Understanding how human settlements and economic activities are distributed with reference to the geographical location of streams and rivers is of fundamental relevance for several issues, such as flood risk management, drought management related to increased water demands by human population, fluvial ecosystem services, water pollution and water exploitation. Besides the spatial distribution, the evolution in time of the human presence constitutes an additional key question. This work aims at understanding and analysing the spatial and temporal evolution of human settlements and associated economic activity, derived from nighttime lights, in the Eastern Alpine region. Nightlights, available at a fine spatial resolution and for a 22-year period, constitute an excellent data base, which allows one to explore in details human signatures. In this experiment, nightlights are associated to five distinct distance-from-river classes. Our results clearly point out an overall enhancement of human presence across the considered distance classes during the last 22 years, though presenting some differences among the study regions. In particular, the river network delineation, by considering different groups of river pixels based on the Strahler order, is found to play a central role in the identification of nightlight spatio-temporal trends.
Anthropogenic closeness to rivers is of fundamental relevance for socio-hydrological purposes, including flood and drought management, water pollution and exploitation, but also the human pressure on river ecosystems. In order to analyse human signatures in the proximity of streams and rivers, census data and satellite data such as Landscan could be easily employed (Small, 2004; Kummu et al., 2011), even though they cannot provide spatially and temporally detailed information about human presence. While census data are usually provided on a yearly basis at subnational level (i.e. coarse spatial resolution), spatially detailed Landscan data at 1 km resolution do not allow for a temporal trend analysis. To overcome this weakness, recent studies (Elvidge et al., 1997; Ceola et al., 2014, 2015) used fine scale remotely sensed data, as nighttime lights, to support global and local analyses of human presence and water related issues.
We explore here new opportunities offered by nightlight data to better decipher the interactions between human and water systems. More specifically, we provide insights about the spatio-temporal evolution of human presence along the river network in the European Eastern Alpine region and in its immediate proximity, by adopting satellite images of nighttime lights, available as yearly snapshots from 1992 to 2013 at a high spatial resolution (i.e., nearly 1 km at the equator). In particular, nighttime lights are associated to the river network position and to additional four distance classes.
Nighttime lights data set, satellite number and observation year.
Nighttime light time series, collected by the US Air Force Weather Agency
under the Defense Meteorological Satellite Program (DMSP) – Operational
Linescan System (OLS), are provided as freely available digital products by
the National Geophysical Data Center from the National Oceanic and
Atmospheric Administration (NOAA) at
Nightlight data, produced on a yearly basis from 1992 to 2013, represent
cloud-free nocturnal luminosity from sites with protracted lighting (i.e.,
cities, towns, gas flares). Sunlit and moonlit data and observations from
ephemeral phenomena like fires are excluded from the data set. Nightlight
values, expressed as an adimensional digital number DN
Nightlights cover almost the entire world (180
Regarding the location of the river network, the JRC's Catchment
Characterisation and Modelling (CCM, version 2.1) open database is used
(
In order to analyse the spatio-temporal evolution of human presence in the
Eastern Alpine region, freely available vector files for Austria
(
In order to get a unique and representative nightlight value for each pixel and for each year, for those years presenting two different satellites operating simultaneously (i.e., 1994, 1997, 1998, 1999, 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, see Table 1), a new nightlight product is first obtained as the average nocturnal luminosity from the two overlapped data sets.
Second, because raw nightlight data are not on-board calibrated and cannot be
compared among the 22 year period, a preliminary intercalibration procedure
is required. Therefore, a well-established empirically based intercalibration
technique is employed (see e.g., Elvidge et al., 2009; Chen and Nordhaus,
2011). This technique uses F121999 as the reference satellite composite,
because it is characterized by the highest DN
Third, all data associated to gas flares are excluded from the nightlight database, because they are deemed to be irrelevant for the analysis, and finally, a 22-year time series of nightlights for each of the considered study regions is extracted.
To identify how the human presence is settled across streams and rivers, five distinct distance-from-rivers classes are defined. The original vectorial CCM river network is converted to a raster file and then pixels are classified by adopting the euclidean distance approach. Distance-0 pixels represent river network pixels, distance-1 pixels identify all pixels adjacent to streams and rivers, while distance-2, distance-3, and distance-4 pixels are defined from farther concentric zones (i.e., distance classes 1, 2, 3 and 4 correspond to 1, 2, 3 and 4 km far from the river network, respectively).
The performed analysis focuses on the following different groups of river
pixels and associated distance-from-river pixels (see Fig. 1): CCM river
pixels with Strahler order (i)
Repurposed nighttime lights (expressed as DN values) for year 2013
masked along the river network in the Eastern Alpine region (Austria and
North Eastern Italian regions – Trentino Alto Adige, Veneto and Friuli
Venezia Giulia): CCM river pixels with Strahler order
To account for the human presence as derived from nightlights, for each study
region
In order to visualize tendencies in time, for each region
Spatial and temporal trend of yearly nightlight values in Austria
(first row), Trentino Alto Adige (second row), Veneto (third row) and Friuli
Venezia Giulia (forth row). Columns 1, 2, 3 and 4 refer to CCM river pixels
with Strahler order
In order to identify human signatures across the European Eastern Alpine
region, for each group of river pixels and associated distance-from-river
pixels, we analysed repurposed nightlight data. Figure 1 shows, as an
example, 2013 nightlights in correspondence of the river network pixels as
defined from the aforementioned groups. As outlined in the legend, red pixels
refer to areas with maximum DN values, which correspond to extensively
urbanized areas (significant anthropogenic presence and associated economic
activity), while blue pixels represent areas without nocturnal luminosity,
likely characterized by the absence of human settlements and economic
activities. Spatio-temporal trends of averaged nightlights DN
From the temporal perspective, regardless of the group of river pixels identified by the Strahler order, a clear enhancement of nightlights in time is revealed for each study region and distance-from-river class, thus clearly proving that the human presence close to streams and rivers consistently increased in the Eastern Alpine region from 1992 to 2013.
From the spatial perspective, the nightlight trends across distance classes
between the considered groups of river pixels reveal completely different
behaviours. More specifically, river pixels with Strahler order
Conversely, river pixels with Strahler order
Concerning the ranges of variability of average DN
The spatially and temporally extensive analysis of human signatures from nightlights performed so far (i.e., by using detailed information on the river network location and nearby pixels) provide valuable insights into the evolution of human presence. Our results clearly point out an overall enhancement of human presence across the considered distance classes during the last 22 years, though presenting some differences among the study regions. From 1992 to 2013 average nightlights increased with respect to their initial value of about 30 % for Austria, 15 % for Trentino Alto Adige and 12 % for Veneto and Friuli Venezia Giulia. In addition, the river network delineation is found to play a central role in the identification of nightlight spatio-temporal trends, as highlighted by our results. Perspective work envisages to compare these outcomes with demographic data, as well as the European Settlement Map (i.e., a spatial raster data set that is mapping human settlements in Europe based on SPOT5 and SPOT6 satellite imagery, produced with Global Human Settlement Layer technology by the European Commission, Joint Research Centre, Institute for the Protection and Security of the Citizen, Global Security and Crisis Management Unit). Furthermore, linkages between nightlights and drought issues due to enhanced human water demands are also planned to be uncovered.
The research leading to these results has received funding from the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement no. 603587, project “SWITCH-ON” (Sharing Water-related Information to Tackle Changes in the Hydrosphere – for Operational Needs).