Identification of drought extent using NVSWI and VHI in Iaşi county area, Romania

Drought is a stochastic natural phenomenon that appears from considerable lacking in precipitation. Among natural hazards, drought is known to provoke extensive damage and affects a important number of people. Techniques for observing agricultural drought from R.S. are indirect. These depend on using images based parameters to exemplifed soil moisture condition when the soil is often obscured by a vegetation cover. The procedure are mainly based on determing vegetation health or greenness using VI , often in combination with canopy temperature anomalies using thermal infrared wavebands. In this study were used remote sensing images from the Landsat 8 OLI, taken in may and june 2017. The study area was the county of Iasi. To evaluate drought in this study, for Iasi county, Normalized Vegetation Supply Water Index (NVSWI) and Vegetation Health Index (VHI), were used. VSWI is derived from The Vegetation Supply Water Index (VSWI). This index was developed to combine the NDVI and the land surface temperature (LST) to detect the moisture condition. VHI was developed through a combination of Vegetation Condition Index (VCI), one of the important vegetation indicators when monitoring weather-related variations, such as droughts, and Temperature Condition Index (TCI), which reflects the stress of temperature, that both indicies can be successfully used to determine the spatiotemporal extent of agricultural drought. After applying NVSWI to determine the degree of drought we noticed that for the satellite image of May prevailed “slight drought” and for june “normal”. Second index, VHI indicate that in both months, may and june, is “no drought”. It can be concluded that VHI is a very good indicator for studing extreme drought and NVSWI offer information about areas “normal” and “wet”

ACCURACY ASSESSMENT OF A COMPLEX BUILDING 3D MODEL RECONSTRUCTED FROM IMAGES ACQUIRED WITH A LOW-COST UAS

Nowadays, Unmanned Aerial Systems (UASs) are a wide used technique for acquisition in order to create buildings 3D models, providing the acquisition of a high number of images at very high resolution or video sequences, in a very short time. Since low-cost UASs are preferred, the accuracy of a building 3D model created using this platforms must be evaluated. To achieve results, the dean's office building from the Faculty of “Hydrotechnical Engineering, Geodesy and Environmental Engineering” of Iasi, Romania, has been chosen, which is a complex shape building with the roof formed of two hyperbolic paraboloids. Seven points were placed on the ground around the building, three of them being used as GCPs, while the remaining four as Check points (CPs) for accuracy assessment. Additionally, the coordinates of 10 natural CPs representing the building characteristic points were measured with a Leica TCR 405 total station. The building 3D model was created as a point cloud which was automatically generated based on digital images acquired with the low-cost UASs, using the image matching algorithm and different software like 3DF Zephyr, Visual SfM, PhotoModeler Scanner and Drone2Map for ArcGIS. Except for the PhotoModeler Scanner software, the interior and exterior orientation parameters were determined simultaneously by solving a self-calibrating bundle adjustment. Based on the UAS point clouds, automatically generated by using the above mentioned software and GNSS data respectively, the parameters of the east side hyperbolic paraboloid were calculated using the least squares method and a statistical blunder detection. Then, in order to assess the accuracy of the building 3D model, several comparisons were made for the facades and the roof with reference data, considered with minimum errors: TLS mesh for the facades and GNSS mesh for the roof. Finally, the front facade of the building was created in 3D based on its characteristic points using the PhotoModeler Scanner software, resulting a CAD (Computer Aided Design) model. The results showed the high potential of using low-cost UASs for building 3D model creation and if the building 3D model is created based on its characteristic points the accuracy is significantly improved