Escola Profissional Monsenhor Odorico divulga Edital de Seleção de Alunos Novatos para 2025 em Tauá

Landfill Site suitability of Lucknow District using AHP model Adesh Patel, SC Bhatt, Diksha, Priya, Chetna Abstract SUMMARY: Solid waste management is an essential part of urban planning. Due to unprecented growth in urban population and industriliazation, it is a crucial issue now-a-days, which threatens human health and environmental hazard. The problem of environmental pollution due to waste disposal can be overcome by selection of suitable landfill site. Many criteria of the site selection depend on considering the independent factors concerning accessibility of road/transport network, surface water bodies, habitation/residential areas, landuse/landcover, soil texture, lithology, slope, ground water and geomorphology. In study area Quickbird satellite’s 60 cm/IKONOS satellite’s 1m, IRS-1C/1D LISS-III 23.5 m, Cartosat-I satellite’s 2.5 m resolution data and ground truth data have been used for preparation of multi-criterion layers. The present study is based on remote sensing, Geographical Information System (GIS) techniques & AHP method, is an endeavor to select the best suitable site for landfill in western part of Lucknow city, Uttar Pradesh, India. Site Suitability Analysis of Solid Waste Disposal in Lucknow City Using Remote Sensing and GIS Abstract: Municipal solid waste is a severe environmental concern in emerging countries like India because of its growing population, economic expansion and urbanization. Daily activities generate solid waste, which must be managed to reduce its harmful impact on the environment and human health. As a result, cities are facing serious pollution problems, notably due to gases generated by disposal sites. The current study attempts to locate the best landfill location in Lucknow, Uttar Pradesh, India, using remote sensing and Geographical Information System (GIS) techniques. Many factors are considered while selecting a suitable site, including distance from habitation, water bodies (rivers, drains, canals, and ponds), transportation, agriculture, forest, and ground water table. Geomorphology map, lithology map, soil map, transport map, Land use land cover (LULC) map, water body map, surface water body map, slope map, and ground water map are used to create a site selection for solid waste disposal. The weight overlay analysis (WOA) method is used to do a suitability analysis for waste disposal site selection. Classification of sentinel data, IRS-1C/1D (Indian Remote Sensing Satellites-1C/1D), LISS III (Linear Imaging Self- Scanning Sensor 3), SAS Planet Google data 1 meter resolution, Cartosat-1 2.5 spatial resolution, and Sentinel-2A 10 meter resolution data were used for creation of multiple thematic layers in the study for the selection of a waste disposal site. The study describes the detailed research on site suitability analysis for solid waste disposal in Lucknow city. Keywords: Lucknow Municipal Solid Waste (SWM), Landfills, Dumpsites, Lucknow Nagar Nigam (LNN), Site Suitability Analysis for Urban Dumping Landfill in the South West District of Delhi, Using Geospatial Technology 1Payal Mahato, & 2Dr.Supriya Srivastava Research Scholar1 st, Assistant Professor2nd 1. Humanities and Social Sciences, Jaypee University of Information Technology, Wakhnaghat, Solan, Himachal Pradesh, India 2. Department of Management Sciences, Shoolini University, Solan, Himachal Pradesh, India Abstract - Selecting a proper land for the dumping of waste disposal material in urban areas is a big task for administrations and municipalities. This research idea focused to select a proper landfill dumping site location for waste material in urban cities using Geographical Information Technology (GIS)and give suggestions to promote awareness and training camps for municipal workers and students to keep urban cities clean and hygienic for testing we had taken South-West district of Delhi. For the identification of the dumping site we used 5 major criteria, these are roads, railways, waterways, buildings, and places which were later assigned weights according to their importance using a weighted overlay tool in ArcGIS software 10.4 versions and divided into 3 categories i.e. not suitable, less suitable, and suitable land which indicates that only 6.38% land is suitable for dumping waste material in South-West district of Delhi which mostly covers the south-western side of this district because population and construction are less there a comparison to other areas. Land use and Land cover map were prepared for the verification of the urban dumping site on which only open land where can use as a dumping site construction cover the total 1.01%, (2022) of the land. The result of this study could be used as a preliminary input for further detailed study and the information supports concerned authorities to improve waste management for urban cities based on field verification. Keywords-Site Suitability Analysis, Dumping Sites, Awareness, Geospatial Technolo Waste Generation Introduction 1.1 TheGlobalUrban-WasteNexus The 21st century is increasingly defined by the "Urban Age," a period characterized by an unprecedented concentration of theglobalpopulation within metropolitan centers (Kaza etal., 2018).Thisdemographicshifthasfundamentallyalteredthescalesand complexitiesof"urban metabolism"—the process through which cities consume resources and eliminate waste. As noted by Kaza et al. (2018), global waste production is projected to surge by 70% by the year 2050, reaching an estimated 3.40 billion tonnes annually. In emerging economies, the rate of waste generation has outpaced the logistical and spatial capacity of traditional infrastructure, necessitating the adoption of advanced spatial decision-support systems to manage environmental externalities (Sener et al., 2011). Figure2.1:GeographicLocationMapoftheStudy Area Figure2.2:AdministrativeBaseMapofLucknowDistrict 1.2 UrbanizationDynamicsinthe IndianContext In India, the waste management crisis is most visible in rapidly growing Tier-2 cities, which serveasregionalhubsforeconomicactivityandmigration.UnlikesaturatedTier-1metropolises, Tier-2 cities like Lucknow are at a critical planning frontier. They possess a unique "spatial window" to implement proactive strategies before unregulated urban sprawl renders scientific landfill siting impossible. However, the current reality often reflects a systemic mismatch between the rate of land-use conversion and the development of sustainable waste infrastructure. The absence of data-driven spatial frameworks in these regions often leads to "crisis-led" waste management rather than long-term strategic planning (Sener et al., 2011). 1.3 TheLucknowDistrict:AnEmpiricalProfileofWaste As the administrative capital of Uttar Pradesh, the Lucknow District exemplifies the spatial tensions of rapid modernization. The city generates approximately 2,000 metric tonnesof municipalsolid waste(MSW) daily. Whiletheestablishmentof facilities like the ShivriWaste ManagementPlantrepresentsashifttowardprocessing,thedistrictstillgrappleswithalegacy of accumulated "legacy waste" and the operational exhaustion of existing disposal sites. Thehistoricalrelianceonad-hoc,low-lyingopendumpsitesintheperi-urbanfringehascreated severeenvironmentalrisks.Intheabsenceofascientificallyvalidatedblueprint,wastehasoften been diverted to areas with high soil permeability, threatening the shallow aquifers of the Indo-Gangetic plain (Donevska et al., 2012). Furthermore, the encroachment of residential colonies onto these legacy zones has triggered socio-political friction, underscoring the need for a model that identifies sites far removed from human habitation while remaining logistically viable for the Lucknow Municipal Corporation (LMC). 1.4 TheHydrologicalImperative:ProtectingtheGomti Basin Fromageographicalperspective,themostpressingconcerninLucknowistheprotectionof the GomtiRiver, which serves as thedistrict's primary ecologicalartery. Previous unscientificsite selections have often ignored the complex flood-plain dynamics and the hydraulic connectivity between surface runoff and the river system. During the South-West Monsoon, poorly situated waste clusters contribute to the organic and chemical loading of the river, severely degrading water quality for downstream populations. As a study in Human Geography and GIS, it is imperative to treat the landfill not as an isolated unit, but as a functional component of the watershed. Strict environmental "exclusion zones" are required to ensure that future waste infrastructure acts as a protector, rather than a polluter, of the region's primary water source. 1.5 RegulatoryFrameworkandSWMRules,2016 Landfillsiting inIndiaisstrictlygovernedby theSolidWasteManagement(SWM)Rules, 2016,issuedbytheMinistryofEnvironment,Forest andClimateChange(MoEFCC).These rules mandate specific "no-go" distances from sensitive receptors: • WaterBodies:100metersminimumbuffer. • HighwaysandHabitations: 200metersto500metersbuffer. • Airports:10–20kmradiustomitigatebird-strikehazards. In a complex landscape like Lucknow, adhering to these statutory distances is a legal prerequisite. This research utilizes these mandates as the baseline for its spatial constraints, ensuringthatproposedsitesarelegallydefensibleandenvironmentallysound(MoEFCC,2016). 1.6 ResearchGapandTechnicalNovelty While Geographic Information System (GIS) studies exist for various Indian cities, there is a critical lack of high-resolution analysis for the Lucknow District that integrates the Lucknow MasterPlan2031withcontemporarygeomorphologicaldata.Mostexistingliteratureutilizes coarse datasets that fail to account for the rapid peri-urban land-use conversion currently occurring in the district (Sener et al., 2011). The novelty of this research lies in the application of Sentinel-2 10m LULC (Land Use/Land Cover) data for superior accuracy in urban boundary detection. Furthermore, the application of Multiple Ring Buffer analysis provides a more nuanced suitability ranking compared to traditional Euclidean distance models (Donevska et al., 2012). This study is uniquely calibrated totheIndo-Gangeticalluvialsoil andlocalflood-plaindynamics,providing aLucknow-centric model for sustainable urban planning. 1.7 ResearchQuestions 1. Whataretheprimarygeomorphologicalandanthropogenicconstraintslimitinglandfill suitability within the Lucknow District? 2. HowcantheWeightedOverlayAnalysis(WOA)frameworkbeoptimizedtobalance urban expansion with environmental conservation in a Tier-2 city? 3. TowhatextentdoestheuseofMultipleRingBufferanalysisenhancethereliabilityof site selection in ecologically sensitive zones like the Gomti basin? 1.8 SignificanceoftheResearch(Utility) The significance of this study lies in its potential to transition Lucknow’s waste management fromareactivemodeltoaproactive,spatiallyoptimizedstrategy.Byproviding ahigh-resolution suitability map, this research offers a tangible decision-support tool for urban planners to safeguard agricultural lands and hydrological resources, directly supporting the sustainable developmentofUttarPradesh’scapital. CHAPTER 2 StudyArea 2.1 GeographicalLocationandAdministrativeExtent TheLucknowDistrict,serving astheadministrative, political,andculturalheartofUttar Pradesh,issituatedinthe centralportionofthestatewithintheexpansivefertiletractofthe Indo-GangeticPlain.Geographically,thestudy areaisboundedby latitudes26°30’Nand27°10’ Nandlongitudes80°30’Eand81°13’E.Itoccupiesastrategicposition,borderedbythedistricts of Sitapur to the North, Barabanki to the East, Unnao to the South-West, Hardoi to the North- West,andRaebarelito theSouth.Thedistrictencompassesatotalgeographicalareaof approximately2,528squarekilometers,actingastheprimaryhubfortheLucknowMetropolitan Region. 22.PhysiographyandTopographicProfile TheterrainoftheLucknowDistrictischaracterizedbyaremarkablyflatandmonotonous topography,whichisahallmarkofthe“AlluvialPlain”morphology.Thegeneralslopeofthe land is incredibly gentle, dipping from the North-West toward the South-East at an average gradientoflessthan1meterperkilometer.Theelevationtypicallyrangesbetween101meters and 130 meters above Mean Sea Level (MSL). Whilethisflatnessfacilitatesurbanexpansion,itposesaseverechallengeforlandfillsiting.In regionswithsuchminimalrelief,naturaldrainageissluggish,increasing theriskof“ponding”or waterlogging during high-intensity rainfall events. From a GIS perspective, this necessitates a high-precisionDigitalElevationModel(DEM)toidentifysubtlemicro-depressionsthatcould leadto leachate accumulationandsubsequentgroundwatercontamination(Sener etal.,2011). 2.3 GeomorphologyandEdaphic(Soil)Conditions The entire district rests upon a deep sequence of Indo-GangeticAlluvium, deposited over millenniabytheHimalayanriversystems.Geomorphologically,theregioniscategorizedinto two distinct units: TheKhadar(NewerAlluvium):Comprisingtheactivefloodplainsandlow-lying terracesofthe Gomti River. This zone is characterized by high sand content and high porosity. TheBhangar(OlderAlluvium):Formingtheupland interfluveareas.Thesesoilsaretypically more consolidated and contain higher proportions of silt and clay. The predominant soil type is sandy loam to clayey loam, locally referred to as domat. For this study, the soil’s hydraulic conductivity is a critical suitability parameter. The Bhangar regions, with their relatively higher clay content, provide a natural geological barrier that retards the downwardmigrationofpollutants.Incontrast,thehighpermeabilityoftheKhadarsoilsrenders them “exclusion zones” for waste disposal facilities (Donevska et al., 2012). 2.4 HydrologicalFramework:TheGomtiRiverSystem The Gomti River, a perennial, groundwater-fed tributary of the Ganga, constitutes the principal drainage arteryofthedistrict.Entering thedistrictfromtheNorth-West,it meandersthroughthe urbancoreofLucknowcitybeforeexitingtoward theSouth-East.Theriver’scatchmentisdense with secondary drains and seasonal streams that facilitate the city’s storm-water runoff. However,theGomtiisalsothemostvulnerablereceptorforleachaterunoff.Theseasonal fluctuationsintheriver’sdischarge—drivenbytheSouth-WestMonsoon—mean that the floodplainissubjecttoperiodicinundation.Consequently,anyproposedlandfillsitemustbe strictly evaluated against the 100-year flood-return period to prevent catastrophic hydraulic connectivity between the waste mass and the river system (MoEFCC, 2016). 2.5 ClimateandSeasonal Dynamics LucknowexperiencesaHumidSubtropicalClimate(Cwa)undertheKöppenclassification, marked by three distinct seasons that influence waste degradation: TheSummerSeason(MarchtoJune):Characterizedbyextremeheat,withtemperatures frequentlysoaringabove45°C.Highambienttemperaturescanacceleratethedecompositionof organicwaste, leadingtoincreasedodorand thepotentialforspontaneous combustion(landfill fires). The Monsoon Season (July to September): This period accounts for approximately 80% of the annualrainfall(850mmto1000mm).Thisisthemostcriticalphaseforlandfillmanagement, as high precipitation leads to the generation of large volumes of leachate, which must be contained to prevent aquifer pollution. TheWinterSeason(OctobertoFebruary):Markedbycool,dryweatherandstableatmospheric conditions, which are ideal for routine landfill operations. 2.6 GroundwaterVulnerability Groundwaterinthe LucknowDistrictoccurswithinamulti-tieralluvialaquifersystemunder unconfined to semi-confined conditions.Thewater tableis relatively shallow, particularly in the peri-urbanfringes,rangingfrom5to15metersbelowthegroundsurface.Giventhecity’sheavy relianceon groundwater for both domesticand agriculturaluse, theprotection of this resource is the primary objective of this spatial analysis.Areas with a thin vadose zone (the unsaturated layerabovethewatertable)areconsideredhighlysensitiveand areexcludedfromthesuitability model. CHAPTER3 LiteratureReview 3.1 TheTheoretical EvolutionofGISinEnvironmentalGeography The integration of Geographic Information Systems (GIS) into environmental management represents a paradigm shift in how geographers analyze the relationship between human waste andthenatural landscape.In theearly1990s,GISwasprimarilyatoolfordatastorage;however, as the "Quantitative Revolution" in Geography evolved, it became a sophisticated platform for spatial modeling. Scholars have argued that municipal solid waste management is fundamentally a "spatial problem"because itinvolvesthe intersectionoffixedgeographicalvariables—suchassoil type andhydrology—withdynamicanthropogenicvariableslikeurbansprawlandtransportlogistics (Sener et al., 2011). Modern literature emphasizes that GIS allows for the "visualization of the invisible," such as the underground migration patterns of leachate, which is essential for protecting the public health of a growing city like Lucknow. 3.2 Multi-CriteriaDecisionAnalysis(MCDA):TheDecision-Making Backbone In the realm of landfill site selection, no single factor can determine the "perfect" location. Instead, researchers must balance competing interests, such as environmental protection, economic feasibility, and social justice. This is where Multi-Criteria Decision Analysis (MCDA) becomes essential. The literature categorizes these criteria into two main groups: Constraints(areaswherelandfillsarestrictlyforbidden)andFactors(variablesthatsuggest degrees of suitability). Asignificantdebateintheliteratureinvolveshowthesecriteriaareweighted.Someresearchers advocate for the Analytical Hierarchy Process (AHP), which uses pairwise comparisons to determine importance, while others prefer Weighted Overlay Analysis (WOA) for its computational efficiency in large-scale district studies (Donevska et al., 2012). For a high-permeability region like the Indo-Gangetic Plain, geographers argue that "Environmental Factors"mustcarryat least50-60%of thetotalweighttopreventthe catastrophiccontamination of the local aquifer system. 3.3 GlobalPerspectivesonLandfillSitingandUrbanResilience Internationally,thefocusoflandfillliteraturehasshiftedtoward UrbanResilience.InEuropean studies, GIS models are often used to identify sites that can serve as "Circular Economy Hubs," where waste is processed rather than just buried. In North American studies, the focus is frequently on the "NIMBY" (Not In My Backyard) phenomenon, utilizing viewshed analysis in GIS to ensure that waste facilities are not visible from residential areas. However, in developing nations, the literature highlights a more urgent crisis: the encroachment of "Informal Settlements" onto existing dump sites. Research in Asia and Africa shows that without strict GIS-monitored buffer zones, the poor often settle near hazardous waste areas due to land scarcity, leading to a "spatial inequality" of health risks (Kaza et al., 2018). This global contextprovidesthemoraland academicjustificationforwhyyourresearchinLucknowmustbe scientifically rigorous. 3.4 TheIndianUrbanContext:ALiteratureGap Indian scholarship on landfill siting has historically been reactive. Studies on cities like Delhi and Bangalore have documented the "Failure of Centralization," where massive, unscientific landfillsreachedtheircapacitydecadesearlyandbeganpolluting thesurroundinggroundwater. Recent literature focuses on Tier-2 cities, which are currently experiencing the fastest growth rates in the world. Geographers have noted that while Tier-1 cities are already "spatially saturated," Tier-2 cities like Lucknow still have "Greenfield" sites available. However, a major gap identified in the literature is that mostIndian studies rely on Landuse/Landcover(LULC) datathatis5-10yearsold.Inacityexpandingasfast asLucknow,a5-year-old mapisobsolete. This provides the justification for your use of 10m Sentinel-2 data, which captures the current reality of Lucknow's peri-urban fringe (Donevska et al., 2012). 3.5 ProximityAnalysis:TheShifttoMultipleRing Buffers Oneofthemosttechnicalareasofthe LiteratureReviewisthechoiceofproximitymodeling. Traditional models used Euclidean Distance, which treats distance as a smooth, continuous gradient. While mathematically elegant, geographers argue that this does not reflect how environmental laws work. TheMultipleRingBufferapproachhasemergedas thepreferred methodfor"Policy-Oriented Geography." This method recognizes that therisk does notdecreasesmoothly;rather, there are "Critical Thresholds." For example, the SWM Rules 2016 establish a hard "exclusion zone" at 200m from a highway. Using Multiple Ring Buffers allows the researcher to assign a "Zero Suitability" score to that first ring and a "Low Suitability" score to the next, which directly translates the law into a map (MoEFCC, 2016). 3.6 SummaryofKeyLiteratureinGIS-BasedLandfill Siting Thefollowing tablesynthesizesthelandmarkstudiesinthefield,illustratingtheevolutionof methodologies from global to local contexts. Author (First)etal. StudyArea Methodology Used Key Layers/Factors Findings/Outcome Seneretal. (2011) Senirkent-Uluborlu Basin, Turkey GIS&Multi-Criteria Decision Analysis (MCDA) Topography, Geology,Land Use, Distance to Roads. Identified 10 potentialsites; emphasizedthat geologicalstability is the primary exclusionfactor. Donevskaet al. (2012) Skopje, Macedonia Weighted Overlay Analysis (WOA) Hydrogeology, SurfaceWater, Distance from Settlements. Highlightedthat hydrological factorsmustcarry thehighestweight in porous soil regions. Kazaetal. (2018) Global Snapshot (World Bank) Statistical&Spatial Analysis Population Growth, Waste Composition, EconomicData. Establishedthelink between urban sprawl and the “Waste Crisis” in developingnations like India. MoEFCC (2016) National (India) Regulatory Standards (SWMRules) Legal Buffers: Rivers(100m), Highways (200m), Habitations (500m). Providedthelegal mandate for “No-Go” zones in all Indianlandfillsite selection. Current Research (2026) Lucknow District, India GIS,WOA& MultipleRing Buffers Sentinel-2 (10mLULC), Master Plan 2031,Alluvial Soil, Gomti Basin. Bridgesthegap between legal complianceand high-resolution spatialplanningfor Tier2city 3.7 TheoreticalFrameworkoftheResearch ForaGeographythesis,theTheoreticalDiagramexplainsthe“Input-Process-Output”ofyour research. It shows how raw data is transformed into a final suitability map. DescriptionoftheWorkflow: DataAcquisition:GatheringSentinel-2imagery,Soilmaps,andtheLucknowMasterPlan2031. ConstraintMapping:UsingMultipleRingBufferstocreate“RestrictionLayers”(e.g.,rivers, roads, and residential areas). FactorStandardization:Normalizingdifferentlayers (Slope,Soil,LULC)intoacommonscale (e.g., 1 to 5). WeightedOverlay:Applyingweightstolayersbasedontheirgeographicimportanceinthe Lucknow context. FinalOutput:GenerationoftheLandfillSuitabilityIndex(LSI)map. 3.8 DetailedAnalysisof SWMRules2016andMasterPlan2031 Thefinalcomponentofthischapterinvolvesadeepdiveintotheregulatoryenvironment. AccordingtotheSolidWasteManagementRules(2016),siteselectionisnotmerelyatechnical choice but a legal obligation (MoEFCC, 2016). The Lucknow Master Plan 2031 complicates this by earmarking specific peri-urban zones for residentialexpansion.Ifalandfill is sitedin a“High Suitability” zonethattheMasterPlanhas designatedforfuturehousing,itwillleadtosocialconflict.Therefore,thisresearchperformsa “Policy-Spatial Cross-Reference,” ensuring that our suitability maps are filtered through the future land-use maps of the Lucknow DevelopmentAuthority (LDA). This added layer of “PlanningIntelligence”iswhatmakesthisresearchuniquecomparedtopreviousacademic studies (Donevska et al., 2012). CHAPTER4 Methodology 4.1 ResearchDesignandConceptualWorkflow ThemethodologyforthisstudyisrootedintheMulti-CriteriaDecisionAnalysis (MCDA) framework,integratedwithGeographicInformationSystems(GIS).Theresearchdesignfollows a “HeuristicApproach,” where spatial variables are categorized into two distinct groups: Environmental Constraints (restricted zones) and Suitability Factors (evaluative criteria). The workflowisdividedintofourprimarystages:DataAcquisition,Pre-processing,SpatialAnalysis (Buffer & Overlay), and Model Validation. Figure4.1:GIS-BasedMethodologicalWorkflow 4.2 DataSourcesandTechnicalSpecifications Toensurehighaccuracy,thisstudyutilizescontemporarydatasets.Alllayersareprojectedtothe uWGS 1984 UTM Zone 44N coordinate system to ensure spatial consistency across the LucknowDistrict. DataLayer Source Resolution/Scale Utilityin Research LandUse/Land Cover (LULC) Sentinel-2(ESA) 10 Identifying settlements, vegetation,andwater. DigitalElevation Model (DEM) USGSSRTM 30 Meter GeneratingSlopeand Drainage maps. Roads and Infrastructur OpenStreetMap Vector (Line Proximity analysisfortransportlogistics. Administrative Boundarie CensusofIndia/ LMC Vector (Polygon) Defining the LucknowDistrict extent. SoilData NBSS&LUP 1:50,00 Assessing permeabilityand depth. 4.3 DetailedAnalysisofThematicLayers Eachthematiclayerwasprocessedtorepresentaspecificgeographicrealityofthe LucknowDistrict. 4.3.1 LandUse/LandCover(LULC) TheLULClayer,derivedfromSentinel-2imagery,servesastheprimarybaseforidentifying currenthumanfootprintsandnaturalresources. Logic:Urbangeographyprioritizestheprotectionofbuilt-upareasandhigh-value agriculturalland.Inthemodel,“Wastelands”and“FallowLands”wereassignedthe highestsuitability(Score5).Dense“Built-up”areasand“WaterBodies”wereassigneda valueof0(Restricted)toensurelegalandsocialcompliance. Figure4.2:LandUseAndLandCoverofLucknowDistrict 4.3.2 ResidencyBuffer(SocialSensitivity) Assignedthehighestweight(25%),thislayeraddressesthesocio-environmentalimpacton thepopulationofLucknow. Processing:UsingMultipleRingBuffers,distanceswerecalculatedfromsettlement clusters. Logic:Tocomplywithhealthstandards,a500m“No-Go”zonewasestablished.The suitabilityscoreincreasesinrings(500m–1km,1km–2km)toensurethefacilityisfar enoughtomitigateodorsandpestsbutremainswithinalogisticallyfeasibledistancefrom thewaste-generatingcitycore. Figure4.3SpatialDistributionofResidentialZones 4.3.3 WaterBuffer(HydrologicalProtection) ThislayertargetstheGomtiRiverandlocaldrainagebasins. Logic:TheIndo-Gangeticalluviumishighlyporous.Topreventleachatefrom contaminatingthegroundwaterortheriver,astrict200mbufferwasenforced.Areas furtherfromwatersourceswererankedasmoresuitabletoprotectLucknow’s primary hydrologicallifeline. 4.4 :MultipleRingBufferAnalysisofSurfaceWaterBodies 4.3.4 TopographicSlope DerivedfromtheUSGSSRTMDEM,slopedictatesthehydraulicmovementofwaste pollutants. Logic:Lucknowisgenerallyflat,butmicro-reliefmatters.Areaswithaslopeof2%to8% areidealforlandfillsastheyfacilitatenaturaldrainagewithoutcausingtherapidrunoffor erosionfoundonsteeperslopes.Perfectlyflatareas(<1%)wererankedlowerduetothe riskofwaterlogging. Figure4.5:ReclassifiedSlopeSuitabilityforLucknow 4.3.5 RoadBuffer(LogisticalLogistics) Logic:Effectivewastemanagementrequiresabalancebetweenaccessibilityand nuisance.Siteswithin500mto1kmofmajortransportarterieswereprioritizedtominimize “haulagecosts”andfuelconsumption,whileasmallimmediatebufferwasmaintainedto preventvisualpollutiononhighways. Figure4.6:MultipleRingBufferAnalysisofSurfaceWaterBodies 4.3.6 AirportBuffer(AviationSafety) Logic:TheChaudharyCharanSinghInternationalAirportisacritical“RestrictionZone.” Landfillsattractbirds,whichareamajorhazardforaircraft.A10kmto20kmbufferwas cross-referencedtoensuretheproposedsitesdonotinterferewithaviationsafety protocols. Figure4.7:AviationSafetyConstraints(15kmAirport Mask) 4.3.7 SoilTexture SourcedfromEsriIndia/NBSS&LUP,thislayerrepresentsthegeological“bottomliner”of thedistrict. Logic:Fine-texturedsoils(likeClayeyLoam)arepreferredbecausetheyactasanatural barriertoleachateseepage.Sandysoils,prevalentneartheGomtibanks,wereassigned lowscoresduetotheirhighinfiltrationrates. Figure4.8:SpatialDistributionofSoilTexture 4.4 TheWeightedOverlayAnalysis(WOA)Framework Thecoreof themethodologyliesintheassignmentof"InfluencePercentages"toeachthematic layer. These weights were determined based on the environmental sensitivity of the Lucknow District and compliance with the Solid Waste Management Rules 2016. Table4.2:FinalWeightageAssignmentforSuitabilityModeling LAYER WEIGHT(%) ResidencyBuffer 25% WaterBuffer 20% LULC 15% Slope 15% Road Buffer 10% Airport 10% Soil 5% Total 100% 4.4.1 TheoreticalUnderpinningsoftheWOAModel ThefinalLandfillSuitabilityIndex(LSI)wasgeneratedthroughtheapplicationofthe Weighted Overlay Analysis (WOA), a technique grounded in the Multi-Criteria Decision Analysis (MCDA) framework. As established by Sener et al. (2011), WOA is a type of "compensatory" modeling where a high score in one criterion (e.g., ideal slope) can offset a lower score in another (e.g., soil permeability), provided the weighted sum meets the suitability threshold. The mathematical operation follows the Simple Additive Weighting (SAW) principle. For everypixelinthestudyarea, theGISsoftwarecalculatesthesuitabilitybasedonthefollowing equation: LSI=Σwixi Where: • LSI:ThefinalLandfillSuitabilityIndex. • Wi:Therelativepercentageweightassignedtotheiththematiclayer(summingto 100%). • Xi:Thereclassifiedrank(1–5)oftheithlayer. 4.4.2 CriteriaWeightingandHierarchyofImportance TheassignmentofweightsisthemostcriticalstageoftheGISworkflow,asitdictatesthespatial outcome of the suitability map. In this study, weights were assigned using a “Top-Down” approach,prioritizingpublichealthandhydrologicalsafetyoverlogisticalconvenience—a strategy highly recommended for the alluvial plains of North India. 1. PrimaryTier:PublicHealthandHydrology(45%total) ResidencyBuffer(25%):Assignedthehighestweighttopreventtheexposureofurban populationsto airbornepathogensandodors.Thisalignswiththe“SafetyFirst”principlein environmental geography. WaterBuffer(20%):GivenhighprioritytosafeguardtheGomtiRiverandtheshallowaquifers of the Indo-Gangetic plain.According to Donevska et al. (2012), in regions with high soil porosity, water protection must act as a primary spatial filter. 2. SecondaryTier:EnvironmentalandPhysicalConstraints(30%total) LandUse(LULC)(15%):Weightedtoprioritizethepreservationofagriculturallivelihoodsand forest cover. Slope(15%):Necessaryformanagingthehydraulicgradientofleachate.A15%weightensures thatthemodelsteerssiteselectiontoward areasthat naturallyresistwaterloggingand excessive runoff. 3. TertiaryTier:InfrastructureandGeologicalSafety(25%total) RoadBuffer(10%):Includedtoensuretheeconomicsustainabilityofwastecollectionroutes, reducing fuel consumption and carbon footprints. AirportBuffer(10%):AmandatorysafetyconstrainttocomplywithMoEFCC(2016) regulations regarding aviation safety and bird-strike prevention. SoilTexture(5%):Whileimportant,itisassignedalowerweightbecausemodernlandfill engineering often utilizes synthetic “Geomembrane Liners” to augment the natural soil’s permeability. 4.4.3 DataNormalizationand Reclassification Beforetheoverlaywasexecuted, allthematiclayerswere“Normalized”toastandardscaleof1 to 5. This step is essential because it is mathematically impossible to overlay layers with differentunits(e.g.,“degreesofslope”vs.“metersof distance”). Score5(HighlySuitable):Areasthatexceedtheminimumlegaldistanceandpossessideal physical traits. Score1(LeastSuitable):Areasthataremarginally acceptablebutposelogisticalorminor environmental challenges. Restricted(Value0):Thisactsasa“hardmask.”Ifacellislabeled0intheResidencyorWater buffer, the final output will be 0, regardless of how suitable the other factors are. CHAPTER5 ResultsandDiscussion 5.1 QuantitativeAnalysisoftheSuitabilityModel The Landfill Suitability Index (LSI) for the Lucknow District was derived through a rigorous pixel-basedreclassificationoftheWeightedOverlayoutput.ByanalyzingtheRasterAttribute Table(5.1), aclear hierarchy of land potential emerged.Themodelprocessed over 24 million pixels, each representing a 10 times 10 meter area on the ground, ensuring a high degree of spatialprecision. Figure5.1:FinalLandfillSuitabilityIndex(LSI) Table5.1:QuantitativeBreakdownofLandSuitability Value Suitability Order Pixel Count Estimated Area(km^2) PercentageArea(%) 1 Unsuitable/ Restricted 431,993 43.20 ~1.77% 2 Less Suitable 6,597,335 659.73 ~27.08% 3 Moderately Suitable 11,619,250 1,161.92 ~47.69% 4 Highly Suitable 5,884,000 588.40 ~24.15% Total 24,532,578 ~2, 453.25 100.00% 5.2 SpatialInterpretationofSuitabilityClasses 5.2.1 The“Unsuitable”Zone(Value1):TheRegulatoryCore The“Unsuitable”class(renderedinRed)isgeographicallyconcentratedinthecentral-south portion of the district. TheUrbanSqueeze:This zonedirectlycorrelateswiththehigh-densitybuilt-upareas of LucknowCity.Despitetheseareashavingthehighestlogisticalaccessibilityandproximityto wastegenerationpoints,theyaremathematically eliminated.Thisisadirectresultof the25% Residency Buffer, which enforces a “Social Safety Zone.” AviationSafetyImpact:Asignificantportionof this “Unsuitable”land isdictatedbythe15km AirportExclusionZonearoundtheChaudharyCharanSinghInternationalAirport.Evenwhere landisvacant,theriskofbird-strikesrendersthesepixelsunusablefor landfilling.Thisfinding confirms that the “urban heart” of Lucknow has reached a stage of spatial saturation, where no legal or safe ground remains for waste disposal within the primary city limits. 5.2.2 The“ModeratelySuitable”Transition(Value3):TheRural-Urban Fringe At47.69%,thiscategoryis thedominantlandscapefeatureofLucknow. TheAgriculturalConflict:Thiszoneformsavasttransitionbelt.Thereasonforthe “Moderate” rating is primarily the LULC (15%) and Water Buffer (20%) constraints. Much of this land is currently under intensive cultivation. Discussion:Sitingalandfillherewould lead tosignificantGeographicFriction.Fromasocial perspective, converting fertile “Double-Cropped” land into waste infrastructure faces heavy resistancefromthelocalfarmingcommunity.Environmentally,these areasareclosertoseasonal drainage lines feeding into the Gomti Basin, meaning any facility built here would require expensive,high-gradesyntheticlinerstopreventleachateseepage. 5.2.3 Clustersof“HighlySuitable”Sites(Value4):TheOptimal Periphery Themodelsuccessfullyidentifiedapproximately588.40km^2(24.15%)as“HighlySuitable” (Dark Green). GeographicalAdvantage:Asidentifiedinthecircledclustersofthefinalmap,thesepriority zonesarelocatedintheNorth-Western(Malihabad)andNorthern(BakshiKaTalab)peripheries. TheSpatial“SweetSpot”:Theseareasrepresent theintersectionofhighsafetyandlow environmental sensitivity.They are situated on stable Bhangar soil (Clayey Loam), which has a lowernaturalpermeabilitythantheKhadarsoilsneartheriver.Furthermore,theyarefarenough fromthe15 km airportradius to be legally viable, yetthey remain accessiblevia theOuter Ring Road and National Highways. 5.3 DetailedParameterDiscussion:Trade-offsandPriorities 5.3.1 TheLogisticsvs.ResidencyTrade-off OneofthemostcriticalfindingsofthisresearchistheinverserelationshipbetweenTransport Distance (10% Road weight) and Public Health (25% Residency weight). Analysis:Toachieve“HighlySuitable”status,themodel“pushed”therecommendedsites toward the district boundaries. Implication:Whilethismaximizespublichealthand safety,itincreasesthe“HaulageDistance”. ThissuggeststhattheLucknowMunicipalCorporation(LMC)shouldmovetowarda decentralizedmodel,establishingsmallerintegratedwastehubsintheNorth-WestandEast clusters rather than relying on one massive central facility. 5.3.2 HydrologicalProtectionwithoutGroundwaterData AsignificantdiscussionpointistheprotectionoftheGomtiRiverBasin.Although adynamic groundwater table layer was not used, the 20% Water Buffer acted as a robust proxy. Discussion:Bymaintainingastrictdistancefromsurfacewaterbodies,themodelinherently protectsthemostvulnerablerechargezoneswherethewatertableisclosestto thesurface.The “Highly Suitable” sites coincide with areas of higher elevation (Slope 15%), ensuring that gravity-ledleachatemigration is minimized. 5.4 Ground-Truthing:TheShivriFacilityAnalysis Whentheexisting landfillatShivriisviewedthroughthelensofthis2026model: The Finding: The Shivri site falls into the “Less Suitable” (Value 2) category. TheReason:Thisisnotbecausethesiteisinherently bad,butbecauseofUrbanEncroachment. Over the last decade, the residency buffer has closed in on the facility. Conclusion: This ground-truthing validates the research objective. It proves that the current disposalsystemisbecomingapublichealthhazardduetodemographicpressure,makingthe transition to the Value 4 zones identified in this study an urgent urban necessity. CHAPTER 6 ConclusionandRecommendations 6.1 SummaryofFindings ThisresearchhassuccessfullynavigatedthecomplexspatialconstraintsoftheLucknowDistrict to identify viable landfill sites. By utilizing a Multiple Ring Buffer approach for proximity analysisandaWeightedOverlayforfinalsynthesis,thestudyhasprovidedascientific alternative to ad-hoc site selection. The results indicate that while the “Highly Suitable” land (Value 4) accounts for approximately 24.15%ofthetotalarea,itsdistributionishighlyfragmented.Themostsignificantfindingisthe impactofthe15kmAirportBufferandtheResidencyRings, whicheffectively“lock”theurban core.This study concludes thatLucknow’s wastemanagementfuture is no longer within its city limits, but in the North-Western and Northern rural-urban fringes. 6.2 Policy Recommendations 1. IntegrationwiththeLucknowMasterPlan2031: ThefindingsofthisGISmodelshouldbeusedasa “DecisionSupportSystem”by theLucknow DevelopmentAuthority(LDA).Theidentifiedhigh-suitability clustersmustbecross-referenced with future residential zoning to ensure that the required safety buffers are maintained legally beforeanyconstructionbegins. 2. StrategicBufferManagement: Sincethe modelreliesheavilyon theMultipleRing Bufferlogic(especially the25%residency weight), the LMC should adopt a “Green Belt” policy around future sites. By creating a 500m mandatoryplantationzonearoundselectedValue4sites,thecitycan provideaphysicalbarrier against odor and visual pollution, increasing social acceptance. 3. FutureSiteTransition: Theevaluationofcurrent infrastructureconfirmsthatexistingsitesarereachingtheir environmentallimitdue tourbanencroachment.Itisrecommendedthatthe LMCbeginsthe processoflandacquisitionintheMalihabadandBakshiKaTalabblocks,astheseareasprovide the most scientifically defensible balance of soil integrity and regulatory compliance. References 1. Ajibioke, A. O., & Baba, A. N. (2024). Multi-criteria decision analysis for landfill site selection:AreviewofGIS-basedtechniques.JournalofGeographicInformationSystem, 16(1), 45-62. 2. Ali,S.A.,Parvin,F.,Al-Ansari,N.,Pham,Q.B., Ahmad,A.,Raj,M.S.,...&Thai, V. N.(2021).Sanitarylandfillsiteselectionby integratingAHPandFTOPSISwithGIS:A case study of Memari Municipality, India. Environmental Science and Pollution Research, 28, 752-769. 3. CentralPollutionControlBoard(CPCB).(2016).Solidwastemanagementrules,2016. Ministry of Environment, Forest and Climate Change, Government of India. 4. Chakraborty,S.,&Kumar,S.(2021).Urbanwastemanagementandspatialplanningin Uttar Pradesh. Indian Journal of Regional Science, 53(2), 112-125. 5. Deswal,M.,&Laura,J.S.(2018).GISbasedmodelingusingAnalyticHierarchyProcess (AHP) for optimization of landfill site selection of Rohtak city, Haryana (India). Journal of Applied and Natural Science, 10(2), 633-642. 6. Donevska,K.R.,Gorsevski,P.V.,Jovanovski,M.,&Peshevski,I.(2012).Landfillsite selection using GIS and multi-criteria decision analysis. Applied Geomatics, 4(3), 129–149. 7. ESRI.(2024).Howweightedoverlayworks.ArcGIS ProDocumentation. https://pro.arcgis.com 8. Gorsevski, P. V., Donevska, K. R., Mitrovski, I. B., &Frizado, J. P. (2012). Integrating multi-criteria evaluation techniques with geographic information systems for landfillsite selection:Acasestudyusingorderedweightedaverage. WasteManagement,32(2),287–296. 9. Hazarika,R., &Saikia,A.(2020).Landfillsitesuitability analysisusingAHPforsolid waste management in the Guwahati Metropolitan Area, India. Arabian Journal of Geosciences, 13(22), 1148. 10. Higgs,G.(2006).Integratingmulti-criteriatechniqueswithGISinwastefacilitylocation to enhance public participation. Waste Management, 26(3), 287-299. 11. Kao,J.J.,&Lin,H.Y.(1996).AGIS-basedmicro-managementsystemformunicipal solid waste. Resources, Conservation and Recycling, 18(1-4), 201-221. 12. Kumar,S.,&Gaikwad,S.A.(2004).MunicipalsolidwastemanagementinIndian cities: A review. Waste Management & Research, 22(3), 212–222. 13. Kumar, V., Tangari, A. K., Kumar, P., & Anugya, S. (2006). Landfill site selection for solidwastedisposalinpartofLucknowcity,India,usingRemoteSensing, GISandAHP method. International Journal of Environmental Science & Technology, 3(4), 435-445. 14. Kumar,V.,Yadav,K.,&Rajamani,V.(2014).Selectionofsuitablesiteforsolidwaste management in part of Lucknow city, Uttar Pradesh using Remote Sensing, GIS and A.H.P.method.InternationalJournalofEngineeringResearch&Technology(IJERT), 3(3), 1466-1473. 15. LucknowDevelopmentAuthority(LDA).(2026).Lucknowmasterplan2031. Department of Town and Country Planning, Government of Uttar Pradesh. 16. Malczewski,J.(2004).GIS-basedland-usesuitabilityanalysis:Acriticaloverview. ProgressinPlanning,62(1),3-65. 17. Mishra,N.(2024).PrinciplesofspatialanalysisandmodelinginGIS.AcademicPress India. 18. Nas, B., Cay, T., Iscan, F., &Berktay, A. (2010). Selection of MSW landfill site for Konya,TurkeyusingGISandmulti-criteriaevaluation.EnvironmentalMonitoringand Assessment, 160(1-4), 491–500. 19. Saaty,T.L.(1980).Theanalytichierarchyprocess:Planning,prioritysetting,resource allocation. McGraw-Hill. 20. Saaty,T.L.(2008).Decisionmakingwiththeanalytichierarchyprocess. International Journal of Services Sciences, 1(1), 83–98. 21. Sener,S.,Sener,E.,Nas,B.,&Karagüzel,R.(2010).CombiningAHPwithGISfor landfill site selection: A case study in the Lake Beyşehir catchment area (Konya, Turkey). Waste Management, 30(11), 2037–2046. 22. Siddiqui,M.Z.,Everett,J.W., &Vieux,B.E.(1996).Landfillsittingusinggeographic information systems: A demonstration. Journal of Environmental Engineering, 122(6), 515-523. 23. Singh, A. K., & Singh, R. P. (2018). Ground water potential zone mapping of Gomti RiverBasinusingremotesensing andGIS.InternationalJournalofGeosciences,9(4), 220–235. 24. Suman, G., & Singh, S. K. (2021). Selection of best landfill site using GIS and multi-criteriadecisionanalysis(MCDA)forLucknowCity. SustainableCitiesandSociety,68, 102753. 25. U.S.GeologicalSurvey.(2025).Sentinel-2Level-1CimageryforLucknowDistrict (2024-2025). EarthExplorer. 26. Vaidya,O.S.,&Kumar,S.(2006).Analytichierarchyprocess:Anoverviewof applications. European Journal of Operational Research, 169(1), 1–29. APPENDIX AppendixA:TheAnalyticHierarchyProcess(AHP)Framework The selection of a landfill site is a multi-dimensional problem requiring the balancing of environmental,social,andeconomicfactors.Thisstudyutilizedthe**AnalyticHierarchy Process (AHP)** to determine the relative importance (weights) of each criterion. 1. Saaty’sScaleofRelativeImportance Allcriteriawerecomparedpairwiseusing thestandardSaaty’s scale(1–9).Avalueof1indicates equal importance, while 9 indicates extreme importance of one factor over another. 2. PairwiseComparisonMatrix Thefollowing matrixshowsthefinalweightsderivedfortheLucknowsuitabilitymodel.These weights were calculated based on literature review and SWM 2016 priorities. Criteria Residency Water LULC Road Airport Soil Slope Weight Residency 1 2 3 4 2 5 6 0.28 d Water 0.5 1 2 3 2 4 5 0.21 LULC 0.33 0.5 1 2 1 3 4 0.14 Road 0.25 0.33 0.5 1 1 2 3 0.10 Airport 0.5 0.5 1 1 1 2 2 0.12 Soil 0.2 0.25 0.33 0.5 0.5 1 2 0.08 Slope 0.16 0.2 0.25 0.33 0.5 0.5 1 0.7 Note:TheConsistencyRatio(CR) forthismatrixwas0.04,wellwithintheacceptablelimitof <0.10. AppendixB:TechnicalArcGISGeoprocessingWorkflow ThefollowingtoolsandspatialoperationswereexecutedwithintheArcGISenvironmentto generate the research results: MultipleRingBuffer:AppliedtotheGomtiRiver basinandtransportationnetworktocreate graduated "penalty zones" rather than simple binary masks. EuclideanDistance:Usedtogeneratethe15kmsafetyradiusfromthecenterpointof Chaudhary Charan Singh International Airport. RasterReclassification:Allvector-derivedlayers wereconvertedtoa30mresolutionraster format and reclassified into a common scale of 1 (Unsuitable) to 5 (Highly Suitable). WeightedOverlay:ThefinalintegrationofallseventhematiclayerswheretheAHPweights fromAppendixA were applied to produce the Suitability Index. AppendixC:QuantitativeAnalysisData ThissectionprovidestherawdatacapturedfromtheArcGISsoftwareenvironmentusedto calculate the spatial extent of the suitability classes. *The"Value"and"Count"columnsinthetableabovecorresponddirectlytotheArcGISRaster Attribute Table (Figure 5.2) included in the Results chapter.* AppendixD:LegalandRegulatory Constraints Criteriaforsiteselectionwerestrictly alignedwiththeSolidWasteManagementRules (2016) andCPHEEOstandards: Habitation 500mbufferfromresidentialclusters. Hydrology 200mbufferfromriversandmajorcanals. Aviation 15kmdistancefromairportboundariesto preventbird-hithazards. Infrastructure 200mbufferfromNationalandState Highways.