Investigation of the effects of image compression on the geometric quality of digital protogrammetric imagery

We are living in a decade, where the use of digital images is becoming increasingly important. Photographs are now converted into digital form, and direct acquisition of digital images is becoming increasing important as sensors and associated electronics. Unlike images in analogue form, digital representation of images allows visual information to· be easily manipulated in useful ways. One practical problem of the digital image representation is that, it requires a very large number of bits and hence one encounters a fairly large volume of data in a digital production environment if they are stored uncompressed on the disk. With the rapid advances in sensor technology and digital electronics, the number of bits grow larger in softcopy photogrammetry, remote sensing and multimedia GIS. As a result, it is desirable to find efficient representation for digital images in order to reduce the memory required for storage, improve the data access rate from storage devices, and reduce the time required for transfer across communication channels. The component of digital image processing that deals with this problem is called image compression. Image compression is a necessity for the utilisation of large digital images in softcopy photogrammetry, remote sensing, and multimedia GIS. Numerous image Compression standards exist today with the common goal of reducing the number of bits needed to store images, and to facilitate the interchange of compressed image data between various devices and applications. JPEG image compression standard is one alternative for carrying out the image compression task. This standard was formed under the auspices ISO and CCITT for the purpose of developing an international standard for the compression and decompression of continuous-tone, still-frame, monochrome and colour images. The JPEG standard algorithm &Us into three general categories: the baseline sequential process that provides a simple and efficient algorithm for most image coding applications, the extended DCT-based process that allows the baseline system to satisfy a broader range of applications, and an independent lossless process for application demanding that type of compression. This thesis experimentally investigates the geometric degradations resulting from lossy JPEG compression on photogrammetric imagery at various levels of quality factors. The effects and the suitability of JPEG lossy image compression on industrial photogrammetric imagery are investigated. Examples are drawn from the extraction of targets in close-range photogrammetric imagery. In the experiments, the JPEG was used to compress and decompress a set of test images. The algorithm has been tested on digital images containing various levels of entropy (a measure of information content of an image) with different image capture capabilities. Residual data was obtained by taking the pixel-by-pixel difference between the original data and the reconstructed data. The image quality measure, root mean square (rms) error of the residual was used as a quality measure to judge the quality of images produced by JPEG(DCT-based) image compression technique. Two techniques, TIFF (IZW) compression and JPEG(DCT-based) compression are compared with respect to compression ratios achieved. JPEG(DCT-based) yields better compression ratios, and it seems to be a good choice for image compression. Further in the investigation, it is found out that, for grey-scale images, the best compression ratios were obtained when the quality factors between 60 and 90 were used (i.e., at a compression ratio of 1:10 to 1:20). At these quality factors the reconstructed data has virtually no degradation in the visual and geometric quality for the application at hand. Recently, many fast and efficient image file formats have also been developed to store, organise and display images in an efficient way. Almost every image file format incorporates some kind of compression method to manage data within common place networks and storage devices. The current major file formats used in softcopy photogrammetry, remote sensing and · multimedia GIS. were also investigated. It was also found out that the choice of a particular image file format for a given application generally involves several interdependent considerations including quality; flexibility; computation; storage, or transmission. The suitability of a file format for a given purpose is · best determined by knowing its original purpose. Some of these are widely used (e.g., TIFF, JPEG) and serve as exchange formats. Others are adapted to the needs of particular applications or particular operating systems

A comparative estimate of air temperature from modis land surface temperatures in Ghana

AbstractThis study is aimed at establishing a comparative estimate of air temperature (Tair) from Moderate Resolution Imaging Spectroradiometer (MODIS) Land Surface Temperature (LST) between 1 km and 6 km spatial resolutions and to investigate and quantify spatial variability of LST—Tair relationships. The test area is Republic of Ghana located in the sub-region of West Africa. The purpose of the research is to establish an optimal performance of Tair between two spatial resolutions. Arithmetic Mean method was employed for computation of the datasets. Seventy (70) pairs of composite LSTs consisting of Terra and Aqua MODIS observations which correspond to 70 meteorological stations were used. Due to problem of missing data and outliers, 277 pairs of LST data points per resolution were used. Application of Regression Analyses revealed a good direct correlation existing between values of Tair and LSTs in 1 km with coefficient of determination, R2 = 0.8124 while, 6 Km resolution recorded R2 = 0.8031. Hence, MODIS LST in 1 km is a better estimator of air temperature in Linear Regression study. Statistical indices of 1 km procedure were found to be lower than the 6 km procedure. The 1 km resolution registered a Root Mean Square Error (RMSE) of 1.97°C, Standard Error of regression, 1.14°C and Coefficient of Variation, CV of 10.19%. Meanwhile, 6 km resolution yielded a RMSE of 2.13°C, Standard Error of regression, 1.22°C and CV of 10.68% respectively. Therefore, 1 km resolution datasets show better accuracy and performance of air temperature estimation than 6 km data products. Hence, a good result would be achieved when 1 km datasets are processed

Water Quality Changes Associated with Cassava Production: Case Study of White Volta Basin

The outcome reveal that as the land use in the catchment areas change from mixed agricultural to cassava cultivation, the simulated loads and concentrations of nitrogen species from cassava land-use scenario recorded reduction. The resultant concentrations of nitrate and nitrite for both current and future land-use scenarios are all below the daily limit suggested by the WHO, (World Health Organization). For the phosphate concentration, an increase of 4.21% was depicted under cassava land-use scenario. The results show that SWAT is a reliable water quality model, capable of simulating accurate information for developing environmental management plans

Water quality changes associated with cassava production: case study of White Volta Basin

The outcome reveal that as the land use in the catchment areas change from mixed agricultural to cassava cultivation, the simulated loads and concentrations of nitrogen species from cassava land-use scenario recorded reduction. The resultant concentrations of nitrate and nitrite for both current and future land-use scenarios are all below the daily limit suggested by the WHO, (World Health Organization). For the phosphate concentration, an increase of 4.21% was depicted under cassava land-use scenario. The results show that SWAT is a reliable water quality model, capable of simulating accurate information for developing environmental management plans

Geospatial Analysis of Land Use and Land Cover Transitions from 1986–2014 in a Peri-Urban Ghana

Recently, peri-urbanisation has led to the transformation of the rural landscape, changing rural land uses into peri-urban land uses, under varying driving factors. This paper analyzes the dynamic transitions among identified land use and land cover (LULC) types in the Bosomtwe district of Ghana, from 1986 to 2014. An integrated approach of geo-information tools of satellite remote sensing in Earth Resource Data Analysis System (ERDAS) Imagine 13 and ArcMap 10.2 Geographic Information System (GIS), with Markov chain analytical techniques were used to examine the combined forest land cover transitions, relative to build-up, recent fallows and grasslands and projected possible factors influencing the transitions under business as usual and unusual situations. Statistical analyses of the classified Landsat TM, ETM+ and Landsat 8 Operational Land Imager and Thermal Infrared Sensor (OLI/TIS) indicated that over the period of 24 years, the Bosomtwe district has undergone a series of land use conversions with remarkable forest losses especially between 2002 and 2010. In 2010 dense forest cover was degraded to low forest by 4040 ha indicating 0.40% transition probability in the future. There was a remarkable increase of built-up/bare and concrete area with a 380% increment in the 1986–2002 transition periods. The application of the Markov futuristic land use dynamics by the years 2018 and 2028, projected from the 2014 LULC indicated a future steady decline in the area coverage of the dense forest to low forest category. This is currently being driven (as at the 2017 LULC trends), by the combined effects of increasing build up bare and concrete surface land uses as well as the expanding recent fallows and grassland. The paper concluded that the health of the ecosystem and biodiversity of the lake Bosomtwe need to be sustainably managed by the Bosomtwe district assembly