Trend Analysis of Las Vegas Land Cover and Temperature Using Remote Sensing

Abstract

The Las Vegas urban area expanded rapidly during the last two decades. In order to understand the impacts on the environment, it is imperative that the rate and type of urban expansion is determined. Remote sensing is an efficient and effective way to study spatial change in urban areas and Spectral Mixture Analysis (SMA) is a valuable technique to retrieve subpixel landcover information from remote sensing images. In this research, urban growth trends in Las Vegas are studied over the 1990 to 2010 period using images from Landsat 5 Thematic Mapper (TM) and National Agricultural Imagery Program (NAIP). The SMA model of TM pixels is calibrated using high resolution NAIP classified image. The trends of land cover change are related to the land surface temperature trends derived from TM thermal infrared images. The results show that the rate of change of various land covers followed a linear trend in Las Vegas. The largest increase occurred in residential buildings followed by roads and commercial buildings. Some increase in vegetation cover in the form of tree cover and open spaces (grass) is also seen and there is a gradual decrease in barren land and bladed ground. Trend analysis of temperature shows a reduction over the new development areas with increased vegetation cover especially, in the form of golf courses and parks. This research provides a useful insight about the role of vegetation in ameliorating temperature rise in arid urban areas.

Remote Sensing Data Processing of Urban Land Using Based on Artificial Neural Network

“…It is composed of a Sigmoid function and a matrix operation. e calculation process of the forgets is shown in (7), where W f is the weight matrix of the forget gate, and b f is the bias matrix of the forget gate.…”

“…It is also meaningful for the development of the country to grasp and predict information such as land utilization and coverage in a timely manner [6]. Reasonable urban land use classification plays an important role in urban infrastructure planning, socioeconomic improvement, natural disaster prevention, and crisis management [7]. However, we consume a lot of manpower and physics every 10 years to carry out intensive urban land use surveys.…”

Opportunities and Challenges of Spaceborne Sensors in Delineating Land Surface Temperature Trends: A Review

“…To study the urban impact on LST, 16 images were used in obo-Dioulasso (Burkina Faso, Sub-Shaharan Africa) over 22 years (1991-2013) [83], 11 images in the semi-arid city Erbil, Iraq over 21 years (1992-2013) [84], and two images in Changchun, China over 12 years (1993-2005) [85]. Also, LST trend analysis was performed in urban areas (cities) in Ghana [86], India [87], Iran [88], Thailand [89], and the USA [90,91] using variable numbers of Landsat images in the study periods, i.e., three in six, eight (two in each year) in 30, four in 30, six in 10, and 53 in five years, respectively. Other studies performed LST trends in finding relationships with LULC-Land Use Land Cover changes [92,93], forest cover changes [94], and changes in NDVI-Normalized Difference Vegetation Index [95]- [97] and green roof [98].…”