SlideShare a Scribd company logo
1 of 22
Preparation of landuse/landcover map
using RS and GIS techniques
Mentor :
Dr. CHANDER PRAKASH
Prepared by:
ARUN KUMAR (17142)
NITISH THAKUR (17137)
KAPIL THAKUR (17141)
NEERAJ KUMAR (17190)
1
• Land use/cover are two separate terminologies which are often used
interchangeably.
• Land cover refers to the physical characteristics of earth’s surface
(vegetation, water, soil and other physical features of the land, including
those created by human activities e.g., settlements.
• Land-use refers to the way in which land has been used by humans.
2
Introductions
Objective
• DEM-Based stream and watershed Delineation.
• Visually interpreting the satellite data to map different categories of
land use/ land cover (LULC) of delineated watershed.
• Change assessment of watershed using remote sensing and GIS and
understanding the impact on the ecosystem .
3
Study Area
UPPER BEAS WATERSHED
Kullu, Himachal Pradesh.
Kullu
Beas river rises in the Himalayas in central
Himachal Pradesh.
Outlet point of watershed –
• Location - Bhunter
• Coordinates –
Latitude - 31°53'44.06"N
Longitude - 77° 8'31.31"E
4
ASTER DEM -
ASTER provides high-resolution images of
the planet Earth in 14 different bands of
the electromagnetic spectrum, ranging
from visible to thermal infrared light.
The resolution of images ranges between 15
and 90 meters. ASTER data are used to
create detailed maps of surface temperature
of land, emissivity, reflectance, and
elevation.
ASTER GDEM V3 From NASA Earth-data
5
DATASETS AND SOFTWARE USED:
LANDSAT-8 SATELLITE
DATA -
The Landsat 8 satellite payload consists of
two science instruments—the Operational
Land Imager (OLI) and the Thermal Infrared
Sensor (TIRS). These two sensors provide
seasonal coverage of the global landmass at
a spatial resolution of 30 meters (visible,
NIR, SWIR); 100 meters (thermal); and 15
meters (panchromatic).
Landsat-8 Satellite data From USGS earth-explorer
DATASETS AND SOFTWARE USED:
Satellite Date of Generation Path-Row Sensor Band Spatial Resolution
Landsat 8 2020-10-14 147-38 Operational Land Imager
(OLI)
Band 1 - Coastal /
Aerosol
30 m
Band 2 - Blue 30 m
Band 3 - Green 30 m
Band 4 - Red 30 m
Band 5 - Near Infrared 30 m
Band 6 - Short
Wavelength Infrared
30 m
Band 7 - Short
Wavelength Infrared
30 m
Band 8 - Panchromatic 15 m
Thermal Infrared Sensor
(TIRS)
Band 10 - Long
Wavelength Infrared
100 m
Band 11 - Long
Wavelength Infrared
100 m
7
The Landsat 8 OLI/TIRS C1 Level-1 satellite image captured on 2020-10-14 is used. The images were downloaded
from United States Geological Survey (USGS,https://earthexplorer.usgs.gov/) earth explorer.
DATASETS AND SOFTWARE USED:
Software Used -
The following software were used for satellite data processing and GIS
analysis-
ERDAS Imagine for Pre-processing.
ArcGIS 10.2 for database creation, analysis and map composition.
Hec-GeoHMS ArcGIS extension tool is used for watershed delineation and
catchment characteristics.
8
DATASETS AND SOFTWARE USED:
Digital Elevation Model (DEM) based Hydro processing and Watershed delineation are estimated by using the HEC-GeoHMS tools
of Arc GIS Software.
9
METHODOLOGY :
Fig. Flow chart for Watershed delineation.
10
Various steps involved in the Preprocessing :
• Fill sinks: Fill sinks operation removes local depression from a DEM by replacing
the local depressions by flat areas in the output DEM.
• Flow Direction : Flow Direction grid, contains cells with only the numerical values
dictated by the 8-direction pour point model.
PREPROCESSING
• Flow Accumulation: It is used to determine the ultimate flow path of every
cell on the landscape grid.
• Stream Definition and segmentation : With a flow accumulation grid, streams
may be defined through the use of a threshold flow accumulation value.
• Catchment Polygon Processing: The function of catchment polygon processing
is to convert a catchment grid into a catchment polygon feature.
• Drainage Line Processing: Drainage Line Processing converts the input Stream
Link grid into a Drainage Line feature class.
Fig. HEC-GeoHMS tool bar.
WATERSHED DELINEATION
11
The values represent flow in particular direction i.e.
1 – East, 2 – South East, 4 – South, 8 – South West,
16 – West, 32 – North West, 64 – North and 128 –
North East.
 For ASTER DEM, the maximum flow is in the
Southwest (SW) direction, whereas the minimum flow
is in the North (N) direction.
Flow Direction Map of Beas Watershed
WATERSHED DELINEATION
12
Fig. Process from the determination of flow direction to flow pattern.
WATERSHED DELINEATION
13
 Start New Project:
Go to start new project and enter the project name. Specify the
outlet point of the basin model by using ‘Add Project Points’ tool.
 Generate Project:
Generate the project by using the method of generating as
Original stream definition. Watershed is delineated and project
setup is completed.
PROJECT SETUP
WATERSHED DELINEATION
Fig. Project Setup in HEC-GeoHMS
14
Fig. Delineated Watershed with subbasins from ASTER DEM.
HEC-
GeoHMS
Flow Chart for making land use/land cover map (LULC)
15
LULC MAPPING :
• For image Pre-processing and performing supervised classification of the satellite imageries,
mosaicking of data tiles is performed initially.
• For Image Enhancement, several corrections and layer stacking of satellite imageries are done to
convert multiple bands into a single layer.
• Resultant shapefile of watershed area produced through watershed delineation process was used
to clip the study area from the imageries using ArcGIS.
• These clipped images are then re-projected to Universal Transverse Mercator zone 43N and
resampled, if needed.
• FCC of the study area was also generated using band 5, 3 & 4.
R = 5 (NIR band)
G = 3 (red band)
B = 4 (green band)
16
LULC MAPPING :
Image Pre-processing :
17
LULC MAPPING :
LULC Mapping:
• Visual image interpretation technique of classification was applied in the study
• This Comprises of the following six major steps-
- Selection and acquisition of data
- Pre-field interpretation
- Ground data collection and verification
- Post-field interpretation and modification
- Computation of area
- Final cartographic map preparation and reproduction.
• Then all satellite data were studied by assigning per-pixel signatures. The whole watershed is
differentiated into five classes- Forest, vegetation, bare land, water bodies and snow.
• The maximum likelihood algorithm is used for supervised classification of the imagery.
Image interpretation key for LULC classification -
18
• A final interpretation key for the various classes was
prepared using spectral characteristics of classes and
field knowledge.
• Red in false color composite image indicates the
density of the vegetation.
• Water bodies were appeared in dark blue or light blue
tone with smooth texture
• Patches of light red tones represented vegetation.
Tone Texture Shape Spectral
Signature
Description
Dark red
to light
red
Rough Irregular Tree cover (forest
canopy density >40%)
Light Red Smooth Irregular Tree cover (forest
canopy density 10-
40%)
Light red or
pinkish red
Coarse Varying Bushy vegetation with
shrubs or scattered
trees (forest canopy
density <10%)
Pinkish red to
light green
Medium
Smooth
Irregular Scattered
trees/shrubs with
exposed ground
surface; canopy
density <10%.
Pinkish or
light green
or light
blue or
light cyan
Medium
Smooth
Regular Crops/ current
fallow Lands,
surrounded by small
to medium size
settlements.
Cyan Rough Irregular/
regular
Urban as well rural
(Maximum rural)
Dark blue or
light blue
Smooth Irregular/
Linear
River, stream and
pond
LULC MAPPING :
Supervised
classification
LULC
MAPPPING
19
Results
• The visual interpretation of the satellite data with
the ground truth was used to map different
categories of land use/ land cover (LULC) map of
UPPER BEAS WATERSHED.
• Five categories of LULC were classified which
include forest(open forest, dense forest and
degraded forest), vegetation, snow, other land use
(agriculture, settlement) and water bodies. Brief
descriptions of different categories of land use/ land
cover are given further
20
21
Results
• Area statistics of different categories of land
use/ land cover is also given in table.
• Pie chart shows distribution of different
categories of land use/land cover.
• It can be concluded that the bare land (including
settlements) and Forest land have the highest
percentage of the total area covered in the study
area of upper Beas watershed.
• For many planning activities accurate and current information on land use and land cover is required.
• Visual interpretation method allows the most detailed differentiation of structures and objects which is
advantageous in detecting spatial patterns and in drafting precise boundaries around relatively
homogenous area.
• We can further use this knowledge to assess the LULC scenario and assessment by applying the
methodology on maps of past years and deriving data will along with land use change assessment table
for those years.
• Further for comprehensive study certain figures like temporal pattern and relative change in land will be
drawn and a cross tabulationa i.e. two-way cross-matrix containing different combinations of ‘‘from–to’’
change classes will be formed on pixel-by-pixel basis using in order to determine the quantity of
conversions from one land cover to other land cover category within the time frame.
• At last accuracy assessment will be done by site visiting or using google earth pro.
Discussion
22

More Related Content

What's hot

APPLICATIONS OF REMOTE SENSING AND GIS IN WATERSHED MANAGEMENT
APPLICATIONS OF REMOTE SENSING AND GIS IN WATERSHED MANAGEMENTAPPLICATIONS OF REMOTE SENSING AND GIS IN WATERSHED MANAGEMENT
APPLICATIONS OF REMOTE SENSING AND GIS IN WATERSHED MANAGEMENTSriram Chakravarthy
 
Integrated water resource management
Integrated water resource managementIntegrated water resource management
Integrated water resource managementCPWF Mekong
 
Remote Sensing and GIS in Land Use / Land Cover Mapping
Remote Sensing and GIS in Land Use / Land Cover MappingRemote Sensing and GIS in Land Use / Land Cover Mapping
Remote Sensing and GIS in Land Use / Land Cover MappingVenkatKamal1
 
identification of ground water potential zones using gis and remote sensing
identification of ground water potential zones using gis and remote sensingidentification of ground water potential zones using gis and remote sensing
identification of ground water potential zones using gis and remote sensingtp jayamohan
 
CE8603 Irrigation Engineering NOTES.pdf
CE8603 Irrigation Engineering NOTES.pdfCE8603 Irrigation Engineering NOTES.pdf
CE8603 Irrigation Engineering NOTES.pdfParandh M
 
Iirs overview -Remote sensing and GIS application in Water Resources Management
Iirs overview -Remote sensing and GIS application in Water Resources ManagementIirs overview -Remote sensing and GIS application in Water Resources Management
Iirs overview -Remote sensing and GIS application in Water Resources ManagementTushar Dholakia
 
Unit 1 Crop Water Requirement
Unit 1 Crop Water RequirementUnit 1 Crop Water Requirement
Unit 1 Crop Water RequirementLeema Margret A
 
drought monitoring and management using remote sensing
drought monitoring and management using remote sensingdrought monitoring and management using remote sensing
drought monitoring and management using remote sensingveerendra manduri
 
Watershed Delineation in ArcGIS
Watershed Delineation in ArcGISWatershed Delineation in ArcGIS
Watershed Delineation in ArcGISArthur Green
 
Watershed management: Role of Geospatial Technology
Watershed management: Role of Geospatial TechnologyWatershed management: Role of Geospatial Technology
Watershed management: Role of Geospatial Technologyamritpaldigra30
 
LECTURE 3-HYDROLOGICAL DATA FOR WATERSHED PLANNING.pptx
LECTURE 3-HYDROLOGICAL DATA FOR WATERSHED PLANNING.pptxLECTURE 3-HYDROLOGICAL DATA FOR WATERSHED PLANNING.pptx
LECTURE 3-HYDROLOGICAL DATA FOR WATERSHED PLANNING.pptxCHU DICKSON
 
Prioritizing watersheds
Prioritizing watershedsPrioritizing watersheds
Prioritizing watershedsMeer Raashid
 
Losses IN Canals
Losses IN CanalsLosses IN Canals
Losses IN CanalsAnand Kumar
 
REMOTE SENSING DATA FOR HYDROLOGICAL MODELING
REMOTE SENSING DATA FOR HYDROLOGICAL MODELINGREMOTE SENSING DATA FOR HYDROLOGICAL MODELING
REMOTE SENSING DATA FOR HYDROLOGICAL MODELINGShyam Mohan Chaudhary
 
Measurement of evapotranspiration
Measurement of evapotranspirationMeasurement of evapotranspiration
Measurement of evapotranspirationVijithaVikneshwaran
 

What's hot (20)

APPLICATIONS OF REMOTE SENSING AND GIS IN WATERSHED MANAGEMENT
APPLICATIONS OF REMOTE SENSING AND GIS IN WATERSHED MANAGEMENTAPPLICATIONS OF REMOTE SENSING AND GIS IN WATERSHED MANAGEMENT
APPLICATIONS OF REMOTE SENSING AND GIS IN WATERSHED MANAGEMENT
 
Integrated water resource management
Integrated water resource managementIntegrated water resource management
Integrated water resource management
 
Remote Sensing and GIS in Land Use / Land Cover Mapping
Remote Sensing and GIS in Land Use / Land Cover MappingRemote Sensing and GIS in Land Use / Land Cover Mapping
Remote Sensing and GIS in Land Use / Land Cover Mapping
 
identification of ground water potential zones using gis and remote sensing
identification of ground water potential zones using gis and remote sensingidentification of ground water potential zones using gis and remote sensing
identification of ground water potential zones using gis and remote sensing
 
CE8603 Irrigation Engineering NOTES.pdf
CE8603 Irrigation Engineering NOTES.pdfCE8603 Irrigation Engineering NOTES.pdf
CE8603 Irrigation Engineering NOTES.pdf
 
Introduction to gis
Introduction to gisIntroduction to gis
Introduction to gis
 
Iirs overview -Remote sensing and GIS application in Water Resources Management
Iirs overview -Remote sensing and GIS application in Water Resources ManagementIirs overview -Remote sensing and GIS application in Water Resources Management
Iirs overview -Remote sensing and GIS application in Water Resources Management
 
Watershed management
Watershed managementWatershed management
Watershed management
 
Unit 1 Crop Water Requirement
Unit 1 Crop Water RequirementUnit 1 Crop Water Requirement
Unit 1 Crop Water Requirement
 
drought monitoring and management using remote sensing
drought monitoring and management using remote sensingdrought monitoring and management using remote sensing
drought monitoring and management using remote sensing
 
Surface runoff
Surface runoffSurface runoff
Surface runoff
 
Watershed Delineation in ArcGIS
Watershed Delineation in ArcGISWatershed Delineation in ArcGIS
Watershed Delineation in ArcGIS
 
Watershed management: Role of Geospatial Technology
Watershed management: Role of Geospatial TechnologyWatershed management: Role of Geospatial Technology
Watershed management: Role of Geospatial Technology
 
GPS ERRORS
GPS ERRORS GPS ERRORS
GPS ERRORS
 
LECTURE 3-HYDROLOGICAL DATA FOR WATERSHED PLANNING.pptx
LECTURE 3-HYDROLOGICAL DATA FOR WATERSHED PLANNING.pptxLECTURE 3-HYDROLOGICAL DATA FOR WATERSHED PLANNING.pptx
LECTURE 3-HYDROLOGICAL DATA FOR WATERSHED PLANNING.pptx
 
Prioritizing watersheds
Prioritizing watershedsPrioritizing watersheds
Prioritizing watersheds
 
Watershed management dr.chandan
Watershed management  dr.chandanWatershed management  dr.chandan
Watershed management dr.chandan
 
Losses IN Canals
Losses IN CanalsLosses IN Canals
Losses IN Canals
 
REMOTE SENSING DATA FOR HYDROLOGICAL MODELING
REMOTE SENSING DATA FOR HYDROLOGICAL MODELINGREMOTE SENSING DATA FOR HYDROLOGICAL MODELING
REMOTE SENSING DATA FOR HYDROLOGICAL MODELING
 
Measurement of evapotranspiration
Measurement of evapotranspirationMeasurement of evapotranspiration
Measurement of evapotranspiration
 

Similar to Watershed delineation and LULC mapping

APPLICATIONS OF RS AND GIS FOR DEVELOPMENT OF SMALL HYDROPOWER PLANTS (SHP)
APPLICATIONS OF RS AND GIS  FOR DEVELOPMENT OF SMALL HYDROPOWER PLANTS (SHP)APPLICATIONS OF RS AND GIS  FOR DEVELOPMENT OF SMALL HYDROPOWER PLANTS (SHP)
APPLICATIONS OF RS AND GIS FOR DEVELOPMENT OF SMALL HYDROPOWER PLANTS (SHP)Abhiram Kanigolla
 
morphometric analysis of sitla rao final.pptx
morphometric analysis of sitla rao final.pptxmorphometric analysis of sitla rao final.pptx
morphometric analysis of sitla rao final.pptxShubhamSaini156493
 
Scale-dependency and Sensitivity of Hydrological Estimations to Land Use and ...
Scale-dependency and Sensitivity of Hydrological Estimations to Land Use and ...Scale-dependency and Sensitivity of Hydrological Estimations to Land Use and ...
Scale-dependency and Sensitivity of Hydrological Estimations to Land Use and ...Beniamino Murgante
 
Lidar and radar.pptx
Lidar and radar.pptxLidar and radar.pptx
Lidar and radar.pptxBivaYadav3
 
Groundwater Prospectus Map for Suryanagar Subwatershed
Groundwater Prospectus Map for Suryanagar Subwatershed     Groundwater Prospectus Map for Suryanagar Subwatershed
Groundwater Prospectus Map for Suryanagar Subwatershed Mohammed Badiuddin Parvez
 
Role of remote sensing and gis in infrastructural plan and identifying ecolog...
Role of remote sensing and gis in infrastructural plan and identifying ecolog...Role of remote sensing and gis in infrastructural plan and identifying ecolog...
Role of remote sensing and gis in infrastructural plan and identifying ecolog...PRADEEP M.S
 
Quantitative Morphometric analysis of a Semi Urban Watershed, Trans Yamuna, ...
Quantitative Morphometric analysis of a Semi Urban Watershed,  Trans Yamuna, ...Quantitative Morphometric analysis of a Semi Urban Watershed,  Trans Yamuna, ...
Quantitative Morphometric analysis of a Semi Urban Watershed, Trans Yamuna, ...IJMER
 
Detection of Fish Farm Location Using Satellite Image
Detection of Fish Farm Location Using Satellite ImageDetection of Fish Farm Location Using Satellite Image
Detection of Fish Farm Location Using Satellite ImageDegonto Islam
 
Resource potential appraisal assessment and to
Resource potential appraisal  assessment and toResource potential appraisal  assessment and to
Resource potential appraisal assessment and toeSAT Publishing House
 
Resource potential appraisal
Resource potential appraisalResource potential appraisal
Resource potential appraisaleSAT Journals
 
Identification Of Ground Water Potential Zones In Tamil Nadu By Remote Sensin...
Identification Of Ground Water Potential Zones In Tamil Nadu By Remote Sensin...Identification Of Ground Water Potential Zones In Tamil Nadu By Remote Sensin...
Identification Of Ground Water Potential Zones In Tamil Nadu By Remote Sensin...IJERA Editor
 
Application of remote sensing and gis for groundwater
Application of remote sensing and gis for groundwaterApplication of remote sensing and gis for groundwater
Application of remote sensing and gis for groundwaterRamodh Jayawardena
 
Identification of Groundwater Potential Survey Using QGIS of DBATU campus, Ma...
Identification of Groundwater Potential Survey Using QGIS of DBATU campus, Ma...Identification of Groundwater Potential Survey Using QGIS of DBATU campus, Ma...
Identification of Groundwater Potential Survey Using QGIS of DBATU campus, Ma...IRJET Journal
 
Easter Desert Project
Easter Desert ProjectEaster Desert Project
Easter Desert ProjectIwl Pcu
 

Similar to Watershed delineation and LULC mapping (20)

APPLICATIONS OF RS AND GIS FOR DEVELOPMENT OF SMALL HYDROPOWER PLANTS (SHP)
APPLICATIONS OF RS AND GIS  FOR DEVELOPMENT OF SMALL HYDROPOWER PLANTS (SHP)APPLICATIONS OF RS AND GIS  FOR DEVELOPMENT OF SMALL HYDROPOWER PLANTS (SHP)
APPLICATIONS OF RS AND GIS FOR DEVELOPMENT OF SMALL HYDROPOWER PLANTS (SHP)
 
morphometric analysis of sitla rao final.pptx
morphometric analysis of sitla rao final.pptxmorphometric analysis of sitla rao final.pptx
morphometric analysis of sitla rao final.pptx
 
WATERSHED ANALYSIS .pptx
WATERSHED ANALYSIS .pptxWATERSHED ANALYSIS .pptx
WATERSHED ANALYSIS .pptx
 
Scale-dependency and Sensitivity of Hydrological Estimations to Land Use and ...
Scale-dependency and Sensitivity of Hydrological Estimations to Land Use and ...Scale-dependency and Sensitivity of Hydrological Estimations to Land Use and ...
Scale-dependency and Sensitivity of Hydrological Estimations to Land Use and ...
 
Lidar and radar.pptx
Lidar and radar.pptxLidar and radar.pptx
Lidar and radar.pptx
 
Land cover and Land Use
Land cover and Land UseLand cover and Land Use
Land cover and Land Use
 
Groundwater Prospectus Map for Suryanagar Subwatershed
Groundwater Prospectus Map for Suryanagar Subwatershed     Groundwater Prospectus Map for Suryanagar Subwatershed
Groundwater Prospectus Map for Suryanagar Subwatershed
 
Wetland mapping
Wetland mappingWetland mapping
Wetland mapping
 
Role of remote sensing and gis in infrastructural plan and identifying ecolog...
Role of remote sensing and gis in infrastructural plan and identifying ecolog...Role of remote sensing and gis in infrastructural plan and identifying ecolog...
Role of remote sensing and gis in infrastructural plan and identifying ecolog...
 
Ground water prospects map
Ground water prospects mapGround water prospects map
Ground water prospects map
 
Quantitative Morphometric analysis of a Semi Urban Watershed, Trans Yamuna, ...
Quantitative Morphometric analysis of a Semi Urban Watershed,  Trans Yamuna, ...Quantitative Morphometric analysis of a Semi Urban Watershed,  Trans Yamuna, ...
Quantitative Morphometric analysis of a Semi Urban Watershed, Trans Yamuna, ...
 
Ijirt148701 paper
Ijirt148701 paperIjirt148701 paper
Ijirt148701 paper
 
Detection of Fish Farm Location Using Satellite Image
Detection of Fish Farm Location Using Satellite ImageDetection of Fish Farm Location Using Satellite Image
Detection of Fish Farm Location Using Satellite Image
 
Resource potential appraisal assessment and to
Resource potential appraisal  assessment and toResource potential appraisal  assessment and to
Resource potential appraisal assessment and to
 
Resource potential appraisal
Resource potential appraisalResource potential appraisal
Resource potential appraisal
 
Identification Of Ground Water Potential Zones In Tamil Nadu By Remote Sensin...
Identification Of Ground Water Potential Zones In Tamil Nadu By Remote Sensin...Identification Of Ground Water Potential Zones In Tamil Nadu By Remote Sensin...
Identification Of Ground Water Potential Zones In Tamil Nadu By Remote Sensin...
 
lect 1-2.pdf
lect 1-2.pdflect 1-2.pdf
lect 1-2.pdf
 
Application of remote sensing and gis for groundwater
Application of remote sensing and gis for groundwaterApplication of remote sensing and gis for groundwater
Application of remote sensing and gis for groundwater
 
Identification of Groundwater Potential Survey Using QGIS of DBATU campus, Ma...
Identification of Groundwater Potential Survey Using QGIS of DBATU campus, Ma...Identification of Groundwater Potential Survey Using QGIS of DBATU campus, Ma...
Identification of Groundwater Potential Survey Using QGIS of DBATU campus, Ma...
 
Easter Desert Project
Easter Desert ProjectEaster Desert Project
Easter Desert Project
 

Recently uploaded

Oxy acetylene welding presentation note.
Oxy acetylene welding presentation note.Oxy acetylene welding presentation note.
Oxy acetylene welding presentation note.eptoze12
 
main PPT.pptx of girls hostel security using rfid
main PPT.pptx of girls hostel security using rfidmain PPT.pptx of girls hostel security using rfid
main PPT.pptx of girls hostel security using rfidNikhilNagaraju
 
Introduction to Machine Learning Unit-3 for II MECH
Introduction to Machine Learning Unit-3 for II MECHIntroduction to Machine Learning Unit-3 for II MECH
Introduction to Machine Learning Unit-3 for II MECHC Sai Kiran
 
INFLUENCE OF NANOSILICA ON THE PROPERTIES OF CONCRETE
INFLUENCE OF NANOSILICA ON THE PROPERTIES OF CONCRETEINFLUENCE OF NANOSILICA ON THE PROPERTIES OF CONCRETE
INFLUENCE OF NANOSILICA ON THE PROPERTIES OF CONCRETEroselinkalist12
 
Concrete Mix Design - IS 10262-2019 - .pptx
Concrete Mix Design - IS 10262-2019 - .pptxConcrete Mix Design - IS 10262-2019 - .pptx
Concrete Mix Design - IS 10262-2019 - .pptxKartikeyaDwivedi3
 
Application of Residue Theorem to evaluate real integrations.pptx
Application of Residue Theorem to evaluate real integrations.pptxApplication of Residue Theorem to evaluate real integrations.pptx
Application of Residue Theorem to evaluate real integrations.pptx959SahilShah
 
Work Experience-Dalton Park.pptxfvvvvvvv
Work Experience-Dalton Park.pptxfvvvvvvvWork Experience-Dalton Park.pptxfvvvvvvv
Work Experience-Dalton Park.pptxfvvvvvvvLewisJB
 
What are the advantages and disadvantages of membrane structures.pptx
What are the advantages and disadvantages of membrane structures.pptxWhat are the advantages and disadvantages of membrane structures.pptx
What are the advantages and disadvantages of membrane structures.pptxwendy cai
 
GDSC ASEB Gen AI study jams presentation
GDSC ASEB Gen AI study jams presentationGDSC ASEB Gen AI study jams presentation
GDSC ASEB Gen AI study jams presentationGDSCAESB
 
Call Girls Narol 7397865700 Independent Call Girls
Call Girls Narol 7397865700 Independent Call GirlsCall Girls Narol 7397865700 Independent Call Girls
Call Girls Narol 7397865700 Independent Call Girlsssuser7cb4ff
 
EduAI - E learning Platform integrated with AI
EduAI - E learning Platform integrated with AIEduAI - E learning Platform integrated with AI
EduAI - E learning Platform integrated with AIkoyaldeepu123
 
Internship report on mechanical engineering
Internship report on mechanical engineeringInternship report on mechanical engineering
Internship report on mechanical engineeringmalavadedarshan25
 
Gurgaon ✡️9711147426✨Call In girls Gurgaon Sector 51 escort service
Gurgaon ✡️9711147426✨Call In girls Gurgaon Sector 51 escort serviceGurgaon ✡️9711147426✨Call In girls Gurgaon Sector 51 escort service
Gurgaon ✡️9711147426✨Call In girls Gurgaon Sector 51 escort servicejennyeacort
 
CCS355 Neural Network & Deep Learning UNIT III notes and Question bank .pdf
CCS355 Neural Network & Deep Learning UNIT III notes and Question bank .pdfCCS355 Neural Network & Deep Learning UNIT III notes and Question bank .pdf
CCS355 Neural Network & Deep Learning UNIT III notes and Question bank .pdfAsst.prof M.Gokilavani
 
Artificial-Intelligence-in-Electronics (K).pptx
Artificial-Intelligence-in-Electronics (K).pptxArtificial-Intelligence-in-Electronics (K).pptx
Artificial-Intelligence-in-Electronics (K).pptxbritheesh05
 
complete construction, environmental and economics information of biomass com...
complete construction, environmental and economics information of biomass com...complete construction, environmental and economics information of biomass com...
complete construction, environmental and economics information of biomass com...asadnawaz62
 
Biology for Computer Engineers Course Handout.pptx
Biology for Computer Engineers Course Handout.pptxBiology for Computer Engineers Course Handout.pptx
Biology for Computer Engineers Course Handout.pptxDeepakSakkari2
 
Gfe Mayur Vihar Call Girls Service WhatsApp -> 9999965857 Available 24x7 ^ De...
Gfe Mayur Vihar Call Girls Service WhatsApp -> 9999965857 Available 24x7 ^ De...Gfe Mayur Vihar Call Girls Service WhatsApp -> 9999965857 Available 24x7 ^ De...
Gfe Mayur Vihar Call Girls Service WhatsApp -> 9999965857 Available 24x7 ^ De...srsj9000
 
Past, Present and Future of Generative AI
Past, Present and Future of Generative AIPast, Present and Future of Generative AI
Past, Present and Future of Generative AIabhishek36461
 
Introduction-To-Agricultural-Surveillance-Rover.pptx
Introduction-To-Agricultural-Surveillance-Rover.pptxIntroduction-To-Agricultural-Surveillance-Rover.pptx
Introduction-To-Agricultural-Surveillance-Rover.pptxk795866
 

Recently uploaded (20)

Oxy acetylene welding presentation note.
Oxy acetylene welding presentation note.Oxy acetylene welding presentation note.
Oxy acetylene welding presentation note.
 
main PPT.pptx of girls hostel security using rfid
main PPT.pptx of girls hostel security using rfidmain PPT.pptx of girls hostel security using rfid
main PPT.pptx of girls hostel security using rfid
 
Introduction to Machine Learning Unit-3 for II MECH
Introduction to Machine Learning Unit-3 for II MECHIntroduction to Machine Learning Unit-3 for II MECH
Introduction to Machine Learning Unit-3 for II MECH
 
INFLUENCE OF NANOSILICA ON THE PROPERTIES OF CONCRETE
INFLUENCE OF NANOSILICA ON THE PROPERTIES OF CONCRETEINFLUENCE OF NANOSILICA ON THE PROPERTIES OF CONCRETE
INFLUENCE OF NANOSILICA ON THE PROPERTIES OF CONCRETE
 
Concrete Mix Design - IS 10262-2019 - .pptx
Concrete Mix Design - IS 10262-2019 - .pptxConcrete Mix Design - IS 10262-2019 - .pptx
Concrete Mix Design - IS 10262-2019 - .pptx
 
Application of Residue Theorem to evaluate real integrations.pptx
Application of Residue Theorem to evaluate real integrations.pptxApplication of Residue Theorem to evaluate real integrations.pptx
Application of Residue Theorem to evaluate real integrations.pptx
 
Work Experience-Dalton Park.pptxfvvvvvvv
Work Experience-Dalton Park.pptxfvvvvvvvWork Experience-Dalton Park.pptxfvvvvvvv
Work Experience-Dalton Park.pptxfvvvvvvv
 
What are the advantages and disadvantages of membrane structures.pptx
What are the advantages and disadvantages of membrane structures.pptxWhat are the advantages and disadvantages of membrane structures.pptx
What are the advantages and disadvantages of membrane structures.pptx
 
GDSC ASEB Gen AI study jams presentation
GDSC ASEB Gen AI study jams presentationGDSC ASEB Gen AI study jams presentation
GDSC ASEB Gen AI study jams presentation
 
Call Girls Narol 7397865700 Independent Call Girls
Call Girls Narol 7397865700 Independent Call GirlsCall Girls Narol 7397865700 Independent Call Girls
Call Girls Narol 7397865700 Independent Call Girls
 
EduAI - E learning Platform integrated with AI
EduAI - E learning Platform integrated with AIEduAI - E learning Platform integrated with AI
EduAI - E learning Platform integrated with AI
 
Internship report on mechanical engineering
Internship report on mechanical engineeringInternship report on mechanical engineering
Internship report on mechanical engineering
 
Gurgaon ✡️9711147426✨Call In girls Gurgaon Sector 51 escort service
Gurgaon ✡️9711147426✨Call In girls Gurgaon Sector 51 escort serviceGurgaon ✡️9711147426✨Call In girls Gurgaon Sector 51 escort service
Gurgaon ✡️9711147426✨Call In girls Gurgaon Sector 51 escort service
 
CCS355 Neural Network & Deep Learning UNIT III notes and Question bank .pdf
CCS355 Neural Network & Deep Learning UNIT III notes and Question bank .pdfCCS355 Neural Network & Deep Learning UNIT III notes and Question bank .pdf
CCS355 Neural Network & Deep Learning UNIT III notes and Question bank .pdf
 
Artificial-Intelligence-in-Electronics (K).pptx
Artificial-Intelligence-in-Electronics (K).pptxArtificial-Intelligence-in-Electronics (K).pptx
Artificial-Intelligence-in-Electronics (K).pptx
 
complete construction, environmental and economics information of biomass com...
complete construction, environmental and economics information of biomass com...complete construction, environmental and economics information of biomass com...
complete construction, environmental and economics information of biomass com...
 
Biology for Computer Engineers Course Handout.pptx
Biology for Computer Engineers Course Handout.pptxBiology for Computer Engineers Course Handout.pptx
Biology for Computer Engineers Course Handout.pptx
 
Gfe Mayur Vihar Call Girls Service WhatsApp -> 9999965857 Available 24x7 ^ De...
Gfe Mayur Vihar Call Girls Service WhatsApp -> 9999965857 Available 24x7 ^ De...Gfe Mayur Vihar Call Girls Service WhatsApp -> 9999965857 Available 24x7 ^ De...
Gfe Mayur Vihar Call Girls Service WhatsApp -> 9999965857 Available 24x7 ^ De...
 
Past, Present and Future of Generative AI
Past, Present and Future of Generative AIPast, Present and Future of Generative AI
Past, Present and Future of Generative AI
 
Introduction-To-Agricultural-Surveillance-Rover.pptx
Introduction-To-Agricultural-Surveillance-Rover.pptxIntroduction-To-Agricultural-Surveillance-Rover.pptx
Introduction-To-Agricultural-Surveillance-Rover.pptx
 

Watershed delineation and LULC mapping

  • 1. Preparation of landuse/landcover map using RS and GIS techniques Mentor : Dr. CHANDER PRAKASH Prepared by: ARUN KUMAR (17142) NITISH THAKUR (17137) KAPIL THAKUR (17141) NEERAJ KUMAR (17190) 1
  • 2. • Land use/cover are two separate terminologies which are often used interchangeably. • Land cover refers to the physical characteristics of earth’s surface (vegetation, water, soil and other physical features of the land, including those created by human activities e.g., settlements. • Land-use refers to the way in which land has been used by humans. 2 Introductions
  • 3. Objective • DEM-Based stream and watershed Delineation. • Visually interpreting the satellite data to map different categories of land use/ land cover (LULC) of delineated watershed. • Change assessment of watershed using remote sensing and GIS and understanding the impact on the ecosystem . 3
  • 4. Study Area UPPER BEAS WATERSHED Kullu, Himachal Pradesh. Kullu Beas river rises in the Himalayas in central Himachal Pradesh. Outlet point of watershed – • Location - Bhunter • Coordinates – Latitude - 31°53'44.06"N Longitude - 77° 8'31.31"E 4
  • 5. ASTER DEM - ASTER provides high-resolution images of the planet Earth in 14 different bands of the electromagnetic spectrum, ranging from visible to thermal infrared light. The resolution of images ranges between 15 and 90 meters. ASTER data are used to create detailed maps of surface temperature of land, emissivity, reflectance, and elevation. ASTER GDEM V3 From NASA Earth-data 5 DATASETS AND SOFTWARE USED:
  • 6. LANDSAT-8 SATELLITE DATA - The Landsat 8 satellite payload consists of two science instruments—the Operational Land Imager (OLI) and the Thermal Infrared Sensor (TIRS). These two sensors provide seasonal coverage of the global landmass at a spatial resolution of 30 meters (visible, NIR, SWIR); 100 meters (thermal); and 15 meters (panchromatic). Landsat-8 Satellite data From USGS earth-explorer DATASETS AND SOFTWARE USED:
  • 7. Satellite Date of Generation Path-Row Sensor Band Spatial Resolution Landsat 8 2020-10-14 147-38 Operational Land Imager (OLI) Band 1 - Coastal / Aerosol 30 m Band 2 - Blue 30 m Band 3 - Green 30 m Band 4 - Red 30 m Band 5 - Near Infrared 30 m Band 6 - Short Wavelength Infrared 30 m Band 7 - Short Wavelength Infrared 30 m Band 8 - Panchromatic 15 m Thermal Infrared Sensor (TIRS) Band 10 - Long Wavelength Infrared 100 m Band 11 - Long Wavelength Infrared 100 m 7 The Landsat 8 OLI/TIRS C1 Level-1 satellite image captured on 2020-10-14 is used. The images were downloaded from United States Geological Survey (USGS,https://earthexplorer.usgs.gov/) earth explorer. DATASETS AND SOFTWARE USED:
  • 8. Software Used - The following software were used for satellite data processing and GIS analysis- ERDAS Imagine for Pre-processing. ArcGIS 10.2 for database creation, analysis and map composition. Hec-GeoHMS ArcGIS extension tool is used for watershed delineation and catchment characteristics. 8 DATASETS AND SOFTWARE USED:
  • 9. Digital Elevation Model (DEM) based Hydro processing and Watershed delineation are estimated by using the HEC-GeoHMS tools of Arc GIS Software. 9 METHODOLOGY : Fig. Flow chart for Watershed delineation.
  • 10. 10 Various steps involved in the Preprocessing : • Fill sinks: Fill sinks operation removes local depression from a DEM by replacing the local depressions by flat areas in the output DEM. • Flow Direction : Flow Direction grid, contains cells with only the numerical values dictated by the 8-direction pour point model. PREPROCESSING • Flow Accumulation: It is used to determine the ultimate flow path of every cell on the landscape grid. • Stream Definition and segmentation : With a flow accumulation grid, streams may be defined through the use of a threshold flow accumulation value. • Catchment Polygon Processing: The function of catchment polygon processing is to convert a catchment grid into a catchment polygon feature. • Drainage Line Processing: Drainage Line Processing converts the input Stream Link grid into a Drainage Line feature class. Fig. HEC-GeoHMS tool bar. WATERSHED DELINEATION
  • 11. 11 The values represent flow in particular direction i.e. 1 – East, 2 – South East, 4 – South, 8 – South West, 16 – West, 32 – North West, 64 – North and 128 – North East.  For ASTER DEM, the maximum flow is in the Southwest (SW) direction, whereas the minimum flow is in the North (N) direction. Flow Direction Map of Beas Watershed WATERSHED DELINEATION
  • 12. 12 Fig. Process from the determination of flow direction to flow pattern. WATERSHED DELINEATION
  • 13. 13  Start New Project: Go to start new project and enter the project name. Specify the outlet point of the basin model by using ‘Add Project Points’ tool.  Generate Project: Generate the project by using the method of generating as Original stream definition. Watershed is delineated and project setup is completed. PROJECT SETUP WATERSHED DELINEATION Fig. Project Setup in HEC-GeoHMS
  • 14. 14 Fig. Delineated Watershed with subbasins from ASTER DEM. HEC- GeoHMS
  • 15. Flow Chart for making land use/land cover map (LULC) 15 LULC MAPPING :
  • 16. • For image Pre-processing and performing supervised classification of the satellite imageries, mosaicking of data tiles is performed initially. • For Image Enhancement, several corrections and layer stacking of satellite imageries are done to convert multiple bands into a single layer. • Resultant shapefile of watershed area produced through watershed delineation process was used to clip the study area from the imageries using ArcGIS. • These clipped images are then re-projected to Universal Transverse Mercator zone 43N and resampled, if needed. • FCC of the study area was also generated using band 5, 3 & 4. R = 5 (NIR band) G = 3 (red band) B = 4 (green band) 16 LULC MAPPING : Image Pre-processing :
  • 17. 17 LULC MAPPING : LULC Mapping: • Visual image interpretation technique of classification was applied in the study • This Comprises of the following six major steps- - Selection and acquisition of data - Pre-field interpretation - Ground data collection and verification - Post-field interpretation and modification - Computation of area - Final cartographic map preparation and reproduction. • Then all satellite data were studied by assigning per-pixel signatures. The whole watershed is differentiated into five classes- Forest, vegetation, bare land, water bodies and snow. • The maximum likelihood algorithm is used for supervised classification of the imagery.
  • 18. Image interpretation key for LULC classification - 18 • A final interpretation key for the various classes was prepared using spectral characteristics of classes and field knowledge. • Red in false color composite image indicates the density of the vegetation. • Water bodies were appeared in dark blue or light blue tone with smooth texture • Patches of light red tones represented vegetation. Tone Texture Shape Spectral Signature Description Dark red to light red Rough Irregular Tree cover (forest canopy density >40%) Light Red Smooth Irregular Tree cover (forest canopy density 10- 40%) Light red or pinkish red Coarse Varying Bushy vegetation with shrubs or scattered trees (forest canopy density <10%) Pinkish red to light green Medium Smooth Irregular Scattered trees/shrubs with exposed ground surface; canopy density <10%. Pinkish or light green or light blue or light cyan Medium Smooth Regular Crops/ current fallow Lands, surrounded by small to medium size settlements. Cyan Rough Irregular/ regular Urban as well rural (Maximum rural) Dark blue or light blue Smooth Irregular/ Linear River, stream and pond LULC MAPPING :
  • 20. Results • The visual interpretation of the satellite data with the ground truth was used to map different categories of land use/ land cover (LULC) map of UPPER BEAS WATERSHED. • Five categories of LULC were classified which include forest(open forest, dense forest and degraded forest), vegetation, snow, other land use (agriculture, settlement) and water bodies. Brief descriptions of different categories of land use/ land cover are given further 20
  • 21. 21 Results • Area statistics of different categories of land use/ land cover is also given in table. • Pie chart shows distribution of different categories of land use/land cover. • It can be concluded that the bare land (including settlements) and Forest land have the highest percentage of the total area covered in the study area of upper Beas watershed.
  • 22. • For many planning activities accurate and current information on land use and land cover is required. • Visual interpretation method allows the most detailed differentiation of structures and objects which is advantageous in detecting spatial patterns and in drafting precise boundaries around relatively homogenous area. • We can further use this knowledge to assess the LULC scenario and assessment by applying the methodology on maps of past years and deriving data will along with land use change assessment table for those years. • Further for comprehensive study certain figures like temporal pattern and relative change in land will be drawn and a cross tabulationa i.e. two-way cross-matrix containing different combinations of ‘‘from–to’’ change classes will be formed on pixel-by-pixel basis using in order to determine the quantity of conversions from one land cover to other land cover category within the time frame. • At last accuracy assessment will be done by site visiting or using google earth pro. Discussion 22