Landslides (LS) represent geomorphological processes that can induce changes over time in the physical, hydrogeological, and mechanical properties of the involved materials. For geohazard assessment, the variations of these properties might be detected by a wide range of non-intrusive techniques, which can sometimes be confusing due to their significant variation in accuracy, suitability, coverage area, logistics, timescale, cost, and integration potential; this paper reviews common geophysical methods (GM) categorized as Emitted Seismic and Ambient Noise based and proposes an integrated approach between them for improving landslide studies; this level of integration (among themselves) is an important step ahead of integrating geophysical data with remote sensing data. The aforementioned GMs help to construct a framework based on physical properties that may be linked with site characterization (e.g., a landslide and its subsurface channel geometry, recharge pathways, rock fragments, mass flow rate, etc.) and dynamics (e.g., quantification of the rheology, saturation, fracture process, toe erosion, mass flow rate, deformation marks and spatiotemporally dependent geogenic pore-water pressure feedback through a joint analysis of geophysical time series, displacement and hydrometeorological measurements from the ground, air and space). A review of the use of unmanned aerial vehicles (UAV) based photogrammetry for the investigation of landslides was also conducted to highlight the latest advancement and discuss the synergy between UAV and geophysical in four possible broader areas: (i) survey planning, (ii) LS investigation, (iii) LS dynamics and (iv) presentation of results in GIS environment. Additionally, endogenous source mechanisms lead to the appearance of deformation marks on the surface and provide ground for the integrated use of UAV and geophysical monitoring for landslide early warning systems. Further development in this area requires UAVs to adopt more multispectral and other advanced sensors where their data are integrated with the geophysical one as well as the climatic data to enable Artificial Intelligent based prediction of LS.

The use of geophysical characterization of karst systems can provide an economical and non-invasive alternative for extracting information about cavities, sinkholes, pathways for water infiltration as well as the degree of karstification of underlying carbonate rocks. In the present study, three geophysical techniques, namely, Ground Penetrating Radar (GPR), Electrical Resistivity Tomography (ERT) and Very Low Frequency Electromagnetic (VLFEM) methods were applied at three different locations in relation to fluvial karst, which is listed as an environmentally sensitive area in Rio Vermelho, Mambaí, Goiás, Brazil. In the data acquisition phase, the GPR, direct-current (DC) resistivity and VLFEM profiles were obtained at the three locations in the area. Data were analyzed using commonly adopted processing workflows. The GPR results showed a well-defined lithology of the site based on the amplitude of the signal and radar typologies. On the other hand, the inverted resistivity cross-sections showed a three-layered stratigraphy, pathways of water infiltration and the weathered structures in carbonate (Bambui group). The interpretation of VLFEM as contours of current density resulted from Fraser and Karous–Hjelt filters, indicated the presence of conductive structures (high apparent current density) that might be linked to the weathered carbonate and other conductive and resistive anomalies associated with the water-filled and dry cavities (cave), respectively. The results encourage the integrated application of geophysical techniques such as the reconnaissance for further detailed characterization of the karst areas.

The new IMERG and GSMaP-v6 satellite rainfall estimation (SRE) products from the Global Precipitation Monitoring (GPM) mission have been available since January 2015. With a finer grid box of 0.1°, these products should provide more detailed information than their latest widely-adapted (relatively coarser spatial scale, 0.25°) counterpart. Integrated Multi-satellitE Retrievals for GPM (IMERG) and Global Satellite Mapping of Precipitation version 6 (GSMaP-v6) assessment is done by comparing their rainfall estimations with 247 rainfall gauges from 2014 to 2016 in Bolivia. The comparisons were done on annual, monthly and daily temporal scales over the three main national watersheds (Amazon, La Plata and TDPS), for both wet and dry seasons to assess the seasonal variability and according to different slope classes to assess the topographic influence on SREs. To observe the potential enhancement in rainfall estimates brought by these two recently released products, the widely-used TRMM Multi-satellite Precipitation Analysis (TMPA) product is also considered in the analysis. The performances of all the products increase during the wet season. Slightly less accurate than TMPA, IMERG can almost achieve its main objective, which is to ensure TMPA rainfall measurements, while enhancing the discretization of rainy and non-rainy days. It also provides the most accurate estimates among all products over the Altiplano arid region. GSMaP-v6 is the least accurate product over the region and tends to underestimate rainfall over the Amazon and La Plata regions. Over the Amazon and La Plata region, SRE potentiality is related to topographic features with the highest bias observed over high slope regions. Over the TDPS watershed, the high rainfall spatial variability with marked wet and arid regions is the main factor influencing SREs.