Calò F. | Notti D. | Galve J.P. | Abdikan S. | Görüm T. | Orhan O. | Makineci H.B.

Conference Object | 2018 | International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives42 ( 3W4 ) , pp.129 - 135

Groundwater depletion caused by rapid population growth, global climate change, water resources overexploitation is a major concern in many regions of the world. Consequences are not limited to a non-renewable water loss but extend to environmental degradation and geo-hazards risk increase. In areas where excessive groundwater withdrawal occurs, land subsidence induced by aquifer compaction is observed, resulting in severe socio-economic damage for the affected communities. In this work, we apply a multi-source data approach to investigate the fragile environment of Konya plain, central Turkey. The area, which is under strong anthro . . .pogenic pressures and faces with serious water-related problems, is widely affected by land subsidence. In order to analyze the spatial and temporal pattern of the subsidence process we use the Small BAseline Subset DInSAR technique to process two datasets of ENVISAT SAR images spanning the 2002-2010 period and to produce ground deformation maps and associated time-series. Results, complemented with meteorological, stratigraphic and piezometric data as well as with land-cover information, allow us to obtain a comprehensive picture of the climatic, hydrogeological and human dynamics of the study area. © Authors 2018. CC BY 4.0 License Daha fazlası Daha az

Gurbuz G. | Jin S.

Conference Object | 2018 | International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives42 ( 3W4 ) , pp.239 - 243

Turkey is located in Africa-Eurasia-Saudi Arabian plate converged areas with surrounding by the Black Sea and the Mediterranean Sea. Apart from its tectonic conditions, the climate is complexly varying according to regions. As an example while in the northern regions floods often endanger human life, and in the middle regions, drought is a serious situation. To understand the Earth system and its temporal changes, a reliable measurement of various geophysical processes and mass redistribution is needed, which are mostly related to the regional water cycle and coupling processes associated with a mass exchange between the oceans, the . . . lands and the atmosphere at seasonal and inter-annual timescales. Nowadays, dense and continuous GPS (Global Positioning System) observations provide direct measurements to capture such signals. In this paper, continuous GPS coordinate time series and interannual height variations are obtained and investigated from Turkish CORS network called TUSAGA-Active with more than 140 stations from 01 Jan. 2010 to 01 Jan. 2016 processed by GAMIT/GLOBK software. Results show significant inter-annual variations of GPS height time series with a period of about 2.8 years at most GPS stations. Furthermore, some relationship between interannual height and rainfall as well as ENSO index will be further investigated, indicating that inter-annual height variations are mostly related to climate changes, such as drought. These results will contribute to understand continuous GPS measurement signals in Turkey as well as applications in near-real-time geohazards estimations. © Authors 2018. CC BY 4.0 License Daha fazlası Daha az

Abdikan S. | Sekertekin A. | Ustunern M. | Balik Sanli F. | Nasirzadehdizaji R.

Conference Object | 2018 | International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives42 ( 3 ) , pp.9 - 13

Temporal monitoring of crop types is essential for the sustainable management of agricultural activities on both national and global levels. as a practical and efficient tool, remote sensing is widely used in such applications. in this study, Sentinel-1 Synthetic Aperture Radar (SAR) imagery was utilized to investigate the performance of the sensor backscatter image on crop monitoring. Multi-temporal C-band VV and VH polarized SAR images were acquired simultaneously by in-situ measurements which was conducted at Konya basin, central Anatolia Turkey. During the measurements, plant height of maize plant was collected and relationship . . .between backscatter values and plant height was analysed. The maize growth development was described under Biologische Bundesanstalt, bundessortenamt und CHemische industrie (BBCH). Under BBCH stages, the test site was classified as leaf development, stem elongation, heading and flowering in general. The correlation coefficient values indicated high correlation for both polarimetry during the early stages of the plant, while late stages indicated lower values in both polarimetry. As a last step, multi-temporal coverage of crop fields was analysed to map seasonal land use. To this aim, object based image classification was applied following image segmentation. About 80% accuracies of land use maps were created in this experiment. As preliminary results, it is concluded that Sentinel-1 data provides beneficial information about plant growth. Dual-polarized Sentinel-1 data has high potential for multi-temporal analyses for agriculture monitoring and reliable mapping. © Authors 2018 Daha fazlası Daha az

Ustuner M. | Sanli F.B. | Abdikan S. | Esetlili M.T. | Bilgin G.

Conference Object | 2018 | International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives42 ( 1 ) , pp.451 - 456

Crops are dynamically changing and time-critical in the growing season and therefore multitemporal earth observation data are needed for spatio-temporal monitoring of the crops. This study evaluates the impacts of classical roll-invariant polarimetric features such as entropy (H), anisotropy (A), mean alpha angle (?¯) and total scattering power (SPAN) for the crop classification from multitemporal polarimetric SAR data. For this purpose, five different data set were generated as following: (1) H?¯, (2) H?¯Span, (3) H?¯A, (4) H?¯ASpan and (5) coherency [T] matrix. A time-series of four PolSAR data (Radarsat-2) were acquired as 13 Jun . . .e, 01 July, 31 July and 24 August in 2016 for the test site located in Konya, Turkey. The test site is covered with crops (maize, potato, summer wheat, sunflower, and alfalfa). For the classification of the data set, three different models were used as following: Support Vector Machines (SVMs), Random Forests (RFs) and Naive Bayes (NB). The experimental results highlight that H?ASpan (91.43% for SVM, 92.25% for RF and 90.55% for NB) outperformed all other data sets in terms of classification performance, which explicitly proves the significant contribution of SPAN for the discrimination of crops. Highest classification accuracy was obtained as 92.25% by RF and H?ASpan while lowest classification accuracy was obtained as 66.99% by NB and H?. This experimental study suggests that roll-invariant polarimetric features can be considered as the powerful polarimetric components for the crop classification. In addition, the findings prove the added benefits of PolSAR data investigation by means of crop classification. © Authors 2018. CC BY 4.0 License Daha fazlası Daha az

Gormus K.S. | Kutoglu S.H. | Gurbuz G. | Capar O.F. | Akgul V.

Conference Object | 2018 | International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives42 ( 3W4 ) , pp.227 - 230

Landslides are one of the leading causes of loss of life and property in the World. Landslides are the most profound ones within other mass movements. Especially in the Northern region of Turkey is severely threatened by landslides. Mass movements can be divided several main classes which are falls, slides, creeps, flows and complex movements. Landslides can occur due to a variety of reasons and most basic one of them is the angle of repose or slope of the hillside. If the angle is overly steep, gravity will pull the material downward, causing a mass movement. Many studies have been carried out in Turkey to monitor landslides, preve . . .nt and reduce landslides damage. These studies mostly focused on forecasting of landslides and damage determination after landslides. Activities required to be carried out in the field can be resulted with unwanted consequences for work safety while the landslide is still active. A landslide is triggered at Devrek, Zonguldak on July 16th, 2015 which affected an area of 40 hectares. For this reason, 88 buildings and a school are evacuated by authorities. To support emergency action plan while ongoing active landslide occurrence at Devrek, apart from the geotechnical approach, aerial photogrammetry, terrestrial laser scanning, land-based SAR methods are used. This study is a summary of studies carried out simultaneously with an active landslide at Devrek, Zonguldak on July 20th - August 8th, 2015. © Authors 2018. CC BY 4.0 License Daha fazlası Daha az

Becek K. | Boguslawski P.

Conference Object | 2018 | International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives42 ( 4 ) , pp.41 - 44

This paper discusses a current issue for several experimental science disciplines, which is the Big Data Problem (BDP). This research study focused on light intensity and ranging (LiDAR) datasets, which are collected for modelling spatial features found on the surface of the earth. Currently, LiDAR datasets are known to be extremely redundant for many applications. Using a formula that allows for calculating the variance of the target-induced error (so-called T-error) caused by the discretisation and quantisation of a 3D surface as a criterion for the quantitative assessment of the fidelity of a model, the use of a Q-tree-based spli . . .t of the surface is proposed for cells of various sizes depending on the fidelity requirements. A LiDAR dataset representing a 1 km x 1 km terrain surface tile using approximately 12 x 106 points was used during the experiments. The initial LiDAR dataset was used to produce a digital terrain model (DTM) at a 0.5 m x 0.5 m resolution, which was used as a reference model. Subsequently, the initial LiDAR dataset was decimated at various rates, and the resulting DTMs were compared with the reference model. The Q-tree based data structure was utilised to illustrate that the Q-tree approach allows for the production of DTMs at a ‘controlled’ fidelity with a considerable reduction in data volume. © Authors 2018 Daha fazlası Daha az

Avsar N.B. | Jin S. | Kutoglu S.H.

Conference Object | 2018 | International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives42 ( 3W4 ) , pp.83 - 85

Sea level rise causes devastating effects on coastal habitats. For example, coastal erosion and saltwater intrusion are major threats for the Black Sea coasts. So, determining sea level changes in the Black Sea is important in terms of coastal risk assessment and coastal planning. In this study, present-day sea level change in the Black Sea is estimated from satellite altimetry and gravity measurements. Altimetry data demonstrate that the Black Sea level has risen at an average rate of 2.5 ± 0.5 mm/year from January 1993 to May 2017. During this period, inter-annual variability of the non-seasonal sea level change is quite strong. F . . .urthermore, mass contribution to this change for the period 2002-2017 has been detected as 2.3 ± 1.0 mm/year from the Gravity Recovery And Climate Experiment (GRACE) mascon solutions. © Authors 2018. CC BY 4.0 License Daha fazlası Daha az