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Application of Remote Sensing and GIS tools in delineating Environmentally-Fragile-Areas (EFAs) for sustainable land use planning: A case study of Delhi Region

Land use classification
The remote sensing technology along with GIS is an ideal tool to identify, locate and map various types of lands associated with different landform units (Dhinwa, 1992; Palaniyandi and Nagarathinam, 1997; Murthy & Venkateswara, 1997; Khan et al., 1999). The timely information about the changing pattern of land use plays significant role in land use planning and sustainable land development. The mapping and monitoring of the land use/land cover requires a land use classification system. One of the most widely used data format for information extraction about the land use and land cover is the infrared False Colour Composite (FCC) image. The extraction of information from such images about ground reality is done by image interpretation for which generally three methods namely photo interpretation, spectral analysis and data integration are used. Prasad and Sinha (2002) describe the image characteristics and visual interpretation techniques of various land cover and land use categories which is summarised in the table 1.

Table 1: Land cover/land use and their image characteristics

Land Cover/land use	Image Characteristics
1. Settlements	Light grey clustering with particular patterns for the urban area. There may be brownish maroon patches for in between vegetation. For the rural settlement there occur no particular patterns of such image characteristics.
2. Agriculture	Identify rabbi if the month of data acquisition is January or February or March and colour is brown red. For the kharif crops same characteristics in image occur if the image data are acquired in the month of September, October or November.(b)Fallow land is identified by light grey colour within cropped area (red colour).(c) Plantation occurs as brownish maroon patches.
3. Forest (a) Dense forests (b) Degraded forest (c) Forest blank (d) Forest plantation	Dense forests are identified by dark red colour patterns. In the case of degraded forest the dark red colour patterns contain small brown or white patches. The blanks in the forest show creamy patches in the dark red/ background. Forest plantations are identified by dark red colour sign of particular pattern.
4. Waste Land (a) Muddy water logging (b) Clear water logging (c) Temporary water logging (d) Permanent water logging (e) Marshy area water logging (f) Gullied land (g) Land with scrub (h) Land without scrub (i) Sandy area	Muddy water logging occurs as blackish or deep blue spots while clear water logging area is identified by dark/bright blue patches. Comparing the images of rainy season and out of rainy season identifies temporary and Permanent water logging. Marshy area is recognized as a sign of vegetation (red/pink spots) in the water logged (blackish blue/bright blue) area. Gullied land occurs as white/grey spot. The image of land with scrub contains white patches in the land area. Sandy area is classified as bright white coloration along the course of river.
5. Water bodies (a) River/stream (b) Canal (c) Lake/ Reservoirs (d) Embankments	River/stream is identified as long non-linear path coloured with dark blue/ bright blue line in white background. Canals are identified as line segments sign of water. Lake/reservoirs are identified as patterns along the river. Embankment occurs as light grey structure along the river.
6. Others	Grasslands are identified as uneven appearance characterized by red (light to medium grey tones) snow is identified as white patches on the hills.

Source: Prasad and Sinha (2002)

Methodology


Figure 1: Flowchart of simplified methodology

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