1 Introduction

Soil moisture is an important factor in the natural ecology that provides physiological state to the plant and microorganism growth and development as well as for plant rooting (Noguchi et al. 2016). Variation in soil moisture content impacted the hydrological mechanism such as evapotranspiration, transport of water and soil solutes (Yamashita et al. 2003). Not only does soil moisture play an important role in watering plants (Sawatsky and Li, 1997), to water (Rawls et al., 2003) plant (Li et al., 2011) but it also plays an important part in agriculture (Jensen, 1982). The availability of detailed data on soil moisture is also critical for classifying habitat in relation to water gradient because plants have different relationships with water that are also associated with topographical variation in water availability (Marryanna et al., 2012). Soil moisture studies are important for irrigation management practices in parched and semi-parched land (Subbaiah, 2013; Bell et al., 2020) as well as to improve crop productivity (Bodner, Nakhforoosh, and Kaul, 2015; Medrano et al., 2015).

Remote sensing performed spatial scale (Cheema, 2011), which was used to collect surface hydrology and vegetation information (Chen et al., 2005). Soil moisture spatio-temporal volatility can be studied by retrieving spatio-temporal continuous soil moisture and other various data from remote sensing images (Zhang et al., 2020). Medium-resolution spectrometers and microwave radiometer satellites for soil water and seawater salinity were part of the remote sensing data image products that are widely used in soil moisture research (Petropoulos, Ireland, and Barrett, 2015; Karthikeyan et al., 2017; Reichle, 2008).

Bibliometrics or systematic analysis is a tool that provides network mapping and trends in the state of the art for a given specified fields related to scientific knowledge (Wang, 2015). This analysis can identify, interpret and classify the performance of the publications by author, keyword, country, year and others that quantitatively highlight research niche and trends (Zhang et al., 2020). Various articles with different scopes for soil moisture using remote sensing research (Cui et al., 2019; McColl et al., 2017) but only few bibliometric review that can reflect the trend has been conducted.

To understand the direction and gaps in soil moisture assessment using remote sensing as a tool in research, bibliometric analysis is conducted to find the pattern and trend from 2000 until 2020 with various perspectives to expose the variance and contemporary research method in the global trend. This study is conducted by clarifying the correlation between annual publications, keywords, source country, institutions and journals. Innovative approach was implemented, such as collaborative network analysis and keyword mapping to reveal the trend and pattern from multiple perspectives. Further studies should be conducted in the future to reduce the knowledge gap in this subject by using remote sensing in research methods that are available in global research networks and trends.

2 Material and Methods

2.1 Data Collection

Data exploitation of this research is searched and compiled from SCOPUS database over 10 years recent from 2000 to 2020. The search data keywords used are “soil moisture” AND “remote sensing” with extended search to document titles, abstracts and keywords of the entire SCOPUS database. The search queries the keywords in 2000 until 2020. The publications that matched the search keywords were 6417 articles, which were then collected for further study and analysis.

2.2 Data Analysis

Bibliometric analysis was performed to expose trends, network mapping and patterns in the soil moisture using remote sensing study research by multiple features such as annual publications, keywords, source country, institutions and journals. From the SCOPUS dataset provided from the search query, the individual data and details were downloaded in Microsoft Excel for data processing. Data network mapping was visualised using software VOSviewer (Wolfe et al., 2002). The software creates co-occurrence and frequency network from the data downloaded and presents the network mapping of each feature. The node represents the degree of centrality, while the thickness of the line represents the intensity of collaboration. The larger the nodes, the more crucial it is, while the thicker the line of the network, the stronger the relation.

3 Results and Discussion

3.1 Development of Research Activity by Quantitative Method by Article Outputs

Figure 1 shows the distribution lines of the annual number of articles and citation per article from 2000 to 2020. MODIS or shorted form of the Moderate Resolution Imaging Spectroradiometer was launched on December 1999 (Wolfe et al., 2002). MODIS is a remote sensing algorithm that derives time series globally on multiple geophysical parameters (Vermote et al., 2002). This research focusing on articles that published after MODIS was launched starting from the year 2000. The numbers of citations per article are increasing and reach its peak value (47.71) in the year 2002 and then went down and keep dropping until year 2020. This is because citation rates are highly influenced by the discipline and the number of people employed in that field. For the numbers of articles, the published article keeps increasing gradually until recent year. After rapid evolution, internet became easier to access online publication that increases the number of articles. Meanwhile, it can lead to lower citations per article where researchers have large number of publications but shorter publication time.

Fig. 1
figure 1

The annual number of articles and citations per article from 2000 to 2020

Full size image

From the total acquired 6417 articles related to soil moisture and remote sensing research, the data were sorted by annual total publications from the years 2000 until 2020. Table 1 shows the total number of articles published by year, total citations and number of citations per article. The number of articles shows a significant increase from 134 in 2000 to 185 in 2007 which represent the launching of MODIS specifically in soil moisture research. MODIS remote sensing images are generally used to evaluate ecology system and have been engaged as susceptibility model of environment (Leuven & Poudevigne, 2002; Maina et al., 2008) and build resilience indices and work structure (Ares & Bertiller, 2001; Forbes et al., 2009). In the matter of disaster readiness, remote sensing has the capability to equip essential reinforcement and monitoring during disaster and post-disaster rebuilding (Forbes et al., 2009). As a result of the fast growth of the internet, where publications and articles are simpler to access internationally, the total number of articles increased to 318 in 2008, more than double from 2007. As summary, the table illustrates the pattern of rising, except for total citations illustrating the expanding inflation of scientific knowledge in soil moisture using remote sensing research study in the past two decades.

Table 1 Article output in soil moisture using remote sensing research from 2000 to 2020
Full size table

3.2 Analysis of Journals and Institutions

The root of the journal with high acknowledgement can be identified based on the statistical study of the distribution of journals that publish articles in the soil moisture using remote sensing research field (Hengl et al., 2009). Table 2 shows the top 20 productive journals that publish articles in this research field along with the total number of citations and number of citations per article. International Geoscience and Remote Sensing Symposium (IGARSS) published the most articles (895) in the last two decades reckoning 25.8% of the total. Remote Sensing of Environment ranked first in terms of total citations with 19,227 accounting 25.01% compared to other journals. This figure indicates that remote sensing topic attracted a wide discussion especially in environment element on the monitoring approach with a modest amount of outputs. The International Society for Optical Engineering also ranked high as they published 289 articles (8.32%) and ranked third in terms of articles publications and second for total citations is IEEE Transactions on Geoscience and Remote Sensing journal which accounting for 309 articles published (8.89%) and 15,063 citations (19.60%) respectively.

Table 2 The top 20 productive journals in remote sensing soil moisture research from 2000 to 2020
Full size table

Table 3 shows the top 20 productive institutions in the soil moisture study using remote sensing tools for research for the last two decades. The top institutions scattered across the USA and China and added with institutions from Austria, Belgium, Australia, France, the UK and Italy. In terms of the number of publications, US Department of Agriculture in the USA and the Chinese Academy of Sciences were relatively higher than other institutions with 297 articles (17.61%) and 213 articles (12.63%) respectively. Meanwhile, NASA Goddard Space Flight Centre recorded high number of citations (7031) followed by US Department of Agriculture (6600) and California Institute of Technology (6080). However, in terms of citation number per article, these three institutions drop to rank number 8th, 12th and 10th, respectively. This is due to high low number of published articles in those countries. The leading institutions for number of citations per article are European Centre for Medium-Range Weather Forecasts in the UK which is accounting for 81.28. Next to them is Vienna University of Technology in Austria (66.49) and IEEE in the USA (64.51).

Table 3 The top 20 productive institutions in remote sensing soil moisture research from 2000 to 2020
Full size table

3.3 Analysis of Productive Countries

Table 4 summarises the top 20 productive countries that contributed to soil moisture using remote sensing research with total number of articles and citations for independent and collaborative published articles. The USA and China lead the development of the study by publishing generous number of articles which are 3391 and 2786, respectively. Nonetheless, China still ranked one of the lowest number citations per article (8.60) as the total citations only 23,968 compared to the USA due to short publication time. One explanation for the low impact factor is that Chinese scientists prefer to publish papers with few references. Another explanation is that, like scientists in other countries, Chinese scientists tend to publish their best work in big or top English-language journals. Austria contributed a high number of citations per article (40.35) and ranked first because of the lower number of publications but high number of citations. Meanwhile, Spain, Germany, Australia, the Netherlands, Canada, Belgium and Brazil where the average of citations per article is above 20 had performed the fundamental roles in soil moisture using remote sensing research study. The USA and China also had contributed significantly in collaborating research with other countries. In addition, the ratio of international collaboration is higher than independent articles for all 20 countries. This indicates that the international cooperation gave the influence of research outputs in the soil moisture using remote sensing. It is remarkable that the publications of the articles were notably correlated with country economy development. All the G7 countries, the USA, France, Italy, Germany, Canada, the UK and Japan, were in the top 20 countries accounting a total of 51.63% articles in the last two decades.

Table 4 The top 20 productive countries in remote sensing soil moisture research from 2000 to 2020
Full size table

Figure 2 shows the cooperation network of the top 20 productive countries in soil moisture using remote sensing research fields. The bigger node had the most collaborative network with more countries, and the degree of centrality is also an outstanding. The USA is the centre of the global network followed by China and France. The USA had associated mostly with China, France, Spain and the Netherlands based on the thickness of the network line of the countries. Thick line network signified the large number of collaborative articles globally. South Korea and the Russian Federation showed thin lines of collaborative network as they published more independent articles that collaborate with other countries. Among the top 20 countries, Israel and Taiwan not have published any internationally cooperation with other top 20 countries. Major countries such as the USA, France and others were also expanded their collaboration network outwards. From the visualisation network and analysis, it can be proved that countries with advanced technology of science manage the direction of soil moisture using remote sensing research fields. In addition, global collaboration also can contribute to advancement of the study.

Fig. 2
figure 2

Core international collaboration network map of the top 20 productive countries

Full size image

3.4 Analysis of Keywords

Researchers used lists of keywords to obtain expressive terms of particular genres (Tang et al., 2020). For a specific scientific field study, keyword plays a large role as it can reflect the root contents of articles and compilation of keywords can reveal the pattern and trends of specific academic research (Wang et al., 2012). In the study of soil moisture using remote sensing, noticeably there was a gap of keywords that are missing in the early MODIS launched between the years 2000 and 2005. Keywords that are related to plant growth mechanism such as “evapotranspiration” and agricultural production such as “agriculture” and “drought” as shown in Table 5 are missing in the early stages. After MODIS was launched in December 1999, the frequencies of keywords were the combination of soil moisture and remote sensing research. With the rapid development of remote sensing and computer technology in recent years, the research of soil moisture and other soil properties has become significantly matured and shown noteworthy increase frequency of keywords since 2006.

Table 5 The top 20 high-frequency keywords from 2000 to 2020
Full size table

Alongside the search terms, “climate change” is one of the greatest global concerns that captivated worldwide attention which was ranked 9th in 2011 and recent indicated that soil moisture is a vital role in forecasting climate change. Research had been done and it is proved that soil moisture can be a limiting factor for land carbon uptake where, through the water stress, it could decrease the gross primary production and worsen climate extremes (Green et al., 2019). Mainly, the study of soil moisture in climate change topic consists of the effect of climate change on soil moisture and soil moisture erosion (Guo et al., 2019; Haile, Tang, Li, Liu, & Zhang, 2020) applying the soil moisture as one of the essential variables that plays a major role in predicting the climate change models (Berg & Sheffield, 2018).

Figure 3 is a visualised network of keywords that had a frequency more than 50 and more using VOSviewer software from the recent years of 2011 until 2020. The network is divided into four clusters and illustrated by different colours. For the biggest cluster which is displayed in red colour, keywords “water content”, “drought”, “evapotranspiration” and other keywords that were related to “soil moisture” were included. This searched cluster indicated the relationship between soil moisture and agricultural production and growth mechanisms. It is essential to focus on the soil moisture in monitoring drought predicting, early warning and others as soil moisture drought can give huge influences the irrigation agriculture and long period of draught can be a threat to food security (Haile et al., 2020). In the smallest cluster in yellow colour, keywords related to soil–vegetation–atmosphere system such as “vegetation” and “atmospheric temperature” were included. This cluster is highly related to climate change as there are differences in responses of soil moisture to climate change in various parts worldwide, and the projection of soil moisture remained uncertainties (Berg & Sheffield, 2018). Therefore, further research needs to be done to enhance the prediction and forecast models of climate change and drought by understanding and investigating among the element of soil–vegetation–atmosphere mechanism.

Fig. 3
figure 3

The co-occurrence network map of keywords from 2011 to 2020

Full size image

“Satellite data,” “radiometer” and “calibration” alongside with other keywords were included in green cluster as it was related to the MODIS remote sensing tools. Almost related to blue cluster, both of these cluster describing the research approach of soil moisture based on remote sensing technology. This method used to improve and upgrade the accuracy of soil moisture measurement and monitoring as remote sensing technology is establishing multi-index or multivariate soil moisture inversion models by using multiple satellite datasets (Zhang et al., 2020). Soil moisture data in deep soil layers can be obtained by developing method by using satellite data thus can be a great approach on drought monitoring in large spatial scale (Haile et al., 2020).

4 Conclusions

In this study, bibliometric review was portrayed to analyse and reveal the trends and patterns in soil moisture using remote sensing research fields. MODIS is one of the remote sensing satellites launched that benefitted soil moisture study. This study collected reliable SCOPUS database from 2000 until 2020 with data interpreted software VOSviewer. The exported and analysed data shows that annually, the number of articles gradually increases steadily proving that soil moisture using remote sensing had wide study prospects. Global cooperation specifically between developed countries such as the USA, France and other countries is noticeably an essential incentive to the further study in soil moisture using remote sensing. This can be seen from the published articles, and citations per article of international cooperation had higher frequency than independent published articles. As for developing countries, more high impact articles and outputs are needed to be produced in the future. Many developed countries’ universities lack the framework of ethical oversight boards. Colleagues from both developing and developed countries could work together on requests for support from agencies. Researchers from developing countries will be able to access the existing ethical review processes at universities in developed countries as a result of this collaboration. In terms of soil moisture, the study is mostly related to agriculture production and life such as environmental, agriculture and ecology. The soil moisture data are also important as it can be applied for drought and climate change prediction models. With the aid of remote sensing technology, the ease of access of internet, advanced satellite data and high-quality references from the previous studies by other researchers, the accuracy of the models can be improved remarkably. Hence, global warming issue that concerned worldwide could be reducing with high precision models.