SEARCH RESULT

The international initiatives developed in the context of combating global warming are based on the monitoring of Land Use, Land Use Changes, and Forests (LULUCEF). Determination of changes in land use patterns is used to determine the effects of greenhouse gas emissions and to reduce adverse effects in subsequent processes. This process, which requires the investigation and control of quite large areas, has undoubtedly increased the importance of technological tools and equipment. Remote sensing and geographic information system (GIS) are intensively used tools in both scientific and practical works. Technological developments provide remote sensing techniques with the most cost-effective data production with natural sciences (forestry, agriculture, etc.) and different disciplines. The use of carrier platforms and commercially cheaper various sensors have become widespread. Lowaltitude unmanned aerial vehicles provide significant opportunities in high-resolution analyzes to monitor rapid changes in land use (Hunt et al 2010; Kooistra et al 2014). The RGB images obtained with these tools also provide the possibility to produce orthophotos where land cover, soil erosion and terrain topographical information can be obtained (d'Oleire-Oltmanns et al 2012; Bending et al 2014; Mancini et al 2013). Such devices are used in mainly biomass and land cover analyzes due to the attached NDVI, lidar, or radar cameras (Hunt et al 2010; Wallace et al 2012). In this study, multispectral cameras were used to determine the land use pattern with high sensitivity. Unmanned aerial flights were carried out in the research fields of Kahramanmaras Sutcu Imam University campus area. Unmanned aerial vehicle (UAV) (multi-propeller hexacopter) was used as a carrier platform for aerial photographs. Preflight planning with the ground control unit was carried out with the "Mission planner" (Figure 1). The Multispectral Camera (Tetracam ADC Snap) mounted on UAV is used as a sensor. Taking into consideration of the actual land use, flight safety and the sensor characteristics used, the altitude of the aerial photography was set to 50 m, front (forward) and side overlap rates were fixed as 80% and 60%. Before the flight, the estimated resolution was 3.99 cm and a total of 88 aerial photographs have been planned. Flight information was transferred to the UAV's PixHawk flight controller. The flight was performed by taking necessary precautions within the flight area. Pixel wrench, Photoscan and ArcGIS software were used in the image processing, evaluation and visualization. The duration of the planned flight lasted about 7 minutes in light windy and cloudy weather conditions. A total of 88 aerial photographs were taken. The raw multispectral images obtained with Tetracam were processed according to the purpose using Pixel wrench 2 software (Figure 2a). Raw data were first colored and converted to TIFF format (Figure 2b) for photogrammetric processing (Heinold, 2007; Tetracam, 2017). Photoscan software was used to obtain orthophoto from aerial photographs produced in NIR / R / G bands. Based on the principle of structure from motion, photographs were initially placed on the flight path and a point cloud was obtained (Figure 3, Photoscan, 2016). Total of 57 aerial photographs could be processed and the average flight height was calculated as 53.5 m. Depending on the light and vibration, some photographs were not detected by the program. The resulting RMS error was 0.392 pixels. A computer was used for image processing with a 2 GB graphics card with an I7 processor and about 45 minutes were spent for high quality orthomosaic image production (Figure 4a). The resolution of the produced image was determined to be 3.2 cm / pixel. The orthophoto image has been converted to the WGS84 UTM Zone 37 projection using ground control points located according to the PhotoScan user’s Manuel. In the geographical coordinate process of the orthophoto image, the total RMS error was 0.09 m. The types of land use were determined from the orthophoto image using the ArcGIS program. NDVI images were classified by using the threshold values of reflection values according to the supervised classification process in ArcGIS program (Figure 4b, ESRI, 2010). NDVI values calculated from multispectral images ranged from -1 to 1. Six different land covers have been identified by classifying the NDVI values (Figure 5) such as water, soil, vegetation (low, medium and frequent density) and others (shadow, object and unidentified area and man-made objects etc.) (Table 1). Total of 60 random points were used to determine the classification accuracy (Figure 6). The classification success was 90.74% and the kappa value was 74.9% (Table 2a and 2b). The results revealed that the sensors used for mapping the actual land uses increased the success with the high-intensity UAV. Thus, three bands (NIR / Red / Green) generated from the multispectral cameras have been useful in identifying the land use differences with higher accuracy. Aerial photographs from low altitude UAVs and multispectral cameras are one of the important tools in sensitively determining changes in land use. Flight time, flight speed and altitude, lighting status and stable flight position have been found to be very important for obtaining high quality photographic products. The use of UAV- based studies are to give opportunities to obtain high quality photometric data as well as time and cost advantages than other expensive technologies (LIDAR, Satellite Images etc.).

International Workshop on GeoInformation Science
GEOADVANCES

T. Dindaroğlu R. Gündoğan S. Gülci

Generating digital surface models (DSMs) by unmanned air vehicles (UAV) and mountable systems become an appropriate and common method for scientific assessments and also for engineering related works. UAV classes, the specification of mounted sensors, flight height and speed may vary according to the aim and specific scope of the research (Watts et al., 2012; Wings et al., 2014; Gülci and Akay, 2016). The UAV-based studies that include before and after the flight stages, should be well designed for the quality of produced photogrammetric data and security (Akgül et al., 2016). This study examined a multicopter (hexacopter) as an air platform to seek opportunity in generating DSM with high resolution (Table 1). Flights were performed in Kahramanmaras Sutcu Imam University Campus area in Turkey. Preassessment of field works, mission, tests and installation were prepared by using a Laptop with an adaptive ground control station. Hand remote controller unit was also linked and activated during flight to interfere with emergency situations. Canon model IXSUS 160 was preferred as sensor. This sensor mounted on hexacopter has a record ability on the secure digital (SD) Card inside the camera, was mounted on air platform (Figure 1;2) (Remondino et al., 2011; Chao et al., 2016). Total of 8 ground control points were surveyed by using Global navigation satellite system (GNSS), which has almost millimeter accuracy in spatial measurements, and these points were considered as reference point in geo-rectification. Mission planner, which is an open-source interface software, provided flight mission to acquire block pattern. The flight altitude was defined 100 m, and the ratio of side and forward overlaps were planned as 80% (forward) and 60% (side). At the end of flight, total of 75 air photos were obtained from sensor (Figure 3). Processing and analysis of images were performed with PhotoScan, which works under the base of SfM (Structure from motion) approaches, and Cloud Compare, which is an open-source interface (Figure 4) (Westboy et al., 2012; Gülci et al., 2017; Cloud, 2017). Image processing steps by PhotoScan can be summarized as 1. identification of common points and creation of photo plane for block (alignment of photo), 2. point cloud generation, 3. image meshing, and 4. image texture (Agisoft, 2016). The initial options on image processing stages were implemented on PhotoScan as shown in Table 1. Hence, alignment of photo was completed with considering 74817 tie points detected. Then, analysis of dense cloud point generation figured out, totally, as 40.153.034 points (413.129 points/m2). Estimated image acquisition height was 111 m. The resultant resolution of the DSM and orthophoto were 4.92 cm and 2.46 cm/pix (Table 2). Briefly, topographic maps with high resolution can be derived from the use of UAV systems. It provides convenience for researchers by removing time and area constraints (Akgül et al., 2016). UAVs, which are presently defined as effective measuring instruments, can be used for measurements and evaluation studies in medium scale large fields. Accordingly, UAVs are effective tools that can produce high-precision and resolution data for use in geographic information system-based work. The orthophotos can be produced by RGB (Red-green-blue) images obtained with UAV , herewith information on terrain topography, land cover and soil erosion can be evaluated (d’Oleire-Oltmanns et al., 2012; Bending et al., 2014; Inan and Öztürk, 2016).

International Workshop on GeoInformation Science
GEOADVANCES

S. Gülci T. Dindaroğlu R. Gündoğan

Large part of soil losses in the Mediterranean region takes place with the gully erosion in agricultural lands and is caused by heavy rains of the early spring (Poesen, 1995). Calculation of gullies by remote sensing images obtained from satellite or aerial platforms is often not possible because gullies in agricultural fields, defined as the temporary gullies are filled in a very short time with tillage operations. Therefore, fast and accurate estimation of sediment loss with the temporary gully erosion is of great importance. Although temporary gully erosion, firstly identified in 1986 by Foster is common throughout the world, it commonly takes place in the terrains of arid and semi-arid regions where morphological activity and dynamics are high (Cassali et al., 1999). The survey area has a 30% concave topography and a slope of about 14% and a slope length of 300 m. The soils of survey area have been classified as Typic Calcixererts (Gundogan et al., 2013), and are characterized by clay loam texture, slightly alkaline and high cation exchange capacity. The skeleton material (rock fragment) content ranges from 12.2% to 30.4%. The lime content of surface soils is lower than 15% and subsoil lime content is between 44% and 66%. Organic matter content in surface horizon is 1.23% and is below 1.0% in subsoil (Gündogan et al., 2013). In this study, it is aimed to monitor and calculate soil losses caused by the gully erosion that occurs in agricultural areas with low altitude unmanned aerial vehicles. The image was taken by unmanned aerial vehicle at an altitude of 80 m on April 24, 2017 (Figure 1). A 1.82 cm resolution of digital elevation model was produced from the ortho photographs obtained from these images. In the study area, during the period of October 2016 to May 2017 (14/04/2017), the gully was formed after 40.1 mm of rainfall (Table 1). A total of 945 m gully channels has formed following this precipitation. The depth of channel ranged from 5 to 18 cm and the width ranged from 10 to 23 cm (Figure 2). According to the calculation with Pix4D (Fig. 2), gully volume was estimated to be 10.41 m3 and total loss of soil was estimated to be 14.47 Mg (Table 2). The RMSE value of estimations was found to be 0.89. The results indicated that unmanned aerial vehicles could be used in predicting temporary gully erosion and losses of soil.

International Workshop on GeoInformation Science
GEOADVANCES

R. Gündoğan V. Alma T. Dindaroğlu H. Günal T. Yakupoğlu T. Susam K. Saltal