Landscape Influences on Stream Habitats and Biological Assemblages

2006 ◽  
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Benthic Invertebrate ◽  
Base Flow ◽  
Flow Index ◽  
Physical Habitat ◽  
Land Use Land Cover ◽  
Surficial Geology ◽  
Impervious Cover ◽  
Base Flow Index

<em>Abstract.</em>—–We demonstrate the effects of percent impervious cover (PIC) on biophysical properties of Lake Ontario tributary streams. Biophysical data (fish assemblages, benthic invertebrate assemblages (benthos), instream physical habitat, and temperature) were collected from more than 575 wadeable stream sites. A geographic information system application was developed to characterize the landscape upstream of each site (i.e., drainage area, surficial geology, land use/land cover, slope, stream length, and climate). Total PIC of catchments was estimated from land use/land cover, and a base flow index was derived from the surficial geology. The relationship between PIC and biophysical responses was determined after statistically removing the effects of natural landscape features (i.e., catchment area, slope, base flow index) on those responses. Contrasts in PIC from natural conditions (<3% to 10%) were related to variations in fish and benthos assemblages. Both coldwater sensitive and warmwater tolerant fish and diverse benthos assemblages were found in catchments with low PIC. At more than 10 PIC (i.e., about 50% urban), both fish and benthos consisted of mainly warmwater or tolerant assemblages. For example, trout were absent and minnows were dominant. While some of the apparent PIC effect may have been confounded by land use/land cover and surficial geology, the consistency of the findings even after natural catchment conditions were considered suggests that the threshold response is valid. Percent impervious cover had a weaker effect on instream geomorphic variables than on biological variables. The models derived from this study can be used to predict stream biophysical conditions for catchments with varying levels of development.

scholarly journals Fully Convolutional Neural Network for Impervious Surface Segmentation in Mixed Urban Environment

2021 ◽  
Vol 87 (2) ◽  
pp. 117-123
Author(s):  
Joseph McGlinchy ◽  
Brian Muller ◽  
Brian Johnson ◽  
Maxwell Joseph ◽  
Jeremy Diaz
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Area Under The Curve ◽  
Band Model ◽  
Land Use Land Cover ◽  
Residential Areas ◽  
High Resolution Data ◽  
Impervious Cover ◽  
Surface Segmentation ◽  
Improved Performance

The urgency of creating appropriate, high-resolution data products such as impervious cover information has increased as cities face rapid growth as well as climate change and other environmental challenges. This work explores the use of fully convolutional neural networks (FCNNs )—specifically UNet with a ResNet-152 encoder—in mapping impervious surfaces at the pixel level from WorldView-2 in a mixed urban/residential environment. We investigate three-, four-, and eight-band multispectral inputs to the FCNN. Resulting maps are promising in both qualitative and quantitative assessment when compared to automated land use/land cover products. Accuracy was assessed by F1 and average precision (AP) scores, as well as receiver operating characteristic curves, with area under the curve (AUC ) used as an additional accuracy metric. The four-band model shows the highest average test-set accuracies (F1, AP, and AUC of 0.709, 0.82, and 0.807, respectively), with higher AP and AUC than the automated land use/land cover products, indicating the utility of the blue-green-red-infrared channels for the FCNN. Improved performance was seen in residential areas, with worse performance in more densely developed areas.

Impact of Urbanization on Land Use/Land Cover — Case Study: The Western Part of Khartoum State, Sudan

2017 ◽  
Vol 04 (03) ◽  
pp. 272-277
Author(s):  
Tawhida A. Yousif ◽  
Nancy I. Abdalla ◽  
El-Mugheira M. Ibrahim ◽  
Afraa M. E. Adam
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Use Land Cover ◽  
Impact Of Urbanization

Analysis of Land Use/Land Cover Change in Yangzhou City Based on CLUE-S Model

2011 ◽  
Vol 13 (5) ◽  
pp. 695-700
Author(s):  
Zhihua TANG ◽  
Xianlong ZHU ◽  
Cheng LI
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Cover Change ◽  
Land Use Land Cover ◽  
S Model

Analysis of Land Use Land Cover in Annapurna Conservation Area in Gandaki Province, Nepal using Vegetation Index and Land Use Land Cover Datasets

2019 ◽  
Vol 2 (2) ◽  
pp. 87-99
Author(s):  
Shiva Pokhrel ◽  
Chungla Sherpa
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Vegetation Index ◽  
National Level ◽  
Climate Mitigation ◽  
Land Use Land Cover ◽  
Conservation Area ◽  
Barren Land ◽  
Wide Range ◽  
Annapurna Conservation Area

Conservation areas are originally well-known for protecting landscape features and wildlife. They are playing key role in conserving and providing a wide range of ecosystem services, social, economic and cultural benefits as well as vital places for climate mitigation and adaptation. We have analyzed decadal changes in land cover and status of vegetation cover in the conservation area using both national level available data on land use land cover (LULC) changes (1990-2010) and normalized difference vegetation index (NDVI) (2010-2018) in Annapurna conservation area. LULC showed the barren land as the most dominant land cover types in all three different time series 1990, 2000 and 2010 with followed by snow cover, grassland, forest, agriculture and water body. The highest NDVI values were observed at Southern, Southwestern and Southeastern part of conservation area consisting of forest area, shrub land and grassland while toward low to negative in the upper middle to the Northern part of the conservation area.

Optical and Radar Data Analysis for Land Use Land Cover Mapping in Peru

2019 ◽  
Vol 3 (1) ◽  
pp. 14-27
Author(s):  
Barry Haack ◽  
Ron Mahabir
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Window Size ◽  
Radar Data ◽  
Optical Data ◽  
Land Cover Mapping ◽  
Land Use Land Cover ◽  
Texture Image ◽  
Site Class ◽  
Spectral Signatures

This analysis determined the best individual band and combinations of various numbers of bands for land use land cover mapping for three sites in Peru. The data included Landsat Thematic Mapper (TM) optical data, PALSAR L-band dual-polarized radar, and derived radar texture images. Spectral signatures were first obtained for each site class and separability between classes determined using divergence measures. Results show that the best single band for analysis was a TM band, which was different for each site. For two of the three sites, the second best band was a radar texture image from a large window size. For all sites the best three bands included two TM bands and a radar texture image. The original PALSAR bands were of limited value. Finally upon further analysis it was determined that no more than six bands were needed for viable classification at each study site.

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