The SCATSAT-1 (Scatterometer Satellite) was launched by ISRO (Indian Space Research Organisation) on September 26, 2016 from the Satish Dhawan Space Centre, Sriharikota, India. With nearly five years of its journey, the Ku-band (13.5 GHz) based SCATSAT-1 made a profound impact on many scientific domains such as ocean-atmosphere dynamics, soil moisture and vegetation dynamics, climate change, hydrology and polar sea-ice and snowmelt studies. As a successor of the Oceansat-2 Scatterometer (OSCAT), the SCATSAT-1 supports the long-term analysis in climate studies, crop yield prediction, and forecasting analysis. In addition, the SCATSAT-1 provides the four different levels of data products at an enhanced resolution to improve the scope of the scatterometer in different applications. Recently the SCATSAT-1 has been explored in many emerging applications apart from oceanography e.g., crop growth, snow cover analysis, jute crop detection and river level estimation with advanced algorithms i.e., machine learning-based classification, information fusion, and super-resolution mapping. Therefore, it is desired to summarise all operational SCATSAT-1 products, applications, and their emerging trends at the global level in the various scientific domains. This paper has summarized the progress made by SCATSAT-1 in different scientific domains since its launch. A meta-analysis has also been conducted in this paper (using the SCOPUS database) to analyse the current research status of SCATSAT-1 in terms of study area targets. This study highlights the features, challenges, and future directions for the scatterometer improvements.

Forest fires are frequent in the Siberian taiga and are predicted to increase in frequency as a result of increased fire risk under drought conditions, and prolonged fire seasons caused by climate change. There is, however, some uncertainty as to the extent to which drought influences forest fire frequency at a regional scale. Here, we present an analysis of satellite derived soil moisture anomaly data from ERS-1/2 (ERS: Earth Resources Satellite) scatterometer data and burned area maps from MODIS/AVHRR/ATSR (Moderate Resolution Imaging Spectroradiometer/Advanced Very High Resolution Radiometer/Along-Track Scanning Radiometer) over Central Siberia for the years 1992-2000. The purpose of this study is to investigate the relationship of remotely sensed soil moisture deviations from the long-term mean and fire within the boreal biome on a sub-continental scale. Results show that wet surface soil moisture conditions limit the extent of burned area. They can prevent the outbreak of fires but the magnitude of a negative (dry) deviation does not determine the maximum size of fire affected areas. It is known from the literature, however, that an ignition is more likely to occur under low surface wetness conditions, such as those that we observed during July and August in both permafrost and non-permafrost regions. Although the burned area under drier conditions in July is lowest over non-permafrost, the actual number of fires is as high as over continuous permafrost. Approximately 80% of all events occurred under such conditions during that month. The fire size was below 50 km(2) under moist conditions. Larger burned areas have in general not been detected when the surface wetness deviation exceeded +5%.