Modeling sprawl of unauthorized development using geospatial technology: case study in Kuantan district,Malaysia

Abstract

The paper explores a framework combining remote sensing and GIS-cellular automata (CA) concepts aimed at improving the modeling of unauthorized land use sprawl. Remote sensing data have been used in urban modeling and analysis, the use of high-resolution remote sensing data in assessing unauthorized development is quite unexplored. This work has demonstrated systematic combination utilization of geospatial analyses tools to acquire a new level of information to enable urban modeling and sprawl analysis in assisting urban sustainable management. In this study, Kuantan city, Malaysia was selected in simulation of the unauthorized land use with CA concept for a period of 15 years (2000–2015), with main input time-series land use observation from 1995 to 2005. The 2000 and 2005 land use input was also used as calibrated and test assessment of the simulation. The results show excellent agreement between in-situ changes of the unauthorized land use classes and the corresponding simulated classes within the same periods. In conclusion, CA model can lead to new levels of understanding of how urban areas grow and change as in view of digital earth aspiration.     

Groundwater potential modelling using remote sensing and GIS: a case study of the Al Dhaid area,United Arab Emirates

The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) DEM and LANDSAT images of spatial resolution 30?m were used to construct groundwater potential zones (GPZ) map by integrating geological fractures, drainage network, slope and relief, and convergence index maps of the study area. Weight and score of each map were developed according to their level of contribution toward groundwater accumulation and spatial distribution of groundwater wells. The area that has very high potential for groundwater is located at the foot of Oman Mountains and Al Dhaid Depression covering an area of about 59.33?km², which is 4.40% of the study area. Further hydrological map and data on hydraulic properties of shallow aquifer, as recorded from observation wells in the regions, have been used to validate the produced GPZ map. The validation result showed sufficient agreement between the produced GPZ map.     

Application of Remote Sensing and GIS Technology to the Study of Desertification of Arable Lands in North Shaanxi, China

The policy of the Chinese government concerning the horizontal expansion of the cultivated land through the reclamation of desert soils result in a total increase of 665. 985 km^2 during the period 1987-1999 in North Shaanxi. This increase is less than the loss in arable land by urbanization. The accelerated rate of change in agricultural areas calls for more rapid surveys of urbanization and loss of arable land. Remote sensing has a number of advantages over ground-based methods for such surveys. The multi-scale concept of remote sensing data help us study the problem in four towns. Several maps were produced to analyze the situation of urban coverage in different times. The evaluation of the status, rate and risk of urbanization are based on an accepted average of urban increase as 2% of population growth per year.     

Application of remote sensing and GIS technology to the study of desertification of arable lands in North Shaanxi,China

The policy of the Chinese government concerning the horizontal expansion of the cultivated land through the reclamation of desert soils result in a total increase of 665. 985 km2 during the period 1987–1999 in North Shaanxi. This increase is less than the loss in arable land by urbanization. The accelerated rate of change in agricultural areas calls for more rapid surveys of urbanization and loss of arable land. Remote sensing has a number of advantages over ground-based methods for such surveys. The multi-scale concept of remote sensing data help us study the problem in four towns. Several maps were produced to analyze the situation of urban coverage in different times. The evaluation of the status, rate and risk of urbanization are based on an accepted average of urban increase as 2% of population growth per year.     

Remote detection of geological structures: an application to the Aravalli region,western India

Optical and microwave remote sensing data are used in conjunction with a digital elevation model to map lineaments in the central parts of the Aravalli region, Rajasthan, western India. Lineament maps interpreted from each data-set are subsequently combined to derive a composite lineament map of the area. Rose plots are used to identify the prominent trends of the lineaments and compared with published structural map of the study area. Three major trends are identified, namely, the NE–SW, NNE–SSW and EW, which are interpreted to be, related to the DF1, DF2 and DF4 deformation phases identified by the previous workers through field studies. The lineaments are classified as fold axes or faults, and a total of 10-fold axes and 30 faults mapped in the area.     

Urban growth monitoring and projection using remote sensing and geographic information systems: a case study in the Twin Cities Metropolitan Area,Minnesota

This study investigates urban growth dynamics from regional to local scales in the Twin Cities Metropolitan Area and demonstrates how metropolitan growth can be driven by policies. Urban change from 1975 to 2006 was detected using Landsat imagery. Future growth in 2030 was modelled based on two scenarios with or without regional development policies incorporated. City- or township-level growth was examined by a zonal analysis. Results show urban grew 126,700 ha from 1975 to 2006. The Markov-Cellular Automata model projected at least another 67,000 ha of urban growth from 2006 to 2030. When regional development policies were incorporated, homogeneous and compact growth patterns were predicted along the urban periphery; however, actual land supplies within the cities along the urban edge are facing challenges to accommodate the projected growth as large portions of suitable lands are located outside of the 2030 Municipal Urban Service Area boundary.     

A Geographic Information System (GIS)-based approach for relating anthropogenic impact and environmental stress: a case study within the African Albertine Rift

This study introduces a potentially cost-effective methodology to assess habitat quality remotely using anthropogenic variables derived from both Geographic Information System (GIS) and remote sensing. We related anthropogenic impact to organism-level response across the Albertine Rift of East-Africa, which was measured using body condition (BC) in Lophuromys aquilus, the dark-coloured brush-furred rat. We chose seven variables to measure anthropogenic impact, ranging from land cover/land use to nighttime light radiance. Using a principal component analysis, we extracted four components that describe human impact and correlated each with BC. We documented that BC tended to be higher in more disturbed areas. We recommend this GIS-based methodology to relate anthropogenic impact to organismal-level response in the Albertine Rift region, and we provide broad guidelines for its application to assess habitat quality for species of conservation concern.     

Prediction of soil loss differences and sediment accumulation at the Nilufer creek watershed,Turkey, using multiyear satellite data in a GIS

This study integrates the RUSLE, remote sensing and GIS to assess soil loss and identify sensitive areas to soil erosion in the Nilufer creek watershed in Bursa province, Turkey. The annual average soil loss was generated separately for years 1984 and 2011, in order to expose possible soil loss differences occurred in 27 years. In addition, sediment accumulation and sediment yield of the studied watershed was also predicted and discussed. The results indicated that very severe erosion risk areas in 1984 was 13.4% of the area, but it was increased to 15.3% by the year 2011, which needs immediate attention from soil conservation point of view. Furthermore, the estimated annual sediment yield of the Nilufer creek watershed was increased from 903 to 979 Mg km^?2 y^?1 in 27 years period. The study also provides useful information for decision-makers and planners to take appropriate land management practices in the area.     

Demonstration of uncertainty resulting from MODerate resolution Imaging Spectroradiometer-like geometries: an albedo case study

This research examines uncertainty in MODerate resolution Imaging Spectroradiometer (MODIS) observations, and demonstrates the direct influence of geometric distortions resulting from the standard practice of geolocating swath observations. MODIS observations vary dependent on the ground sample distance, which varies dependent on the view zenith angle that changes with every orbit. MODIS Level 2G (L2G) land products are generated by applying a geolocation algorithm that resamples the variable observation geometries to a consistent grid of fixed pixel size and location, a process which itself introduces variability associated with the changing observational footprint. For this study, broadband albedo was simulated for five validation sites, representing five distinct land cover types, exhibiting quantifiable variability, with additional seasonal variability exhibited in some sites. All site simulations exhibit compounded uncertainty attributable to the geometric distortion sufficient to influence climate models (i.e. ranges from 0.01 to 0.045 albedo). These results indicate there is a minimum level of uncertainty associated with the variable geometry that should be factored into L2G-based products, particularly for nominal 250?m band data. Aggregating the data to coarser resolutions and smoothing the data through average resampling can mitigate the uncertainty.     

Detecting and mapping slums using open data: a case study in Kenya

ABSTRACT

The worldwide slum population currently stands at over one billion, with substantial growth expected in the coming decades. Traditionally, slums have been mapped using information derived mainly from either physical indicators using remote sensing data, or socio-economic indicators using census data. Each data source on its own provides only a partial view of slums, an issue further compounded by data poverty in less-developed countries. To overcome such issues, this paper explores the fusion of traditional with emerging open data sources and data mining tools to identify additional indicators that can be used to detect and map the presence of slums, map their footprint, and map their evolution. Towards this goal, we develop an indicator database for slums using open sources of physical and socio-economic data that can be used to characterize slum settlements. Using this database, we then leverage data mining techniques to identify the most suitable combination of these indicators for mapping slums. Using three cities in Kenya as test cases, results show that the fusion of these data can improve the mapping accuracy of slums. These results suggest that the proposed approach can provide a viable solution to the emerging challenge of monitoring the growth of slums.     

Cartography and the others – aspects of a complicated relationship

ABSTRACT

Cartographic visualizations have been known for thousands of years and have brought forth a wealth of different map projections and cartographic products. Yet, cartography as an independent science has been established only about 100 years ago and sometimes its position among the spatial disciplines is challenged by the scientific community. In this respect it is a young science based on a very long tradition of map making, globe production, and the development of map projections. Maps and map related visualizations play an important and indispensable role in many other spatial disciplines such as geography and geodesy. Cartography has many overlaps with these traditional disciplines as well as with the more recent ones of photogrammetry and remote sensing. This paper reviews fundamental aspects of the conception of space and time throughout human history, the historic development of cartography from a technique of map making to a spatial science, highlighting major milestones in the history of the discipline. As a young science and confronted with major technological developments in the late 20^th century cartography underwent several crises as to what exactly is cartography and how it relates to other spatial sciences, in particular to geographic information systems. Major pitfalls and misconceptions are discussed and the three major scientific pillars of cartography are identified. The relationships of cartography with neighboring disciplines are discussed and the position of cartography vis a vis the others is delineated. Finally, desirable future developments of scientific cartography are discussed.     

A transboundary study of urban sprawl in the Pacific Coast region of North America: The benefits of multiple measurement methods

Sprawling urban development has emerged as a primary concern of policy makers, land preservationists and both urban and rural communities in developing regions across the globe. For the first time in history, more global residents lived in urban areas than not and the trend to urbanization is in full force at the start of the 21st century. An understanding of the nature and character of urban sprawl is complicated by a failure to satisfactorily define it and by the limitations of measurement techniques designed to characterize complex landscape forms. Like other landscape patterns, the quantification of urban sprawl is highly spatially and temporally scale-dependent. This paper summarizes a recent project to measure urban sprawl in the transboundary region of the Pacific Coast of North America. The metropolitan centers of Portland, OR, Seattle, WA and Vancouver, BC, span two nations, three state/provincial governments and dozens of cities. As a region, this was a global leader in population growth in the 1990s. The study relied on three separate methods – an impervious surface metric, a neighborhood density metric and a building permit metric – for quantifying urban growth. The results provide insight on the strengths and shortcomings of different methods with respect to the challenges posed by data availability and format. Taken together they demonstrate the richer understanding that combined methods may offer in characterizing phenomena as difficult to communicate and agree upon as urban sprawl.     

Geospatial analysis of land-use change processes in a densely populated coastal city: the case of Port Harcourt,south-east Nigeria

This study examines the pattern and processes of land-use change in a densely populated coastal city in the oil-rich Niger Delta region of Nigeria for 27?years using remote sensing and Geographic Information Systems. The results indicate that between 1986 and 2013, settlement/bare surface, mangrove forest/wetland and water body increased at 0.84% per year, 0.05% per year and 0.10% per year, respectively, while arable land/secondary vegetation and natural forest loss at 0.47% per year and 0.52% per year, respectively. This implies that intensity of change varies temporally. The implications of these changes include loss of valuable environmental goods and services, alteration of the food chain and increased impacts of climate change–related disasters. It is recommended that steps be taken to slow down the rate of land-use change in the study area to reduce its impact on the environment and social well-being.     

Demarcation of potential avalanche sites using remote sensing and ground observations: a case study of Gangotri glacier

This study demonstrates the effectiveness of remote sensing and analytical hierarchy process for avalanche hazard mapping. The layers incorporated in this study were of slope, aspect, profile curvature, ground cover and elevation. The accuracy of output was determined using the registered avalanche sites based on ground observations and field-based modelling techniques. 93.35% of avalanche-affected areas came under maximum and moderate hazard zones, thus proving the effectiveness of this technique for Gangotri glacier basin. A parallel study was done to observe the change in the results, if any, by using high-resolution DEM and Cartosat-1 imagery. Similar methodology was adopted and the outcome was having significant improvement over the previous result as 98.8% of the preregistered avalanche area falling within maximum and moderate hazard zones.     

A novel approach for predicting the spatial patterns of urban expansion by combining the chi-squared automatic integration detection decision tree,Markov chain and cellular automata models in GIS

Urban development is a continuous and dynamic spatio-temporal phenomenon associated with economic developments and growing populations. To understand urban expansion, it is important to establish models that can simulate urbanization process and its deriving factors behaviours, monitor deriving forces interactions and predict spatio-temporally probable future urban growth patterns explicitly. In this research, therefore, we presented a hybrid model that integrates the chi-squared automatic integration detection decision tree (CHAID-DT), Markov chain (MC) and cellular automata (CA) models to analyse, simulate and predict future urban expansions in Tripoli, Libya in 2020 and 2025. First, CHAID-DT model was applied to investigate the contributions of urban factors to the expansion process, to explore their interactions and to provide future urban probability map; second, MC model was employed to estimate the future demand of urban land; third, CA model was used to allocate estimated urban land quantity on the probability map to present future projected land use map. Three satellite images of the study area were obtained from the periods of 1984, 2002 and 2010 to extract land use maps and urban expansion data. We validated the model with two methods, namely, receiver operating characteristic and the kappa statistic index of agreement. Results confirmed that the proposed hybrid model could be employed in urban expansion modelling. The applied hybrid model overcame the individual shortcomings of each model and explicitly described urban expansion dynamics, as well as the spatio-temporal patterns involved.     

A simple retrieval method of land surface temperature from AMSR-E passive microwave data—A case study over Southern China during the strong snow disaster of 2008

The analysis of the passive microwave radiance transfer equation certifies that there is a linear relationship between satellite-generated brightness temperatures (BT) and in situ observation temperature and that land surface temperature (LST) is largely influenced by vegetation cover conditions. Microwave polarization difference index (MPDI) is an effective indicator for characterizing the land surface vegetation cover density. Based on the analysis of LST models from AMSR-E BT with 6.9 GHz MPDI intervals at 0.04, 0.02 and 0.01, respectively, this paper developed a simplified LST regression model with MPDI-based five land cover types, combining observation temperatures from 86 meteorological observation stations. The study shows that smaller MPDI intervals can obtain higher accuracy of AMSR-E LST simulation, and that the combination of HDF Explorer and ArcGIS software was useful for automatically processing the pixel latitude, longitude and BT information from the AMSR-E HDF imagery files. The RMSE of the five LST simulation algorithms is between 1.47 and 1.92 °C, with an average LST retrieval error of 0.91–1.30 °C. Besides, only 7 polarization bands and 5 land surface types are required by the proposed simplified model. The new LST simulation models appears to be more effective for producing LST compared to past most studies, of which the accuracy used to be more than 2 °C. This study is one of the rare applications that combine the meteorological observation temperature with MPDI to produce the LST regression analysis algorithms with less RMSE from AMSR-E data. The results can be referred to similar areas of the world for LST retrieval or land surface process research, in particular under extreme bad weather conditions.     

基于遥感与GIS的干旱区石油城镇用地扩展分析——以克拉玛依市独山子区为例

以克拉玛依市独山子区为例,采用1989年、1999年、2006年三期Landsat TM遥感图像数据为基础数据源,在遥感和GIS技术的支持下,阐述了提取研究时段内城镇用地扩展数据的技术路线,并结合城市地理学方法,进一步对城镇空间扩展进行了定量分析,结合社会经济统计数据,对独山子区城市用地扩展驱动力进行了尝试性分析,并对以后城市扩展提出对策,以期探讨遥感与GIS技术用于城市地理学的方法和过程。     

未种植耕地动态变化遥感识别——以阿根廷为例

连续多年的高强度耕作会导致耕地层土壤养分、土壤有机质等逐渐下降,在作物收获之后作物秸秆还田量较少的情况下尤其突出,而对耕地利用状况动态变化(种植耕地与未种植耕地的动态变化)的识别,能够有效地反映出不同作物的轮作模式以及耕地种植强度的变化。本文以阿根廷3大农业主产省份(布宜诺斯艾利斯省、科尔多瓦省以及圣太菲省)为研究区,利用中分辨率成像光谱仪(MODIS)16天合成的归一化植被指数(NDVI)数据产品,在分析不同地物类型、不同耕作模式下的NDVI动态变化过程的基础上,结合地面样本数据统计获得有作物种植农田与无作物种植农田的识别阈值,综合利用阈值法和植被指数动态变化过程分析法对阿根廷3大主产省份开展了耕地利用状况动态变化遥感识别,实现了不同年份的耕地利用状况动态变化识别。地面观测数据验证结果表明,在阿根廷3大主产省内有作物种植耕地和未种植耕地的总体识别精度高于97%,但在不同的作物生长阶段,未种植耕地识别结果的精度差异较明显,在作物生长季内作物生长较为茂盛的时期,有作物种植耕地和未种植耕地的识别精度几乎达到99%,但在双季或多季作物种植区,作物轮作期间的耕地利用状况识别精度相对偏低,总体精度在95%左右,主要是受16天合成NDVI数据的最大值合成法限制。     

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.     

Indicator kriging applied to absorption band analysis in hyperspectral imagery: A case study from the Rodalquilar epithermal gold mining area,SE Spain

A new approach to the analysis of hyperspectral data for the purpose of surface compositional mapping is presented in this paper. We use an interpolated value of the absorption band position and the absorption band depth for the diagnostic of mineral absorption features. Using thresholds for this depth and position, the data is transformed to indicator [0,1] values. By kriging these values, we obtain the probability of exceeding certain absorption depth and the probability of a pixel exhibiting absorption features within a specified wavelength region. Using Bayesian statistics, the indicator kriging derived probabilities are used to produce a hard classification result. By adapting the prior probabilities to the dominant mineralogy in the various alteration facies mapped, data stratification is achieved. The classification results are compared to results derived using the spectral angle mapper and maximum likelihood classification. In addition, the results are statistically compared to field spectral data classified into dominant mineralogy. The indicator approach and the spectral angle mapper produce favourable results relative to field data and in comparison to the maximum likelihood classifier. A data set from the Rodalquilar high-sulfidation epithermal gold system in SE Spain, consisting of HyMAP airborne imaging spectrometer data and ASD field spectra focusing on the key minerals alunite, kaolinite, illite and chlorite, is used to illustrate the methodology.