California’s Coast

Coastal Sage ◽  
2017 ◽  
Author(s):  
Thomas J. Osborne
Keyword(s):  
Real Estate ◽  
Built Environment ◽  
Plate Tectonics ◽  
Rapid Development ◽  
California Current ◽  
Gold Rush ◽  
Southern California Bight ◽  
Public Concern ◽  
Franciscan Complex ◽  
Spanish Missions

The origins and natural features of California’s coast and seaward islands, which Douglas understood well, are surveyed, followed by a chronological overview of ever-increasing development from the Spanish missions of the late 18th century to the eve of passage of Proposition 20 in 1972. Plate tectonics, the Southern California Bight, the California Current, the Franciscan Complex, El Niño, and more are explained in the first part of this chapter. The built environment, spurred by the gold rush and followed by real estate booms, population explosion, urbanization, and industrialization, is taken up in the last half of the chapter. Rapid development along California’s scenic shore set the stage for a rising public concern about a vanishing coast.

scholarly journals Information Spillover Effects of Real Estate Markets: Evidence from Ten Metropolitan Cities in China

2021 ◽  
Vol 14 (6) ◽  
pp. 244
Author(s):  
Junjie Li ◽  
Li Zheng ◽  
Chunlu Liu ◽  
Zhifeng Shen
Keyword(s):  
Real Estate ◽  
Rapid Development ◽  
House Price ◽  
Principal Component ◽  
Spillover Effects ◽  
Real Estate Markets ◽  
The Real ◽  
The Real Estate ◽  
Information Interaction ◽  
Information Spillover

With the rapid development of information communication technology and the Internet, information spillover between cities in real estate markets is becoming more frequent. The influence of information spillover in real estate markets is becoming more and more prominent. However, the current research of information spillover between cities is still relatively insufficient. In view of this research gap, this paper builds a research framework on the information conduction effect in the real estate markets of 10 Chinese cities by using Baidu search data, text mining and principal component analysis and analyzes the information interaction and dynamic influence of the real estate markets in each city by using the vector autoregressive model empirically. The results show that the information interaction among the real estate markets in each city has a network pattern and there is a significant two-way information spillover effect in most cities. When the “information distance” becomes closer, the information interaction between the markets of the cities becomes closer and it is easier for cities to influence each other. The results help to explain the information spillover mechanism behind the house price spillover and to improve the ability to predict and analyze the information spillover process in real estate markets.

Research on the Design of Community Landscape Planning under Eco-House Perspective

2014 ◽  
Vol 716-717 ◽  
pp. 541-544
Author(s):  
Xu Dan Zhou ◽  
Chun Li Zhao ◽  
Yue Qi ◽  
Hao Qi ◽  
Da Wei Jiang
Keyword(s):  
Real Estate ◽  
Landscape Planning ◽  
Rapid Development ◽  
Landscape Design ◽  
Living Environment ◽  
Success Factor ◽  
The Real Estate ◽  
Planning And Design ◽  
Residential Quarter ◽  
Real Estate Developers

With the advent of the knowledge economy and the rapid development of information technology era, people's demand for the living environment has been far more than mere material comfort. In this paper, good landscape design for residential quarter not only provides appropriate living conditions for dweller, satisfies people's yearning for home, improves the quality of urban environment, but also is the main prerequisites which measure the green quality and management of the community. Landscape planning and design of residential environment exists failed plant landscape design, weak user-friendly design, ignoring landscape such as issues. We have identified the principles of landscape planning and design community, and allocation of green plants. It is the important weights that real estate developers sell their items, which is an important success factor that the real estate developers operate company, and people will pay more and more attention to the landscape design.

Salinity Variations in the Southern California Current*

2005 ◽  
Vol 35 (8) ◽  
pp. 1421-1436 ◽  
Author(s):  
Niklas Schneider ◽  
Emanuele Di Lorenzo ◽  
Pearn P. Niiler
Keyword(s):  
Large Scale ◽  
Southern California ◽  
Current System ◽  
California Current ◽  
Southern California Bight ◽  
Small Scale ◽  
Climate Indices ◽  
California Current System ◽  
The Mean ◽  
Salinity Variations

Abstract Hydrographic observations southwestward of the Southern California Bight in the period 1937–99 show that temperature and salinity variations have very different interannual variability. Temperature varies within and above the thermocline and is correlated with climate indices of El Niño, the Pacific decadal oscillation, and local upwelling. Salinity variability is largest in the surface layers of the offshore salinity minimum and is characterized by decadal-time-scale changes. The salinity anomalies are independent of temperature, of heave of the pycnocline, and of the climate indices. Calculations demonstrate that long-shore anomalous geostrophic advection of the mean salinity gradient accumulates along the mean southward trajectory along the California Current and produces the observed salinity variations. The flow anomalies for this advective process are independent of large-scale climate indices. It is hypothesized that low-frequency variability of the California Current system results from unresolved, small-scale atmospheric forcing or from the ocean mesoscale upstream of the Southern California Bight.

Gap analysis of green features in condominiums between potential homeowners and real estate agents

Facilities ◽  
2016 ◽  
Vol 34 (11/12) ◽  
pp. 630-648 ◽  
Author(s):  
Sui Pheng Low ◽  
Shang Gao ◽  
Ling Ling Grace Teo
Keyword(s):  
Real Estate ◽  
Built Environment ◽  
Environmental Sustainability ◽  
Carbon Dioxide Emissions ◽  
Energy Savings ◽  
Gap Analysis ◽  
Content Type ◽  
Awareness Campaigns ◽  
Real Estate Agents ◽  
The Government

Purpose The building sector is one of the main contributors to carbon dioxide emissions in Singapore. Over 90 per cent of life-cycle carbon emissions are due to the operations phase of buildings, and 90 to 98 per cent of the building cost is associated with operation, maintenance and personnel costs. Hence, occupants have a major role in achieving environmental sustainability objectives. This study aims to understand the awareness level of potential homeowners and real estate agents concerning environmental sustainability issues in the built environment, to identify the types of green features required by potential homeowners and to understand real estate agents’ perceptions of the types of green features required by the homeowners in a green condominium. Design/methodology/approach The features of the Green Mark (GM)-awarded buildings, as well as the benefits derived by homeowners were identified from the literature. A survey of a group of potential homeowners and real estate agents was carried out in Singapore to analyse the gap, if any, between the potential homeowners’ needs and expectations and real estate agents’ perceptions of these needs and expectations with respect to the green features in the homes. Findings The results indicate that potential homeowners are more aware of environmental sustainability issues in the built environment than are real estate agents; potential homeowners seem to be more supportive of environmentally sustainable development than the real estate agents are aware of, despite the fact that the price of the apartment remains an important deciding factor; and potential homeowners are more concerned about the ease of maintaining green homes and paying greater attention to green features in the areas most heavily promoted by the government. However, green features do not constitute the main considerations of potential homeowners when making the decision to buy a green home. Research limitations/implications To close the gaps identified in the analysis, recommendations are suggested, including having public education and awareness campaigns to emphasize the long-term energy savings of green homes, conducting GM courses for real estate agents and involving real estate agents in the developers’ project consultancy team. Originality/value As there has been no prior research in this area, this study serves to provide fresh perspectives on how developers can better select the types of green features to be included in the green homes, so as to meet the potential homeowners’ needs and expectations and, at the same time, balance mandatory GM requirements with such demands. Choosing the right type of green features to incorporate in a residential development for homeowners to utilize increases the owners’ satisfaction level and allows them to reap the intended benefits of green features.

Volume and Heat Budgets in the Coastal California Current System: Means, Annual Cycles, and Interannual Anomalies of 2014–16

2020 ◽  
Vol 50 (5) ◽  
pp. 1435-1453 ◽  
Author(s):  
Katherine D. Zaba ◽  
Daniel L. Rudnick ◽  
Bruce D. Cornuelle ◽  
Ganesh Gopalakrishnan ◽  
Matthew R. Mazloff
Keyword(s):  
Mixed Layer ◽  
Heat Budget ◽  
Current System ◽  
California Current ◽  
Southern California Bight ◽  
Heat Advection ◽  
California Current System ◽  
Annual Cycles ◽  
The Mean ◽  
Heat Budgets

AbstractThe data-assimilating California State Estimate (CASE) enables the explicit evaluation of spatiotemporally varying volume and heat budgets in the coastal California Current System (CCS). An analysis of over 10 years of CASE model output (2007–17) diagnoses the physical drivers of the CCS mean state, annual cycles, and the 2014–16 temperature anomalies associated with a marine heat wave and an El Niño event. The largest terms in the mean mixed layer (from−50 to 0 m) volume budgets are upward vertical transport at the coast and offshore-flowing ageostrophic Ekman transport at the surface, the two branches of the coastal upwelling overturning cell. Contributions from onshore geostrophic flow in the Southern California Bight and alongshore geostrophic convergence in the central CCS balance the mean volume budgets. The depth-dependent annual cycle of vertical velocity exhibits the strongest upward velocity between −40- and −30-m depth in April. Interannual volume budgets show that over 50% of the 2013.5–16.5 time period experienced downwelling anomalies, which were balanced predominantly by alongshore transport convergence and, less often, by onshore transport anomalies. Mixed layer temperature anomalies persisted for the entirety of 2014–16, reaching a maximum of +3° in October 2015. The mixed layer heat budget shows that intermittent high air–sea heat flux anomalies and alongshore and vertical heat advection anomalies all contributed to warming during 2014–16. A subsurface (from −210 to −100 m) heat budget reveals that in September 2015 anomalous poleward heat advection into the Southern California Bight by the California Undercurrent caused deeper warming during the 2015/16 El Niño.

Landscape Changes in the Andaman and Nicobar Islands (India) after the December 2004 Great Sumatra Earthquake and Indian Ocean Tsunami

2006 ◽  
Vol 22 (3_suppl) ◽  
pp. 43-66 ◽  
Author(s):  
Javed N. Malik ◽  
C. V. R. Murty ◽  
Durgesh C. Rai
Keyword(s):  
Indian Ocean ◽  
Built Environment ◽  
Plate Tectonics ◽  
Tsunami Wave ◽  
Indian Ocean Tsunami ◽  
Sumatra Earthquake ◽  
Landscape Changes ◽  
Andaman And Nicobar Islands ◽  
Nicobar Islands ◽  
Reconnaissance Surveys

Plate tectonics after the 26 December 2004 Great Sumatra earthquake resulted in major topological changes in the Andaman and Nicobar islands. Aerial and land reconnaissance surveys of those islands after the earthquake provide evidence of spectacular plate tectonics that took place during the earthquake. Initial submergence of the built environment and the subsequent inundation upon arrival of the tsunami wave, as well as emergence of the new beaches along the islands—particularly on the western rims of the islands and in the northern islands—are the major signatures of this Mw=9.3 event.

scholarly journals The Impact of Property Tax on the Development of Real Estate Industry

2021 ◽  
Vol 4 (3) ◽  
pp. 73-75
Author(s):  
Ruoke Hu ◽  
Fangke Li
Keyword(s):  
Real Estate ◽  
Rapid Development ◽  
Housing Prices ◽  
Property Tax ◽  
Real Estate Industry ◽  
High Property ◽  
The Real ◽  
The Real Estate ◽  
Significant Growth ◽  
The Impact

In recent years, due to the rapid development of the real estate industry in China, land speculation has begun in addition to the significant growth in economy. However, this rapid development has led to an extreme rise in housing prices, largely owing to high property tax. This article analyzed the impact of property tax on the development of real estate industry and provided countermeasures.

scholarly journals Estimating Warehouse Rental Price using Machine Learning Techniques

2018 ◽  
Vol 13 (2) ◽  
pp. 235-250 ◽  
Author(s):  
Yixuan Ma ◽  
Zhenji Zhang ◽  
Alexander Ihler ◽  
Baoxiang Pan
Keyword(s):  
Machine Learning ◽  
Random Forest ◽  
Real Estate ◽  
Rapid Development ◽  
Supply And Demand ◽  
Machine Learning Techniques ◽  
Gradient Boosting ◽  
Logistics Industry ◽  
Real Estate Price ◽  
Learning Techniques

Boosted by the growing logistics industry and digital transformation, the sharing warehouse market is undergoing a rapid development. Both supply and demand sides in the warehouse rental business are faced with market perturbations brought by unprecedented peer competitions and information transparency. A key question faced by the participants is how to price warehouses in the open market. To understand the pricing mechanism, we built a real world warehouse dataset using data collected from the classified advertisements websites. Based on the dataset, we applied machine learning techniques to relate warehouse price with its relevant features, such as warehouse size, location and nearby real estate price. Four candidate models are used here: Linear Regression, Regression Tree, Random Forest Regression and Gradient Boosting Regression Trees. The case study in the Beijing area shows that warehouse rent is closely related to its location and land price. Models considering multiple factors have better skill in estimating warehouse rent, compared to singlefactor estimation. Additionally, tree models have better performance than the linear model, with the best model (Random Forest) achieving correlation coefficient of 0.57 in the test set. Deeper investigation of feature importance illustrates that distance from the city center plays the most important role in determining warehouse price in Beijing, followed by nearby real estate price and warehouse size.

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