Understanding Land Use and Land Cover Dynamics from 1976 to 2014 in Yellow River Delta

Abstract

Long-term intensive land use/cover changes (LUCCs) of the Yellow River Delta (YRD) have been happening since the 1960s. The land use patterns of the LUCCs are crucial for bio-diversity conservation and/or sustainable development. This study quantified patterns of the LUCCs, explored the systematic transitions, and identified wetland change trajectory for the period 1976-2014 in the YRD. Landsat imageries of 1976, 1984, 1995, 2006, and 2014 were used to derive nine land use classes. Post classification change detection analysis based on enhanced transition matrix was applied to identify land use dynamics and trajectory of wetland change. The five cartographic outputs for changes in land use underlined major decreases in natural wetland areas and increases in artificial wetland and non-wetland, especially aquafarms, salt pans and construction lands. The systematic transitions in the YRD were wetland degradation, wetland artificialization, and urbanization. Wetland change trajectory results demonstrated that the main wetland changes were wetland degradation and wetland artificialization. Coastline change is the subordinate reason for natural wetland degradation in comparison with human activities. The results of this study allowed for an improvement in the understanding of the LUCC processes and enabled researchers and planners to focus on the most important signals of systematic landscape transitions while also allowing for a better understanding of the proximate causes of changes.

Assessment of Land Cover Changes in the Hinterland of Barranquilla (Colombia) Using Landsat Imagery and Logistic Regression

“…Landsat TM/ETM/OLI imagery of the study area was obtained for the time span 1985 until 2017 ( Table 1). Temporal range, multispectral characteristics, free availability, spatial resolution and frequency of the Landsat sensors make the imagery highly suitable for mapping land use and land cover changes at a regional scale [25,42,43]. The EarthExplorer website (https://earthexplorer.usgs.gov/) of the United States Geological Survey (USGS) was used to preview Landsat imagery and to select the best cloud-free scenes.…”

Estimating Built-Up Area Change in Ulaanbaatar City, Mongolia

“…The rate of change of land use from initial years to next time steps was used for the transition state matrix. Land-use change for each land use/cover class i was calculated as Zhang et al (Aldwaik and Pontius, 2012;Jiyuan et al, 2002;Zhang et al, 2017):…”

Analysis of High Temporal Resolution Land Use/Land Cover Trajectories

“…Due to factors as the difference of acquisition dates, atmospheric conditions, phenology and spectral confusion, the multidate maps present likely errors and incongruencies [44,45]. For instance, under the assumption of a random spatial distribution of error, the probability of obtaining a sequence entirely accurate based on a series of seven maps with overall accuracy of 80% is only 0.21 (0.8 7 ). Due to error propagation, the accuracy decreases rapidly with the increase in the number of dates.…”

“…For instance, Baral et al [4] depicted eight forest cover change trajectories using two categories (forest/non forest) and three dates. Zhang et al [7] classified 61 wetland land cover change trajectories, based on three land cover classes and five dates, using similarity, turnover, and diversity indices. Nevertheless, nowadays the increased number of satellites with improved temporal resolution allows the acquisition of frequent images and cloud computing enables users to process huge multidate data sets in order to produce LUCC maps with a high temporal resolution.…”