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This research examines the social-spatial dynamics of human–environment interactions in Evansville, Indiana, USA as well as the surrounding Vanderburgh County. Employing geographically weighted regression, this paper models the observed relationship between the Normalized Difference Vegetation Index (NDVI) and key sociodemographic parameters (housing value, median household income, percent of residents in poverty, population density and percent of population white). Further, this paper demonstrates that geographically weighted regression utilized within a GISci framework can be effectively used to visualize urban human–environment interactions and that the spatial distribution of environmental resources co-varies with socioeconomic conditions. Finally, the paper demonstrates that greenness indicators derived from remote sensing data can be used as proxy measures for observed sociodemographic variables.

This paper presents a spatial autoregressive (SAR) method-based cellular automata (termed SAR-CA) model to simulate coastal land use change, by incorporating spatial autocorrelation into transition rules. The model captures the spatial relationships between explained and explanatory variables and then integrates them into CA transition rules. A conventional CA model (LogCA) based on logistic regression (LR) was studied as a comparison. These two CA models were applied to simulate urban land use change of coastal regions in Ningbo of China from 2000 to 2015. Compared to the LR method, the SAR model yielded smaller accumulated residuals that showed a random distribution in fitting the CA transition rules. The better-fitting SAR model performed well in simulating urban land use change and scored an overall accuracy of 85.3%, improving on the LogCA model by 3.6%. Landscape metrics showed that the pattern generated by the SAR-CA model has less difference with the observed pattern.

This paper presents a land use and land cover (LULC) classification approach that accounts landscape heterogeneity. We addressed this challenge by subdividing the study area into more homogeneous segments using several biophysical and socio-economic factors as well as spectral information. This was followed by unsupervised clustering within each homogeneous segment and supervised class assignment. Two classification schemes differing in their level of detail were successfully applied to four landscape types of distinct LULC composition. The resulting LULC map fulfills two major requirements: (1) differentiation and identification of several LULC classes that are of interest at the local, regional, and national scales, and (2) high accuracy of classification. The approach overcomes commonly encountered difficulties of classifying second-level classes in large and heterogeneous landscapes. The output of the study responds to the need for comprehensive LULC data to support ecosystem assessment, polic...

Temporal analysis of Landsat-TM imageries reveals a saturated state of Kolkata (Calcutta) Metropolitan Area. However, the city has witnessed accelerated growth in real estate construction in recent past. This study applies digital photogrammetry to quantify the changes in Kolkata’s skyline. Recently, released SRTM DEM of 1 Arc Second and a digital surface model derived from WorldView-1 stereo images were used to account for the past and recent surface heights, respectively. Consequently, this paper examines whether the sustained addition in housing capacity has been necessarily driven by a growth in the urban population/number of households. Results show that 40.31% of the area experienced vertical growth, majorly by replacing older dwellings with taller apartment blocks. Further analysis reveals that part of these newly added residences has remained unoccupied as they were purchased by non-resident Indians for using as a second home or was never sold due to recent economic slowdown.

This paper summarizes a new methodology which is available for topographic mapping purposes at scales of 1: 50 000 or smaller. The process, referred to as STARMAP, uses airborne Synthetic Aperture Radar (SAR) data collected in stereo mode, from which a digital terrain model (DTM) is derived and used to remove terrain displacement effects during rectification of the imagery. A new product ‐the Radar Image Map ‐ is presented in the paper and the elements of a hypothetical operational STARMAP program are described. This methodology provides a means by which topographic mapping products can be reliably obtained in habitually cloud or haze covered regions. For many user agencies in such regions, this may be the only method available for generating high quality topographic maps.

This paper decribes the challenge posed by Canada's size to the Canadian map making community. Discussed first is the map maintenance problem. This is followed by an outline of the application of LANDSAT to map updating, including results achieved to date. The paper closed with a look to the near term future including the use of SPOT imagery.

This paper investigates the disappearing residential geography of Detroit, Michigan, between 1975 and 2005 by examining the relationship between the ‘greenness’ of the urban landscape and the structural thinning of residential areas via satellite imagery and census data. The study uses normalized difference vegetation index (NDVI) and key housing variables as a proxy for observed changes in neighbourhood structure that correspond to the neighbourhood life cycle. Ordinary least squares and geographically weighted regression (GWR) were used to visualize the observed trends and performance of the models across space. Results from GWR analyses suggest the shifting residential geography of Detroit has changed from uniformly developed residential blocks to neighbourhoods that have experienced severe structural thinning across an urban landscape characterized by uneven development. The performance of the study models and parameters demonstrate how the relationships among NDVI and housing indicators, though signi...

This study aims to investigate the effectiveness of three main textural indices for the automatic evaluation and classification of landscape scenic quality using digital ground photographs. Based on the textural indices that are commonly used in landscape ecology, the richness, diversity and dominance indices were selected to be examined, and the results from the application of these indices to a sample of ground photographs are described in this paper. The application of the textural indices to the sample of photographs takes place in two different ways, using a geographic information system (GIS) that aims to describe the general and partial heterogeneity of the landscape appearing in each photograph. Furthermore, we investigate the effectiveness of the indices selected as to the classification of the landscape's scenic quality, with the results being compared to other results derived from a research programme of the National Technical University of Athens. Comments and suggestions are presented for fur...

Hong Kong as an international metropolis is well known for its vibrant urban life, which attracts millions of mass conventional tourists for shopping and business. Recently, ecotourism has flourished and attracts ecotourists who visit the ecological and cultural resources of the rural landscape, country parks and marine parks. Yan Chau Tong, also known as ‘Double Haven’, is remote from the urban centre, which helps preserve its natural flavour and cultural heritages such as Hakka walled villages. It is noted as an important site for developing ecotourist activities. A symbiosis of humans and nature cannot be achieved without a sound planning and zoning scheme. This paper investigates the use of IKONOS imagery and a geographic information system for rational planning of ecotourist activities and conservation measures. Through image classification of IKONOS and integrated with ecological data, essential habitats can be mapped and a spatial database is established. Suitable sites for recreational activities ...

This paper explores the feasibility of integrating GPS and remote sensing data into a GIS database through rectification of satellite images of both urban and rural areas using uncorrected GPS coordinates. A GPS receiver was used to log the coordinates of 25 ground control points (GCPs) in a rural area and 20 GCPs in an urban area. Their coordinates were also read from topographic maps. Both sets of coordinates were used to rectify Landsat TM, and SPOT panchromatic (PAN) and multispectral (XL) images. It is found that none of the GPS coordinates are able to achieve an acceptable accuracy level of integration unless some inaccurate GCPs are excluded. The percentage of useable GCPs varies from less than 50 to nearly 90, depending on the spatial resolution of the image and the ease of GCP identification. On average, the difficulty in identifying GCPs on the ground and the image degrades integration accuracy by up to one pixel.

Census is the count or inventory of specific phenomenon, such as population, wild life, industry, livestock etc. Another aspect is that census is carried out periodically to show the changing trends of the phenomenon and state. Space based imaging systems, from their vantage position, has unambiguously demonstrated their capability in providing vital information on natural resources. With the availability of high-resolution multi-spectral and panchromatic earth observation images and geographic information system, can we now consider a natural resources census? The census of natural resources - land, water, soils, forests and other elements conducted in a systematic manner and with a repeat cycle to depict changes and modifications can provide a "snap-shot" of a country's status of natural resource at a particular moment of time and help in identifying areas of rapid and significant changes, which can be monitored in detail. Such inventory with periodic monitoring would help in managing the natural resources and will provide inputs to meet the demands of large population in terms of more food production, more energy generation, water management, better civic amenities, more infrastructure built-up and increasing per-capital expenditure for maintaining a quality of life. In India, Natural Resources Census (NRC) programme has been conceptualized and is being implemented. The NRC will use Indian Remote Sensing satellite images and prepares natural resources information layers of 7 key themes (land use/land cover, soil, geomorphology, vegetation, snow/glacier, land degradation, wetlands) at 1:50,000 scale with the periodicity of 5-20 years for different themes. The NRC maps and data support the repository of natural resources information and contribute to the operationalisation of a spatial data infrastructure (SDI). Recognising that standardization of methodology for mapping and spatial database generation to enable NRC for SDI is important, few proto-type NRC studies has been conducted. This paper discusses the concept of a nation-wide NRC programme and the results of one of the proto-type studies (Bangalore urban district) that India has carried out. The concept, methodology and standards suggested for NRC will be certainly useful for any country.

A quick search of “exurbia” on the internet yields various definitions: ‘the region outside the suburbs of a city, consisting of residential areas (exurbs) that are occupied predominantly by rich commuters (exurbanites) (www. wordreference.com/English); and the cryptically self-referential ‘a typically exurban area’ (www.bartleby.com). Nighttime satellite imagery provided by the Defense Meteorological Satellite Program’s Operational Linescan System (DMSP OLS) shows expansive areas of low light surrounding all major metropolitan areas. These areas would be characterized as pure vegetation by 30 meter resolution Landsat imagery yet they contain large numbers of people who have significant social, economic, and ecological impacts (e.g. traffic congestion and problems associated with the urban-wildlands interface). Questions explored in this paper are: 1) How big are ‘exurban’ areas in the United States?; 2) What cities have relatively large exurban areas and what cities have relatively small exurban areas?; How many people live in exurban areas?; 4) What are the costs and benefits of exurban areas and who pays for and/or receives them?; and finally, 5)Who lives in exurban areas? Conventional wisdom suggests that these ‘exurbanites’ are rich commuters who choose to live in natural settings beyond the city and suburbia; however, astronomic increases in real estate prices in places like Boston, New York, San Francisco, and Los Angeles suggest that many ‘exurbanites’ may be middle income teachers, police officers, and nurses trying to find affordable real estate. Our initial results suggest that 37% of the U.S. population lives in exurban areas that account for 14% of the land area. Purely urban areas account for 1.7% of the land area and house 55% of the population; and, rural areas (84% of the land area) contain only 8% of the population.

Land cover maps, especially vegetation maps, are of increasing interest and use to resource agencies. This paper describes a three‐stage hybrid classification method for regional‐scale multi‐level land cover mapping. The first stage involves an unsupervised classification and stratification. The second stage includes supervised classification of forest types, rule‐based clustering of non‐forested vegetation, and estimation of percent impervious area with a regression model. The third stage is final map generation and post processing. Landsat TM/ETM+ images of three (spring, summer, fall) dates were used to classify land cover of the seven‐county Twin Cities Metropolitan Area of Minnesota into three levels of the modified Minnesota Land Cover Classification System. The overall accuracies for Level‐1 and Level‐2 classes were 95% and 89%, respectively, and the agreement between the estimation of percent impervious surface in Level‐3 classification and the measurements from digital ortho photographs ...

In this paper, methods were developed to detect recently constructed buildings in the city of Beijing using remotely sensed data. The city of Beijing is going through a rapid developing period, both in the suburbs and inside the old city. To detect the building development in and around the city, Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper (ETM+) and SPOT High Resolution Visible (HRV) panchromatic (PAN) images were collected in 1994 and 2001. The two data sources were merged using a spectral‐preserving fusion method. An unsupervised classification was performed first on the merged dataset to separate urban built‐up areas with non built‐up areas. Buildings in the built‐up areas were then extracted using a classification method based on high‐pass filtered SPOT images. Our results show that over 83% of multi‐storey buildings can be detected using the merged dataset. The comparison of buildings extracted for the two years indicated the locations of building development between 1994 and ...

The paper describes the use of Principal Component Analysis (PCA) of remote sensing images as a method of change detection for the Kafue Flats, an inland wetland system in southern Zambia. The wetland is under human and natural pressures but is also an important wildlife habitat. A combination of Landsat MSS and TM images were used. The images used were from 24 September 1984 (MSS), 3 September 1988 (MSS), 12 September 1991 (TM) and 20 September 1994 (TM). They were geometrically co‐registered and, in the process, the 80m resolution MSS images were resampled to 30m using nearest neighbour resampling. Preliminary PCA revealed that for the MSS images most of the data variance was in near infrared reflectance while for the TM images it was in mid and thermal infrared bands. Holding sensor type constant, separate inter‐band correlation analysis for each image could indicate whether the wetland was drier or wetter on one date versus another. The 1994 image was made the reference image and equivalent g...

In this paper, we tested the use of active and passive sensor fusion for relating forest fire history to landscape spatial patterns. Principal Components Analysis (PCA) was implemented to combine Landsat Thematic Mapper (TM) and Shuttle Imaging Radar (SIR-C) data from October 1994. Resulting PCs were converted to landscape patch maps. Plots with known fire history were delineated using a fire atlas of the study area. These plots came from four fire history categories: unburned (nine plots), once burned (three plots), twice burned (three plots), and multiple burned (three plots). Landscape metrics were calculated for each plot, including a shape index, mean patch size, Shannon’s Diversity Index, and Shannon’s Evenness Index. Spearman’s Rank Correlation Analysis was used to compare the patch map-derived landscape metrics to fire history characteristics, such as average fire-free interval and number of fire-free years in different time periods. Results showed that landscape patterns derived from fused data were significantly (p < 0.05) related to fire history and typically performed better than SIR-C data (a greater number of significant correlations), but not as well as TM data.

This paper addresses multiple semi‐automated methods for discriminating landuse/landcover (LULC) classification in the absence of field data. The study site comprises a heterogeneous mixture of physiographic landscape elements in a remote area of eastern Mexico. Classification of modified Tasseled Cap transformations as well as a hybrid unsupervised‐supervised classification technique were employed using a Landsat 7ETM+ scene; the panchromatic band was reserved for accuracy assessment. Using a random stratified sampling scheme, overall accuracies ranged from 61.5% to 83.3% and Khat accuracies varied from 56% to 81.1%. The classifications derived from modified Tasseled Cap transformations did not appropriately discriminate landscape components, possibly owing to landscape heterogeneity. Classification results were improved through the use of landscape stratification in the attribution phase in the hybrid classification procedure, recommended for complex environments. Lastly, this work underscores ...

This paper investigates the combination of metric aerial photography and near-infrared (NIR) videography data to improve the design of field-survey sampling frameworks. Spatial data collection can contribute up to 80% of the cost of deploying a Geographic Information System (GIS) based Decision Support System (DSS). The use of remotely sensed information, field survey using differential Global Positioning System (dGPS) and geostatistical interpolation methods maximises data quality for a given rate of sampling. Medium-format colour aerial photography and NIR videography were orthorectified to the national map base and mosaiced using ERDAS Imagine. The green and red layers of the aerial photography were combined with the NIR videography to form a false-colour composite image. Two sampling strategies were tested. The first stratified sampling on a per field basis, creating four points per hectare, randomly located within each field. The second strategy used the remotely sensed information to identify within-field variability classes for each field, using redgreen difference or normalised difference vegetation index (NDVI) models. These variability classes were used as a sub-stratification framework with each class sampled at the same rate of 4 per hectare. For both strategies the sample points were generated within ESRI ArcView and were located in the field using dGPS. Maps of stone content were created using geostatistical methods and validated against samples collected on a 100 metre grid. It was concluded that combining the two image sources to create a within-field stratification framework improved the precision of the results obtained from field-survey.

Recreational boating activities represent one of the highest risk populations in the marine environment. Moreover, there is a trend of increased risk exposure by recreational boaters such as those who undertake adventure tourism, sport fishing/hunting, and personal watercraft (PWC) activities. When trying to plan search and rescue activities, there are data deficiencies regarding inventories, activity type, and spatial location of small, recreational boats. This paper examines the current body of research in the application of remote sensing technology in marine search and rescue. The research suggests commercially available very high spatial resolution satellite (VHSR) imagery can be used to detect small recreational vessels using a sub-pixel detection methodology. The sub-pixel detection method utilizes local image statistics based on spatio-spectral considerations. This methodology would have to be adapted for use with VHSR imagery as it was originally used in hyperspectral imaging. Further, the authors examine previous research on ‘target characterization’ which uses a combination of spectral based classification, and context based feature extraction to generate information such as: length, heading, position, and material of construction for target vessels. This technique is based on pixel-based processing used in generic digital image processing and computer vision. Finally, a preliminary recreational vessel surveillance system - called Marine Recreational Vessel Reconnaissance (MRV Recon) is tested on some modified VHSR imagery.

The outward expansion of cities in the United States has been a source of concern and policy debate for well over forty years. This sprawling urban landscape has been cited as a contributing factor behind the loss of open space, environmental damage and increased congestion. To better understand urban expansion, monitoring programs are required to facilitate the systematic observation of urban expansion, and to provide critical information in order to adjust urban development policies. Monitoring the urban landscape has been a major application focus of satellite remote sensing technologies. Yet, research has shown that the complexity of the urban landscape frustrates simple characterization of cumulative land cover processes such as sprawl. In this paper an approach to the remote detection and characterization of sprawl is introduced based on the use of Dempster‐Shafer Theory of Evidence. Functioning as a soft‐classification algorithm, Demptster‐Shafer Theory offers a unique solution to the mapp...

The harvesting of any wildlife dictates that accurate monitoring of abundance is undertaken to ensure that viable populations of all the species involved are sustained. Currently, in South Australia, the monitoring of kangaroos is conducted by ‘trained observers’ visually counting the different kangaroo species from a Cessna 182 flying at a height of 250 feet and at a speed of 100 knots. Scientists involved with these survey methods acknowledge the inaccuracy of such fixed‐wing strip transects preferring to use helicopter line transects. However, the cost of the latter renders them unsuitable for large‐scale annual surveys. This paper reports on the outcomes of a pilot study introducing an alternative means of kangaroo population monitoring. The method involved using fixed‐wing aerial scanners utilizing both digital videography and a thermal scanner over a fauna reserve with known kangaroo numbers. The results show that the digital scanners have the potential to be used as a means of counting kan...

The short‐grass area of the Great Plains of the United States is a large, sparsely population region, which at one time was the home to millions of American buffalo. By the late 19th century, the buffalo had been basically eliminated from the region. For the last fifty years the region has faced major out‐migration and dwindling employment opportunities. Due to these conditions, a proposal dubbed the “Buffalo Commons” was introduced in 1987, which would return the short‐grass area to the buffalo. Such a proposal is not likely to materialize but a new national park based on the short‐grass ecology and the buffalo might be feasible, especially if it would generate the economy through tourism. This paper discusses a GIS instructional module designed to have students select a location for a “Buffalo Commons” national park.

Landsat Thematic Mapper (TM) data have been used to monitor land cover types and to estimate biophysical parameters. However, studies examining the spatial relationships between land cover change and biophysical parameters are generally lacking. With the integration of remote sensing and Geographic Information Systems (GIS), these relationships can be better explored. The research reported in this paper applies this integrated approach for detecting urban growth and assessing its impact on vegetative greenness in the Zhujiang Delta, China. Multi-temporal Landsat TM data were utilized to map urban growth and to extract and identify changes in vegetative greenness. GIS analyses were conducted to examine the changing spatial patterns of urban growth and greenness change. Statistical analyses were then used to examine the impact of urban growth on vegetative greenness. The results revealed that there was a notably uneven urban growth pattern in the delta, and urban development had reduced the scaled Normalized Difference Vegetation Index (NDVI) value by 30% in the urbanized area.

This paper examines the feasibility of spectral mixture analysis (SMA) in deriving comparable physical measures of urban land cover that describe the morphological characteristics of cities. SMA offers a way of analyzing satellite imagery of urban areas that may be superior to more standard methods of classification. Mixing models are based on the assumption that the remotely measured spectrum of a given pixel can be modeled as a combination of pure spectra, called endmembers. SMA, using four image endmembers (vegetation, impervious surface, soil, and shade), was applied to an IRS‐1C multispectral image in order to extract measures that describe the anatomy of the Greater Cairo region, Egypt, in terms of endmember fractions. The resulting fractions were then used to classify the urban scene into eight classes of natural and human‐built features through a decision tree (DT) classifier. The accuracy of the DT classification was compared to the accuracies of two per‐pixel supervised classifications ...

GIS is as indicative of the tools of modem geography but as obscure to most undergraduate students as barbecue is familiar and representative of the cultural traits of the American South. The purpose of this paper is to describe a GIS laboratory exercise that has proven to be effective for undergraduate students who have a variety of talents, backgrounds, and skills. The exercise demonstrates the application of GIS techniques through the use of a regional and cultural geography real world database. It permits exploration of GIS as a spatial association device and encourages students to explore statistical inferences as well as map display.

A major concept in urban geography deals with determining the spheres of influence for urban centers. This paper describes an instructional module used in two different geography courses showing students how a model might be developed to measure spheres of influence for multiple urban centers within a given region. A geographic information system (GIS) is employed throughout the development of the model. This module is incorporated into a traditional undergraduate urban geography course and a beginning GIS course. The software packages used are MapViewer and Grapher. The region is the Mississippi Lowlands with five urban centers: New Orlenas, Memphis, Little Rock, Jackson, and Baton Rouge. Keywords: GIS, spheres of influence, MapViewer, urban geography.

This paper reports on the application of an airborne digital video imaging system with visible red (R) (0.625‐0.635 μm), near‐infrared (NIR) (0.845‐0.857 μm), and mid‐infrared (MIR) (1.631‐1.676 μm) spectral sensitivity for distinguishing among a diversity of ecological ground conditions in a rangeland area in southern Texas. The system produces false color imaging similar to that of the Landsat Thematic Mapper (TM) satellite bands 5, 4, 3. Imagery from this system was useful for differentiating among a diversity of cover types including brushlands, grasslands, and wetlands. Computer analysis of the imagery showed that many of the ecological variables could be quantified. An accuracy assessment performed on the classified image showed an overall accuracy of 85%. The imagery was also useful for interpreting the coarser resolution TM. Ground radiometric reflectance measurements were made on various ecological ground types to assist in interpreting the imagery.

This paper describes the coastal Geomorphology of Godavari Delta studied by using airborne X-band Synthetic Aperture Radar (SAR) images and optical images of IRS‐1A LISS II. Palaeo‐offshores and the associated fluviomarine geomorphic features have been interpreted. The river morphology has been built with the help of interpretative maps prepared by the digital and visual analysis of SAR and LISS II data. X‐band airborne SAR images provided better tonal and textural variation and sharpness to delineate geomorphic features. The delineation of features such as meanderscars, palaeochannel scars and other features with greater ease compared to IRS‐1A LISS II vividly demonstrates it. Two geomorphic environments viz., fluvial and marine have been identified based on the interpreted landforms. The Godavari delta was built up with distributaries in four stages, displaying various geomorphic features. On the basis of field studies and images interpretation five strandlines have been identified. A younger s...

The area of interest is located at the border between Chile and Argentina at 27°10’ S. latitude and 68°30’ W. longitude in the High Cordillera of the Andes and includes the second‐highest mountain of America, the Nevado Ojos del Salado. Although the official Chilean altitude is given as 6,880 m, other figures can be found in the literature and various other maps. Situated in a picturesque volcanic terrain rising above the Puna de Atacama, Nevado Ojos del Salado is not only interesting from a geomorphological point of view, it is, e.g., the world's highest volcano, but also has recently become a much‐favored destination of the mountaineering world. Unfortunately, this area is not covered by reliable and publicly available maps at scales larger than 1:250,000. Therefore, this paper describes the methods employed in and results obtained from topographic mapping of this remote area using spaceborne as well as airborne remotely sensed data. Exploiting Space Shuttle Earth‐viewing photographs, ERS‐1 Syn...