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2. Land Use Land Cover Mapping (Level-I) Using Satellite Imagery
1. Introduction:
Image classification is an important part of remote sensing, image analysis and pattern
recognition. In some instances, the classification itself may be the object of the analysis.
For example, classification of land use from remotely sensed data produces a map-like
image as the final product. The image classification therefore forms an important tool for
examination of digital images to prepare thematic map of an Area.
2. Objective:
The objective of the project is to generate Level I Land Cover map for 2022-2023 using
sentinel data for Madhya Pradesh
3. Scope of the Project:
Using Remote Sensing Images, precisely either sentinel or LISS IV, disseminating the 5
basic classes to prepare semi-automated process to extract the Level I classes for Madhya
Pradesh to provide the requirements of the different departments.
4. Data:
Sentinel Satellite Data will be used and archived as separate scenes and a state mosaic.
5. Methodology:
There is a consistent logic to all of the unsupervised classification routines in almost all
image processing software’s, especially in ERDAS or ESRI ArcGIS and or ArcGIS Pro
regardless of whether they are hard or soft classifiers . In addition, there is a basic sequence
of operations that must be followed no matter which of the unsupervised classifiers is used.
Classification Schema with descriptions need to be added here

3. Figure 1 Classification Schema recommended by IGBP and adopted by NRSC – Landuse department for India
Class name Description
Agriculture land Land predominantly occupied with crop or left as fallow
Barren land Land appears white on an FCC image and does not show any trace of
vegetation in all the seasons
Built-up This class includes all the dwelling either urban or rural and made up of any
material
Grass/Grazing Dry mud are areas where it was mapped wetland in post-monsoon period
but dried and appears white in pre-monsoon image
Forest/Tree Forest are mapped as areas with natural forest or a larger size whereas Trees
are either a single tree or a bunch of trees mapped in non-forest land To
simplify the map forest and tree are presented with similar colour though
mapped separately
Wetland /Water Wetlands are mapped that are not water or forest but appears red on an FCC
embedded with black background and Land areas having any form of water
Table 1 Level I Class description
5.1. Image Enhancement
The Satellite images comprise of low brightness level. This calls for the importance of
image enhancement with the preservation of important details without loss of information.
Contrast is an important parameter considered on subjectively evaluating an image in terms
of its quality. Contrast, from human perception, is what differentiates object-to-object with
background. In other words, it is the color and brightness difference between the objects
and background.
5.2. Unsupervised Classification:

4. Unsupervised classification technique uses clustering mechanisms to group satellite image
pixels into unlabelled classes/clusters. Later analyst assigns meaningful labels to the clusters
and produces well classified satellite image.
5.3. Level I Classification:
Simple Unsupervised classification (commonly referred to as clustering) is an effective
method of partitioning remote sensor image data to classify the image in to Lvel1
classification categories . Those are
1. Built Up
2. Agriculture land
3. Forest Land
4. Wasteland
5. Grass land
6. Water Bodies
7. Process flow diagram:
Archival of the Data
Satellite Images
Preprocessing
5 Classes Thematic Map
Generation
Remote Sensing Data
Download
Image Processing
Unsupervised
Classification
END
Post Processing
QC Observations
Quality
>90

5. 8. Deliverables:
At the end thematic map with basic classes has to be prepared and disseminated in GDB
format.
8.1. Built Up:
Built-up areas are characterized by substitution of the original ,partial natural cover or water
surface with an artificial, often impervious, cover. This artificial cover is usually
characterized by long cover duration. Basically they are the area of human habitation that
has a cover of buildings, transport and communication, utilities in association with water,
vegetation and vacant lands.
8.2. Agriculture Land:
These are the lands primarily used for agriculture for production of food, fibre, and other
commercial and horticultural crops. It includes land under crops which includes irrigated
and non-irrigated lands. In a broad sense, agricultural lands may be defined as those lands
which are cultivated to produce food crops and related activities.
8.3. Forest Land:
The term forest is used to refer to land with a tree canopy cover of more than 10 percent
and area of more than 0.5 hectares. Forests are determined both by the presence of trees
and the absence of other predominant land uses within the notified forest boundaries.
Grass land: Grass is the shortest life form among any vegetation cover, that can be
differentiated based on its smooth texture and pinkish tone on an optical satellite image.
8.4. Wastelands:
Wasteland is described as degraded land which can be brought under vegetative cover with
reasonable effort and which is currently not utilized and land which is lack of appropriate
water and soil management or on account of natural causes. Wastelands can result from
inherent/imposed disabilities such as by location, environment, chemical and physical
properties of the soil or financial or management constraints.
8.5. Waterbodies:
Water bodies category comprises of areas with surface water, either impounded in the form
of ponds, lakes and reservoirs or flowing as streams, rivers, canals etc. These are seen clearly
on the satellite image in blue to dark blue or cyan colour depending on the depth of water.

6. 8.6. Grasslands:
These are the areas of natural grass along with other vegetation, predominantly grass‐like
plants. It includes natural/semi‐natural grass/ grazing lands of Alpine/Sub‐Alpine or
temperate or sub‐ tropical or tropical zones, desertic areas and manmade grasslands.
9. Budget Estimate:
S.No Particulars Amount (In Lakhs)
1 Resource Cost 10.77
2 Contingency Cost @ 10% 0.00
3 Administrative Cost 0.00
Project Cost 10.77
4 GST @ 18% 1.94
Total Project Cost 12.70
S.No. Resource
No. of
Resources
Total Man
days Expenditure
1 Business Analyst 1 15 90,000
2
Database Administrator 1
5
30,000
3 GIS Executive 3
300
(3X100)
6,00,000
4 Senior GIS Executive 2 100 2,50,000
5 GIS Data Specialist 1 80 1,06,667
Total 6 500 10,76,667