The Application of Remote Sensing and Geographic Information System in Environmental Changes Studies

Studies in Surveying and Mapping Science (SSMS) Volume 1 Issue 3, September 2013

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The Application of Remote Sensing and Geographic Information System in Environmental Changes Studies (Case Study: The East of Mazandaran) V. Gholami Assistant professor, Department of Range and Watershed Management, University of Guilan, Faculty of Natural Resources, Sowmeh Sara, Iran.

Gholami.vahid@gmail.com Abstract Cartography is applied in providing different kinds of maps such as landuse, slope and DEM and so on, which is very time consuming. Today, many maps are provided using Remote Sensing (RS) in a short time with in an acceptable accuracy. In this study, ASTER and ETM+ (LANDSAT) images have been used to provide landuse, DEM and drainage density maps. Kasilian Watershed (northern Iran) landuse has been provided using supervised classification technique and ETM+ image. Then ETM+ image ability was investigated in terms of different land uses separation. Also, Digital Elevation Model (DEM) was generated using ASTER image in the south of Gorgan Gulf and then DEM accuracy was investigated. Channels network map was extracted analyzing topographic conditions using DEM in GIS (ArcView) and the results for accuracy were controlled and confirmed comparing these results with those of topography maps. The results proved the capability of RS in environmental studies and in providing different maps.

Keywords Remote Sensing; Cartography; Environmental Changes; Iran

Introduction Nowadays, remote sensing (RS) has caused many significant changes in a variety of natural sciences.

Using the satellite data, a lot of studies have been done worldwide. Cartography has also been developed to provide different kinds of thematic maps such as hand use, slope, aspect and channels network. Some maps such as the maps of land use are one of the necessities of the natural scientists for future programming.

Surveying is one of the main method for providing the maps, but surveying and mapping an area is costly and time consuming. Nowadays, using satellite images, the land use maps and the other maps can be made in a short time by different techniques. Traditional methods

to gather demographic data, censuses, and analysis of environmental samples are not adequate to cope with multi complex environmental studies, since many problems are often presented in environmental issues and great complexity of handling the multidisciplinary data; new technologies are developed like satellite remote sensing and Geographical Information Systems (Berlanga-Robles and Ruiz-Luna, 2002 ; Maktav et al., 2005), Using Remote Sensing, (Anderson et al., 1976; Gunaid et al., 2013; Weicheng et al., 2002) investigated the landuse changes and land cover. Tahir et al. (2013) investigated land use and land cover changes in Mekelle City, Ethiopia (north east Africa) over a period of 25 years using remotely sensed data. Multi-temporal satellite data of Landsat was used to map and monitor urban land use changes occurring during 1985 and 2010. A pixel base supervised image classification was used to map land use land cover classes for maps of both time set. Phukan et al. (2013) investigated land use changes in Golaghat district of Assam using satellite images of 1989 and 2009. The study has revealed that the major changes occurred in cropland and scrubland. The reason behind this is that the area under scrubland is converted into agricultural or crop zone (Phukan et al., 2013) Also, Tucker et al. (2001) extracted channels network by using Digital Elevation Model. Toutin (2001, 2002), Zollinger (2003) and Tokunaga et al. (1996) produced the Digital Elevation Model (DEM) from ASTER satellite stereoscopic. Their studies proved the RS capabilities in investigations on environmental conditions. Besides that, Hiranoa et al. (2003) investigated and controlled the accuracy of the Digital Elevation Model (DEM) made of ASTER data. Binford et al. (2001) investigated the efficiency of the obtained

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Studies in Surveying and Mapping Science (SSMS) Volume 1 Issue 3, September 2013

data of Remote Sensing in vegetation studies in the USA, and obtained proper results using RS. Aniello (2003) and Giles et al. (1996) used the satellite images to simulate the 3D model of the surface in the case study. The present research has investigated the efficiency of the satellite images ETM+ (landsat) and ASTER to provide land use map, Digital Elevation Model (DEM), rivers and channels network in the east of Mazandaran Province, northern Iran.

Materials and Methods The present research has been done on the surface of the Kasilian watershed located in the east of Mazandaran in the eastern longitude 53o 18´ to 53o 30´ and northern latitude 35o 58´ to 36o 7´ using ETM+ images (Landsat) and also in an area located in the south of the Gorgan Gulf (in the east of Mazandaran Province) using ASTER. There are four different types of land use on the surface of the Kasilian watershed as follows: jungle, dry farming, pastureland and residential land where the ability of ETM+ images was investigated using supervised classification technique to provide the land use map. In addition, ASTER stereoscopic pair data was used to provide DEM in an area located in the south of the Gorgan Gulf using the software PCI Geomatica. First, the satellite images were georeferenced. To investigate the efficiency of ETM+ image in providing land use, the map of the watershed used the bands of 2,3 and 4 showing that the selection of appropriate bands for classification would cause decrease of the time of the classification and increase of the accuracy of the obtained results.

For each of these land uses on the surface of the watershed with field studies and traverse of an area using GPS, a number of trained samples to perform the supervised classification technique and a number of ground control points (GCPS) to investigate the accuracy of the classified results were considered. The results accuracy was investigated by results comparison between obtained and testing sample location (the percentage of results accuracy). However, choosing the trained samples, the number and their dispersion on the surface of the case study considerably affected the classified results. Then using the ENVI software, ETM+ images was classified based on land use using supervised classification technique.

In the next step, the accuracy of the results was investigated using the ground control points (GCPS) of each land use. ASTER image was applied to provide Digital Elevation Model (DEM) and create contours by PCI software. An ASTER scene covering 61.5-km×63-

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km contains data from 14 spectral bands. ASTER is composed of three separate instrument subsystems representing different ground resolutions: three bands in the visible and near infrared spectral range (VNIR, 0.5-1.0 μm) with 15 m spatial resolution, six bands in the shortwave infrared spectral range (SWIR, 1.0-2.5 μm) with 30 m resolution, and five bands in the thermal infrared spectral range (TIR, 8-12 μm) with 90 m resolution. The surface of the case study was simulated in 3D and then in the next step from analyzing topography or the obtained DEM from ASTER satellite image, the channels network of the region was extracted in Arcview software. The accuracy of DEM and the obtained channels network from the ASTER satellite images was controlled and confirmed by topographic maps (scale: 1:25000 and 1: 50000).

Results As it was pointed out before, using supervised classification technique, ETM+ Remote Sensing image (Landsat) was used for providing land use of the watershed. The obtained results of the classification are presented as a map in FIG. 1. Four kinds of land use were observed in the surface of the watershed which the supervised classification steps for each of them have separately been done and the accuracy of the classification has been evaluated. The black areas included the areas that were not classified due to the existence of cloud or to having a kind of use except the four kinds of land use on the surface of the watershed (the areas out of the surface of the watershed). Also, the evaluated results of the classification accuracy have been given in table1. ASTER image was applied for 3D simulating and providing DEM located in an area in the south of the Gorgan Gulf in the east of Mazandaran (northern Iran). DEM (15 m) was generated using ASTER image and RS capabilities. The 3D model of the Gorgan Gulf coasts resulting from ASTER image can be observed in FIG. 2. Further, Digital Elevation Model and contours of this area made of ASTER image are presented in FIG. 3. On the other hand, the channels network of the area can be extracted by analyzing topographic conditions of the area (Mousavi et al., 2011), that is, in each surface, channels are made and by analyzing DEM of the surface of the area (created of ASTER) in the Arc view (GIS), the position and route of existing rivers and channels on the surface of the case study have been recognized, which is presented in FIG. 4.

Studies in Surveying and Mapping Science (SSMS) Volume 1 Issue 3, September 2013

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FIG 1. THE LANDUSE MAP (2002) WAS GENERATED USING SUPERVISED CLASSIFICATION TECHNIQUE AND ETM+ IMAGE IN KASILIAN WATERSHED (THE BLACK AREAS INCLUDE THE AREAS THAT WERE NOT CLASSIFIED DUE TO THE EXISTENCE OF EXISTING CLOUD OR A KIND OF LANDUSE EXCEPT THE FOUR KINDS OF LAND USE ON THE SURFACE OF THE WATERSHED)

FIG. 2. A 3D VIEW WAS GENERATED FROM ASTER DEM (15M) IN GORGAN GULF COAST

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Studies in Surveying and Mapping Science (SSMS) Volume 1 Issue 3, September 2013

FIG. 3. THE DEM AND CONTOUR LINES WERE GENERATED FROM ASTER IMAGE IN GORGAN GULF COAST

FIG. 4. CHANNELS NETWORK MAP WAS GENERATED FROM THE DEM OF ASTER IMAGE (DRAINAGE DENSITY IS 3 KM/ KM2) TABLE 1. THE RESULTS OF SUPERVISED CLASSIFICATION USING ETM+ IMAGE IN THE KASILIAN WATERSHED; 50 GROUND CONTROL POINTS (GCPS) FOR EVERY LAND USE TYPE

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Land use type

%Classification accuracy

Land use area (%)

forest

100

47.5

peddy

96.6

26.6

rangelands

86.2

8.46

settlement

86.6

11.4

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providing the data for this study and for helping us with data-preprocessing.

Conclusions Remote Sensing has made many significant changes in various natural sciences and cartography. The results of the supervised classification of ETM+ image showed that using this image is not suitable for providing land use maps in the settlements and ragelands area, but that can be applied to determinate forest area well.

Previous studies have shown that land use/land cover changes using Remote Sensing data and GIS at an urban area in India. Their results proved the RS capabilities in providing Landuse and land cover maps (Kumar Mallupattu et al., 2013). In fact, this image with about 28-meter (2,3 and 4 bands) resolution does not have much efficiency in comparison with other satellite images with more resolution, that is, reevaluation of the supervised classification results shows that the classes of farming, residential land and rangelands interfere with each other and just the forest class have accurately been determined. Land use and land cover maps can be provided using RS techniques within a suitable accuracy (Anderson et al., 1976).

The high resolution satellite data such as LISS III data and LANSAT ETM+ are good source to provide information accurately (Phukan et al., 2013). The land use and land cover maps can be provided without much difficulty by visible interpreting the satellite images with high resolution such as IKNOS image (1meter resolution). Using ASTER image to provide channels network maps of DEM has shown proper results. The accuracy of produced DEM from ASTER data has been evaluated by topographic maps, ground control points and acceptable results has been presented. ASTER DEM has potential to be a best tool to study 3D model (Mousavi et al., 2011). Actually, using satellite images with higher resolution to make Digital Evaluation Model of the surface such as IKNOS image has shown more exact results.

Channels network extracted by analyzing topographic conditions, DEM of the surface of the case study was compared with the existing channels network in topographic maps and this investigation showed that the obtained channels network by analyzing DEM from ASTER data has presented a set of more exact and compressed hydrography networks, channels and rivers. Therefore, using Remote Sensing to provide various thematic maps causes the reduction of the cost and especially time.

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