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In order to develop sustainable models for agricultural land, its changing structure and land management, it is necessary to determine and evaluate the parameters that cause temporal change and to use them. With the contribution of remote sensing (UA) and Geographic Information System (GIS), suitable models for agricultural lands can be developed. In this study, changes in agricultural areas, a sample area was selected within the borders of the Centre District of Çorum Province, located in the Central Black Sea Region, and the analyzes obtained by writing the relevant codes for data mining operations of remotely sensed data via Google Earth Engine platform and webGIS applications were examined. With the Terra Climate application, monthly climate and climatic water balance data and monthly climate change for 2020 were examined. Land classification was made with the Sentinel-2 data, and the densities and plant health of the plants were determined with the band combinations. To determine the changes in plants, seven different index values for 2021 were calculated; Changes in vegetation, moisture and water content in agricultural lands were evaluated. When the results obtained are examined; In the agricultural lands in the sample area, the highest temperature in the land heat exchange occurs in September and the lowest temperature is in 2021 February, the vegetation cover in the agricultural lands, while it has a moderately healthy plant density in 2021 April, May and June, it has been determined that it has unhealthy and weak plant density in 2021 October, November and December. From the examination of the climate data, it was seen that the precipitation values decreased considerably in the summer months and increased in the winter months, considering the climatic characteristics of the region. According to the 2021 climate report of the General Directorate of Meteorology, the average temperature of the ground surface in Turkey in 2020 was 14.9°C, while it was determined that this temperature was 19.01°C above the average value in the study area. [ABSTRACT FROM AUTHOR]

The subsidence mechanism of ground surface is a complex phenomenon when multiple seam coal mining operations are carried out. Particularly, the coal mining beneath karstic formations causes a very special form of subsidence. The subsidence causes elasto-plastic deformation of the karstic layers and the collapse of cavities leads to dolinization and/or sinkhole formation. In this study, a sinkhole with a depth of 90 m and a width of 25 m formed in Gelik district within the coalbasin of Zonguldak (NW, Turkey) induced by multiple seam coal mining operations in the past has been presented as a casehistory together with two-dimensional numerical simulations and InSAR monitoring. The computational results proved that the sinkhole was formed as a result of severe yielding in the close vicinity of the faults in contact with karstic formation due to multiple seam longwall mining at different levels. [ABSTRACT FROM AUTHOR]

TK-350 stereo-scenes of the Zonguldak testfield in the north-west of Turkey have been analysed. The imagery had a base-to-height ratio of 0·52 and covered an area of 200 km × 300 km, with each pixel representing 10 m on the ground. Control points digitised from 1:25 000 scale topographic maps were used in the test. A bundle orientation was executed using the University of Hanover program BLUH and PCI Geomatica OrthoEngine AE software packages. Tests revealed that TK-350 stereo-images can yield 3D geopositioning to an accuracy of about 10 m in planimetry and 17 m in height. A 40 m resolution digital elevation model (DEM) was generated by the PCI system and compared against a reference DEM, which was derived from digitised contour lines provided by 1:25 000 scale topographic maps. This comparison showed that accuracy depends mainly on the surface structure and the slope of the local terrain. Root mean square errors in height were found to be about 27 and 39 m outside and inside forested areas, respectively. The matched DEM demonstrated a systematic shift against the reference DEM visible as an asymmetric shift in the frequency distribution. This is perhaps caused by the presence of vegetation and buildings. [ABSTRACT FROM AUTHOR]