Effects of Urbanization on Stream Ecosystems

2005 ◽  
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Geographical Information Systems ◽  
Reference Conditions ◽  
Ordinary Least Squares ◽  
Urban Land ◽  
Limiting Factor ◽  
Physical Habitat ◽  
Santa Clara Valley ◽  
Biological Responses

<em>Abstract.</em>—Lotic habitats in urban settings are often more modified than in other anthropogenically influenced areas. The extent, degree, and permanency of these modifications compromise the use of traditional reference-based study designs to evaluate the level of lotic impairment and establish restoration goals. Directly relating biological responses to the combined effects of urbanization is further complicated by the nonlinear response often observed in common metrics (e.g., Ephemeroptera, Plecoptera, and Trichoptera [EPT] species richness) to measures of human influence (e.g., percentage urban land cover). A characteristic polygonal biological response often arises from the presence of a generalized limiting factor (i.e., urban land use) plus the influence of multiple additional stressors that are nonuniformly distributed throughout the urban environment. Benthic macroinvertebrates, on-site physical habitat and chemistry, and geographical information systems– derived land cover data for 85 sites were collected within the 1,600-km2 Santa Clara Valley (SCV), California urban area. A biological indicator value was derived from EPT richness and percentage EPT. Partitioned regression was used to define reference conditions and estimate the degree of site impairment. We propose that an upper-boundary condition (factor-ceiling) modeled by partitioned regression using ordinary least squares represents an attainable upper limit for biological condition in the SCV area. Indicator values greater than the factor-ceiling, which is monotonically related to existing land use, are considered representative of reference conditions under the current habitat conditions imposed by existing land cover and land use.

scholarly journals Risk Assessment of Future Climate and Land Use/Land Cover Change Impacts on Water Resources

Hydrology ◽  
2021 ◽  
Vol 8 (1) ◽  
pp. 38
Author(s):  
Nick Martin
Keyword(s):  
Risk Assessment ◽  
Land Use ◽  
Water Resources ◽  
Land Cover ◽  
Water Balance ◽  
Water Availability ◽  
Reference Conditions ◽  
Weather Generator ◽  
Future Climate ◽  
Lulc Change

Climate and land use and land cover (LULC) changes will impact watershed-scale water resources. These systemic alterations will have interacting influences on water availability. A probabilistic risk assessment (PRA) framework for water resource impact analysis from future systemic change is described and implemented to examine combined climate and LULC change impacts from 2011–2100 for a study site in west-central Texas. Internally, the PRA framework provides probabilistic simulation of reference and future conditions using weather generator and water balance models in series—one weather generator and water balance model for reference and one of each for future conditions. To quantify future conditions uncertainty, framework results are the magnitude of change in water availability, from the comparison of simulated reference and future conditions, and likelihoods for each change. Inherent advantages of the framework formulation for analyzing future risk are the explicit incorporation of reference conditions to avoid additional scenario-based analysis of reference conditions and climate change emissions scenarios. In the case study application, an increase in impervious area from economic development is the LULC change; it generates a 1.1 times increase in average water availability, relative to future climate trends, from increased runoff and decreased transpiration.

scholarly journals Urban Bare Land Classification Using NDBaI Index Based on Combination of Sentinel 2 MSI and Landsat 8 Multiresolution Images

2020 ◽  
Vol 36 (2) ◽  
Author(s):  
Trinh Le Hung
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Satellite Image ◽  
Urban Land ◽  
Landsat 8 ◽  
Land Classification ◽  
Infrared Band ◽  
Urban Land Cover ◽  
Bare Land ◽  
Sentinel 2

The classification of urban land cover/land use is a difficult task due to the complexity in the structure of the urban surface. This paper presents the method of combining of Sentinel 2 MSI and Landsat 8 multi-resolution satellite image data for urban bare land classification based on NDBaI index. Two images of Sentinel 2 and Landsat 8 acquired closely together, were used to calculate the NDBaI index, in which sortware infrared band (band 11) of Sentinel 2 MSI image and thermal infrared band (band 10) of Landsat 8 image were used to improve the spatial resolution of NDBaI index. The results obtained from two experimental areas showed that, the total accuracy of classifying bare land from the NDBaI index which calculated by the proposed method increased by about 6% compared to the method using the NDBaI index, which is calculated using only Landsat 8 data. The results obtained in this study contribute to improving the efficiency of using free remote sensing data in urban land cover/land use classification.

scholarly journals An Analysis of Urban Land Use/Land Cover Changes in Blantyre City, Southern Malawi (1994–2018)

2020 ◽  
Vol 12 (6) ◽  
pp. 2377 ◽  
Author(s):  
John Mawenda ◽  
Teiji Watanabe ◽  
Ram Avtar
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Urban Land ◽  
Urban Land Use ◽  
Sustainable Growth ◽  
Sub Saharan Africa ◽  
Support Vector ◽  
Land Use Land Cover ◽  
Lulc Changes ◽  
Bare Land

Rapid and unplanned urban growth has adverse environmental and social consequences. This is prominent in sub-Saharan Africa where the urbanisation rate is high and characterised by the proliferation of informal settlements. It is, therefore, crucial that urban land use/land cover (LULC) changes be investigated in order to enhance effective planning and sustainable growth. In this paper, the spatial and temporal LULC changes in Blantyre city were studied using the integration of remotely sensed Landsat imageries of 1994, 2007 and 2018, and a geographic information system (GIS). The supervised classification method using the support vector machine algorithm was applied to generate the LULC maps. The study also analysed the transition matrices derived from the classified map to identify prominent processes of changes for planning prioritisation. The results showed that the built-up class, which included urban structures such as residential, industrial, commercial and public installations, increased in the 24-year study period. On the contrary, bare land, which included vacant lands, open spaces with little or no vegetation, hilly clear-cut areas and other fallow land, declined over the study period. This was also the case with the vegetation class (i.e., forests, parks, permanent tree-covered areas and shrubs). The post-classification results revealed that the LULC changes during the second period (2007–2018) were faster compared to the first period (1994–2007). Furthermore, the results revealed that the increase in built-up areas systematically targeted the bare land and avoided the vegetated areas, and that the vegetated areas were systematically cleared to bare land during the study period (1994–2018). The findings of this study have revealed the pressure of human activities on the land and natural environment in Blantyre and provided the basis for sustainable urban planning and development in Blantyre city.

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