From space to coast: a semi-automatic quantative review on remote sensing of coastal ecosystems
RS-eco
Abstract
Direct sampling of marine communities can be very difficult. Thus, marine research intensively relies on indirect observation methods, such as tethered video surveys or the use of Remotely Operated Vehicles (ROVs) and Autonomous Underwater Vehicles (AUVs). Bathymetry and environmental data are often gathered through ship-based sensors or airborne and satellite systems, which allow for continuous sampling over large spatial and temporal scales. In situ observations using unmanned aerial vehicles (UAVs), camera traps and acoustic sensors provide another indirect sampling method. All these methods have been increasingly used and have helped to acquire a vast amount of data, which helps us to further our scientific understanding and make predictions about future changes in marine ecosystems. Although, coastal communities are more accessible than most of the marine realm and can thus also be easily studied without remote sensing, the accessibility also means that they are more easily threatened by anthropogenic activities, such as coastal pollution and land use change. Thus, coastal ecosystems are an important research area, which are frequently studied using direct sampling but also remote sensing. Here, a quantitative literature review of the current literature on remote sensing and coastal ecosystems was performed. A total number of 3835 peer-reviewed journal publications was identified using Web of Knowledge and significant patterns and trends in these publications were identified. There was an exponential increase in the number of publications from 1990 - 2017, with a particular sharp increase since 2000. Most studies on remote sensing in coastal ecosystems have been conducted in China, India, Mali, Australia, Brazil, North America and Mexico. There was a strong difference in the number of publications by research topic, as well as by coastal ecosystem and taxonomic group. Most studies further utilised multispectral imagery, rather than hyperspectral, lidar or radar data and also mostly used Modis and Landsat imagery. …
Keywords: marine, satellite, biodiversity, conservation, climate change, pollution
Introduction
Global change is a hot topic in environmental and ecological research. It imposes challenges not only to the research, but also to the management and policy community and these challenges are likely to increase even further in the future (Pereira et al. 2010). Understanding current and making reliable predictions of future changes, enables us to prepare for these challenges, but also requires the collection of a vast amount of data.
Collecting field data is generally very resource intensive and difficult
to implement across large spatial and temporal scales. Remote Sensing
(RS) offers a good alternative and thus is an important tool for
measuring environmental conditions, as well as the state of biological
diversity and ecosystem services across multiple spatial and temporal
scales. Thus, it is not surprising that the use of RS has experienced an
exponential increase over the past decade (Pettorelli et al. 2014).
Sensors, methodologies and data availability have strongly developed and
using RS has become simpler and more widespread (Palmer et al. 2014).
This is not only true for the terrestrial environment, but RS has also
become increasingly important in studying coastal and marine ecosystems
(Brewington et al. 2014).
The direct sampling of coastal and marine communities is much harder
than the direct sampling of terrestrial communities. Thus, coastal and
marine research intensively relies on indirect observation methods, such
as tethered video surveys (Biber et al. 2014) or the use of Remotely
Operated Vehicle (ROVs; Lorance & Trenkel 2006) and Autonomous
Underwater Vehicle (AUVs; Eriksen et al. 2001, Yoerger et al. 2007).
Bathymetry and environmental data are often gathered through ship-based
sensors or airborne (Scheritz & Dietrich 2002, Koh & Wich 2012) and
satellite systems (Baldock et al. 2014), which allow for continuous
sampling over large spatial and temporal scales. In situ observations
using unmanned aerial vehicles (UAVs), camera traps (Bailey et
al. 2007, Ahumada et al. 2011) and acoustic sensors (Van Parijs et
al. 2009) provide another indirect sampling method.
These methods have already been applied in a large range of areas of coastal and marine research (Brewington et al. 2014). Environmental variables, such as sea surface temperature (Smit et al. 2013, Baldock et al. 2014), chlorophyll-α (Dierssen 2010, Raitsos et al. 2013), salinity (Lagerloef et al. 1995, 2008) and suspended particulate matter concentration (Evans et al. 2012, Bowers et al. 2014) can be easily obtained from satellite measurements and are frequently used in marine environmental research. Sea floor features and bathymetry have been widely mapped using ship-based depth soundings and satellite altimetry (Smith 1997, Becker et al. 2009). Remote sensing can also be used for shoreline change detection (Chen & Rau 1998, Li et al. 2001), mapping of coastal habitats, such as salt marshes (Ozesmi & Bauer 2002, Belluco et al. 2006), coral reefs (Lirman et al. 2007, Huvenne et al. 2011), as well as seagrass (Pasqualini et al. 2001) and mangrove ecosystems (Giri et al. 2011, Satyanarayana et al. 2011), fisheries management (Stuart et al. 2011), species movements (Lander et al. 2013) and risk assessment (Gillespie et al. 2007, Römer et al. 2012).
Although, coastal communities are more accessible than most of the marine realm and so can be studied much easier than for example the deep-sea, the better accessibility also means that they are more easily threatened by anthropogenic activities. A significant proportion of the global human population lives in close proximity to the coast and so causes the pollution and land degradation of coastal ecosystems. Thus, coastal ecosystems are an important research area, which are frequently studied using direct sampling but also remote sensing.
Rose et al. (2014) identified 10 topics, where using remotely sensed data would help to answer important conservation questions. These topics are: species distributions and abundances, species movements and life stages, ecosystem processes, climate effects, rapid response, protected areas, ecosystem services, conservation effectiveness, agricultural and aquacultural expansions and changes in land use land cover (LULC) and degradation and disturbance regimes. These topics highlight the importance of RS not only for conservation but also for environmental research in general, especially with regard to climate and land-use change.
In the following, trends and patterns in the current literature on remote sensing and coastal ecosystems will be analysed. I will further highlight, which of the 10 topics, identified by Rose et al. (2014), are already intensively studied in coastal ecosystems and where further research is required in the future in order to provide essential information for mitigating future effects of global change.
Materials and Methods
A literature search for peer-reviewed publications, published in English over the period 1990–2018, describing coastal studies using remote sensing was performed. The literature search was undertaken using the commercial search engine Web of Science. Combinations of the following search terms were used: ‘remote sensing’, ‘coast’, ‘marine’, ‘landsat’, ‘MODIS’, ‘Sentinel’, ‘seagrass’, ‘corals’, ‘mangroves’, ‘salt marsh’, ‘salt marshes’, ‘biodiversity’ and ‘conservation’. For a list of the exact search terms and the resulting number of publications see Table S1. The number of publications that overlapped among the different search terms is further depicted in Fig. S1. Only peer-reviewed articles were chosen as they form the main body of literature widely available to researchers. The articles used therefore did not include any university theses, technical governmental reports or conference proceedings.
Results
The search terms resulted in a total of 8803 studies of which 3754 publications (43%) were related to coastal studies and remote sensing. Of the 3754 publications that were analysed, 30 publications did not contain an abstract.
There was an exponential increase in the number of publications from 1990 - 2017, with a particular sharp increase since 2000. Only from 1999 to 2000 and from 2008 to 2010 there was a decrease in the number of publications. 94% of publications have been published since 2000, and 50% within the last 5 years (Fig. 1, Fig. S2). The majority of studies have been published in four journals (Remote Sensing of Environment, Remote Sensing, Journal of Coastal Research, International Journal of Remote Sensing, Fig. S3).
Fig. 1. Number of coastal publications over time, which are related to remote sensing, until 2016. Number of publications is subdivided by the different research themes (biodiversity, climate change, conservation and pollution). Publications where non of the 4 research themes could be identified are highlighted in grey. See Fig. S2 for number of publications until now.
Studies were conducted in 184 different countries. In the majority of countries (85) only a few studies (0-5) have been conducted, while most studies have been conducted in China, India, Mali (> 250 studies per country) and Australia, Brazil, Mexico, United States (100 - 250 studies per country) (Fig. 2).
Fig. 2. (a) Number of studies per country and (b) number of countries with a certain number of studies. 498 studies were conducted in multiple countries.
Coastal publications covered all major research themes. Most studies focused on conservation (288 publications), climate change and pollution were similarly frequently studied themes (211 and 212 publications), while biodiversity was the least studied theme in coastal remote sensing research (149, Fig. 1 & Fig. S3).
Fig. 3. Word cloud of the 100 most frequently used words in
abstracts and titles of the considered coastal literature.
Most studies focused on land-use and land cover change and conservation
effectivness (390 and 288 publications). Species distributions and
abundances and agricultural and aquacultural expansion were also studied
by more than 100 studies. A fair number of studies also studied species
movements and life stages, protected areas and ecosystem services, while
only a marginal number of studies dealt with rapid response, ecosystem
processes and climate effects (Fig. 4).
Fig. 4. Number of publications by research topic.
Mangrove forests were the coastal ecosystem that has been studied most using remote sensing (316 publications), followed by wetlands and coral reefs, which both have more than 200 publications. Salt marshes, intertidal zones and seagrass meadows have also been intensively studied (> 100 publications), while estuaries, kelp forests, mud flats, rocky shores and sandy shores have only been of minor interest (Fig. 5a).
Fishes are by far the most studied taxonomic group (371 publications), followed by birds (144 publications). Invertebrates and mammals were not so frequently studied, while marine reptiles have been hardly studied at all (Fig. 5b).
Fig. 5. Number of studies per coastal ecosystem (a) and taxonomic group (b).
By far, the most number of studies (1240) were conducted using multispectral satellite imagery. Radar data was used in 548 publications, while hyperspectral and lidar data were used the least frequent (144 and 141 publications, Fig. 6a). MODIS, Landsat and Aster data has been used the most, but Envisat, Seawifs, Sentinel and Spot data have also been used frequently (Fig. 6b).
Fig. 6. Number of publications per spectrum (a) and Earth-observation satellite (b).
Discussion
Remote sensing has experienced an increasing use in recent decades (Pettorelli et al. 2014), which corresponds with the exponential increase in studies related to coastal remote sensing (Fig. 1). In recent years, RS has been more widely applied in the marine and coastal realm, but generally lies far behind the terrestrial application of RS. New upcoming satellite missions and open access to data products together with an increasing effort in teaching the analysis of remote sensing data to non-experts is most likely the cause for this. Nevertheless, technological difficulties are still hampering the use of RS, in particular in marine systems.
…
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Supplementary Material
Supplementary Tables
Table S1. Search terms used and the resulting number of publications from the Web of Science Core Collection.
| Search term | Number of publications |
|---|---|
| remote sensing* coast | 1960 |
| remote sensing* marine | 2268 |
| landsat* coast | 516 |
| landsat* marine | 248 |
| MODIS* coast | 535 |
| MODIS* marine | 570 |
| Sentinel* coast | 282 |
| Sentinel* marine | 547 |
| remote sensing* seagrass | 228 |
| remote sensing* corals | 552 |
| remote sensing* mangroves | 472 |
| remote sensing* salt marsh | 203 |
| remote sensing* salt marshes | 203 |
| remote sensing* biodiversity | 1812 |
| remote sensing* conservation | 2658 |
Table S2. Category, value and the keywords used to identifiy the value of each category for each publication. All keywords word searched for in the title and abstract of each publication.
| Category | Value | Keywords |
|---|---|---|
| relevance | terrestrial | land, terrestrial |
| relevance | coastal | coast, estuar, intertidal, shore |
| relevance | marine | marine, deep-sea |
| country | countries | countries |
| theme | biodiversity | biodiversity |
| theme | conservation | conservation |
| theme | climate change | climate change |
| theme | pollution | pollution |
| topic | Species distributions and abundances | distribution & species, abundance & species |
| topic | Species movements and life stages | movement species, life & stage |
| topic | Ecosystem processes | ecosystem process |
| topic | Climate effects | climate effect |
| topic | Rapid response | rapid response |
| topic | Protected areas | protected area |
| topic | Ecosystem services | ecosystem service |
| topic | Conservation effectivness | conservation |
| topic | Agricultural and aquacultural expansion | agriculture, aquaculture |
| topic | Change in LULC and degradation and disturbance regimes | land use, degradation, disturbance |
| ecosystem | Seagrass meadows | sea grass, seagrass |
| ecosystem | Coral reefs | coral |
| ecosystem | Mangroves | mangrove |
| ecosystem | Salt marshes | salt marsh, saltmarsh |
| ecosystem | Rocky shores | rocky shore |
| ecosystem | Sandy shores | sandy shore |
| ecosystem | Mudflats | mud flat, mudflat |
| ecosystem | Estuary | estuary, estuaries, river |
| ecosystem | Intertidal zones | intertidal |
| ecosystem | Kelp forests | kelp |
| taxonomic group | Fishes | fish |
| taxonomic group | Mammals | mammal |
| taxonomic group | Birds | bird |
| taxonomic group | Invertebrates | invertebrate |
| taxonomic group | Reptiles | reptile |
| sensor | multispectral | multispectral, modis, landsat |
| sensor | hyperspectral | hyperspectral |
| sensor | radar | radar, sar |
| sensor | lidar | lidar |
| EO satellite | sentinel | sentinel |
| EO satellite | landsat | landsat-8 |
| EO satellite | MODIS | modis, aqua, terra |
| EO satellite | RapidEye | rapid & eye |
| EO satellite | Envisat | envisat, meris |
| EO satellite | Pleiades | pleiades |
| EO satellite | Spot | spot |
| EO satellite | SeaWifs | seawifs |
| EO satellite | Aquarius | aquarius |
| EO satellite | Grace | grace |
| EO satellite | GOCI | goci |
| EO satellite | Ikonos | ikonos |
| EO satellite | Aster | aster |
| EO satellite | Hyperion | hyperion |
| EO satellite | Aviris | aviris |
Supplementary Figures
Fig. S1. Number of publications that were identified by one or multiple search terms. Only search term combinations that yielded more than 5 publications are shown.
Fig. S2. Number of coastal publications over time, which are related to remote sensing, covering the entire time period (1990 - 2018).
Fig. S3. a) Number of publications by research theme (Pollution, Conservation, Climate Change, Biodiversity) and where multiple themes are covered. 3035 publications did not cover any of the research themes considered. b) Number of publications by climate change thematic.
Fig. S4. Number of coastal publications, which are related to remote sensing, per journal and year. Only journals were more than 5 publications were found are shown.