This study analyzes the characteristics of land use/land cover change in Jordan’s Irbid governorate, 1984–2018, and predicts future land use/land cover for 2030 and 2050 using a cellular automata-Markov model. The results inform planners and decision makers of past and current spatial dynamics of land use/land cover change and predicted urban expansion, for a better understanding and successful...

Surface waters are the most important economic resource for humans which provide water for agricultural, industrial and anthropogenic activities. Surface water quality plays vital role in protecting aquatic ecosystems. Unplanned urbanization, intense agricultural activities and deforestation are positively associated with carbon, nitrogen and phosphorous related water quality parameters. Multip...

This paper is concerned with data and classifications that confuse the concepts of land cover and land use. Conceptual confusion is problematic for data integration and modelling. This has resulted in calls for the separation of land use and land cover from the global land monitoring community. Text mining approaches are combined with social network analyses as a method for unravelling the diff...

Abstract Decadal changes in land use/land cover for Balachaur watershed in Nawanshahar district, Punjab, India were studied using black and white aerial photographs for March 1984 on approximately 1:20,000 scale and multidate geocoded false colour composites (FCC) of IRS-1D LISS-III on 1:50,000 scale for March 2002, September 2002, and May 2003 and interpreted visually to prepare land use/land...

A ca. 1980 national-scale land-cover classification based on aerial photo interpretation was combined with 2000 AVHRR satellite imagery to derive land cover and land-cover change information for forest, urban, and agriculture categories over a seven-state region in the U.S. To derive useful land-cover change data using a heterogeneous dataset and to validate our results, we a) stratified the cl...

A number of national, regional and global land cover classification systems have been developed to meet specific user requirements for land cover mapping exercises, independent of scale, nomenclature and quality. However, this variety of land-cover classification systems limits the compatibility and comparability of land cover data. Furthermore, the current lack of interoperability between diff...

Land cover classification is the most important element of land cover mapping and is a key input to many societal benefits. Traditional classification methods require a large amount of remotely sensed images, which are time consuming and labour intensive. Recently, crowdsourcing geographic information (CGI), including geo-tagged photos and other sources, has been widely used with lower costs, b...