To meet the various information requirements in forest management, different data sources like field survey, aerial photography, and satellite imagery is used, depending on the level of detail required and the extension of the area under study.

1. Seminar On
Forest Monitoring Through Remote Sensing
PRITAM KUMAR BARMAN
ID No: 20MSFBTI003
M.Sc. Forestry
Advisor: Dr. Afaq Majid Wani
Department of Forest Biology & Tree Improvement
College of Forestry
Sam Higginbottom University of Agriculture, Technology and Sciences
Prayagraj-211007, U.P.

2. CONTENTS
1 • Introduction
2 • Remote Sensing
3 • Types of RS
4 • Applications of RS
5 • Geographic Information Systems
6 • Applications of GIS
7 • Conclusion
8 • Reference

3. INTRODUCTION
 To meet the various information requirements in forest
management, different data sources like field survey,
aerial photography and satellite imagery is used,
depending on the level of detail required and the
extension of the area under study.
 Nowadays several types of remote sensing data,
including aerial photography, multi-spectral scanner
(MSS), Radar(Radio Detection and Ranging), Lidar (Light
Detection and Ranging), Laser and videography data
have been used by forest agencies to detect, identify,
classify, evaluate and measure various forests.

4.  For large areas, satellite imagery has been shown
effective for forest classification, and consequently
mapping. As RS and GIS technologies are widely used,
forest resource investigation method is improved
highly.
Fig. 1: Visualization of the remote sensing simulation model [LiDAR].
(source: https://www.ufz.de/index.php?en=36383)

5. REMOTE SENSING
 The art and science of obtaining
information about an object without
physically contact between the object and
sensor.
 “Remote sensing is the science of acquiring
information about the Earth's surface
without actually being in contact with it.
This is done by sensing and recording
reflected or emitted energy and processing,
analyzing, and applying that information".
(Source: CCRS Tutorial “Fundamentals of
remote sensing”)

6. TYPES OF REMOTE SENSING
1. Active remote sensing
Active remote sensing
instruments operate with
their personal source of
emission or light, while
passive ones rely on the
reflected one. Radiation also
differs by wavelengths that fall
into short (visible) and long
(microwave).
Active
Remote
Sensing
Lidar
Radar
Laser
altime
ter
Sound
er
Scattero
meter
Fig. 2: Active Remote Sensing Instruments

7. TYPES OF REMOTE SENSING (CONTINUED)
2. Passive Remote Sensing
Passive sensors in remote sensing
do not streamline energy of their
own to the researched object or
surface, unlike active ones. Passive
remote sensing depends on natural
energy (sunrays) bounced by the
target. Passive remote sensing
employs multispectral or
hyperspectral sensors that measure
the acquired quantity with multiple
band combinations.
Passive
Remote
Sensing
Spectro
meter
Radiom
eter
Sounder
Acceler
ometer
Imaging
Radiom
eter
Hyperspe
ctral
Radiomet
er
Fig. 3: Passive Remote Sensing Instruments

8. REMOTE SENSING PROCESS COMPONENTS
 Energy Source or Illumination (A)
 Radiation and the Atmosphere (B)
 Interaction with the Target (C)
 Recording of Energy by the Sensor
(D)
 Transmission, Reception, and Pro
cessing (E)
 Interpretation and Analysis (F)
 Application (G) Fig. 4: The Remote Sensing System
(Source: www.nrcan.gc.ca)

9. RESOLUTIONS OF REMOTE SENSING
 Resolution plays a role in how data from a sensor can be
used. Depending on the satellite’s orbit and sensor
design, resolution can vary. There are four types of
resolution to consider for any dataset. They are-
1)Radiometric, 2) Spatial, 3) Spectral, 4) Temporal.
(Source:
https://earthdata.nasa.gov/)

10. SPECIFICATIONS OF REMOTE SENSING SATELLITES
AND SENSORS (Source: DJ Peterson, Susan Resetar, Jennifer Brower, Ronald
Diver, “Forest Monitoring and Remote Sensing”, 37)
Platform Principal
Owner
Initial
Service
Date
Sensor
Type
Spectral
Bands
Spatial
Resolution
(meters)
Swath
Width
(km)
ERS 1, 2 EU 1991 SAR 30 100
IRS 1C India 1995 MS
Pan
4 23
6
142
70
SPOT 1-4 France 1986 MS
Pan
3 20
10
60
Radarsat
1, 2
Canada 1995 SAR 10-100 50-100
NOAA
POES 6-12,
14
USA 1979 MS 4/5 1100 2399
Landsat 4,
5
USA 1982 MS 7 30 185

11. REMOTE SENSING APPLICATIONS IN FOREST
MANAGEMENT
1. Land cover analysis
Fig. 5: Land cover analysis (Source: https://openforests.com/project-all/,
2016)

12. 2. Land-use change detection
Fig. 6: Forest degradation detection based on historical and recent satellite imagery
classification. (Source: https://openforests.com/project-all/, 2016)

13. 3. Distribution of timber resources
4. Tree detection for automated forest
inventories
Fig. 7: Single tree detection based on the Digital Terrain and Surface Model. The circle center show
the spatial position and the circle diameter the relative height of the respective tree. Green circles
indicate successful tree reconstructions and measurements.

14. 5. Analyses of slope steepness
Fig. 8: The violet scale show the slope degree of the terrain in percentage.
(Source: https://openforests.com/project-all/, 2016)

15. 6. High-resolution orthophoto maps for visual
interpretation
Fig. 9: High-resolution drone image taken of a reforestation site before and one year
after reforestation in Central Kalimantan (Source: https://openforests.com/project-all/,
2016)

16. 7. Detection of human-caused disturbances like
encroachment and illegal logging
8. Wildlife observation
9. Monitoring of the logging impact
10. Pest and disease spread
11. Fire threat and fire detection
12. Determination of areas with plant stress
13. Stratification of productivity zones
14. Timber harvesting planning
15. Forest roads planning
APPLICATIONS (CONTINUED)

17. BENEFITS & DRAWBACKS OF REMOTE SENSING
 Benefits:
 Real time data.
 Large Area coverage.
 Different purposes and applications.
 Drawbacks:
 Expensive to build and operate!
 Data interpretation can be difficult
 Need to understand theoretically how the instrument is
making the measurements

18. GIS
(Geographic Information System)

19. GEOGRAPHIC INFORMATION SYSTEMS (GIS)
 GIS are computer-based systems that are used to store
and manipulate geographic information (Aronoff, 1989).
 GIS incorporates various types of data. It uses maps and
3D scenes to examine spatial position and organise
layers of data into visualisations. GIS reveals deeper
insights into data, such as patterns and situations.
(Source : http://www.in.gov)

20. GIS APPLICATIONS IN FOREST MANAGEMENT
 GIS for strategic planning and modelling
 Map production
 Fire management
 Forest road & Harvest scheduling
 Forest resource inventory
 Forest ecosystem management
 Wildlife habitat management
 Forest health monitoring
 Wetlands & watershed management

21. BENEFITS & DRAWBACKS OF GIS
 Benefits:
 GIS allows analysis of data to explicitly incorporate
location.
 GIS provides very accurate data.
 It provides better predictions and analysis.
 Drawbacks:
 GIS technology might be considered as expensive software.
 There might be failures in initiating additional effort in
order to fully implement the GIS.
 Integration with traditional map is difficult.

22. CONCLUSION
 Forests are a dynamic resource, affected by many
coexisting ecological processes and direct management
interventions. Stronger tools are necessary for the
analytical resolution of conflicting suitability’s and
choices in resource allocation.
 Advances in remote sensing will enable quicker and
more focused emergency response, more accurate map
products, improved navigation, and better geospatial
information and derived products for the general public
and professionals in a wide variety of fields. As RS and
GIS technologies are widely used, forest resource
investigation method is improved highly.

23. REFERENCE
 Anon (2015) Applications of GIS. Administration and finance.
Mass GIS.
 Campbell, J.B., 2006. Introduction to remote sensing. Fourth
Edition, Guilford Publication, New York, 608 pp.
 DJ Peterson, Susan Resetar, Jennifer Brower, Ronald Diver, (July
1999). Forest Monitoring and Remote Sensing.
 Franklin, S. E. (2001). Remote Sensing for Sustainable Forest
Management.
 FAO (1990) Remote sensing application to Land Resources.
14th UN/FAO Int. Trg, Course material.
 Kai Wang, Wei-Ning Xiang, Xulin Guo and Jianjun Liu (2012).
Remote Sensing of Forestry Studies, Global Perspectives on
Sustainable Forest Management, Dr. Dr. Clement A. Okia (Ed.),
ISBN: 978-953-51-0569-5, InTech, Available from:
http://www.intechopen.com/books/global-perspectives-on-
sustainable-forestmanagement/remote-sensing-in-forestry-
studies

24. THANK YOU