Using GIS as a decision making support tool for LEED ...

PLEA2016 Los Angeles - Cities, Buildings, People: Towards Regenerative Environments, 11-13 July, 2016

Using GIS as a decision making support tool for LEED credits LEED Location and Transportation and Sustainable Sites categories Walaa S.E. Ismaeel, Marwa Adel El Sayed, Marwa Dabaieh and Inji Kenawy Faculty of Architecture, The British University in Egypt, Sherouq city, Egypt

ABSTRACT: Green building rating systems are voluntary tools intended to promote sustainable building process through approaching several environmental issues that include sustainable design parameters related to the construction site and others related to its surrounding context. Decision making software support tools and methods are needed to guide practitioners on minimizing building’s environmental impact especially for early design decisions. Hence, the study shows how Geographic Information Systems (GIS) is used as a decision-making support tool for assessing location and transportation (LT) together with sustainable site (SS) categories for Leadership in Energy and Environmental Design (LEED) green building rating system. The methodology is applied on the 10th of Ramadan city in Egypt; creating land suitability analysis for these two LEED categories. The analysis considers sensitive land protection, high priority development sites, surrounding density and diverse uses, and access to quality transit on the context level. It also analyses lithology type and condition as well as habitat and open spaces protection on the site level. The result shows the potential role of integrating GIS analysis as a tool for site selection credits for LEED rating systems. This allows for more data integration to set a solid base for objective decision making process based on contextual conditions. The method can be generalized and applied in similar contexts in order to attract private investments for green construction especially in new development areas. Keywords: Decision making process, GIS, LEED, Predictive analysis, Location and Transportation, Sustainable Sites.

INTRODUCTION Building construction industry is recognised by having an increased impact on the environment in terms of energy and raw materials consumption, water use, resulting solid landfill waste and carbon dioxide emission (Newell, 2009). Reducing these effects has been a worldwide concern that encouraged different countries to develop green building rating systems, e.g. LEED, BREEAM, GBTool, CASBEE and GBCA provide guidelines to rate the performance of green buildings (Gou and Lau, 2014, and Ali and Al-Nsairat, 2009). The Leadership in Energy and Environmental Design (LEED) is considered one of the most widespread green building rating systems. LEED Building design and Construction (LEED BD+C) are specifically designed to provide a set of sustainable design guidelines, measurements and verification credits provide a rating for the performance of new building construction. The development process for the latest LEED versions can be seen in (Fig. 1). The figure shows that the sustainable categories covered along the V2.2 and V3.0 for LEED BD+C are: Sustainable Sites (SS), Water Efficiency (WE), Energy and Atmosphere (EA), Materials and Resources (MR), Indoor Environmental Quality (EQ),

Innovation in Design (ID), and Regional Priority (RP). While, the latest version (V4.0) has been developed to express the sustainability of the context under Location and Transportation (LT) category, as well as sustainability of the site itself under Sustainable Sites (SS) category as two separate categories.

Figure 1: Comparing the weight assigned for each LEED category along the latest LEED version development (Ismaeel,2014)

The Sustainable sites (SS) is a crucial category as it has a consecutive effect on optimizing the energy performance, minimizing the water use, selecting the sustainable material, as well as improving indoor environmental quality. Accordingly, early design decisions such as the site selection require particular

PLEA2016 Los Angeles - Cities, Buildings, People: Towards Regenerative Environments, 11-13 July, 2016

attention to optimize consecutive design decisions. Despite this importance, the study conducted by (Lavy et.al, 2009) indicated that LEED Sustainable Sites category has a comparatively lower average adoption rate of 54.9% when compared to other LEED categories, e.g. the adoption rates for the Water Efficiency, Indoor Environmental Quality, and the total average weighting are 58.2%, 70.7% and 55.4% respectively. However, with the complexity of the decision making process using new software programs is becoming essential to help making appropriate decisions along different phases in the building process. Among these multicriteria decisions making tools, is the Geographical Information Systems (GIS). This system can be used to support decisions related to the sustainability of the site as well as the sustainability of its surrounding context. There are several studies that used GIS in combination with LEED. The study conducted by Talen applied a methodological approach to identify which parcels are compliant with the Smart Location prerequisite for LEED Neighbourhood development (LEED-ND) rating system (Talen et al., 2013). A different study used an integrated approach to identify potential landfill sites using GIS software program (Bah & Rg, 2011). Another study by (Son et al., 2012) applied a quantifying model using GIS mapping technique to predict the unit value of improved lands by analysing the relation between three LEED SS credits‟ components and the appraised unit value of improved lands. While, limited studies used the weighted sum component analysis in mapping (Faraji Sabokbar et al., 2014) or used the indexing scheme for redevelopment planning based on LEED evaluation (Chrysochoou et al., 2012). On the other hand, limited studies are found in the Egyptian context discussing the limitation in the applicability of LEED system. The reason was related to ignoring regional considerations including climate, environmental and even cultural and economic aspects (Attia & Dabaieh, 2013). This is in addition to the existing drawbacks in the Egyptian building code, and the conflict between governmental and non-governmental organizations for adopting green building policies (Ismaeel & Rashed, 2015). Moreover, a recent comparative study highlights the most achieved and targeted LEED credits. It stated obtaining LEED SS credits are related to the project type and context (El Yamany, 2016). Hence, This study focuses on LEED LT and SS categories because generally new cities in Egypt are poorly developed in terms of lack of access to quality transit and green facilities, existing sensitive Land that need protection, as well as existing vacant and abandoned land which lacks proper sustainable development guidelines and management techniques. It is concerned with exploring how the GIS can be used for land suitability analysis to support the decision making

process for sustainable site selection and accordingly increase the adoption rate for LEED (V4.0) LT and SS categories. The study starts with analysing the existing LEED projects in Egypt under versions (V2.2, V3.0). Afterwards, it attempts to provide a predictive analysis for applying LEED (V4.0) -LT and SS categories on 10th of Ramadan, a new development city in Egypt. The outcome of the study can be used to identify potential land parcels for LEED LT and SS categories in new development areas for the sake of attracting private investors. STUDY OBJECTIVE AND CASE APPLICATION 10th of Ramadan city is one of the first generation of new satellite cities planned in Egypt, and one of the largest new industrial cities, located close to the city of Cairo. It hosts about 1400 factories with annual production of more than 75,42bn LE, employing about 188,166 workers and its population was estimated to be 260,000 in 2013 (GOPP, 2013). It was established as an integrated city with proximity of residential and work locations, and connected to the main surrounding cities like Cairo, Port Said, Ismailia and Suez. Yet, it suffers from limited services/facilities and unattractive housing developments which do not fulfill occupants‟ basic requirements. Moreover, it is considered one of the polluted industrial cities that did not follow its original strategic development criteria (GOPP, 2013). The Egyptian national strategy aims at putting clear guidelines and standards for the city development. Hence, it encourages development in vacant and abandoned land, and provides efficient intra and intercity connectivity to reduce commute time. This is in addition to promoting the concept of energy efficiency and applying continuous monitoring and follow up parameters, and finally, promoting waste management and recycling plans (GOPP, 2013). Also, it aims at promoting for the overall branding of the city as a green and smart city. The branding strategy should clearly stress on the quality of life, cost of living and environmental aspects. This is through adopting policies, incentives and strategies that encourage sustainable project development using ecofriendly technologies, and promoting environmental awareness into the local community. For this reason, the study attempts to encourage applying LEED green building rating system on the case study area, and focuses on sustainable site selection criteria acknowledging its importance in both national and local planning mechanisms. This shall enhance the attractiveness of the city as an investments destination through provision of world class investors, and create job opportunities. This shall also help the city to become a model for sustainable development of industrial cities

PLEA2016 Los Angeles - Cities, Buildings, People: Towards Regenerative Environments, 11-13 July, 2016

acting as an eco-focal point and landmark to propagate the positive character and image of the city. METHODOLOGY The study applies an investigative and predictive analytical mapping methodology divided into two phases. The first phase analyses the current LEED projects in Egypt in order to define the status quo considering applying LEED system in the Egyptian context. While, the second phase applies GIS as a decision making support tool for LEED LT and SS categories in 10th of Ramadan city located in the Sharqia governorate of Egypt. Along the two phases the study used Google earth online program to geographically locate LEED certified and registered projects in Egypt, and ArcGIS 10.1 software to create a database layering, geo-referencing maps, and used the GIS spatial analysis functions for performing the multi-criteria weighting and evaluation techniques. First Phase: Investigating LEED projects in Egypt This part of the study applies an investigative analysis for LEED projects in Egypt which has been recently introduced in 2010. It analyses the percentages of prevailing LEED types and versions, and highlights the adoption rate of LEED SS credits. According to the USGBC projects‟ directory, and till the time of writing this study, there are eight certified projects and sixteen registered ones. All projects are located in the metropolitan capital Cairo, with exception to one project located in Burj El Arab in Alexandria, as shown in (Fig. 2). All projects belong to private investments under different LEED types and versions.

Second Phase: Mapping LEED LT and SS credits’ requirements using GIS This part of the study produces land suitability analysis for LEED LT and SS categories using GIS application. It is considered a predictive analysis to enable multicriteria decision making process for site selection criteria. The study uses the vector data available for the case study, to create separate feature classes for each credit according to LEED requirements. Within a single raster layer, the decision maker can prioritize values in the following logic: YES (score: 2), MAYBE (score: 1), NO (score: 0) as shown in (Table 1 and 2) respectively. Table 1: GIS weighted overlay maps for LEED LT credits.

LT C2: Sensitive land protection Current land use Desert lands Vacant lands Public molds Military zones LT C3: High priority sites Infill lands Brownfields Vacant lands Rest of land LT C4: Surrounding density and diverse uses Combined densities Rest of land LT C5: Access to quality transit Proximity to public buses Rest of land LT C7: Reduce parking footprint Proximity to parking lots Rest of land LT C8: Green Vehicles Proximity to natural gas fueling stations Rest of land

Yes (2) × √ √ × × Yes (2) √ √ √ × Yes (2) × × Yes (2) √ × Yes (2) × × Yes (2) ×

Maybe (1) × × × √ √ Maybe (1) × × × × Maybe (1) √ × Maybe (1) × × Maybe (1) √ × Maybe (1) √

No (0) √ × × × × No (0) × × × √ No (0) × √ No (0) × √ No (0) × √ No (0) ×

×

×

√

Table 2: GIS weighted overlay maps for LEED SS credits.

Figure 2: Google earth map showing geographical location of LEED certified and registered buildings in Cairo.

SS C1: Site Assessment (Lithology) Graded Sand and Gravel intercalated by clay lensesNo pollution Graded Sand and Gravel intercalated by clay lensesWith pollution Graded Sand and Gravel intercalated by some clay- No

Yes (2) √

Maybe (1) ×

No (0) ×

×

×

√

√

×

×

PLEA2016 Los Angeles - Cities, Buildings, People: Towards Regenerative Environments, 11-13 July, 2016

pollution Graded Sand and Gravel Intercalated by some clay With pollution Sand and Gravel- No pollution Sandy Limestone - No pollution Sandy Limestone - With pollution Undifferentiated Quaternary Deposits - No pollution Undifferentiated Quaternary Deposits - With pollution SS C2: Site developmentProtect or restore habitat Forest Rest of the land SS C3: Open space Existing green areas Rest of the land

×

×

√

√

×

×

×

√

×

×

×

√

×

√

×

×

×

√

Yes (2) × × Yes (2) × ×

Maybe (1) × √ Maybe (1) √ ×

No (0) √ × No (0) × √

The vector feature classes are converted to raster feature ones using Weighted Sum tool in GIS. This tool provides the ability to weight and combine multiple inputs to create an integrated analysis. It is similar to the Weighted Overlay tool in that multiple raster inputs, representing multiple factors, can be easily combined incorporating weights of relative importance. The raster feature classes are grouped into ranges, and each range is assigned a single value. The cell values for each input in the analysis are multiplied by the evaluation scale that follows LEED credits‟ requirements. This enables performing arithmetic operations on raster feature classes. The default values can be assigned to each cell according to the suitability to LEED credits‟ requirements. Then, the influence of each raster is multiplied by its value of the raster feature class, then adding them together to create the resultant output weighted overlay. RESULT Based on the investigative phase of the study, it is found that the major number of LEED projects in Egypt are certified under LEED BD+C (60%), followed by LEED for Core and Shell (25%) as shown in (Fig. 3). It also shows that (83%) are certified under LEED 2009version 3.0 and only (17%) under LEED V2.2, and till the time of this study, there are no projects certified under LEED ND or the new LEED version (4.0) yet.

Figure 3: Analysing LEED projects in Egypt (Ismaeel and Rashed, 2015)

The comparative analysis shown in (Fig. 4) shows the relation between the number of certified projects obtaining the credit, and the relative weight of each credit. It shows that some LEED SS credits are more difficult to obtain than others, e.g. SS C3 (Brownfield Redevelopment) and SS C8 (Light Pollution Reduction) were not obtained by any of the certified buildings, while SS C1 (Site Selection), SS C4 (Alternative Transportation) and SS C7 (Heat Island Effect) were obtained by all the seven certified buildings1.

Figure 4: Comparative analysis for LEED SS credits for seven LEED certified buildings in Egypt

The weighted sum of LEED LT and SS categories are calculated and the land suitability analysis were transformed into the maps shown in (Fig. 5 and 6) respectively. The results show that potential land parcels complying with LEED LT credits‟ category are less than those for LEED SS credits‟ category. The final overlay analysis shows that only 9.5% of the total land area has the potential to obtain points under both LEED LT and SS categories as shown in (Fig. 7).

1

For the purpose of the comparative study, Mobinil building was excluded because it is registered under LEED- Commercial Interior rating system which follows different assessment criteria.

PLEA2016 Los Angeles - Cities, Buildings, People: Towards Regenerative Environments, 11-13 July, 2016

Figure 5: 10th Ramadan city- Land suitability analysis for LEED LT credits using GIS weighted sum overlay analysis

Figure 6: 10th Ramadan city- Land suitability analysis for LEED SS credits using GIS weighted sum overlay analysis

Figure 7: 10th Ramadan city- Land suitability analysis for both LEED Location and Transportation and Sustainable Sites credits using GIS weighted sum overlay analysis

DISCUSSION The first part of the investigative study indicates that private investors in Egypt have recently applied the LEED system; it is gradually spreading, particularly in new development areas in Cairo, as a mean of attracting private investors to comply with the national strategic plans for sustainable development. Most investors in Egypt adopt LEED (BD+C), and follow LEED version (V3.0), while currently, there are no projects registered under LEED V4.0 or LEED ND. Also, LEED SS category has a relatively lower average adoption rate compared with other LEED categories; with some credits being easier credits to obtain than others. The discussion about the suitability of land parcels to LEED credits‟ requirements using GIS analysis covers

two levels; the suitability of land parcels to individual LEED LT and SS credits‟ requirements and their corresponding weighting, and collectively for LEED LT and SS categories. First; on LEED LT and SS credits‟ level, analysing suitable land parcels to LEED LT category shows that LT C2: Sensitive Land Protection (63,000 Km2), LT C3: High Priority Site (7,000 Km2) and LT C5: Access to Quality Transit (8,000 Km2) contribute to „YES‟ scoring. Yet, the greatest area obtained under LT C2 has a single point weighting, also LT C8: Green Vehicles (63,000 Km2) contributes to „MAYBE‟ scoring, and it also has a single point weighting, while LT C4: Surrounding Density and Diverse Uses (92,000 Km2), LT C5: Access to Quality Transit (89,000 Km2), LT C7: Reduced Parking Footprint (87,000 Km2), and LT C8: Green Vehicles

PLEA2016 Los Angeles - Cities, Buildings, People: Towards Regenerative Environments, 11-13 July, 2016

(34,000 Km2) contribute to „NO‟ scoring, and besides their relatively large area, LT C4 and LT C5 have five point weighting, which contributes to „Non suitability‟ decision under LEED LT credits. While, analysing suitable land parcels to LEED SS credits shows that SS C1: Site Assessment (272 Km2) contributes weakly to „YES‟ scoring, while SS C2: Site Development-Protect or Restore Habitat (94,000 Km2) contributes to „MAYBE‟ scoring, and SS C3: Open Space (96,000 Km2) contributes to „NO‟ scoring. Also, SS C2 has twice as much weighting as SS C1 and SS C3, so most potential land parcels obtain the „MAYBE‟ scoring under LEED SS credits. On LEED LT and SS categories‟ level, suitable land area is calculated based on the previously shown weighted sum of LEED credits. The result shows that from the total land area; only 10% may obtain points under LEED LT category and 64% may obtain points under LEED SS category, while 9.5% may obtain points under both categories. This shows that for the case study, site conditions contribute more for obtaining points under LEED credits rather than its surrounding context. CONCLUSION Sustainable building design and construction requires conducting a complex process to optimize all interrelated design parameters. Decision making software support tools and methods are needed to guide practitioners on minimizing their adverse environmental impact especially in early design decisions like site selection. Also, more research is required to comply with the new requirements of LEED (V4.0) which discusses sustainability of the site in two different categories. LEED LT category discusses the sustainability of the surrounding context, while LEED SS category discusses the sustainability of the construction site itself. The paper shows how GIS application can support the decision making process for LEED projects‟ site selection method. The study shows that the use of GIS application can support decisions related to obtaining LEED LT as well as LEED SS credits to facilitate multicriteria analysis and decision making. This allows for more data integration and sets a solid base for objective decision making process. The study presents a predictive analysis obtained from GIS application to identify suitable land parcels to obtain credits under LEED LT and SS categories in 10th Ramadan city. The analysis considered sensitive land protection, high priority development sites, surrounding density and diverse uses, and access to quality transit on the context level. It also analyzed lithology type and condition as well as habitat and open spaces protection on the site level. The outcome of this study aims at encouraging private investments for green construction. The method can be

generalized and applied in similar contexts to create mapping criteria for sustainable sites particularly in new development areas. REFERENCES Ali, H. and Al-Nsairat, S., (2009). Developing a green building assessment tool for developing countries – Case of Jordan, Building and Environment, 44 (5), p. 1053 – 1064. Attia, S. & Dabaieh, M., (2013). The usability of green building rating systems in hot arid climates: A case study in Siwa, Egypt. The 4th Biennial subtropical cities conference, Braving a new world: Design interventions for changing climates. October 17-19, 2013, Fort Lauderdale, FL,USA Bah, Y and Tsiko, Rg., (2011). Landfill Site Selection by Integrating Geographical Information Systems and MultiCriteria Decision Analysis: A Case Study of Freetown, Sierra Leone. African Geographical Review. 30, 1, 67-99. Chrysochoou, M., Brown, K., Dahal, G., Granda-Carvajal, C., Segerson, K., Garrick, N., & Bagtzoglou, A., (2012). A GIS and indexing scheme to screen brownfields for area-wide redevelopment planning. Landscape and Urban Planning, 105(3), 187–198. El Yamany, S. Afifi, M& Hassan, A.,(2016). Applicability and Implementation of U.S. Green Building Council Rating System (LEED) in Egypt (A Longitudinal study for Egyptian LEED Certified Buildings). ISCDC 2015, International Conference on Improving Sustainability Concept in Developing Countries. December 02-08, 2015, Cairo, Egypt. Faraji Sabokbar, H., Shadman Roodposhti, M., & Tazik, E., (2014). Landslide susceptibility mapping using geographicallyweighted principal component analysis. Geomorphology, 226, 15–24. General Organization of Physical Planning (GOPP), (2013). 10th Ramadan strategic planning study, volume One, module report One. Gou, Z. and Lau, S., (2014). Contextualizing green building rating systems: Case study of Hong Kong, Habitat international, 44, p. 282 – 289. Ismaeel, W. & Rashed, A., (2015). Applying green rating system in the Egyptian context: between theory and practice, The first Arab Ministerial forum, 20-22 December 2015, Cairo, Egypt. Ismaeel, W. (2014). Developing a Systemic framework for applying LEED system: Managing Energy and Materials credits, unpublished PhD dissertation, Politecnico di Milano, Milan, Italy, available online on https://www.politesi.polimi.it/handle/10589/89815 Lavy, S., and Fernández-Solís, J. L. (2009). “LEED Accredited Professionals‟ perceptions affecting credit point adoption”, Facilities, 27(13/14) 531-548. Newell, G., (2009). Sustainability Best Practice –The Challenges for Asian Property Companies, Asian Public Real Estate Association. Son, K., Choi, K., Woods, P. and Park, Y.J., (2012). Urban Sustainability Predictive Model Using GIS: Appraised Land Value versus LEED Sustainable Site Credits. Journal of Construction Engineering & Management, 138(9), pp. 1107. Talen, E., Allen, E., Bosse, A., Ahmann, J., Koschinsky, J., Wentz, E. and Anselin, L., (2013). Research paper: LEED-ND as an urban metric. Landscape and Urban Planning, 119, pp. 2034.