IEEE Geoscience and Remote Sensing Magazine - September 2019 - 65

Moreover, we evaluate the performance and highlight
the advantages and disadvantages of major algorithms and
compare and verify typical algorithms. Ultimately, we propose a relational framework between methods, application
scenes, and different spatial resolutions of remote sensing
images (RSIs) for UIS detection. Our findings provide a
valuable reference to select appropriate methods and RSIs
in UIS extraction applications.
A RISING RESEARCH AREA
Urbanization contributes to changes in physical structures and land surface properties in various ways. Urban land-cover changes greatly influence environmental
quality and ecological cycles and directly affect hydrological circulation. Man-made features constitute UISs,
such as transportation systems, human residential systems, intensive commercial districts, and industrial concrete buildings [1], [2]. Over the past two decades, UIS
has quickly expanded spatially and geometrically in tandem with urbanization, becoming an important type of
land cover. UIS is now considered a key environmental
and ecological indicator of various urban issues, including urban inland inundation, heat islands, water and air
pollution, land subsidence, and ecological imbalance,
all of which compromise biodiversity [3], [4].
In UIS regions, rainwater cannot participate in subsurface runoff. Instead, it flows directly into rivers and lakes
with nonpoint-source pollutants, such as pesticides, pathogens, nutrients, and sediment, leading to water-body pollution and urban rainfall floods. Moreover, UIS increases
the absorbed and reflected solar radiation, which alters

heat fluxes within urban environments as vegetation cover
declines [5]. Additionally, UIS has been applied to urbanrelated socioeconomic issues, including population distribution, estimation of urban development, urban planning,
and housing values [6]-[8].
UIS detection provides relatively accurate mapping and
assessment of UIS for these applications. In UIS mapping,
the location, spatial scale, magnitude, elevation, and spatiotemporal characteristics are derived from ground-based collection and RSIs [9]-[12]. Ground-based collection of this
information is time consuming, labor intensive, and costly.
Large-scale ground-based collection is infeasible because of
the significant workload involved. By contrast, remote sensing techniques offer apparent advantages over traditional
manual measurement in terms of wide coverage, lower cost,
objectivity, and timeliness. High-frequency repeat cycles
have surged in UIS detection in recent decades [13]-[16].
We used the keywords remote sensing and impervious surface to retrieve records from Web of Science between 2001
and 2018 (see Figure 1). We ignored related papers published before 2001 because UIS-related publications prior
to that year are scarce. Figure 1 shows the annual statistics
of UIS-related publications (including articles, reviews,
meetings, and other publications) and citations (including
self-citations) from 2001 to 2018. The x-axis represents the
year, and the left and right y-axes represent citations and
publications, respectively. Publications and citations increased continuously and began to accelerate after 2008.
In 2017, total citations reached 3,044, along with a peak
in annual publications (105). These statistics indicate that
UIS-related studies have become a research hot spot.

3,500

120
100

2,500

2,000
60
1,500
40

1,000

500
0
Citations
Publications

Number of Publications

Number of Citations

3,000

0
4
20 40 70 126 195 338 464 539 789 986 1,242 1,810 1,915 2,622 3,044 3,034
1
4
9
11
6
20
14 25 35 28 43 50 62 78 83 102 107 88
2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018

Year
FIGURE 1. RSI-based UIS-related literature statistics, including publications and citations. The statistics are counted according to the
keywords remote sensing and impervious surface from 2001 to 2018 in Web of Science, acquiring a total of 766 publications and
17,238 citations.
SEPTEMBER 2019

IEEE GEOSCIENCE AND REMOTE SENSING MAGAZINE

IEEE Geoscience and Remote Sensing Magazine - September 2019

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