Natural Land Cover Change Research Articles

Spatiotemporal changes in LULC and associated impact on urban Heat Islands over Pakistan using geospatial techniques

Urban Heat Islands arise when the natural land cover changes with dense concentrations of pavement, buildings, roads, and other surfaces that absorb and preserve heat. The current study aimed to assess Land Use Land Cover(LULC) changes and associated impact on Urban Heat Island (UHI) from 2000 to 2020 using Geospatial technologies for four metropolitan cities (Islamabad, Lahore, Multan and Muzaffarabad) of Pakistan. A Supervised Classification algorithm was performed on satellite imageries using ArcGIS software for analyzing LULC changes. The study areas were classified into 4 classes such as built-up, barren land, vegetation, and water bodies. Thermal bands of Landsat 4–5 and 8 were used for retrieved Land Surface Temperature (LST) and UHI. The findings of this study indicate that the urban area in all four districts i.e. Islamabad, Lahore, Multan and Muzaffarabad has increased by 21.3 %, 20.9 %, 6.1 % and 15 % respectively during 2000–2020. The built-up and barren land revealed the highest recorded LST, while vegetation and water bodies showed the lowest measured LST values. From 2000 to 2020, the annual maximum LST in Islamabad rose by 1.1 °C, Lahore by 2.1 °C, and Multan and Muzaffarabad by 1.9 °C and 1.5 °C. The expansion of built-up areas and the reduction in vegetation contribute to a favorable contribution to UHI. The study's findings showed that appropriate action plans are required to manage urban heat and promote sustainable city development.

Feedbacks of soil properties on vegetation during the Green Sahara period

During the early to middle Holocene, the Sahara received enhanced precipitation and was covered by steppe-like vegetation with a large-scale hydrographic network of lakes, wetlands and fans, which is known as the Green Sahara (GS). However, most coupled land-atmosphere models underestimate the precipitation and vegetation cover, suggesting that critical atmospheric or land surface processes are lacking in those models. Climate-induced vegetation cover change can modify soil texture and physical properties over the long term, which in turn have feedbacks on vegetation. In this study, we examine five plausible soil-vegetation processes in a land surface model, which are expected to increase soil moisture for plants and possibly sustain equilibrium vegetation for a lower rainfall level. The annual precipitation required during the GS epoch to match the modelled vegetation distribution with paleorecords is inferred. Results demonstrate that these soil-vegetation processes have strong positive impacts on vegetation and soil moisture, especially the increase of soil evaporative resistance. After including all soil feedbacks on vegetation, the model requires only a mean precipitation of ∼400 mm/yr to reproduce the pollen-inferred GS vegetation, instead of ∼600 mm/yr when no soil feedback is included. From the mid-Holocene to pre-industrial period, we infer that terrestrial carbon stocks decrease by ∼58 PgC due to the removal of carbon in vegetation, soil and litter pools of the GS. This work highlights the importance of soil-vegetation interactions for simulating dry-region vegetation coverage in models, and the impacts of natural land cover change on carbon budgets in the geological past.

Evolution of urbanization and its impact on temperature trends of Quetta city in Pakistan

Quetta is an important economic, historical and culturally a rich city located in the south-west of Pakistan. Like many other cities of the world, Quetta faced massive urbanization during last three decades. It has 1.1 million populations. The consequences of rapid urbanization in Quetta city are significant through changing urban area’s temperatures than its nearby regional areas as a result of alteration of natural land cover change into built-surfaces at city scale. In this context, the objective of this study is to explore the effect of urbanization on variability of minimum (dTn) and maximum (dTx) temperature trends of Quetta city by comparing with non-urban regional stations. For this purpose, first the evolution of urbanization during 1980s to 2013 was analysed by using satellite image processing techniques for the years 1989, 2000 and 2013. To study the impact of urbanization on dTn and dTx of Quetta city, the time series data of daily average monthly minimum (Tn) and maximum (Tx) temperatures ranging from 1947 to 2013 of Quetta city and the seven regional stations were analysed by using linear regression. The results show that during last twenty years, urban population and urban surface area increased to 80% and 194%, respectively. The variation in annual and seasonal temperature trends depicted that Tn and Tx at Quetta city are increasing more than the regional stations and Tn increased faster than Tx at urban and regional scale except winter season.

Change Detection Based on Multi-Feature Clustering Using Differential Evolution for Landsat Imagery

Change detection (CD) of natural land cover is important for environmental protection and to maintain an ecological balance. The Landsat series of satellites provide continuous observation of the Earth’s surface and is sensitive to reflection of water, soil and vegetation. It offers fine spatial resolutions (15–80 m) and short revisit times (16–18 days). Therefore, Landsat imagery is suitable for monitoring natural land cover changes. Clustering-based CD methods using evolutionary algorithms (EAs) can be applied to Landsat images to obtain optimal changed and unchanged clustering centers (clusters) with minimum clustering index. However, they directly analyze difference image (DI), which finds itself subject to interference by Gaussian noise and local brightness distortion in Landsat data, resulting in false alarms in detection results. In order to reduce image interferences and improve CD accuracy, we proposed an unsupervised CD method based on multi-feature clustering using the differential evolution algorithm (M-DECD) for Landsat Imagery. First, according to characteristics of Landsat data, a multi-feature space is constructed with three elements: Wiener de-noising, detail enhancement, and structural similarity. Then, a CD method based on differential evolution (DE) algorithm and fuzzy clustering is proposed to obtain global optimal clusters in the multi-feature space, and generate a binary change map (CM). In addition, the control parameters of the DE algorithm are adjusted to improve the robustness of M-DECD. The experimental results obtained with four Landsat datasets confirm the effectiveness of M-DECD. Compared with the results of conventional methods and the current state-of-the-art methods based on evolutionary clustering, the detection accuracies of the M-DECD on the Mexico dataset and the Sardinia dataset are very close to the best results. The accuracies of the M-DECD in the Alaska dataset and the large Canada dataset increased by about 3.3% and 11.9%, respectively. This indicates that multiple features are suitable for Landsat images and the DE algorithm is effective in searching for an optimal CD result.

Representation of natural and anthropogenic land cover change in MPI‐ESM

The purpose of this paper is to give a rather comprehensive description of the models for natural and anthropogenically driven changes in biogeography as implemented in the land component JSBACH of the Max Planck Institute Earth system model (MPI‐ESM). The model for natural land cover change (DYNVEG) features two types of competition: between the classes of grasses and woody types (trees, shrubs) controlled by disturbances (fire, windthrow) and within those vegetation classes between different plant functional types based on relative net primary productivity advantages. As part of this model, the distribution of land unhospitable to vegetation (hot and cold deserts) is determined dynamically from plant productivity under the prevailing climate conditions. The model for anthropogenic land cover change implements the land use transition approach by Hurtt et al. (2006). Our implementation is based on the assumption that historically pastures have been preferentially established on former grasslands (“pasture rule”). We demonstrate that due to the pasture rule, deforestation reduces global forest area between 1850 and 2005 by 15% less than without. Because of the pasture rule the land cover distribution depends on the full history of land use transitions. This has implications for the dynamics of natural land cover change because assumptions must be made on how agriculturalists react to a changing natural vegetation in their environment. A separate model representing this process has been developed so that natural and anthropogenic land cover change can be simulated consistently. Certain aspects of our model implementation are illustrated by selected results from the recent CMIP5 simulations.

Remote sensing and GIS-based integrated analysis of land cover change in Duzce plain and its surroundings (north western Turkey)

The aim of this study is to research natural land cover change caused by the permanent effects of human activities in Duzce plain and its surroundings, and to determine the current status of the land cover. For this purpose, two Landsat TM images were used in the study for the years 1987 and 2010. These images are analysed by using data image processing techniques in ERDAS Imagine©10.0 and ArcGIS©10.0 software. Land cover change nomenclature is classified according to the Coordination of Information on the Environment Level 2 Classification (1--urban fabric, 2--industrial, commercial and transport units, 3--heterogeneous agricultural areas, 4--forests, and 5--inland wetlands). Furthermore, the image analysis results are confirmed by the field research. According to the results, a decrease of 33.5 % was recorded in forest areas from 24,840.7 to 16,529.0 ha; an increase of 11.2 % was recorded in heterogeneous agricultural areas from 47,702.7 to 53,051.7 ha. Natural vegetation, which is the large part of land cover in the research area, has been changing rapidly because of rapid urbanisation and agricultural activities. As a result, it is concluded that significant changes have occurred on the natural land cover between the years 1987 and 2010 in the Duzce plain and its surroundings.

Holocene vegetation and biomass changes on the Tibetan Plateau – a model-pollen data comparison

Abstract. Results of a transient numerical experiment performed in a coupled atmosphere-ocean-vegetation model with orbital forcing alone are compared to pollen-based vegetation reconstructions covering the last 6000 yr from four representative sites on the Tibetan Plateau. Causes of the vegetation change and consequences of the biomass storage are analysed. In general, simulated and reconstructed vegetation trends at each site are in good agreement. Both methods reveal a general retreat of the biomass-rich vegetation that is particularly manifested in a strong decrease of forests. However, model and reconstructions often differ with regard to the climatic factors causing the vegetation change at each site. The reconstructions primarily identify decreasing summer monsoon precipitation and changes in the temperature of the warm season as the responsible mechanisms for the vegetation shift. In the model, the land cover change mainly originates from differences in warm/cold seasonal temperatures and only to a lesser extent from precipitation changes. According to the model results, the averaged forest fraction on the Plateau shrinks by almost one-third from mid-Holocene (41.4 %) to present-day (28.3 %). Shrubs, whose fraction is quadrupled at present-day (12.3 %), replace most of this forest. Grass fraction increases from 38.1 % during the mid-Holocene to 42.3 % at present-day. This land cover change results in a decrease of living biomass by 0.62 kgC m−2. Total biomass on the Tibetan Plateau decreases by 1.9 kgC m−2, i.e. approx. 6.64 PgC are released due to the natural land cover change.