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Remote sensing and GIS have become essential tools for economic development and environmental protection and planning in Mongolia
-The area covered by sand has increased by 40000 hectare (8.7%) during last 40 years. According to research estimates, 25% of the total pastures are threatened by land degradation. Due to overgrazing, the diversity of plant species in areas near towns has fallen by 80%.
In the most degraded local area, there is a larger number of goats than other local areas and this causes overgrazing. Due to increasing mining activities, there is an increased population number caused by people migrating from the other parts of the country. The climate factors precipitation and air temperature do not have a strong affect on the land degradation.
Mongolia has long suffered from poor mining legislation and almost no regulation of its production . There is a need to undertake analyses of land degradation and land use in Mongolia as an important factor of Environment . This study aim to determine for land use change detection using remote sensing methodology in Uvurkhangai aimag, Mongolia.
Supervised classification typically uses something called training sets or areas Training areas Specified by the analyst to represent the land cover categories of interest Used to compile a numerical “interpretation key” that describes the spectral attributes of the areas of interest Each pixel in the scene is compared to the training sets, and then assigned to one of the categories
The finally we determine change detection on this mining site using change vector analyzing technique on the atmospheric corrected image. Radiometric Correction: removal of sensor or atmospheric &apos;noise&apos;, to more accurately represent ground conditions: to correct data loss, remove haze, enable mosaicking and comparison 2.We analyzing vegetation change in the river basin in last years 1998,2007. Goal is we want to know that how to decrease the vegetation cover when start activity for mining sites. 3. With regard to monitoring land degradation with remote sensing, we applied supervised classification .
Radiometric corrections play a fundamental role in unsupervised change detection based on CVA for increasing the reparability between the classes of changed and unchanged pixels. The results of the COST process minimize the effect of the atmospheric on the study area.
In this study, change vector analysis methodology was applied to Landsat TM and ETM images acquired in 2002 and 2007, respectively and use automatic technique /Matlab algorithm/ . Mining is done legally by companies that have large concessions, but also illegally by so called &quot;Ninjas“ individuals and families that literally dig for gold without a license. Hand level mining contributes to land degradation, Increased small to large-scale mining, as well as illicit activity resulting in exploitation of the country’s mineral resources.
During Mongolia’s transition to a free market, socio-economic factors such as poverty and profit-seeking have greatly increased small and large scale mining activities resulting in exploitation of the environment in Mongolia.
After mining activities, there is no land reclamation attention. Furthermore, all problems caused damage on environment and people’s lifestyle in Mongolia.
Ex2. domestic company’s area
Example1- Ninja’s area In this study, change vector analysis methodology was applied to Landsat TM and ETM images acquired in 2002 and 2007, respectively and use automatic technique /Matlab algorithm/ . And I also applied supervised classification method was applied to Landsat TM images acquired in 2002 and 2007, on the mining site, respectively and use maximum likelihood methodology. We can find the next specific answers from this results : 1. which kind of land cover is more changed? 2. Mining activity how to induced to the ecology.
Huete (1998) suggested a new vegetation index, which was designed to minimize the effect of the soil background, which he called the soil-adjusted vegetation index (SAVI) developed of an iterated version of this vegetation, whi2ch is called MSAVI
I am showing to you about human induced cause for example mining situation. There are a limited research works in Mongolia. Main human cause of land degradation is mining activities.
This study contributes to the research which involves policy makers and stakeholders to define and negotiate relevant scenarios in participatory approaches in the local area and to the studies about linking people to pixels. Concluding that this number will be keeping to increase in the future. This study should be focused change detection analyzing using Matlab function, it’s a new method for Mongolia.
Land cover changes studies
Tungalag A, Tolmon R
NUM-ITC-UNESCO Space Science/Remote Sensing
International Laboratory, National University of Mongolia
8 October 2014, Ulaanbaatar, Mongolia
Remote Sensing/GIS in Mongolia
Mongolia has a big territory,
remote sensing offers a unique
access to primary data about
the research of land surfaces.
•Accessible unreachable places
•Natural Disaster vulnerable
Desertification in Mongolia
-To apply change detection technique and
supervised classification using radiometric and
geometric corrected data for Landsat Image from
years 2002 and 2007.
-To determine mining activity is dangerous
impacted for land degradation.
1. Ground truth
-529 sample points from
high Google Earth
-Climate and Statistic data
- Maximum Likelhood
Discussion and future
Change Vector Analysis
The flow chart of the monitoring
Digital Image processing of satellite images can be divided into:
Enhancement and Transformations
Classification and Feature extraction
Preprocessing consists of:
Geometric correction: conversion of data to ground coordinates by removal of
distortions from sensor geometry
Radiometric Correction: removal of sensor or atmospheric 'noise', to more
accurately represent ground conditions:
to correct data loss, remove haze, enable mosaicking and comparison
Radiometric correction is used to modify DN values to account for
noise, i.e. contributions to the DN that are a result of…
a. the intervening atmosphere
b. the sun-sensor geometry
c. the sensor itself
We may need to correct for the following reasons:
a. Variations within an image (speckle or striping)
b. between adjacent or overlapping images (for mosaicking)
c. between bands (for some multispectral techniques)
d. between image dates (temporal data) and sensors
Supervised classification – a procedure where the analyst
guides or supervises the classification process by specifying
numerical descriptors of the land cover types of interest
Unsupervised classification – the computer is allowed to
aggregate groups of pixels into like clusters based upon
different classification algorithms
Multiband Classification Approaches
Minimum distance classifiers
Maximum likelihood classifiers
Maximum likelihood classifiers
Based on a probability function derived from a
statistical distribution of reflectance values
COST atmospheric correction.
-The inputs to the model are the Earth-Sun Distance, sun
elevation angle, and minimum DN values for each band.
The model first converts each minimum DN value to an
at-satellite minimum spectral radiance value:
Lsat = bias + gain * DN (2)
(Landsat 7 Science Data Users Handbook)
Reflectance conversion + atmospheric correction
Lhaze: upwelling spectral radiance (path radiance), value derived from
image using dark-object criteria; Calculated by using the dark object criteria
(lowest value at the base of the slope of the histogram from either the blue
or green band)
TAUv: atmospheric transmittance along the path from ground to sensor,
assumed to be 1 because of nadir look angle
Eo: solar spectral irradiance
TZ: solar zenith angle, ThetaZ
TAUz: atmospheric transmittance along the path from the sun to the ground
Edown: downwelling spectral irradiance at the atmosphere
Chavez, P.S. Jr (1996). Image-based atmospheric corrections – revisited and improved.
Photogrammetric Engineering and Remote Sensing 62, 1025-1036.
Results of COST Radiometric correction
UNSUPERVISED change detection plays an important role in many
application domains related to the exploitation of multitemporal remote
sensing images. The availability of images acquired on the same geographical
area by satellite sensors at different times makes it possible to identify and
label possible changes that have occurred on the ground
Change vector analysis first computes a multispectral difference image (XD )
subtracting the spectral feature vectors associated with each corresponding
spatial position in the two considered images X1 and X2 . Let XD be the
multidimensional random variable representing the spectral change vectors in
the difference image obtained as follows :
XD = X2 − X1 
(Francesca Bovolo, and Lorenzo Bruzzone, University of Trento)
Supervised Classification (Maximum Likelihood)
In order to make land cover legends, we used the
baseline legends definitions from NELDA research.
The assessment for 7 aggregated land cover classes
included (APN report, 2010)
Contribution to Land Degradation
Land degradation has been identified as one the
priority concerns. Causes of land degradation can be
divided into two categories natural and human
Natural cause: - Climate changes
- Dust and sand storms
Human induced: - Mining
- Pasture Degradation
Discussion and Recommendation
This study contributes to the research which involves policy
makers and stakeholders to define and negotiate relevant
scenarios in participatory approaches in the local area and to
the studies about linking people to pixels.
This case study will enable our researchers to plan for the
future by making more educated decisions in issues
stemming from mining, land degradation, water pollution
and the potential health issues related to these
We will do discussion among participatory mining land
and local people on mining awareness and land degradation.
Also handouts for local environmentalists will be
IN ECONOMIC GROWTH:
THE CASE OF MONGOLIA
UNIVERSITÀ DEGLI STUDI DI TORINO
Oyunjargal Jaltsav, Tungalag A
The thesis of the work tested how environmental elements effect to current
Mongolian economic growth, which is growing economy becase of minig
The study extends the Solow model and the Ramsey-Cass-Koopmans model,
including environmental elementswhich are setallite data degraded land and
vegetation value that analyzed from Num-itc-Unesco space science and
remote: sensing international laboratory of National University of
Mongolia., between the 1995-2013.
A description of the methodology of the study conducted follows together
with thedata collected and econometric estimations and calibration with
The concluding chapter will show the effects of the environmental elements of
Source: http://www.mram.gov.mn/pdac/ (Mineral Resource Authority of Mongolia)
The three pillars or principles of sustainable development
Figure source: http://www.cei-bois.org/en/roadmap-2010/wood-in-sustainable-development
Investment for environment protect and