The Persian Gulf is northern part of the ROPME Sea Area (RSA), and is semi-enclosed shallow sea which located in subtropical climate. Measuring is 1000km in length, varying in width 60-340km, and average depth is about 35m and maximum depth is 105m. This research was carried out during 2005-2010 for reviewing the corals status and determination of coral reef habitats distribution in the Persian...

This study aims to analyze land use patterns using time-series satellite images of Seoul Metropolitan Area for the past 30 years, and present a macroscopic model for predicting future land use patterns using Markov Chain based probability model, and finally examine its applicability to Korea. Several Landsat MSS and TM images were used to acquire land-use change patterns and dynamic land-use ch...

This is a study of modeling urban environments from TM satellite images. Urban environments are so heterogeneous. It is necessary to simplify them as combinations of basic land cover materials in order to enable quantitative studies. The V-I-S model proposed by Ridd in 1995 is a conceptual model to simplify urban environments as combination of three basic ground components: vegetation, impervio...

An important factor in sustainable agriculture and economic management is to calculate areas under different crops that the inputs of agriculture connect to this topic. Planning of agricultural mechanization, fertilizer and pesticide requirements, pests and diseases control, estimates of agricultural production, income and tax and financial planning, all linked to the cultivated areas and estim...

This study used archived remote sensing images to depict the history of changes in soil salinity in the Hetao Irrigation District in Inner Mongolia, China, with the purpose of linking these changes with land and water management practices and to draw lessons for salinity control. Most data came from LANDSAT satellite images taken in 1973, 1977, 1988, 1991, 1996, 2001, and 2006. In these years s...

Classifying the remote sensing images requires a deeper understanding of imagery, machine learning classification algorithms, and profound insight into satellite images’ know-how properties. In this paper, convolutional neural network (CNN) is designed to classify multispectral SAT-4 four classes: trees, grassland, barren land, others. an airborne dataset that captures in 4 bands (R, G, B, infr...

always mazandaran province had been exposed to development and changes because of location in coastline of the caspian sea and having unique conditions. gis and remote sensing can be used to monitor in order to manage this sensitive province. then, this study is trying to detect land cover changes in coastal areas of mazandaran province using lcm. land cover changes detection have done using la...

Urban sprawl is one of the main problems that threaten the limited highly fertile land in the Nile Delta of Egypt. In this research, satellite images Landsat TM 1993, ETM+ 2001 and Egypt Sat-1, 2009 has been used to study the urban sprawl and its impact on agricultural land in Qalubiya Governorate. Maximum likelihood supervised classification and post-classification change detection techniques ...

Received Dec 9, 2016 Revised Mar 27, 2017 Accepted Apr 11, 2017 The accurate land use land cover (LULC) classifications from satellite imagery are prominent for land use planning, climatic change detection and eco-environment monitoring. This paper investigates the accuracy and reliability of Support Vector Machine (SVM) classifier for classifying multispectral image of Hyderabad and its surrou...