Landscape should be analyzed in segments for understanding its texture, structure, function and changes. These segments are used to evaluate landscape structure and function analysis. In this context, the most important segments which form the landscape are the landscape patches. Analysis and understanding of the landscape structure and ecological progress needs the measurement of the landscape patches and evaluation .Therefore, the neighborhood ratio between the patches should be known. In this study, we propose an automated method, which is based on Python language, to compute this ratio with consideration of neighborhood degrees between the patches. The test site is Mugla-Koycegiz town from Turkey, where there is a huge amount population of Liquidambar orientalis trees, and the town is important for shoreline tourism. Urban area, water surface, agricultural areas, marsh, and forest classes are defined. Sentinel 2A multispectral satellite image is used and Random Forest classification method is applied. The derived patches are produced from the classification, and then converted to the vector form. Each vector boundaries were converted to the point features with 10 m intervals. The ratio of number of points which is neighbor to the specific class to the all points along the boundary is computed automatically with developed script. Three different patches are analyzed, and the results are reported.

The Anak Krakatau Island and volcano caldera are located at the Sunda Strait between the Java and Sumatra Islands of Indonesia. The volcano started erupting on 22^nd December 2018 and collapse of the volcano resulted in Tsunami, the large tidal waves caused mass destruction and life loss in the Java and Sumatra islands. The objective of this work is the interferometric SAR coherence and backscatter images based analysis of the Anak Krakatau Island using Sentinel-1 SAR data. 7 datasets of ESA’s Sentinel-1 C-band satellite acquired from 25^th November 2018 to 24^th January 2019 were used in this study. The InSAR RGB composite images were generated by stacking together the Interferometric coherence magnitude images and the sigma nought backscatter images. The Sentinel-2 True Colour Composite (TCC) images before and after volcanic eruption were used to verify the results obtained through InSAR coherence analysis. The sigma nought backscatter image of the 22^nd December 2018 clearly indicates the volcano eruption centre and the ocean waves moving away from the Anak Krakatau due to the seismic shock waves caused due to the volcano eruption. The combined interpretation of the results revealed that the severe volcanic eruption on 22^nd December 2018 caused a large portion of the volcano to collapse and all the rock debris which submerged to the ocean displaced the ocean water and resulted in the Tsunami in the Indonesian islands.

Persistent Scatterer SAR interferometry (PsInSAR) has been widely used in the precise measurement of ground deformation due to anthropogenic and natural disturbance of the Earth's surface. The present study has utilized the spaceborne C-band Sentinel-1 data for PsInSAR processing to generate a displacement map due to the volcanic eruption of Pico do Fogo volcano of the Fogo Island. An eruption was recorded in the year 2014-15 and the Fogo volcano became active on November 23, 2014. It was observed that the intensity of volcanic eruption during 2014-15 had approached the intensity of the volcanic eruption of 1951 which was recorded as one of the strongest eruptions on the island. The volcanic eruption continued for 77 days and it stopped on February 8, 2015. To find the mean line of sight displacement from PsInSAR processing, a total of 7 SLC products of Sentinel-1 data in the interferometric mode was used. The SLC product of the SAR data which was acquired before starting the volcanic eruption was chosen as the master image and all the remaining 6 slave images were precisely coregistered. Selection of persistent scatterers (PS) is the most important step in PsInSAR processing. The initial set of PS was identified by amplitude stability index and the phase analysis was performed to estimate the phase stability of each resolution cell. After PS identification, 3D phase unwrapping was performed. The unwrapping step involved the low-pass filtering of the complex phase difference and time series in the frequency domain using a Gaussian window. The phase difference between each filtered data point is then calculated. The unwrapped phase of the interferogram was used to generate a displacement map for the volcanic field. The PsInSAR based line of sight displacement was measured in the range of -34 mm to +35 mm and the standard deviation of the displacement was ranging from +2 mm to +30 mm.

The most frequent disasters in Saudi Arabia are flash floods, earthquakes, volcanism, especially submarine volcanism causing tsunamis in the Red Sea and submarine mass movements, dust storms and droughts. As the consequences and effects of the climate change will have an increasing impact on the intensity and occurrence of geohazards as flash floods, length of drought periods, or dust storms, the surveillance and systematic, continuous monitoring of these hazards and affected areas using satellite data and integration of the results into a GIS data base is an important issue for hazard preparedness. Over the last 30 years (1981–2011), floods have been the most recurrent disasters recorded in EM-DAT, with at least 300 events, indicating a strong need for early warning systems. The increase of the built environment and the enlargement of urban areas has lead to a great impact on the landscape in Western Saudi Arabia.

Visual interpretation and digital image processing of different satellite images, including radar images, combined with ASTER, SRTM (30 m resolution), and ALOS PALSAR DEM data (12 m) are used for the mapping and inventory of traces of past hazards. Causal or critical environmental factors influencing the disposition to be affected by hazards and the potential damage intensity are analyzed interactively, then, in a GIS database. The interactions and dependencies between different causal and preparatory factors can be visualized and weighted step by step in the GIS environment. Examples are presented how remote sensing and GIS methods contribute to the detection of the following geohazards in Western Saudi Arabia:

• Detection of areas prone to hydrological hazards such as flash floods causing flooding of roads and settlements
• Mapping of dust storms
• Mapping of coastal areas of the Red Sea prone to tsunami flooding and storm surge.
• Mapping of traces of volcanic activity
• Mapping of fault and fracture zones and structural features
• Mapping of local site conditions influencing earthquake shock in case of stronger earthquakes and of areas susceptible to earthquake related secondary effects such as compaction or rock fall.

Mapping of soil properties, especially electrical resistivity measurements that provide integrative information of the physical and chemical properties at different depths, is a key issue in precision farming. Effective management of agricultural fields by delineating areas with comparable status passes through a description of the soil variability at the intra-field spatial scale. In this context, the on-going Sentinel-2 satellite mission provides regular surface observations at a decametric resolution, useful for the monitoring of sub-surface parameters. The aim of this study is thus to assess the possibilities of the VNIR (Visible and Near InfraRed) and SWIR (Short Wavelength InfraRed) satellite data for retrieving intra-plot patterns consistent with soil resistivity measurements. Over a study site located in southwestern France, intra-field soil resistivity measurements were collected at three depths (representing the following soil layers: 0-50, 0-100 and 0-170), by a towed automatic resistivity profiler and equipped with GPS system, together with Sentinel-2 satellite images. The methodology aims at: (i) estimating the electrical resistivity at different depths using a statistical algorithm (optical reflectances constituting the input variables of random forest, alone or in combination with parameters derived from a digital elevation model), and (ii) analyzing the contribution of input variables on the targeted electrical resistivity. The preliminary results only based on optical reflectances and obtained on one monitored field show interesting level of accuracy for the 0-50 and 0-100 layers (with R² of 0.69 and 0.59, and a relative RMSE of 18% and 16% respectively), the performances being lower for the 0-150 layer (R² of 0.39, relative RMSE of 20%). The combined used of optical reflectances with parameters derived from the digital elevation model slightly improves the performances whatever the considered layer (R² of 0.74, 0.64 and 0.47 for the 0-50, 0-100 and 0-150 layers, respectively).

The objective of this study is to address the capabilities of multi-temporal optical images to estimate the fine-scale yields variability of wheat (at a spatial scale of 30 meters). Time series of images were collected over a study site located in southwestern France throughout four successive agricultural seasons, together with intra-field yields measured by a surveying harvesting machine equipped with dGPS system on track mode. The methodology is based on the Landsat-8 and Sentinel-2 satellite images acquired after the sowing and before the harvest of the crop, the reflectance constituting the input variables of a statistical algorithm (random forest). The large dataset allows independent training and validating steps on more than one thousands of measurements, useful for testing the robustness of the proposed approaches.

The best performances are obtained when the NDVI is combined with the previous yield maps, regardless the considered agricultural season. In such case, the agricultural season 2014 shows the lower level of performances with a R² of 0.44 and a RMSE of 8.13 q.h^-1 (corresponding to a relative error of 12.9%), the three other years being associated with values of R² close or upper to 0.60 and RMSE lower than 7 q.h^-1 (corresponding to a relative error inferior to 11.3%). Such level of error on yield estimates appears acceptable, values of RMSE being lower than the observed variability, whatever the considered year (mean standard deviation of 11.8, 9.8, 10.0 and 8.9 q.h^-1 for the yields collected in 2014, 2015, 2016 and 2017, respectively).

Landslide is one of the most devastating natural hazards in the Uttarakhand Himalaya, India. Though it has many active and old hotspots, we have focused on Nainital district only in this study considering recent events and challenges. Although available literature exhibits many such case studies from this area, landslip and landslide events which took place, off late, remains to be one of the major burning issue in this area, albeit. Out of many landslide hazard zonation methods, it is felt appropriate to apply Analytical Hierarchy Process (AHP) in this area which takes cues mainly from measurements through pair wise comparisons of causative factors and relies on the judgement of the experts to derive priority scales to enable stake holders adopting a multi criteria decision making approach. Many thematic layers were, hence, considered for this purpose which includes slope, aspect, hillshade, land use and land cover (LULC), normalised difference vegetation index (NDVI), lineament, geomorphology, geology etc. These raster inputs were derived mainly from high resolution multispectral, open source DEM and other ancillary data sets. Landslide hazard zonation map, thus produced, were successfully validated on the ground. This kind of map for the whole district holds promise for the stake holders to assess potential high hazard zones and plan to provide remedial measures and thereby supporting mitigation mechanism in case of any future potential hazard. However, considering that present day research in the field of landslides has evolved beyond hazard zonation map, it was decided to develop debris flow models at few critical but strategically important sites by numerical simulation technique. This debris flow models are mainly to be fed space-borne and ground based geological and geotechnical inputs. The simulated result provides spatial variation of different geophysical parameters like pressure, momentum, height and velocity in the affected run-out zone. These outputs provide crucial information on real time landslide hazard mitigation and support to the development of early warning systems.

Geology is, from its foundation, a subject study strongly based on field studies.
Nonetheless, offsite studies can frequently play a relevant role in surveying large areas and in preliminary assessments of specific sites, and they could give important contributions to the planning of onsite works.
In this communication are considered diverse online tools, including topographic and geological maps, satellite images and onsite images (Google Street View), which are freely available and can be integrated into a GIS environment (QGIS was used in the present work).
The potential and limitations of these tools will be discussed in the context of subjects relates to Environmental and Engineering Geology, being the discussion supported by some case studies related to examples of these issues, based on observations of terrains (including observations of built structures). Diverse perspectives will be considered, such as restraints to structures development, hazard assessment and hydrological studies, as well as the potential of sites for the teaching of concepts related to these subjects.

Talala, is an excellent place for example of triggered neo-tectonic seismicity between two Dams during monsoon. An earthquake of M_max5.1 on November 06, 2007 at 21.16⁰N; 70.54⁰E, with focal depth 4.5 km and complete sequence first time recoded on latest broadband sensor. This found a Dam/Monsoon induced earthquake preceded by 18 foreshocks of 2≤M_w≤4.8 within 9hr 11 minute and smaller shocks may not recorded because of sparse network coverage. After deploy of local mobile observatories aftershocks of M_w≥1.0 were recorded which continued for months and subsided to background seismicity during four months. The same kind of phenomena repeat with M_max5.0 on October 20, 2011 at 21.06⁰N; 70.50⁰E, focal depth 5.5 km, implies that the potential to generate Dam/Monsoon induced seismicity took nearly 4 years again. This phenomena continue and the sequence recorded by network of 10 broadband seismographs (3 in the Talala area and 7 at epicentral distance 30 to 300 km).

Centroid Moment Tensor (CMT) solutions and spectral source parameters of mainshock and aftershocks are evaluated to understand seismotectonic of the region. The CMT depicts major Strike-slip motion along ENE-WSW with left-lateral plane at 4.5 km depth. This indicates sympathetic fault to extension of Son-Narmada fault. The source parameters of 400 shocks of M_w 1.0 to 5.1, found seismic moment 10¹¹ to 10^16.5 N-m, source radii 120-850 meter and stress drop of 0.003 to 25.43 Mpa. The b-value, p-value, fractal dimension and slip on different faults estimated

The comparison between Talala and Koyna, Dam induced source parameters try to established in comparison to seismicity from different parts of the world

The relationship between injected wastewater produced during oil exploitation and triggered seismicity in Val d'Agri (Southern Italy) is investigated by using the Schuster’s spectrum of the seismicity and the singular spectrum analysis (SSA) of the volume and pressure time series of the wastewater. Our results suggest that most of the cycles found by using the Schuster’s spectrum of the earthquakes have periods very close to those identified in the SSA components of the volume and pressure of the injected wastewater. This could indicate that volume and pressure of the injected wastewater could be able to induce oscillatory variations in the seismic rate, and thus, to trigger earthquakes.