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This year it is nice to once again be writing the September message having just returned from the annual IEEE Geoscience and Remote Sensing Society (GRSS) flagship conference, the IEEE International Geoscience and Remote Sensing Symposium (IGARSS). IGARSS was held in Kuala Lumpur, Malaysia, at the Kuala Lumpur Conference Center, where we enjoyed a week of technical sessions held both in person and online as well as a full agenda of GRSS social events, the Student Paper Competition (SPC), the Three Minute Thesis (3MT) competition, and a map design contest organized by the IGARSS Local Organizing Committee.

A scatterometer, as an active microwave radar sensor, measures the return of radar waves in the form of a backscatter coefficient after reflection or scattering from Earth’s surface. The primary objective of the scatterometer is to record the surface-wind vector observations over the ocean for the study of the climate, monitoring, the forecasting of cyclones/hurricanes, and air–sea interactions. Since its first launch in 1978, many technical improvements have been made to the scatterometer due to its potential for all-weather global-level monitoring. The scatterometer has found many emerging applications in different scientific domains, such as cryosphere, hydrology, agriculture, and climate studies, with the continuous development of methods and models.

Fresh water is considered to be one of the most precious natural resources in many countries. Given that soil moisture plays a salient role in vegetation growth, the continuous and timely measurement of soil moisture content is critical to manage water shortages, especially in the agriculture sector <xref ref-type="bibr" rid="ref1">[1]</xref>, <xref ref-type="bibr" rid="ref2">[2]</xref>, which is the largest water use sector in Australia. A 10&#x0025; water savings in the Australian agriculture sector would be equivalent to a reduction of more than 30&#x0025; of the combined water consumption from Australian capital cities <xref ref-type="bibr" rid="ref3">[3]</xref>. Further, soil moisture influences the process of rainfall being partitioned into runoff and infiltration, and saturated soil could turn heavy rain into floods. Therefore, soil moisture information is essential for accurate climate forecasting as well as improving flood and drought prediction <xref ref-type="bibr" rid="ref3">[3]</xref>&#x2013;<xref ref-type="bibr" rid="ref4"/><xref ref-type="bibr" rid="ref5">[5]</xref>.

This article provides a comprehensive overview of the current state of the art in contactless ground-penetrating radar (GPR) systems. These devices offer many large-scale subsurface sensing possibilities based on different observation platforms and measurement configurations. On the other hand, new challenges must be faced because the radar system is not coupled directly to the ground; hence, data processing plays a crucial role to achieve reliable imaging results. In this respect, microwave tomography (MWT) turns out to be a very flexible tool to address the aforementioned challenges. This methodology allows modeling, in a relatively simple way, of the radar signal propagation in an inhomogeneous medium as well as the handling of arbitrary measurement modalities and radar configurations. Experimental examples regarding different types of contactless GPR are presented to validate the effectiveness of MWT when combined with ad hoc signal filtering procedures.

Aerial tracking, which has exhibited its omnipresent dedication and splendid performance, is one of the most active applications in the remote sensing field. Especially, unmanned aerial vehicle (UAV)-based remote sensing system, equipped with a visual tracking approach, has been widely used in aviation, navigation, agriculture,transportation, and public security, etc. As is mentioned above, the UAV-based aerial tracking platform has been gradually developed from research to practical application stage, reaching one of the main aerial remote sensing technologies in the future. However, due to the real-world onerous situations, e.g., harsh external challenges, the vibration of the UAV mechanical structure (especially under strong wind conditions), the maneuvering flight in complex environment, and the limited computation resources onboard, accuracy, robustness, and high efficiency are all crucial for the onboard tracking methods. Recently, the discriminative correlation filter (DCF)-based trackers have stood out for their high computational efficiency and appealing robustness on a single CPU, and have flourished in the UAV visual tracking community. In this work, the basic framework of the DCF-based trackers is firstly generalized, based on which, 23 state-of-the-art DCF-based trackers are orderly summarized according to their innovations for solving various issues. Besides, exhaustive and quantitative experiments have been extended on various prevailing UAV tracking benchmarks, i.e., UAV123, UAV123@10fps, UAV20L, UAVDT, DTB70, and VisDrone2019-SOT, which contain 371,903 frames in total. The experiments show the performance, verify the feasibility, and demonstrate the current challenges of DCF-based trackers onboard UAV tracking.