INTEGRATION OF REMOTE SENSING DATA WITH GEOGRAPHIC INFORMATION SYSTEM (GIS): ...
Intern report final
1. A SUMMER PROJECT TRAINING REPORT ON
“REMOTE SENSING AND GIS APPLICATIONS IN FOREST MONITORING”
As a partial fulfillment for the award of the degree of MSc in Geoinformatics & Remote sensing
Submitted by:
Md. Fazlul Wahid
Enrollment No- A 13054314010
Amity University, Noida
Under the guidance of:
Dr. Pebam Rocky
Scientist/Engineer “D”
North Eastern Space Applications Centre
Umiam, Shillong
Meghalaya (793103)
AMITY INSTITUTE OF GEOINFORMATICS AND REMOTE SENSING
NOIDA, UTTAR PRADESH
2. Certificate
This is to certify that the Project Titled “Remote Sensing and GIS applications in Forest
Monitoring” is a bonafide work carried by Md. Fazlul Wahid, bearing Enrollment No. A-
13054314010, IIIrd
semester, Master of Science in GIS & RS, Amity Institute of Geoinformatics and Remote
Sensing, Noida, under my guidance and supervision at North Eastern Space Applications
Centre (NE-SAC), Umiam, Meghalaya during June-July 2015. The work has been prepared
as a partial fulfillment for the award of Master of Science in GIS & RS in Amity Institute of
Geoinformatics and Remote Sensing, Noida. Further it is certified that this project has not been
submitted for any other purpose elsewhere.
During his association with me, I found Md. Fazlul Wahid as a sincere and hardworking
student. It is my firm believe that he will do well in his future studies. I wish him all the
best for his future endeavors and a successful professional life.
Approved By
(Dr. Pebam Rocky)
Scientist/Engineer‘SD’
NESAC, UMIAM
(MEGHALAYA)
3. Acknowledgements
First of all I would like to extend my heartfelt gratitude to Dr. S. Sudhakar, Director, North
Eastern Space Applications Centre (NE-SAC), for providing me the opportunity to carry out my project
work under this prestige Organization and to explore new techniques and widen my knowledge.
I owe a very deep sense of gratitude to Dr. Pebam Rocky, Scientist/Engineer (SD),
NE-SAC, for all his precious and most valuable guidance, support, time and help during my entire
period, without which this project would have been impossible. I would additionally like to thank
him for taking me a step forward into the new and better understanding of the Geospatial
environment.
I am very much thankful to Dr. Madhulika Singh, Director, Amity Institute of
Geoinformatics and Remote Sensing, Noida and for her altruistic cooperation and guidance for
successful completion of my project within the given time period.
I am also thankful to Mr. Hari Shanker Prasad, Junior Research Fellow (JRF), NE-SAC,
for his valuable help and advice during my project work.
My sincere thanks also goes to all the staffs (Technical and Non-Technical) of NE-SAC for
their help and encouragement during my project work.
Last but not the least, my deep sense of gratitude to all my family members, seniors and
friends for their ungrudging support all through my career.
Md. Fazlul Wahid
Amity Institute of Geoinformatics and Remote Sensing, Noida
4. 1 | P a g e
INDEX
Sl. Topics Page no
1 INTRODUCTION 2-3
2 ABOUT THE HOST ORGANISATION 4
APPLICATIONS IN FOREST MONITORING
3
FOREST COVER CHANGE ANALYSIS 5-10
4
LOSS OF FOREST COVER DUE TO SHIFTING CULTIVATION 11-18
5
REFERENCE 19
5. Introduction
A geographic information system (GIS) captures, stores, analyses, manages, and presents data,
which is linked to locations or having spatial distribution (IDRC, 2009). It is a computer-based
system that provides four sets of capabilities to handle geo-reference data.
These are:
data capture: graphic data (digitized, converted from existing data) and attribute data (keyed-
in, loaded from existing data files)
data storage and manipulation: file management and editing
data analysis: database query, spatial analysis and modeling
data display: maps and reports GIS is run on all spectrums of computer systems ranging
from personal computers (PCs) to multi-user supercomputers, and are available in a wide
variety of software languages.
A number of tools are essential for effective GIS establishment such as computer, digitizer, GPS
(Global Positioning System), plotter, network, CD-ROM drive, printer and software which links
all of the equipment to run properly. GIS provides a valuable tool for information analysis,
automated mapping and data integration. The powerful GIS software, tools in problem-oriented
systems, provides direct and easy access to large volumes of data. It supports their interactive
analysis and helps to display and interpret results in a format directly understandable and useful
for decision-making processes (Kamal et al, 2000). A GIS can manage different data types
occupying the same geographic space. The major advantage of GIS is that it can read and analyze
different layers of spatial information in the form of maps and satellite images easily and allows
identifying the spatial relationships. The objective of GIS is to help and assert in decision making
processes for the management and effective conservation of natural resources.
Remote sensing (RS) technology has been developed well ahead of GIS technology. RS acquires
information about material objects from measurements made at a distance, without coming into
physical contact with the object. Usually an aircraft or satellite does the process. Remote sensing
technology may be divided into three phases: (i) data collection from a sensor mounted on a
platform eg, a satellite; (ii) data handling; (iii) data interpretation which end up in generating some
thematic maps of the investigated surfaces. A remote sensing system using electromagnetic
6. radiation has four components - a source, interactions with the earth's surface, interaction with the
atmosphere and a sensor. The source of electromagnetic radiation may be natural, like the sun's
reflected light or the earth's emitted heat, or man-made microwave radar. Earth's surface
interaction, that is the amount and characteristics of radiation emitted or reflected from the earth's
surface, is dependent upon the characteristics of the objects. Electromagnetic energy passing
through the atmosphere is distorted and scattered, treated as atmospheric interaction, and the
electromagnetic radiation that has interacted with the atmosphere and the surface of the earth is
recorded by a sensor, such as a radiometer or camera (Alam and Choudhury, 2006).
Aerial photography is the earliest method of remote sensing and even in today's age of Satellites
and electronic scanners it remains the most widely used remote sensing method. Aerial photo
means sensing the image of earth's surface through cameras fitted in an aero plane or balloon.
These photographs are very much useful for preparing large scale maps. Aerial sensor imageries
are collected using radar. Satellite remote sensing is a modern innovation. Remote sensing
satellites have been designed according to the application such as the study of earth's resources,
meteorology, communication or military purposes (Alam and Choudhury, 2006).
The most commonly used earth's resource satellites are - Landsat series of USA, SPOT satellite
series of France, and IRS series of India. These bear different types of scanners, viz, Multispectral
Scanner (MSS), Thematic Mapper (TM), Panchromatic (PAN) scanner, High- Resolution Visible
(HRV) scanner, Linear Imaging and Self Scanning (LISS) system, Wide Field Scanner (WiFS),
etc. NOAA, NIMBUS, GOES Meteos and Himawari are the most commonly used meteorological
satellites. The user countries can buy satellite data either in pictorial or in digital format directly
from the satellite company or from the company's designated receiving stations (Alam and
Choudhury, 2006). Remote sensing data can be digitized and analyzed by GIS tools to give precise
outputs in different formats. The principal areas for application of GIS and RS are land-use
planning and management, management of natural resources (land, water, agriculture and fishery);
forestry and wildlife management, soil degradation studies and enumeration area mapping,
environmental impact studies, natural hazard mapping, disaster forecasting and management,
mineral exploration, etc. The application of GIS and RS is rapidly expanding worldwide for
planning and management of natural as well as man-made resources.
7. About the Host Organization
The North Eastern Space Applications Centre (NESAC), a society registered under the Meghalaya
Societies Registration Act, 1983 has completed 13 years. It is a joint initiative of Department of
Space (DOS) and the North Eastern Council (NEC) to provide developmental support to the north
eastern region (NER) of our country using space science and technology. The major objectives of
the Centre are:
• To provide an operational remote sensing based natural resource information base to assist
activities on development / management of natural resources and infrastructure planning
in the region.
• To provide operational satellite communication applications services in the region in
education, health care, disaster management support, and developmental communication.
• To establish a space science and climatic change research hub by installation of necessary
instrumentation and networking with various academic institutions of NER
RS & GIS facility in NESAC
Remote Sensing (RS) and Geographical Information System (GIS) The Centre has got the state-
of-art facilities for image processing, Geographical Information System (GIS) photogrammetry
workstations for terrain analysis, Differential Geographical Information System (DGPS) for
collecting high precision Ground Control Points (GCPs), high quality printers and plotters and
archive of Survey of India toposheets, reference maps and NORTH EASTERN SPACE
APPLICATIONS CENTRE 10 large volume of satellite data of the region. As on date, complete
coverage of LISS III, AWiFS sensor images of entire north east is available. In addition, large data
from sensors like LISS IV (Multi-spectral), Cartosat-1, Cartosat 2A/2B and few samples Radarsat,
Envisat, Quickbird, Worldview-2 etc. are also available. A regional node of Natural Resources
Data Base (NRDB) has also been established as repository for all the states.
8. REMOTE SENSING & GIS APPLICATIONS IN FOREST MONITORING
1. FOREST COVER CHANGE ANALYSIS:
While the concept of change detection analysis is not new, the emergence of new imaging sensors
and geospatial technologies has created a need for image processing techniques that can integrate
observation from a variety of different sensors and datasets to map, monitor and detect forest
resources. In addition to timber, forests provide such resources as grazing land for animals, wildlife
habitat, water resources and recreation areas and these are threatened constantly by both human
impacts like forest fires, air pollution, clearing of agricultural uses and illegal cutting. Decrease in
vegetation has been a result of anthropogenic activities in the.
The use of remote sensing data in recent times has been of immense help in monitoring the
changing pattern of forest cover. It provides some of the most accurate means of measuring the
extent and pattern of changes in cover conditions over a period of time (Miller, 1998). Satellite
data have become a major application in forest change detection because of the respective coverage
of the satellites at short intervals (Mas, 1999). Forest cover today is altered primarily by direct
human use and any conception of global change must include the persuasive influence of human
action of land surface conditions and processes (Yang, 2002).
Change detection is defined by Singh (1986) as a process of identifying changes in the state of an
object or phenomenon by observing images at different times.
According to IGBP/IHDP (Anon, 1999) change detection studies seek to know
i) Pattern of forest cover change
ii) Processes of forest cover change and
iii) Human response to forest cover change.
Forest have long been regarded as a national treasure and in addition to timber; these forests
provide such resources as grazing land for animals, wildlife habitat, water resources, tourism and
outdoor recreation areas. They are also important for preserving biodiversity as they provide a
habitat for certain specialized forest-related species (Parviainen, 1997). This is important because
the changing pattern of LULC reflect changing economic and social conditions.
9. In view of the importance of forest a change detection exercise was carried out in Kamlang
Reserved Forest, Namsai, Arunachal Pradesh to assess the change in vegetated area over a period
of 8 years using satellite data.
10. Methods:
Vegetation change detections studies are usually done by digital image processing of satellite
imagery over a period of time. In the present exercise two IRS LISS III data pertaining to February
2006 and another of January 2014 were used to analyze the change detection of Kamlang Reserved
Forest under Namsai Forest Division, Arunachal Pradesh.
Kamlang is located in the south eastern region of Lohit District in the state Arunachal Pradesh. It
derives its name from river Kamlang. Kamlang is spread between the famed Namdhapha National
Park, on its south and Lang River on its north. The place is adorned with unmatched natural beauty
featuring perennial water sources, beautiful terrains and mesmerizing landscapes. Government of
Arunachal Pradesh had put much effort to develop the area as an inviting tourist spot. The terrain
is quite high and difficult which makes several regions quite inaccessible. The area is mainly
inhabitant by the Mishmis and their occupation is mainly agriculture.
Image to image registration of the two dataset was done and the radiometry was normalized to
reduce the error in change detection. Image to image registration is the translation and rotation of
alignment process by which two images of the like geometry and of same geographic area are
positioned coincident with respect to one another so that corresponding elements of the same
ground area appears in the same place on the registered image. Normalized Difference Vegetation
Index (NDVI) of the two dataset was generated using the tool available in ERDAS software and a
band subtraction was executed for the two NDVI (2014 – 2006 and vice versa) data using the
model maker tool in ERDAS. The changes from forest to non forests and non forest top forest over
the two time period were identified and proper thresholding was done to elicit the actual change
(reduction or increase in forest cover) over the period.
Results
The change map of forest cover between 2006 and 2014 is shown in figures 2 & 3. In 2006 there
was a non forest area of 3.99 sq km out of the total 130 sq km of the Kamlang Reserved Forest.
There was an increased in deforestation during 2014 with an area of about 7.33 sq km. coming
under non forest category while the non forest area in 2006 has been converted to forest in 2014.
14. 2. FOREST COVER LOSS DUE TO SHIFTING CULTIVATION IN
LONGDING DISTRICT OF ARUNACHAL PRADESH
Figure5:Changemapof2006to2014(nonforesttoforest)
15. Forest has traditionally been used for many products, including timber, fuel and fodder. They are
one of the most important renewable natural resources because of their economic, environmental,
aesthetic and recreational benefits. The north eastern region of India although blessed with good
forest cover have been facing heavy anthropogenic pressure in the form of deforestation owing
mostly to the slash and burn of shifting cultivation which are locally known as jhuming. Jhum is
the main form of agriculture in the hills of northeast India except Sikkim. In the mountainous
terrain, settled cultivation constitutes only a small portion of the total cultivated land, and mostly
confined to valley areas. It invariably involves the clearing of vegetation and the slashing and
burning of the plants. After 2-3 years of cropping, the soil loses its fertility and the farmer shifts
to another piece of virgin or secondary forest for cultivation. The vegetation in the fallow land
regenerates during the fallow period.
In the present exercise we tried to map the deforestation rate in Longding district (forest division)
due to shifting cultivation practice by the inhabitants over a period of time.
Study Area
Longding district was created by bifurcating erstwhile Tirap district of Arunachal Pradesh on 26th
September,2011. The district is inhabitant mainly by the Wancho community. They are culturally
similar to the Naga people.Because of the hilly terrain most of the cultivators in the district follow
a type of slash-and-burn cultivation known as jhum cultivation. Still many people follow animism
through a few have converted to Christianity. Other people inhabitant on the region are Nocte,
Konyak and Naga. Longding is situated at 54kms from Khonsa, the district H/Q of Tirap.
Methods
Visual on screen digitization of LISS III imagery was done for different year to map out the shifting
cultivation using Arc GIS software. Image to image registration of all the IRS LISS III imagery
pertaining to 11.02.2002, 01.02.2006, 06.02.2010, 31.01.2014 were done and shifting cultivation
area was delineated at 1:50,000 scale. Shifting cultivation fields were easily identifiable with their
bright big patches devoid of green vegetation which were more prominent during the rabi season.
The area statistics of all the jhum polygons were generated and analysed for their extent.
16.
17. Results
In the year 2002 the area under jhum cultivation was found to 3927.83 ha which was about 4.32
% of the total geographical area of the district (Table 1). Large patches of jhum fields (more than
2 sq km area) covered about 11% of the jhum fields in the district while about 67% of the jhum
fields were smaller than 1 sq km (figure 8). Based on the interpretation of the 2006 imagery
6194.22 sq km (6.82% of geographical area) was under jhum cultivation and 8% of the jhum fields
were larger than 2 sq km area while about 37 % were below 1 sq km area. Relatively big patches
of jhum fields were seen on most of the hill slopes which were forested in the preceding imagery
(figure 9).
In 2010 interpretation 3984.69 sq km (4.38%) area of the district was under shifting cultivation
with about 5% of the jhum fields were larger than 2 sq km while about 63 % of the fields were
smaller than 1 sq km (figure 10). There was some reduction in the area extent of jhum from 2006
to 2010 but was showing an increasing trend in 2014 where it rose to 4745.95 ha (5.22%) with
about 10% of the jhum fields larger than 2 sq km and 58% of the fields less than 1 sq km (figure
11).
We can conclude that in any given year about 4712 ha of the district is under jhum fields or in
other words deforestation rate in the district due to shifting cultivation is 5.2 % of the total
geographical area.
Table 1: Area under jhum fields in Longding Division
Year Area under jhum P.C. of geographical area
2002 3927.83 4.32 %
2006 6194.22 6.82 %
2010 3984.69 4.38 %
2014 4745.95 5.22 %
23. References:
Alam, Mohd Shamsul and Masud Hasan Chowdhury (2006). Remote Sensing. Banglapedia, The
National Encyclopedia of Bangladesh). [http://www.banglapedia.org/httpdocs/HT/R_0174.HTM]
IDRC (2009). “ICT, natural resource management and local development”, Background paper for
the IDRC regional ICT and local development workshop, Working draft, Dakar, May 2009.
Available at [http://web.idrc.ca/ritc/ev-139502-201-1-DO_TOPIC.html]
IGBP-IHDP. (1999) Land use and land cover change implementation strategy. IGBP Report 48
and IHSP Report 10. IGBP Secretariat, Stockholm, Sweden. Pp287. International Journal
of Remote Sensing 10(6):989 - 1003.
Kamal, Md. Rowshon; Md. Masud Karim and Kwok Chee Yan (2000). GIS Application for
Monitoring Groundwater Arsenic Contamination in Bangladesh. Dhaka 2000
Environmental Conference, Bangladesh Environment Network, 14-15 January 2000,
BUET, Dhaka. Available at [http://www.engconsult. com/pub/iahr.pdf]
Mas, J. F. (1999) Monitoring Land-Cover Changes: A Comparison of Change Detection
Techniques. International Journal of Remote Sensing, 20(1):139 - 152.
Miller, A. B., Bryant, E. S., and Birnie, R. W. (1998) An Analysis of Land Cover Changes in the
Northern Forest of New England Using Multi-temporal LANDSAT MSS Data.
International Journal Remote Sensing, 19(2):215-265.
Parviainen, J. and Päivenen, R. (2007) Information Needs for Biodiversity Assessment Derived
from International Forestry Discussions. In: Bachmann, P., Köhl, M. and Päivinen, R.
(Eds.). Assessment of Biodiversity for Improved Forest Planning, Kluwer Academic
Publishers, Dordrecht, pp. 331–342.
Singh .A. (1986) Review Article: Digital Change Detection Techniques using Remotely Sensed
Data. International Journal of Remote Sensing, 10:989-1003.
Yang, X. and Lo, C. P. (2002) Using a Time Series of Satellite Imagery to Detect Land Use and
Land Cover Changes in the Atlanta, Georgia Metropolitan Area. International Journal of
Remote Sensing, 23:1775–1798.