scholarly journals Impacts of long-term disturbance on soil health with relation to vegetation distribution in a tropical ecosystem

2020 ◽  
Vol 2 (4) ◽  
pp. 149-156
Author(s):  
C. N. Basweti ◽  
◽  
S. Otor ◽  
S. Manohar ◽  
◽  
...  
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Land Cover ◽  
Soil Health ◽  
Integrated Approach ◽  
Soil Productivity ◽  
Land Cover Changes ◽  
Vegetation Distribution ◽  
Grassland Soil

Land-use and land-cover changes are the main cause of soil degradation and associated human and environmental problems. The study was conducted in Mai Mahiu ecosystem, Kenya whose aim was to assess long-term (1985 to 2015) impacts of land-use and land-cover changes on soil health with disturbance-induced vegetation distribution. Landsat archive was utilized to detect land-use change for 30 years at an interval of 15 years and analysed based on supervised image classification. Four land-use practices (undisturbed forest, disturbed forest, cropland and grassland) were selected and soil sampled to 15 cm depth for soil analyses. In this period, cropland increased by 135% at the expense of natural forest while built-up areas increased by three times. Soil bulk density increased significantly (p<0.001) from 0.93±0.02 g cm-3 in forest soil to 1.27±0.02 g cm-3 in disturbed grassland. Soil pH had significant change (p=0.002) that ranged between 6.19±0.14 and 7.18±0.12. Soil organic carbon declined significantly (p=0.008) with land-use change with losses of up to 63% recorded in disturbed grassland. Total nitrogen levels declined from 0.34% in the forest to 0.15% in disturbed grassland soil. The pronounced changes in land-use and land-cover in Mai Mahiu have negatively affected the soil health with a potential drop in soil productivity and ecosystem provisioning. An integrated approach, enforcement of relevant laws and policy implementation are recommended to restoring and maintaining soil quality of this ecosystem.

Generating long-term high-resolution land-use change datasets for regional climate modeling in CORDEX domains

2021 ◽  
Author(s):  
Peter Hoffmann ◽  
Diana Rechid ◽  
Vanessa Reinhart ◽  
Christina Asmus ◽  
Edouard L. Davin ◽  
...  
Keyword(s):  
Land Use ◽  
High Resolution ◽  
Land Use Change ◽  
Land Cover ◽  
Climate Modeling ◽  
Regional Climate ◽  
Regional Climate Modeling ◽  
Local Scale ◽  
Modeling Studies

&lt;p&gt;Land-use and land cover (LULC) are continuously changing due to environmental changes and anthropogenic activities. Many observational and modeling studies show that LULC changes are important drivers altering land surface feedbacks and land-atmosphere exchange processes that have substantial impact on climate on the regional and local scale. Yet, most long-term regional climate modeling studies do not account for these changes. Therefore, within the WCRP CORDEX Flagship Pilot Study LUCAS (Land Use Change Across Scales) a new workflow was developed to generate high-resolution annual land cover change time series based on past reconstructions and future projections. First, the high-resolution global land cover dataset ESA-CCI LC (~300 m resolution) is aggregated and converted to a 0.1&amp;#176; resolution, fractional plant functional type (PFT) dataset. Second, the land use change information from the land-use harmonized dataset (LUH2), provided at 0.25&amp;#176; resolution as input for CMIP6 experiments, is translated into PFT changes employing a newly developed land use translator (LUT). The new LUT was first applied to the EURO-CORDEX domain. The resulting LULC maps for past and future - the LUCAS LUC dataset - can be applied as land use forcing to the next generation RCM simulations for downscaling CMIP6 by the EURO-CORDEX community and in the framework of FPS LUCAS. The dataset includes land cover and land management practices changes important for the regional and local scale such as urbanization and irrigation. The LUCAS LUC workflow is applied to further CORDEX domains, such as Australasia and North America. The resulting past and future land cover changes will be presented, and challenges regarding the application of the new workflow to different regions will be addressed. In addition, issues related to the implementation of the dataset into different RCMs will be discussed.&lt;/p&gt;

Long-term land use and land cover changes (1920–2015) in Eastern Ghats, India: Pattern of dynamics and challenges in plant species conservation

2018 ◽  
Vol 85 ◽  
pp. 21-36 ◽  
Author(s):  
Reshma M. Ramachandran ◽  
Parth Sarathi Roy ◽  
V. Chakravarthi ◽  
J. Sanjay ◽  
Pawan K. Joshi
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Plant Species ◽  
Species Conservation ◽  
Eastern Ghats ◽  
Land Cover Changes

scholarly journals Over 150 Years of Change: Object-Oriented Analysis of Historical Land Cover in the Main River Catchment, Bavaria/Germany

2020 ◽  
Vol 12 (24) ◽  
pp. 4048
Author(s):  
Yrneh Ulloa-Torrealba ◽  
Reinhold Stahlmann ◽  
Martin Wegmann ◽  
Thomas Koellner
Keyword(s):  
Land Use ◽  
Ecosystem Services ◽  
Land Use Change ◽  
Land Cover ◽  
Land Cover Change ◽  
Historical Maps ◽  
River Catchment ◽  
Main River ◽  
Object Based

The monitoring of land cover and land use change is critical for assessing the provision of ecosystem services. One of the sources for long-term land cover change quantification is through the classification of historical and/or current maps. Little research has been done on historical maps using Object-Based Image Analysis (OBIA). This study applied an object-based classification using eCognition tool for analyzing the land cover based on historical maps in the Main river catchment, Upper Franconia, Germany. This allowed land use change analysis between the 1850s and 2015, a time span which covers the phase of industrialization of landscapes in central Europe. The results show a strong increase in urban area by 2600%, a severe loss of cropland (−24%), a moderate reduction in meadows (−4%), and a small gain in forests (+4%). The method proved useful for the application on historical maps due to the ability of the software to create semantic objects. The confusion matrix shows an overall accuracy of 82% for the automatic classification compared to manual reclassification considering all 17 sample tiles. The minimum overall accuracy was 65% for historical maps of poor quality and the maximum was 91% for very high-quality ones. Although accuracy is between high and moderate, coarse land cover patterns in the past and trends in land cover change can be analyzed. We conclude that such long-term analysis of land cover is a prerequisite for quantifying long-term changes in ecosystem services.

scholarly journals A tájhasználat változása a Hódmezővásárhelyi kistérségben a földhasználat és a felszínborítás változásának tükrében

2009 ◽  
Vol 4 (1) ◽  
pp. 42-49
Author(s):  
Krisztián Kis
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Land Cover ◽  
Positive Result ◽  
Arable Land ◽  
Water Bodies ◽  
Land Cover Changes ◽  
Landscape Use ◽  
Uncultivated Land ◽  
Use Categories

The proportion of the land use categories reflects the quality and intensity of the landscape use. According to the data the land use of the micro-region mostly defined by arable land, grassland (meadow/pasture), forest and uncultivated land, which are amounted to 99% of the area of the micro-region during the examined period. In spite of the short examined period it can be concluded from the examination that considerable changes took place in the landscape use of the micro-region which can be derived from the land use and land cover changes. It can be assessed as favourably change that forest areas increased but the increase of uncultivated land at the same time can be less favourable assessed. The proportion of forest and semi-natural areas, wetlands and water bodies also increased as the positive result of the land use change.

Modeling the changing sediment yield of the Amazon under climate change and deforestation scenarios and the possible impacts on the Guiana coast

2020 ◽  
Author(s):  
Safaa Naffaa ◽  
L.P.H. (Rens) van Beek ◽  
Frances E.Dunn ◽  
Steven de Jong
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Land Use Change ◽  
Land Cover ◽  
Sediment Yield ◽  
Coastal Erosion ◽  
Sediment Supply ◽  
Trapping Efficiency ◽  
Amazon River ◽  
Land Cover Changes

&lt;p&gt;The Amazon River is an important source of the sediment that is transported and accumulated along the coast of Suriname. As such it is an important factor in maintaining the coastline as this sediment is deposited in mud banks that move towards the shore and coalesce with it, thus preventing coastal erosion. Accordingly, a steady and adequate supply of sediment from the Amazon river is required especially considering increased coastal erosion rates that may occur as a result of rising sea levels due to climate change. Yet at the same time, climate change may alter the hydrological regime of the Amazon and influence its transport capacity, affecting sediment transport to the mouth and coast. Furthermore, the sediment supply to the river may be altered as a result of land cover changes and other anthropogenic activities, including deforestation and sediment trapping in existing and future planned reservoirs.&lt;br&gt;Studying the transport of sediment from source to sink and quantifying how future changes affect the mean rate of sediment supply to the Surinam coast and its variability will lead to a better understanding of the intricacies involved. We use a spatial-temporal process-based model together with a set of plausible scenarios of future change based on combinations of the Shared Socioeconomic Pathways (SSP) and the Representative Concentration Pathways (RCP). In this study, we used two models: PCRGLOB-Set and PCRGLOB-WB. PCRGLOB-SET is based on the RUSLE equation and is used to assess the local sediment supply including the effects of land cover changes. PCRGLOB-WB simulates hydrological responses and changes under climate and land-use change. Moreover, PCRGLOB-WB is used to determine the trapping efficiency of reservoirs. The PCRGLOB-WB model was applied to a business-as-usual scenario for the 21st century (SSP 2 with RCP 6.0) and we considered uncertainty in the projected climate by using 5 Global Climate Models (GCMs). We apply the model to different future scenarios considering climate, socioeconomic and land-use change. For validation, the observations of six stations along the Amazon river were compared to the estimations of the models for the historical period (1971-2010), which also serves as a reference run to evaluate changes in sediment production and sediment yield.&amp;#160;&lt;/p&gt;

scholarly journals Long-term land-use / land-cover changes in Czech border regions

2019 ◽  
Vol 59 (2) ◽  
Author(s):  
Lucie Kupková ◽  
Ivan Bičík ◽  
Zdeněk Boudný
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Cover Changes ◽  
Land Use Land Cover ◽  
Border Regions

Land Use Land Cover Change and Urban Growth in Khoms District, Libya, 1976−2015

2020 ◽  
Vol 11 (2) ◽  
pp. 42-58
Author(s):  
Omar S. Belhaj ◽  
Stanley T. Mubako
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Cover Change ◽  
Urban Growth ◽  
Qualitative Evaluation ◽  
Integrated Approach ◽  
Land Use Land Cover ◽  
Gis And Remote Sensing ◽  
Formidable Challenge

Rapid and unplanned urbanization presents a formidable challenge to sustainable urban growth in most developing countries. This study applies Geographic Information System (GIS) and remote sensing tools to quantify land use and land cover change in the coastal, economically important district of Khoms, Libya. The study revealed a 16% per year long-term historic urban growth rate, leading to an urbanization increase of 658% from just 800 ha in 1976 to 6,067 ha in 2015 over the 40-year analysis period. Qualitative evaluation of satellite images showed devastating impacts on both terrestrial and marine ecosystems through broad scale clearing of forests and other native areas for agriculture and urban development, and through reclamation of the Mediterranean Sea during the construction of a naval base and port at Khoms City. An integrated approach that explores of a range of innovative approaches to address sustainable development issues faced by Khoms District and other similar fast growing but environmentally fragile developing country locations is recommended.

Detection of land use-land cover changes in Anzali Wetland using a remote sensing-based approach

2021 ◽  
Author(s):  
Amirmoez Jamaat ◽  
Ammar Safaie
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Caspian Sea ◽  
Satellite Image ◽  
Land Cover Changes ◽  
Land Use Land Cover ◽  
Anzali Wetland ◽  
High Resolution Satellite Images

&lt;p&gt;Wetlands are valuable ecological resources which play an essential and important role in the ecosystem of the region. Hence, there is a crucial need for monitoring and characterization of wetland changes caused by natural and anthropogenic disturbance. In this study, we developed a remote sensing-based approach to investigate long term land use/land cover changes (LULC) of Anzali Lagoon located in the southern coast of the Caspian Sea. In recent years, Anzali Wetland has experienced severe threats by human- and climate-induced changes and is drying up at an alarming rate. Here, an enhanced LULC change detection method&amp;#160;is presented using a seasonal harmonic analysis of satellite image based on Normalized Difference Vegetation Index (NDVI) &amp;#160;&amp;#160;that combined with remotely-sensed thermal observations. Machine learning and object-oriented approaches were implemented on high-resolution satellite images to obtain&amp;#160;a comprehensive&amp;#160;land-use classification map of the study area. Then, wetland vegetation changes, such as marshes, were investigated during 2013 to 2020. Additionally, the long-term sea level trend in Caspian Sea was used, along with groundwater storage changes derived by GRACE satellite data, to study their impacts on wetland ecological changes. Results of the developed hybrid model indicate that the western and central parts of the wetland are more subjected to drought stress. Moreover, spatial and temporal changes in density of aquatic plants related to external stressors were identified in the wetland. The results of this study enhance a better understanding of long-term LULC changes in coastal wetlands in response to climate changes and anthropogenic activities.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;

scholarly journals Land Use/Land Cover Change and Its Driving Forces in Shenkolla Watershed, South Central Ethiopia

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Belayneh Bufebo ◽  
Eyasu Elias
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Land Cover ◽  
Agricultural Land ◽  
Driving Forces ◽  
Land Cover Changes ◽  
Land Use Land Cover ◽  
Forest Land ◽  
Central Ethiopia ◽  
South Central

Land use change is one of the challenges that aggravate environmental problems. Understanding the scope of land use change, driving forces, and consequences is very crucial for proper management of land resources. We investigated land use/land cover changes using remote sensing data (for the years 1973, 1995, and 2017), and field observation, household survey, key informant interview, and focus group discussion were used to determine the drivers and consequences of land use/land cover changes in Shenkolla watershed, south central Ethiopia. Unsupervised and supervised classification techniques were employed to get thematic information from satellite imagery. ArcGIS 10.3 and QGIS v 3.0 softwares were used to accomplish the analysis. The results disclosed that Shenkolla watershed has changed significantly during the past 4 decades between 1973 and 2017. This observed change indicates a reduction in forest land and an increase in agricultural land. Forest land was reduced from 29.51% in 1973 to 20.52% in 2017, but agricultural land was expanded from 70.49% in 1973 to 79.48% in 2017. Agricultural expansion, policy change and social unrest, population pressure, shortage of farm land, and biophysical factors were major driving forces of the LU/LC changes. Environmental implications such as climate change, biodiversity loss, scarcity of basic forest products, habitat alteration, decline in quality and availability of water, and crop yield reduction are the consequences of the LU/LC change. The expansion of agricultural land at the expense of forest cover in Shenkolla watershed has negative implications on the natural resources and the livelihood of local people. Hence, appropriate measures need to be employed to reduce the dramatic change in land use and to harmonize environmental conservation with human livelihood.

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