Topology, homogeneity and scale factors for object detection: application of eCognition software for urban mapping using multispectral satellite image

The research scope of this paper is to apply spatial object based image analysis (OBIA) method for processing panchromatic multispectral image covering study area of Brussels for urban mapping. The aim is to map different land cover types and more specifically, built-up areas from the very high resolution (VHR) satellite image using OBIA approach. A case study covers urban landscapes in the eastern areas of the city of Brussels, Belgium. Technically, this research was performed in eCognition raster processing software demonstrating excellent results of image segmentation and classification. The tools embedded in eCognition enabled to perform image segmentation and objects classification processes in a semi-automated regime, which is useful for the city planning, spatial analysis and urban growth analysis. The combination of the OBIA method together with technical tools of the eCognition demonstrated applicability of this method for urban mapping in densely populated areas, e.g. in megapolis and capital cities. The methodology included multiresolution segmentation and classification of the created objects.Comment: 6 pages, 12 figures, INSO2015, Ed. by A. Girgvliani et al. Akaki Tsereteli State University, Kutaisi (Imereti), Georgi

A study on landuse and landcover classification using microwave data in Joida taluk of Uttara Kannada district, Karnataka

The study has been conducted for land use and land cover classification by using SAR data. The study included examining of ALOS 2 PALSAR L- band quad pol (HH, HV, VH and VV) SAR data for LULC classification. The SAR data was pre-processed first which included multilook, radiometric calibration, geometric correction, speckle filtering, SAR Polarimetry and decomposition. For land use land cover classification of ALOS-2-PALSAR data sets, the supervised Random forest classifier was used. Training samples were selected with the help of ground truth data. The area was classified under 7 different classes such as dense forest, moderate dense forest, scrub/sparse forest, plantation, agriculture, water body, and settlements. Among them the highest area was covered by dense forest (108647ha) followed by horticulture plantation (57822 ha) and scrub/Sparse forest (49238 ha) and lowest area was covered by moderate dense forest (11589 ha).   Accuracy assessment was performed after classification. The overall accuracy of SAR data was 80.36% and Kappa Coefficient was 0.76.  Based on SAR backscatter reflectance such as single, double, and volumetric scattering mechanism different land use classes were identified

AGRICULTURAL LAND CONVERSION ON MAKASSAR VICINITY

ASIAN Conference on Remote sensingMakassar city is the capital South Sulawesi province (05\ud 0\ud 08' S; 119\ud 0\ud 25' E) sited \ud on the western coast of the province, with population around 1.4 million (2011). The city laid on the \ud northern side (downstream) of the Jeneberang river and shares the river???s floodplain with the city of \ud Sungguminasa.\ud The city of Makassar is a waterfront city surrounded by fertile agricultural land (mostly the \ud rice field and dry land agriculture) on southern, ea stern and northern sides. The rising demand of \ud residence and business are enhance the sprawling of the city front lines over the fertile and technically \ud irrigated fields on its vicinities. The advance of urban sprawl in Makassar and Sungguminasa traced by \ud analyzing the multi-temporal data of remotely-sensed data on three sub urban area i.e. Kecamatan \ud Pallangga and Sombaopu on south-eastern direction (Kab. Gowa), Jeneberang delta and Kecamatan \ud Biringkanaya on the nothern area.\ud The analyses shows that the sprawling of the city front lines over the last 10 to 15 years has \ud been occurred rapidly, especially on Jeneberang delta where the farms has been converted into massive \ud business area with the rate of conversion around 18% (8.4 ha/yr.) and 34% (30.3 ha/yr.) within the \ud 1999 to 2003 and 2003 to 2010 respectively. The conversion rate in Kecamatan Biringkanaya during \ud 1995 to 2003 and 2010 are 37 and 66 ha/year respectively and in Kecamatan Pallanga and Sombaopu \ud is observed 172 ha/year from 1996 to 201

GIS and RS Integrated Framework for Supporting Planners and Decision Makers

The power of integrations planning supports decision makers to take the right decision in the right time. In order to have good plan, we should gather different kind of information with different perspectives and sources. The integration between all kinds of information supports decision makers to set the right plans and logic strategies in order to achieve their expected goals.Decision makers may suffer from information leakage, un-integrated information from different sources; information which does not represent the current status of reality and ability to represent information geographically. Decision makers should use modern technologies and tools in order to overcome the obstacles which they may face.Remote sensing and Geographic information system can provide realistic source of data and logic solutions which can support the decision makers to take the right decision in the right time. Decision makers should use remote sensing technology  in order to set their future planning and select their right strategies because remote sensing is the science to obtain the date remotely either phenomena like temperature, humidity or even satellite images which provides a realistic representation for the land which may enable the decision maker to track changes which may happened on specific feature  or even extract a specific feature and get the different statistics  or measurements which  definitely important to set the right plans Geographic information system support decision makers by realistic solutions and excellent geographic  data representation  and even the ability to join and migrate different sources of data to be liked geographically with the related features. Keywords: Planning, Decision Making, Remote Sensing, Geographical Information Syste

Investigation and prediction of urban-sprawl and land-use changes for Chennai city using geo-spatial technologies

1443-1451Monitoring urban sprawl is a vital component to assess landscape changes as it directly affects the quality of life. Multi date land-use and land-cover thematic layers were generated using multi-date high resolution remote-sensing data and Survey of India topo-sheet and spatial changes in urban land-use and urban-sprawl were studied using GIS. The residential and commercial urban area of city increased from 14,865.8 and 2,121.27 hectares in 1991 to 35,564 and 3,527.34 hectares in 2014. This study revealed that 51% of agricultural land and 2% of water bodies have been transformed as other urban land use features, in the form of built-ups. Based on current landscape trends, a 29-year forward simulation for the years 1991 to 2020 was performed using GIS land use change modeller analysis tool. The results show that by 2020 the residential and commercial urban of Chennai would increase to 51,059 and 4,246.7 hectares, respectively

IMPACT ASSESSMENT OF A MINE SUBSIDENCE ON NATIVE VEGETATION OF SOUTH EASTERN COALFIELDS, INDIA

This study aims to evaluate the effect of underground coal mining subsidence on the growth of native vegetation. For this study, an underground coal mine of South Eastern Coalfields Limited (SECL), India was selected. Changes in vegetation indices were analyzed using three remote sensing data of the previous five years. Three period’s Landsat 8 OLI resolution image data were used to calculate Normalized Difference Vegetation Index (NDVI) of the years 2014, 2016 and 2018 in QGIS environment. The study showed that the local grassland and forest were affected by the mining exploitation and subsidence but those effects were not significant to have an adverse impact on the same. The short-term mining was having an impact on the vegetation growth but the effects gradually disappeared with the gradual stabilization of the subsided land and in absence of human interference, vegetation recovered well. In long-term, subsidence was not having a major impact on the vegetation growth. Thus, coal resources exploitation and subsidence of the said mine of SECL did not bring out an adverse impact on a wide range of forest and grassland ecosystems, and these ecosystems could carry the partial destruction and ultimately stabilized ecosystems by self-repair

Discriminant Analysis with Spatial Weights for Urban Land Cover Classification

Classifying urban area images is challenging because of the heterogeneous nature of the urban landscape resulting in mixed pixels and classes with highly variable spectral ranges. Approaches using ancillary data, such as knowledge based or expert systems, have shown to improve the classification accuracy in urban areas. Appropriate ancillary data, however, may not always be available. The goal of this study is to compare the results of the discriminant analysis statistical technique with discriminant analysis with spatial weights to classify urban land cover. Discriminant analysis is a statistical technique used to predict group membership for a target based on the linear combination of independent variables. Strict per pixel statistical analysis however does not consider the spatial dependencies among neighbouring pixels. Our study shows that approaches using ancillary data continue to outperform strict spectral classifiers but that using a spatial weight improved the results. Furthermore, results show that when the discriminant analysis technique works well then the spatially weighted approach performs better. However, when the discriminant analysis performs poorly, those poor results are magnified in the spatially weighted approach in the same study area. The study shows that for dominant classes, adding spatial weights improves the classification accuracy.

Applying remote sensing and GIS on monitoring and measuring urban sprawl. A case study of China

The understanding on urban sprawl in China still rest on qualitative discussion instead of quantitative analysis. There is no clear answer to identify and evaluate the extent of sprawl. The existing methods for measuring urban sprawl are mainly put forward within the context of Western developed countries. To find good ways for analyzing the spatial features and unique mechanism of urban sprawl within Chinese context is very important .On this background, the techniques of Remote Sensing and Geographical Information System (GIS) to monitor and measure urban sprawl are described in this paper. The built–up areas were obtained from the Landsat TM classified images of four different periods to monitor the dynamic changes of urban sprawl. Choosing the different indicators and measuring the urban sprawl use these indicators based on GIS, on the basis of the calculation results of comprehensive indicators, the sprawl features of research area were identified