensity and concen-
tration of human activity due to its ability to detect land cover
change. It is equipped with two deep blue bands designed to iden-
tify water composition in a variety of water bodies, such as off-
shore ocean water and lakes, as well as a red edge band to
monitor vegetation growth on land. SDGSAT-1 has a swath width
of 300 km for its three sensors (vs 185 km for Landsat) to ensure
more efficient global data collection.
The multi-mode capacity of SDGSAT-1 allows the synergetic
operation of its three sensors 24 h a day, with the multispectral
imager collecting data in daylight, the glimmer imager working
at night, and the thermal infrared spectrometer operating day
and night, simultaneously with or independent of the other sen-
sors. The simultaneous operation of two sensors makes it possible
to observe the same ground object at the same time under the
same circumstances, improving consistency of information on sub-
jects from different sensors and enabling a more comprehensive
analysis. Although the multispectral and glimmer imagers cannot
operate at the same time, they provide the opportunity to utilize
the spectral response difference from objects on the ground to
characterize their changes between day and night.
The SDGSAT-1 sensors work together to provide multiple types
of data for various SDG indicators at high spatial and temporal res-
olutions, and the data is valuable in conducting research on popu-
lation (SDG 1), agriculture (SDG 2), well-being estimation (SDG 3)
[7], economic livelihoods (SDG 4), water quality (SDG 6), informal
settlements (SDG 11), climate-related hazards and natural disas-
ters (SDG 13), and coastal environments and terrestrial ecosystems
(SDG 14, 15). The data acquired by SDGSAT-1 are available free-of-
charge to the scientific community around the world via the
SDGSAT-1 Open Science Program (https://www.sdgsat.ac.cn)
launched in September 2022.
Fig. 1a–c is chromatic glimmer (10-m image merged from
panchromatic and color data), multispectral, and thermal infrared
images, respectively, taken over Beijing by the three sensors
onboard SDGSAT-1. The glimmer image (Fig. 1a) shows a dazzling
scene at night, including the distribution of light sources, the illu-
mination intensity, and color of lights, which can all be utilized to
map the urban road network, the division of functional areas, and
the distribution of human settlements and activity. The glimmer
data can also be used to estimate and distinguish the levels of eco-
nomic development, which can be inferred from the color and dis-
tribution of the light source. In the multispectral image (Fig. 1b),
the overall layout and distribution of the city, the characteristics
of ground features and surface coverage, and the urban road net-
work and transportation infrastructure are clearly visible. The ther-
mal infrared image (Fig. 1c) is capable of mapping thermal energy
distribution, concentration of urban residential areas, and active
heat source areas, and is helpful in understanding socioeconomic
activity and environmental circumstances. The sub-images in
Fig. 1a–c show the details of the Bird Nest, Water Cube, and their
surroundings, demonstrating the capabilities of SDGSAT-1 to thor-
oughly detect the same object on Earth’s surface via its three
advanced sensors simultaneously.
Fig. 1d–f is color composites of night-light images of Paris,
Dubai, and Hong Kong, respectively. Using these images, the layout
of the cities can be clearly identified in contrast to the surrounding
rivers, coastal areas, and vegetation.
Fig. 1g, h is images captured by the multispectral imager over
the Yellow River Estuary and Lake Taihu in China, respectively.
With the ability to capture information with two deep blue bands,
the multispectral imager can accurately reflect characteristics of
water that are important for studying SDG 14. The image of the
Yellow River Estuary shows the state of gradual mixing and blend-
ing of the river and sea water, and the topography of the seabed
and direction of the sea water can also be identified from the
trends of the river water after flowing into the sea. The image of
Lake Taihu shows that water in the northern part and bays appears
much clearer than the cloudy major waterbody of the lake, which
suggests that sediment accumulated at the lake surface due to
heavy winds at the time the image was captured. The cyanobacte-
rial blooms are detected in the north-central, southern, and east-
central parts of the lake. The urbanization layout and vegetation
around the lake are also clearly visible. Fig. 1c, i is images captured
by the thermal infrared spectrometer over Beijing and the Aksu
region in China, respectively. The image of Aksu, unlike the more
urbanized Beijing, better presents the thermal characteristics of
several natural features, supporting its utility for research related
to SDG 13, SDG 15, and other indicators.
Fig. 1j–l is false color images of Lake Poyang in China collected
by the multispectral imager of SDGSAT-1 in November 2021, April
2022, and September 2022. The series of imagery records the water
body changes of the lake. As shown in Fig. 1j, the lake was in a low-
water period. With the arrival of the flood season in the Yangtze
Table 1
Technical specifications of SDGSAT-1.
Type Index Specifications
Orbit Type Sun-synchronous orbit
Altitude 505 km
Inclination angle 97.5°
Revisit cycle 11 d
Local time of descending
node (LTDN)
9:30 AM
Thermal infrared
spectrometer
Swath width 300 km
Bands 8–10.5
l
m
10.3–11.3
l
m
11.5–12.5
l
m
Spatial resolution 30 m
Designed radiometric
accuracy
Relative: 5%
Absolute: 1 K @ 300 K
Glimmer imager Swath width 300 km
Bands Panchromatic: 444–
910 nm
Blue: 424–526 nm
Green: 506–612 nm
Red: 600–894 nm
Spatial resolution Panchromatic: 10 m, RGB:
40 m
Designed radiometric
accuracy
Relative: 2%
Absolute: 5%
Multispectral
imager
Swath width 300 km
Bands Deep blue 1: 374–427 nm
Deep blue 2: 410–467 nm
Blue: 457–529 nm
Green: 510–597 nm
Red: 618–696 nm
Near infrared (NIR)
: 744–813 nm
Red edge: 798–911 nm
Spatial resolution 10 m
Designed radiometric
accuracy
Relative: 2%
Absolute: 5%
H. Guo et al. Science Bulletin 68 (2023) 34–38
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H. Guo et al. Science Bulletin 68 (2023) 34–38
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River Basin, the coverage of water bodies (the area in blue colors in
Fig. 1k) increased tremendously, and the lake was in a high-water
period. Hit by severe heat waves in the summer of 2022, the lake
suffered from an extreme drought, where a major part of the lake
dried up and the bottom of the lake was exposed, identified as the
white area in Fig. 1l.
Fig. 1m–o is images near Maly Taymyr Island, Russia, close to
the Arctic, captured by thermal infrared sensors onboard MODIS,
Landsat 9, and SDGSAT-1 on 27 April 2022 with an interval of only
several hours. The three images show the same temperature distri-
bution patterns in this area, while more accurate information of
the water bodies, sea ice, and sea ice leads, such as temperature
variation and shape details, are gradually recognized by Landsat
9 and SDGSAT-1 compared to MODIS. With the highest spatial
and radiometric resolutions among them, SDGSAT-1 shows much
better performance in detecting the thermal radiation intensity
and detailed texture of the environment.
In June 2022, during the High-level Dialogue on Global Develop-
ment, China acknowledged the global challenges for sustainable
development and urged joint efforts to build an international con-
sensus on development, while reiterating its commitment to sup-
port the 2030 Agenda (https://en.cppcc.gov.cn/2022-06/27/c_
784447.htm). China also announced its plan to initiate a Sustain-
able Development Satellite Constellation Program to collect and
share SDG data and information with all countries to support their
efforts (https://news.cgtn.com/news/2022–06-25/Chair-s-state-
ment-at-the-High-level-Dialogue-on-Global-Development-1b8ZW
9ekqmA/index.html), which was one of the 32 deliverables of the
event. CBAS will be at the forefront of the effort to develop the
SDG satellite constellation with the motivation to contribute our
efforts to ‘‘Enhance space-derived economic benefits and
strengthen the role of the space sector as a major driver of sustain-
able development”, which is the first overarching objective of the
Space2030 Agenda. CBAS’ efforts are directed toward addressing
the growing demand for spatial information, improving capacity
for Earth observation as a digital solution for SDGs, and providing
new knowledge and data for research and development. Building
upon SDGSAT-1, the SDG satellite constellation is expected to:
(1) Mitigate global data gaps on SDGs. According to the United
Nations Inter-Agency Expert Group on SDG indicators
(IAEG-SDGs), more than 41% of indicators are in Tier II or
Tier III, which means the data to support these indicators
are not regularly available [8]. The planned SDG satellite
constellation is expected to collect a stable stream of global
data to fill in the data gaps [9]. These reliable data will also
enable the development of an automated process to gener-
ate timely and economical information in support of achiev-
ing SDGs.
(2) Facilitate and incentivize data analytics and technology
companies to provide data-driven business strategies and
solutions for businesses on SDG-related challenges for those
operating in developing countries, thereby providing an
important foundation for access to frontier technologies.
(3) Empower cloud-based data analysis systems to strengthen
science-technology-policy frameworks within local gover-
nance structures in developing countries, which may lack
the financial resources to develop indigenous data analysis
systems [10]. Based on this data, public digital SDG products
could help bridge the global digital information divide [11].
Promoting these mechanisms will also help improve infor-
mation outreach to enhance public participation and sup-
port the realization of SDGs.
(4) Provide spatiotemporal attributes for global processes and
systems that can prove to be valuable in data interoperabil-
ity with other sources of big data to enable a more compre-
hensive evaluation of complex processes [12].
(5) Provide valuable data about Earth systems for environment-
related SDGs, helping to improve their geographic coverage
and provide internationally comparable country-level data-
sets [13,14]. This will be particularly useful for SDG indica-
tors that require an understanding of the Earth system,
such as carbon, water, and energy cycling in terrestrial
ecosystems [15].
As the world moves further off track in meeting the SDGs, data
is being widely recognized as a strategic asset to facilitate progress
and understand challenges. Unfortunately, the lack of qualified and
timely datasets and methodologies hinders optimistic expecta-
tions. Within this context and considering the growing relevance
and reliability of Earth observation data from satellites within
science and research, CBAS launched SDGSAT-1 to develop high-
resolution, multi-scale global public data to support policy and
decision support systems for sustainable development. To acceler-
ate the implementation of the 2030 Agenda, new SDG satellites are
being planned to launch into orbit to construct a satellite constel-
lation, which will help provide a continuous stream of data on the
Earth system and human-environment interactions to enable
multi-scale data support to policymakers and fill in data gaps.
Conflict of interest
The authors declare that they have no conflict of interest.
Acknowledgments
This work was supported by the Strategic Priority Research Pro-
gram of Chinese Academy of Sciences (XDA19010000 and
XDA19090000). The authors wish to thank the CASEarth satellite
team and SDGSAT-1 Engineering Project team for their
contributions.
Author contributions
Huadong Guo conceived the concept as the chief scientist of
SDGSAT-1 and created the first draft of the paper and contributed
to its subsequent revisions. Changyong Dou modified the
Fig. 1. Imagery captured by SDGSAT-1. Glimmer (a), multispectral (b), and thermal infrared (c) images of Beijing to demonstrate the ability of SDGSAT-1 for synergetic
observation of the same object. Glimmer images of Paris (d), Dubai (e), and Hong Kong (f), respectively, to show performance of the innovative glimmer imager and its global
data collection capability. Multispectral images of the Yellow River Estuary (g) and Lake Taihu (h) in China to exhibit the potential applications for SDG 6 in different types of
water bodies. Thermal infrared images of Beijing (c) and the Aksu region (i) of China, also in different scenarios, namely supercity and natural environments. Multispectral
images of Lake Poyang in China in November 2021 (j), April 2022 (k), and September (l) 2022, respectively, illustrating water body changes in different seasons recorded by
SDGSAT-1. Thermal infrared images near Maly Taymyr Island in the Russian Arctic, captured by MODIS (m), Landsat 9 (n), and SDGSAT-1 (o), respectively, on 27 April 2022
with an interval of only several hours to compare their performance in environmental object detection.
3
H. Guo et al. Science Bulletin 68 (2023) 34–38
37

investigation plan and contributed to the preparation and revision
of the manuscript. Hongyu Chen, Jianbo Liu, Bihong Fu, Xiaoming
Li, and Ziming Zou provided scientific and technical assistance
and assisted in finalizing the manuscript. Dong Liang assisted in
concept development, and contributed to the drafting and revision
of the manuscript.
Appendix A. Supplementary materials
Supplementary materials to this short communication can be
found online at https://doi.org/10.1016/j.scib.2022.12.014.
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Huadong Guo is the chief scientist of SDGSAT-1, direc-
tor-general of the International Research Center of Big
Data for Sustainable Development Goals, professor of
the Chinese Academy of Sciences Aerospace Information
Research Institute, honorary president of the Interna-
tional Society for Digital Earth, and was a member of the
UN 10-Member Group to support the Technology
Facilitation Mechanism for SDGs (2018–2021). He spe-
cializes in remote sensing, radar for Earth observation,
and Digital Earth science.
H. Guo et al. Science Bulletin 68 (2023) 34–38
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