THE PRICE OF COMFORT:HOW LANDSCAPE AND ARCHITECTURAL DESIGN CAN REDUCE HUMAN DEPENDENCE ON CLIMATE CONTROL

INTRODUCTION In the development of modern sustainable construction there has been a focus on technological solutions.One of the most effective ways to diminish one’s carbon footprint is through reducing residential energy consumption.A simple yet overlooked component of residential energy reduction is to better acclimate people to their local environments.Since the advent of engineered climate control in the mid-20th century,the majority of Americans have“forgotten”how to live with their local climate conditions.This study examines from both quantitative and qualitative perspectives how acclimation via landscape and architecture design interventions can reduce residential energy use.Within a variety of climates in California,it conducts a cost-benefit analysis of reducing enclosed residential square footage to quantify the savings in construction and energy costs.

Impact of chilling accumulation and hydrogen cyanamide on floral organ development of sweet cherry in a warm region

The microscopic investigation of the floral development of sweet cherry（Prunus avium L. cv. Hongdeng） from a warm winter climate（Shanghai） and cold winter climate（Tai＇an, Shandong Province, China） was conducted to explore the reason of low fruit set. The effect of hydrogen cyanamide（HCN） on floral development under warm winter conditions was also investigated. Trees grown in Shanghai with insufficient chilling accumulation exhibited little difference in the progression of microspore development compared to trees in Tai＇an that accumulated adequate chilling, but showed substantial delays in ovule and embryo sac development. The growth of nucelli did not proceed beyond the macrospore mother cell and macrospore stages with abortion rates of 13, 15 and 45% by 6, 3 and 0 d before full bloom, respectively. These abnormalities in the ovule and embryo sac in the Shanghai-grown trees were eliminated by HCN application. These results suggest that chilling regulates the development of female floral organs in winter dormancy; therefore, insufficient chilling accumulation, causing abnormality of the female floral organs, restricts the cultivation of sweet cherry in warm winter regions. Interestingly, HCN application, which decreased the chilling requirements for Hongdeng, may be a potential strategy for sweet cherry cultivation in warm winter regions.

The Accuracy of GIS Tools for Transforming Assumed Total Station Surveys to Real World Coordinates

Most surveying works for mapping or GIS applications are performed with total station. Due to the remote nature of many of the sites surveyed, the surveys are often done in unprojected, local, assumed coordinate systems. However, without the survey data projected in real world coordinates, the range of possible analyses is limited and the value of existing imagery, elevation models, and hydrologic layers cannot be exploited. This requires a transformation from the local assumed to the real world coordinate systems. There are various built-in and add-in tools to perform transformations through GIS programs. This paper studies the effect of using Georeferencing tool, Spatial Adjustment tool (Affine and similarity) and CHaMP tool on the precision and relative accuracy of total station survey. This transformation requires real-world coordinates of at least two control points, which can be collected from different sources. This paper also studies the effect of using geodetic GPS, hand-held GPS, Google Earth (GE) and Bing Basemaps as sources for control points on the precision and relative accuracy of total station survey. These effects have been tested by using 111 points covered area of 60,000 m2and the results have shown that the CHaMP tool is the best for preserving the relative accuracy of the transformed points. The Georeferencing and spatial adjustment (similarity) tools give the same results and their accuracy are between 1/1000 and 1/300 depending on the source of control points. The results have also shown that the cornerstone to preserve the precision and relative accuracy of the transformed coordinates is the relative position of the control points despite their source.

Low Complexity Encoder with Multilabel Classification and Image Captioning Model

Due to the advanced development in the multimedia-on-demandtraffic in different forms of audio, video, and images, has extremely movedon the vision of the Internet of Things (IoT) from scalar to Internet ofMultimedia Things (IoMT). Since Unmanned Aerial Vehicles (UAVs) generates a massive quantity of the multimedia data, it becomes a part of IoMT,which are commonly employed in diverse application areas, especially forcapturing remote sensing (RS) images. At the same time, the interpretationof the captured RS image also plays a crucial issue, which can be addressedby the multi-label classification and Computational Linguistics based imagecaptioning techniques. To achieve this, this paper presents an efficient lowcomplexity encoding technique with multi-label classification and image captioning for UAV based RS images. The presented model primarily involves thelow complexity encoder using the Neighborhood Correlation Sequence (NCS)with a burrows wheeler transform (BWT) technique called LCE-BWT forencoding the RS images captured by the UAV. The application of NCS greatlyreduces the computation complexity and requires fewer resources for imagetransmission. Secondly, deep learning (DL) based shallow convolutional neural network for RS image classification (SCNN-RSIC) technique is presentedto determine the multiple class labels of the RS image, shows the novelty ofthe work. Finally, the Computational Linguistics based Bidirectional EncoderRepresentations from Transformers (BERT) technique is applied for imagecaptioning, to provide a proficient textual description of the RS image. Theperformance of the presented technique is tested using the UCM dataset. Thesimulation outcome implied that the presented model has obtained effectivecompression performance, reconstructed image quality, classification results,and image captioning outcome.

Determination of Potential Runoff Coefficient Using GIS and Remote Sensing

Flash floods in arid environments are a major hazard feature to human and to the infrastructure. Shortage of accurate environmental data is main reason for inaccurate prediction of flash flooding characteristics. The curve number (CN) is a hydrologic number used to describe the storm water runoff potential for drainage area. This study introduces an approach to determine runoff coefficient in Jeddah, Saudi Arabia using remote sensing and GIS. Remote sensing and geographic information system techniques were used to obtain and prepare input data for hydrologic model. The land cover map was derived using maximum likelihood classification of a SPOT image. The soil properties (texture and permeability) were derived using the soil maps published my ministry of water and agriculture in Saudi Arabia. These soil parameters were used to classify the soil map into hydrological soil groups (HSG). Using the derived information within the hydrological modelling system, the runoff depth was predicted for an assumed severe storm scenario. The advantages of the proposed approach are simplicity, less input data, one software used for all steps, and its ability to be applied for any site. The results show that the runoff depth is directly proportional to runoff coefficient and the total volume of runoff is more than 136 million cubic meters for a rainfall of 103.6 mm.

Flood Risk Code Mapping Using Multi Criteria Assessment

Flash flood is a dangers natural disaster causes lots of structure damage, traffic collapse, economic defects and human life loss. An efficient way to reduce its effects is preparing flash flood mapping to identify zones at risk due to flood. Flash flood mapping is a powerful tool for urban planners, traffic and infrastructure engineers, emergency and rescue services. This article proposes an approach utilizes remote sensing (RS) and geographic information system (GIS) to prepare flood risk code (FRC) map for Jeddah city, Saudi Arabia. The proposed approach applied the Curve Number (CN) method of flood modelling and uses runoff depth, land use, soil hydrological parameters, surface slope, and longest flow path to generate FRC. SPOT satellite image of the study area was classified to generate land use map, Digital Elevation Model (DEM) was used for generating slope map and for hydrology analysis using HEC-GeoHMS tool, and soil properties were generated from scanned soil maps. All data were integrated in ArcGIS 10.4.1 to prepare the final flood risk map. The results show that a precipitation of 106.3 mm will generate 136.5 million m3 of flood water. The results according to the developed flood risk code show that due to this amount of precipitation, about 1 million people live in Jeddah are prone to extreme flood risk and about 2 million of population are at major risk, the rest of population (about 0.5 million) are vulnerable to moderate to minor fold risk. The approach was verified using ground truth data and proofed precision.

Alternative Solutions for RTK-GPS Applications in Building and Road Constructions

Currently, Global Positioning System (GPS) techniques are becoming a much larger part of the surveying industry. Many companies are now using GPS in their everyday work activities. The Real Time Kinematic (RTK) positioning is an integral part of topographic surveys, road surveying, constructions and most civil engineering applications. Normally, RTK can be used to collect the positioning data successfully and quickly. The civil and construction projects are designed in ground distances while RTK measurements are done in grid coordinate system, in which the distances between points are different from ground. The RTK measurements should be converted to ground for compatibility with the designed. In this paper, the accuracy of three alternatives for converting RTK measurements to ground was studied. These alternatives are, using scale factor, using two ground reference points and using Low Distortion Projection (LDP) surface. For the accuracy investigation purpose, a traverse of 14 points elongated for a distance of about 1400 m was constructed. Its coordinates were measured using total station, then the misclosure error was computed and the coordinates were adjusted. The traverse points coordinates were measured again using RTK_GPS considering one of them as base point. The three studied alternatives were applied and the results were compared. The results show that the accuracy of the three alternatives is ranging from 2.1 to 2.9 cm in the relative position of points to the base point. For absolute position accuracy, the two ground reference points alternative is the most accurate alternative with an average error of 3.8 cm while the other two alternatives are almost the same with an average error of 12.3 cm.

乌克兰卡霍夫卡大坝损毁的多维度影响评估

Water plays a central role in sustaining a thriving human society. Given its immense importance, safeguarding the related water infrastructure such as dams and reservoirs, which ensures the proper functioning of water ecosystem, becomes crucial.

EFFECT OF SUBSTRATE DEPTH AND TYPE ON PLANT GROWTH FOR EXTENSIVE GREEN ROOFS IN A MEDITERRANEAN CLIMATE

Although numerous examples of green roofs can be found in Turkey,limited research has been conducted on plant material and substrate type in this climate.Both plants and substrate are very important components in green roof design,it is essential to determine the proper substrates and plants in green roof systems for domestic green roof design.Two types of growing substrates:a commercial substrate consisting of crushed brick and clay(45%),pumice(45%),and organic matter(10%),and a recycled substrate including 90%coarse pumice(10-20 mm)and municipal compost(10%),were tested in three depths of 4,7 and 10 cm.Tested plant species included Achillea millefolium,Armeria maritima,Sedum acre and Sedum album.Overall,the commercial substrate performed better than the recycled pumice.In addition,deeper substrates promoted greater survival and growth for nearly all species tested.Either A.maritima or A.millefolium survived in the recycled pumice at any depth,whereas they did survive when grown in the commercial substrate in greater than 7 cm and 10 cm,respectively.They both likely would require supplemental irrigation to be acceptable for green roofs in Istanbul or locations with a similar climate.Both Sedum species survived in all substrate types and depths.Information gained can be utilized by green roof professionals in the Istanbul region and in other parts of the world with a similar climate.

Impact of climate change on dengue fever epidemics in South and Southeast Asian settings:A modelling study

The potential for dengue fever epidemic due to climate change remains uncertain in tropical areas.This study aims to assess the impact of climate change on dengue fever transmission in four South and Southeast Asian settings.We collected weekly data of dengue fever incidence,daily mean temperature and rainfall from 2012 to 2020 in Singapore,Colombo,Selangor,and Chiang Mai.Projections for temperature and rainfall were drawn for three Shared Socioeconomic Pathways(SSP126,SSP245,and SSP585)scenarios.Using a disease transmission model,we projected the dengue fever epidemics until 2090s and determined the changes in annual peak incidence,peak time,epidemic size,and outbreak duration.A total of 684,639 dengue fever cases were reported in the four locations between 2012 and 2020.The projected change in dengue fever transmission would be most significant under the SSP585 scenario.In comparison to the 2030s,the peak incidence would rise by 1.29 times in Singapore,2.25 times in Colombo,1.36 times in Selangor,and>10 times in Chiang Mai in the 2090s under SSP585.Additionally,the peak time was projected to be earlier in Singapore,Colombo,and Selangor,but be later in Chiang Mai under the SSP585 scenario.Even in a milder emission scenario of SSP126,the epidemic size was projected to increase by 5.94%,10.81%,12.95%,and 69.60%from the 2030se2090s in Singapore,Colombo,Selangor,and Chiang Mai,respectively.The outbreak durations in the four settings were projected to be prolonged over this century under SSP126 and SSP245,while a slight decrease is expected in 2090s under SSP585.The results indicate that climate change is expected to increase the risk of dengue fever transmission in tropical areas of South and Southeast Asia.Limiting greenhouse gas emissions could be crucial in reducing the transmission of dengue fever in the future.

Design of hospital healing gardens linked to pre- or post-occupancy research findings

This work examined the evidence-based design （EBD） and post-occupancy research of hospital healing gardens. The lack of statutory design guidelines raises concerns on how such gardens are created and whether they meet the intended design purpose. This issue is particularly important for hospitals because a neutral or even a negative effect on users can be generated. A systematic analysis of the literature in two databases （Scopus and Web of Science） was undertaken. Results showed that pre- and post-occupancy research findings on hospital healing garden design are sparse and design recommendations vary among users. Despite the tack of research on the design of healing gardens, the review showed that while post-occupancy research findings evaluate the effectiveness of design recommendations, pre-occupancy research findings, combined with site analysis, constitute a traditional approach followed in landscape architecture practice and determine the site and user features that must be addressed for each hospital. Pre- and post-research findings must be considered in the design process to create a “successful” healing garden. A summary of EBD recommendations for different users is presented, and the need to enrich the existing amount of EBD recommenda-tions is highlighted.