Assessment of groundwater potential zones in coal mining impacted hard-rock terrain of India by integrating geospatial and analytic hierarchy process (AHP) approach

The study aims at delineating groundwater potential zones using geospatial technology and analytical hierarchy process (AHP) techniques in mining impacted hard rock terrain of Ramgarh and part of Hazaribagh districts, Jharkhand, India. Relevant thematic layers were prepared and assigned weight based on Saaty’s 9-point scale and normalized by eigenvector technique of AHP to identify groundwater prospect in the study area. The weighted linear combination method was applied to prepare the groundwater potential index in geographic information system. Final groundwater prospects were classified as excellent, very good, good, moderate, poor and very poor groundwater potential zones. Study thus revealed that the excellent, very good and good groundwater potential zones, respectively, cover 148.3, 373.66 and 438.86 km² of the study area, whereas the poor groundwater potential zone covers 180.05 km². Validation was done through a receiver operating characteristic curve, which indicated that AHP had good prediction accuracy (AUC = 75.45%).     

Soil erosion prediction based on land cover dynamics at the Semenyih watershed in Malaysia using LTM and USLE models

This study attempts to identify and forecast future land cover (LC) by using the Land Transformation Model (LTM), which considers pixel changes in the past and makes predictions using influential spatial features. LTM applies the Artificial Neural Networks algorithm) in conducting the analysis. In line with these objectives, two satellite images (Spot 5 acquired in 2004 and 2010) were classified using the Maximum Likelihood method for the change detection analysis. Consequently, LC maps from 2004 to 2010 with six classes (forest, agriculture, oil palm cultivations, open area, urban, and water bodies) were generated from the test area. A prediction was made on the actual soil erosion and the soil erosion rate using the Universal Soil Loss Equation (USLE) combined with remote sensing and GIS in the Semenyih watershed for 2004 and 2010 and projected to 2016. Actual and potential soil erosion maps from 2004 to 2010 and projected to 2016 were eventually generated. The results of the LC change detections indicated that three major changes were predicted from 2004 to 2016 (a period of 12 years): (1) forest cover and open area significantly decreased at rates of almost 30 and 8 km², respectively; (2) cultivated land and oil palm have shown an increment in sizes at rates of 25.02 and 5.77 km², respectively; and, (3) settlement and Urbanization has intensified also by almost 5 km². Soil erosion risk analysis results also showed that the Semenyih basin exhibited an average annual soil erosion between 143.35 ton ha^?1 year^?1 in 2004 and 151 in 2010, followed by the expected 162.24 ton ha^?1 year^?1. These results indicated that Semenyih is prone to water erosion by 2016. The wide range of erosion classes were estimated at a very low level (0–1 t/ha/year) and mainly located on steep lands and forest areas. This study has shown that using both LTM and USLE in combination with remote sensing and GIS is a suitable method for forecasting LC and accurately measuring the amount of soil losses in the future.     

Assessment of groundwater potential zones using GIS technique

A case study was conducted to find out the groundwater potential zones in Kattakulathur block, Tamil Nadu, India with an aerial extent of 360.60 km². The thematic maps such as geology, geomorphology, soil hydrological group, land use / land cover and drainage map were prepared for the study area. The Digital Elevation Model (DEM) has been generated from the 10 m interval contour lines (which is derived from SOI, Toposheet 1:25000 scale) and obtained the slope (%) of the study area. The groundwater potential zones were obtained by overlaying all the thematic maps in terms of weighted overlay methods using the spatial analysis tool in ArcGIS 9.2. During weighted overlay analysis, the ranking has been given for each individual parameter of each thematic map and weights were assigned according to the influence such as soil −25%, geomorphology − 25%, land use/land cover −25%, slope − 15%, lineament − 5% and drainage / streams − 5% and find out the potential zones in terms of good, moderate and poor zones with the area of 49.70 km², 261.61 km² and 46.04 km² respectively. The potential zone wise study area was overlaid with village boundary map and the village wise groundwater potential zones with three categories such as good, moderate and poor zones were obtained. This GIS based output result was validated by conducting field survey by randomly selecting wells in different villages using GPS instruments. The coordinates of each well location were obtained by GPS and plotted in the GIS platform and it was clearly shown that the well coordinates were exactly seated with the classified zones.     

Regional yield estimation for winter wheat with MODIS-NDVI data in Shandong, China

The significance of crop yield estimation is well known in agricultural management and policy development at regional and national levels. The primary objective of this study was to test the suitability of the method, depending on predicted crop production, to estimate crop yield with a MODIS-NDVI-based model on a regional scale. In this paper, MODIS-NDVI data, with a 250 m resolution, was used to estimate the winter wheat (Triticum aestivum L.) yield in one of the main winter-wheat-growing regions. Our study region is located in Jining, Shandong Province. In order to improve the quality of remote sensing data and the accuracy of yield prediction, especially to eliminate the cloud-contaminated data and abnormal data in the MODIS-NDVI series, the Savitzky–Golay filter was applied to smooth the 10-day NDVI data. The spatial accumulation of NDVI at the county level was used to test its relationship with winter wheat production in the study area. A linear regressive relationship between the spatial accumulation of NDVI and the production of winter wheat was established using a stepwise regression method. The average yield was derived from predicted production divided by the growing acreage of winter wheat on a county level. Finally, the results were validated by the ground survey data, and the errors were compared with the errors of agro-climate models. The results showed that the relative errors of the predicted yield using MODIS-NDVI are between −4.62% and 5.40% and that whole RMSE was 214.16 kg ha⁻¹ lower than the RMSE (233.35 kg ha⁻¹) of agro-climate models in this study region. A good predicted yield data of winter wheat could be got about 40 days ahead of harvest time, i.e. at the booting-heading stage of winter wheat. The method suggested in this paper was good for predicting regional winter wheat production and yield estimation.     

Delineation of potential zones for artificial recharge using gis

In the present study, potential zones for artificial recharge in Agniar-Ambuliar-Southvellar river basins in Tamilnadu, India have been delineated through integration of various thematic maps using Arc view GIS. The study area, covers an area of 4566 km². Thematic maps pertaining to geology, permeability, effective soil depth, drainage intensity, soil texture, water holding capacity and physiography were prepared on 1:2,50,000 scale using conventional methods. These maps were scanned and registered with reference to a base map and are prepared as separate layers or coverages using Arc view. GIS has been used for the integration of various thematic maps to delineate the potential zones for artificial recharge. Each theme was assigned a weightage depending on its influence on groundwater recharge. Each class or unit in the map was assigned a knowledge based ranking from one to four depending on its significance in storage and transmittance of groundwater. The final map has been prepared showing four different categories of potential zones for artificial recharge.     

Mapping Isolated Wetlands in a Karst Landscape: GIS and Remote Sensing Methods

GIS and remote sensing (RS) techniques using Landsat ETM+ and objectoriented segmentation were developed to identify depressional isolated wetlands in a >2,600 km² mixed land use area of north-central Florida, USA. Both the standalone RS method and the combined GIS/RS method were successful at identifying isolated wetlands > 0.20 ha. Combining the GIS and RS methods yielded producer and user accuracies ranging from 93 to 100% and 86 to 95%, respectively. The methods utilized successfully mapped isolated wetlands and could be used to address questions surrounding national estimates and areal distribution of isolated wetlands.     

Morphometry using remote sensing and GIS techniques in the sub-basins of Kagna river basin, Gulburga district, Karnataka, India

The study area is a part of Kagna river basin in the Gulburga district of Karnataka, India. It covers an area of 1320 km² and it has been subdivided into 4 sub-basins namely Wadi, Chitapur, Sedam and Kurkunta, which range in area from 184 to 537 km². The drainage pattern of these sub-basins are delineated using Geo-coded FCC bands 2,3,4 of IRS 1C and 1D(LISS III+PAN merged) on 1:50,000 scale and Survey of India toposheets as reference. The morphometric parameters are computed using ArcInfo and ArcView GIS softwares. The drainage pattern of the study area is dendritic to sub-dendritic with stream orders ranging from IV to VII orders. Drainage density ranges from 1.40 to 1.86 km/km² suggesting coarse to moderate drainage texture. The change in values of stream length ratio indicate their late youth stage of geomorphic development. The values of bifurcation ratio ranging from 2.00 to 4.71 indicate that all the sub-basins fall under normal basin category. The values of form factor and circulatory ratio, suggest that the Kurkunta sub-basin is elongated and the remaining sub-basins are more or less circular in shape. Elongation ratio indicates that the Wadi sub-basin is a region of very low relief whereas the other sub-basins are associated with moderate to high relief and steep ground slopes. It is concluded that remote sensing and GIS have been proved to be efficient tools in drainage delineation and updation. In the present study these updated drainages have been used for the morphometric analysis.     

深度语义分割支撑下的尾矿库风险检测

尾矿库是矿山企业选矿的必要设施,同时对周围环境也是一个重大的危险源。为研究流域范围内尾矿库的溃坝路径以及对矿区地表造成的风险,以赤城县为例,利用GF-1高分辨率遥感影像,基于遥感RS（Remote Sensing）及地理信息系统GIS（Geographic Information System）手段对尾矿库的流域风险进行了监测分析。首先,通过分析尾矿库在遥感影像上的纹理、色调、形状以及大小等特征,制作了用于目标检测的尾矿库样本集,然后,在原始SSD目标检测网络基础上添加了反卷积模块和连接模块构建多尺度融合目标检测算法MSF_SSD,在目标检测结果基础上使用PSPnet算法实现尾矿库结构分割,得到了尾矿库内部结构—坝体以及库区,运用RS与GIS技术对尾矿库的上游汇水面以及事故可能径流进行提取,进而基于Arc Hydro模型模拟尾矿库的溃坝路径。最后,通过构建溃坝路径的缓冲区,得到尾矿库发生溃坝所造成的地物影响范围及面积。研究结果表明：赤城县尾矿库的溃坝路径总体是从西向东,从北向南,受溃坝影响的地物总面积达到480 km²。其中,林地176.52 km²,耕地175.52 km²,城市建设用地43.74 km²,农村建设用地2.47 km²,水体17.72 km²,草地和牧场分别为3.60 km²、1.22 km²。研究成果可用于分析尾矿库溃坝造成的地物损失以及影响范围面积等信息,提升尾矿库的风险管理水平及应急响应能力,为有关部门制定决策提供理论依据。     

Change of river channel and bank erosion of the burhi dihing river (assam), assessed using remote sensing data and gis

The Burhi Dining river flows in a meandering course for about 220 km through alluvial plains of Assam including a short rocky and hilly tract in between. Sequential changes in the position of banklines of the river due to consistent bank erosion have been studied from Survey of India topographic maps of 1934 and 1972, and digital satellite data of 2001 and 2004 using GIS. Two broad kinds of changes have been observed, e.g. alteration of direction of flow due to neck cut-off and progressive gradual change of the meander bends that accounts for translational, lateral, rotational, extensional and other types of movement of the meander bends. Study of bankline shift due to the bank erosion has been carried out for the periods 1934–1972, 1972–2001, 2001–2004 and 1934–2004 at 13 segments spaced at 5′ longitude interval (average 15 km) as the river course trends nearly east to west. The amounts of the bank area lost due to erosion and gained due to sediment deposition are estimated separately. The total area eroded in both banks during 1934–1972 was more (26.796 km²) as compared to sediment deposition (19.273 km²), whereas total sediment deposition was more (34.61 km²) during 1972-2001 as compared to erosion (23.152 km²). Erosion was again more in 2001–2004 (7.568 km²) as compared to sediment deposition (2.493 km²). During the entire period (1934–2004) of study the overall erosion on the both banks was 31.169 km² and overall sediment deposition was 30.101 km². The highest annual rates of bank erosion as well as bank building of the river are 21055.47 m²/km in 2001–2004 and 9665.81 m²/km in 1972-2001, respectively. Similarly the highest average annual rates of erosion as well as sediment deposition in both banks are observed during 2001–2004 and 1972–2001, respectively. The hard rocks of the hilly tract situated in between result in development of entrenched meandering and this tract has suffered minimum bank erosion.     

Evaluation of groundwater potential zones in the sub-watersheds of north pennar river basin around Pavagada, Karnataka, India using remote sensing and GIS techniques

The study area is one of the watersheds of North Pennar basin, covering an area of 570 km² in Pavagada taluk of Tumkur district. The watershed has been subdivided into nine sub-watersheds namely Dalavayihalli, Maddalenahalli, Talamaradahalli, Puluvalli tank, Nagalamadike, Gowdatimmanahalli, Naliganahalli, Devadabetta and Byadanur. These nine sub-watersheds have been evaluated to delineate groundwater potential zones based on the characteristics of geomorphic units together with slope, geology, lineaments, borewell data using Remote Sensing and Geographic Information System (GIS) techniques. Slope varies from nearly level (0–1%) to very steep (>35%). The different geomorphic units in each sub-watershed consist of denudational hills, residual hills, inselbergs, pediment inselberg complex, pediments, shallow weathered pediplains, moderately weathered pediplains and valley fills. The lineament map for each sub-watershed has been prepared and the trends were analysed with rose diagrams. The analysis of borewell locations and their yield data in association with lineaments at subwatersheds level reveals that the lineaments are acting as a pathway for groundwater movement. The integrated map comprising groundwater potential zones prepared by “Union” function using GIS indicate that valley fills and moderately weathered pediplains are very good to good, shallow weathered pediplains are good to moderate, pediment inselberg complex and pediments are moderate to poor and denudational hills, residual hills and inselbergs are poor to very poor groundwater prospect zones.     

遥感和GIS技术应用于伊拉克南部Basrah省土地利用/覆盖变化及城市扩张研究(英文)

In recent years, land use/cover dynamic change has become a key subject that needs to be dealt with in the study of global environmental change. In this paper, remote sensing and geographic information systems (GIS) are integrated to monitor, map, and quantify the land use/cover change in the southern part of Iraq (Basrah Province was taken as a case) by using a 1:250 000 mapping scale. Remote sensing and GIS software were used to classify Landsat TM in 1990 and Landsat ETM+ in 2003 imagery into five land use and land cover (LULC) classes: vegetation, sand, urban area, unused land, and water bodies. Supervised classification and normalized difference build-up index (NDBI) were used respectively to retrieve its urban boundary. An accuracy assessment was performed on the 2003 LULC map to determine the reliability of the map. Finally, GIS software was used to quantify and illustrate the various LULC conversions that took place over the 13-year span of time. Results showed that the urban area had increased by the rate of 1.2% per year, with area expansion from 3 299.1 km² in 1990 to 3 794.9 km² in 2003. Large vegetation area in the north and southeast were converted into urban construction land. The land use/cover changes of Basrah Province were mainly caused by rapid development of the urban economy and population immigration from the countryside. In addition, the former government policy of “returning farmland to transportation and huge expansion in military camps” was the major driving force for vegetation land change. The paper concludes that remote sensing and GIS can be used to create LULC maps. It also notes that the maps generated can be used to delineate the changes that take place over time. Supported by the Al-Basrah University, Iraq, the Geo-information Science and Technology Program (No. IRT 0438)China).     

Morphometric analysis of sub-watersheds in the pavagada area of Tumkur district,South India using remote sensing and gis techniques

The study area covers 570 km² comprising of 9 sub-watersheds (Dalavayihalli, Maddalenahalli, Talamaradahalli, Puluvalli tank, Nagalamadike, Gowdatimmanahalli, Naliganahalli, Devadabetta and Byadanur) range from 49 to 75 km² forming part of Pennar river basin around Pavagada. The drainage network of 9 sub-watersheds was delineated using remote sensing data - Geocoded FCC of bands - 2 3 4 of IRS 1 C and 1 D (LISS III+PAN merged) on 1:50,000 scale and SOI topomaps were used as reference. The morphometric analysis of 9 sub-watersheds has been carried out using GIS softwares - Arclnfo and Are View. The drainage network shows that the terrain exhibits dendritic to sub-dendritic drainage pattern. Stream orders ranges from fourth to fifth order. Drainage density varies between 1.55 and 2.16 km/ km² and has very coarse to coarse drainage texture. The relief ratio range from 0.006 to 0.021. The mean bifurcation ratio varies from 3.21 to 4.88 and falls under normal basin category. The elongation ratio shows that Devedabetta sub-watershed possesses circular shape while remaining sub-watersheds mark elongated pattern. Hence from the study it can be concluded that remote sensing techniques proved to be a competent tool in morphometric analysis.     

Shoreline and coral reef ecosystem changes in gulf of Mannar, Southeast coast of India

Changes in shoreline, coral reef and seafloor have been mapped using remote sensing satellite data of IRS LISS-III (1998), IRS LISS-II (1988), Survey of India Topographic sheet (1969), Naval Hydrographic Chart (NHO) 1975 and bathymetry data (1999) with ARC-INFO and ARC-VIEW GIS. The analysis of multi-date shoreline maps showed that 4.34 and 23.49 km2 of the mainland coast and 4.14 and 3.31 km² areas of island coast have been eroded and accreted, respectively, in the Gulf of Mannar. The analysis of multi-date coral reef maps showed that 25.52 km² of reef area and 2.16 km² of reef vegetation in Gulf of Mannar have been lost over a period of ten years. The analysis of multi-date bathymetry data indicates that the depth of seafloor has decreased along the coast and around the islands in the study area. The average reduction of depth in seafloor has been estimated as 0.51m over a period of twenty four years. The increased suspended sediment concentration due to coastal and island erosion, and raised reef due to emerging of coast by tectonic movement are responsible for coral reef degradation in the Gulf of Mannar. Validation by ground truth has confirmed these results.     

Runoff estimation and potential recharge site delineation using analytic hierarchy process

One of the prime global issues in the field of hydrological science is water scarcity and its degrading quality. In this paper, geographic information system (GIS) and remote sensing techniques are applied over a study of granite watershed area of ～200 km² with semi-arid climatic conditions for estimating surface runoff using a modified soil conservation service curve number method and subsequent site selection for water harvesting structures such as check dams and percolation ponds to enhance recharge of groundwater. Further, some of the sites selected for appropriate construction of recharge structures through analytic hierarchy process were investigated for site efficacy. All the recharge sites selected were found feasible and appropriately suitable. This study demonstrates the capability of GIS and its application for the construction of water harvesting structures over semi-arid areas.     

Study of a wide-angle laser ranging system for relative positioning of ground-based benchmarks with millimeter accuracy

A wide-angle airborne laser ranging system (WA-ALRS) is developed at the Institut Géographique National (IGN), France, with the aim of providing a new geodesy technique devoted to large (100 km²) networks with a high density (1 km⁻²) of benchmarks. The main objective is to achieve a 1-mm accuracy in relative vertical coordinates from aircraft measurements lasting a few hours. This paper reviews the methodology and analyzes the first experimental data achieved from a specific ground-based experiment. The accuracy in relative coordinate estimates is studied with the help of numerical simulations. It is shown that strong accuracy limitations arise with a small laser beam divergence combined with short range measurements when relatively few simultaneous range data are produced. The accuracy is of a few cm in transverse coordinates and a few mm in radial coordinates. The results from ground-based experimental data are fairly compatible with these predictions. The use of a model for systematic errors in the vehicle trajectory is shown to be necessary to achieve such a high accuracy. This work yields the first complete validation of modelization and methodology of this technique. An accuracy better than 1 mm and a few mm in vertical and horizontal coordinates, respectively, is predicted for aircraft experiments. Received: 19 June 1997 / Accepted: 17 February 1998     

Delineation of groundwater potential zone in hard rock terrain of India using remote sensing,geographical information system (GIS) and analytic hierarchy process (AHP) techniques

The present study has been undertaken to delineate the groundwater potential zones in the hard rock terrain of Palamu district, Jharkhand using the advanced applications of remote sensing, geographical information systems and analytic hierarchy process techniques. The integration and analyses of various thematic databases viz., geomorphology, lithology, soil, slope, lineament density, weathered zone thickness, drainage density and rainfall proved useful in the delineation of GWP zones. The study indicates that only 136?km² of the study area exhibit excellent groundwater potential, 248?km² has very good groundwater potential, whereas 36.89 and 38.23% are under poor and very poor groundwater potential zones, respectively. Hence, only a total of 11.6% of the area (490?km²) is classified as high to excellent groundwater potential. The final groundwater prospect map obtained was classified as excellent potential, very good potential, good potential, moderate potential, poor potential and very poor potential zone.     

Mapping and classification of hydrological parameters from digital terrain data in the Musandam Peninsula,UAE and Oman

Groundwater exploration and modelling requires hydrological parameters and a large volume of hydrologic database. This study integrates remote sensing and geographic information system (GIS) to map and classify hydrological parameters indicates areas of groundwater recharge and discharge. Bivariate quadratic surfaces with moving window size of 5 × 5 were fitted to the digital elevation model and drainage basins, drainage network, topographic wetness index (TWI) and hydroforms were derived. The eight-direction algorithm (D8) that determines in which neighbouring pixel any water in a central pixel will flow naturally was used to delineate drainage basin and drainage network in the study area. The TWI was used to quantify the effect of local topography on hydrological processes and for modelling soil moisture. The results indicate the presence of intensive of stream network (1336 km²), wettest zones and accumulation zones (63.99 km²) within Wadi Bih, the UAE and Wadi Khasb, Oman, suggesting regional recharge.     

Habitat Suitability Assessment of <Emphasis Type="Italic">Ardeotis nigriceps</Emphasis> (Vigors) in Great Indian Bustard Sanctuary,Maharashtra (India) Using Remote Sensing and GIS

Ardeotis nigriceps, commonly known as Great Indian Bustard (GIB), is a Critically Endangered, Evolutionary Distinct and Globally Threatened (EDGE) and endemic species to the Indian subcontinent. GIB is under tremendous threat in its last strongholds and sliding inextricably towards extinction. The GIB sanctuary in Maharashtra (India) is one of the last refuges of the bird constituting an area of 8496 km² spread over in seven talukas of Solapur and Ahemednagar districts. Major portion of the sanctuary (94.3 %) consists of privately owned lands under a variety of economic vocations and large number of villages and townships. In view of the legal restrictions relating to Protected Area under the Wildlife (Protection) Act of India 1972, the inhabitants of villages and townships faced a very difficult situation regarding use of their lands, development of properties and deriving benefits from planned local and regional development. This created conflict between local people and the forest department over the use of land, which necessitated the rationalization of the sanctuary. The objective of the present study was to map the suitable habitat of GIB in GIB Wildlife Sanctuary as an input for the realignment of the GIB Sanctuary by identifying areas that are important for the GIB. Main parameters considered for the habitat suitability assessments are, habit and habitat of GIB, slope, minimum patch size and disturbance sources. Based on the criteria derived for the ecological and biological requirements of GIB, binary deductive habitat suitability modeling has been done using remote sensing and GIS and prioritized the potential habitats of GIB. The net area of important suitable habitat of GIB in GIB sanctuary is 2304.99 km² out of 8496.44 km². The output of the present study has been used as an input by the committee (set by Honorable Supreme court of India) on rationalization of the GIB Sanctuary and the sanctuary has been rationalized with an area of 1222 km².     

Assessment and planning for integrated river basin management using remote sensing,SWAT model and morphometric analysis (case study: Kaddam river basin,India)

Abstract

River basin assessment is crucial for water management and to address the watershed issues. So, an integrated river basin management and assessment model using morphometric assessment, remote sensing, GIS and SWAT model was envisaged and applied to Kaddam river basin, Telangana state, India. Morphometric results showed high drainage density ranging from 2.19 to 5.5?km²/km, with elongated fan shape having elongation ratio of 0.60–0.75 with sparse vegetation and high relief. Land use change assessment showed that 265.26?km² of forest land is converted into irrigated land and has increased sediment yields in watersheds. The calibration (r ²?=?0.74, NSE?=?0.84) and validation (r ²?=?0.72, NSE?=?0.84) of SWAT model showed that simulated and observed results were in agreement and in recommended ranges. The SWAT simulations were used to compute mean annual water and sediment yield from 1997 to 2012, along with morphometric results to categorize critical watersheds and conservation structures were proposed accordingly.     

Improving Spatial Accuracy of Roadway Networks and Geocoded Addresses

Exposure to traffic‐related pollutants is associated with both morbidity and mortality. Because vehicle‐exhaust are highly localized, within a few hundred meters of heavily traveled roadways, highly accurate spatial data are critical in studies concerned with exposure to vehicle emissions. We compared the positional accuracy of a widely used U.S. Geological Survey (USGS) roadway network containing traffic activity data versus a global positioning system (GPS)‐validated road network without traffic information; developed a geographical information system (GIS)‐based methodology for producing improved roadway data associated with traffic activities; evaluated errors from geocoding processes; and used the CALINE4 dispersion model to demonstrate potential exposure misclassifications due to inaccurate roadway data or incorrectly geocoded addresses. The GIS‐based algorithm we developed was effective in transferring vehicle activity information from the less accurate USGS roadway network to a GPS‐accurate road network, with a match rate exceeding 95%. Large discrepancies, up to hundreds of meters, were found between the two roadway networks, with the GPS‐validated network having higher spatial accuracy. In addition, identifying and correcting errors associated with geocoding resulted in improved address matching. We demonstrated that discrepancies in roadway geometry and geocoding errors, can lead to serious exposure misclassifications, up to an order of magnitude in assigned pollutant concentrations.