identification of land-use and land-cover changes in east-asia masayuki tamura, jin chen, hiroya...
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Identification of land-use and land-cover changes in East-Asia
Masayuki Tamura, Jin Chen,
Hiroya Yamano, and Hiroto Shimazaki
National Institute for Environmental Studies
Objectives
To develop a robust and reliable algorithm for detecting land use/cover changes using coarse spatial resolution data (MODIS, NOAA/AVHRR, SPOT/VEGETATION).
To analyze land use/cover changes in China during 1982-1999 using the Pathfinder 8km NDVI and climate data.
1) Satellite data: Pathfinder 8km NDVI data Spatial resolution: 8 x 8 km Temporal resolution: 10-day. 20 years of data (198
1-2000). Preprocessing
2) Climate data: China National Meteorological Bureau. 620 meteorological stations 10-day mean temperatures and precipitations
from 1980-1999. Preprocessing
1) Satellite data: Pathfinder 8km NDVI data Spatial resolution: 8 x 8 km Temporal resolution: 10-day. 20 years of data (198
1-2000). Preprocessing
2) Climate data: China National Meteorological Bureau. 620 meteorological stations 10-day mean temperatures and precipitations
from 1980-1999. Preprocessing
Data Sources
NDVI Data PreprocessingNDVI Data Preprocessing
NDVINDVI
Noises caused by cloud
BISE(Best Index Slope Extraction)BISE(Best Index Slope Extraction)
Kriging InterpolationKriging Interpolation
Climate Data InterpolationClimate Data Interpolation
Meteorological StationsMeteorological Stations
TemperatureTemperature
PrecipitationPrecipitation
NDVI profile differences are used to detect land cover changes between two years.
Normalization and correction of NDVI data Calibration of sensor degradation. Atmospheric correction Normalization of climate conditions (T, P)
NDVI profile differences are used to detect land cover changes between two years.
Normalization and correction of NDVI data Calibration of sensor degradation. Atmospheric correction Normalization of climate conditions (T, P)
MethodMethod
otherwTo NDVINDVI * An observed NDVI (NDVIo) for a pixel can be expressed as: An observed NDVI (NDVIo) for a pixel can be expressed as:
where NDVI * is a potential NDVI in an optimum climate condition. ɛT, and ɛW account for the effects of te
mperature and precipitation differences from the optimum conditions respectively. ɛother accounts for the
effects of sensor degradation and atmospheric condition changes.
Land cover change detection should be performed by comparing NDVI* differences between two years rather than NDVIo directly.
where NDVI * is a potential NDVI in an optimum climate condition. ɛT, and ɛW account for the effects of te
mperature and precipitation differences from the optimum conditions respectively. ɛother accounts for the
effects of sensor degradation and atmospheric condition changes.
Land cover change detection should be performed by comparing NDVI* differences between two years rather than NDVIo directly.
Normalization for Climate ConditionsNormalization for Climate Conditions
otherwToNDVINDVI
111*
ɛother can be moved off through pre-processing of original NDVI data, which includes sensor calibrat
ion, atmospheric correction and cloud filter. ɛT, ɛW can be estimated according to the relationship be
tween vegetation growth and seasonal climate condition.
ɛother can be moved off through pre-processing of original NDVI data, which includes sensor calibrat
ion, atmospheric correction and cloud filter. ɛT, ɛW can be estimated according to the relationship be
tween vegetation growth and seasonal climate condition.
ɛT Estimation ɛT Estimation
ɛT reflects the concept that plant growth is depressed when
plant is growing at a temperature displaced from its optimum temperature.
ɛT reflects the concept that plant growth is depressed when
plant is growing at a temperature displaced from its optimum temperature.
According to existing study (Potter, 1993; Hamlyn G. Jones, 1992) , ɛT has an asymmetric bell shape that falls off mo
re quickly at high than at low temperature.
According to existing study (Potter, 1993; Hamlyn G. Jones, 1992) , ɛT has an asymmetric bell shape that falls off mo
re quickly at high than at low temperature.
-0.2
0
0.2
0.4
0.6
0.8
1
0 5 10 15 20 25 30 35 40
Temperature
Epi
son
T
ToptTopt
4
422
)(
)()()(2
BT
BTBTBT
opt
optT
(Hamlyn G. Jones, 1992)(Hamlyn G. Jones, 1992)
Topt is optimum temperature, defined as the
air temperature when the NDVI reaches its maximum for a long period.
Topt is optimum temperature, defined as the
air temperature when the NDVI reaches its maximum for a long period.
ɛw Estimation ɛw Estimation
ɛw describes the effect of water stress to plant growth. By consi
dering the lag effect of precipitation, it is calculated by
When Sum (PPT) < Sum (PET)
When Sum (PPT) > Sum (PET)
where PET is potential evapotranspiration and determined by Thornthwaite method, PPT is precipitation for calculating period.
ɛw describes the effect of water stress to plant growth. By consi
dering the lag effect of precipitation, it is calculated by
When Sum (PPT) < Sum (PET)
When Sum (PPT) > Sum (PET)
where PET is potential evapotranspiration and determined by Thornthwaite method, PPT is precipitation for calculating period.
22
/5.04.0j
jmm
j
jmmw PETPPT
0
0.2
0.4
0.6
0.8
1
0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2E
piso
n W
1w
12 3
NDVI dataset in 1983NDVI dataset in 1983
Change Vector Calculation
Change Vector Calculation
NDVI(n)NDVI(2)•••
NDVI(1)
NDVI(n)NDVI(n)NDVI(n)NDVI(2)•••NDVI(2)•••NDVI(2)••••••••
NDVI(1)NDVI(1)
NDVI(n)NDVI(2)•••
NDVI(1)
NDVI(n)NDVI(n)NDVI(n)NDVI(2)•••NDVI(2)•••NDVI(2)••••••••
NDVI(1)NDVI(1)
NDVI(n)NDVI(2)•••
NDVI(1)
NDVI(n)NDVI(n)NDVI(n)NDVI(2)•••NDVI(2)•••NDVI(2)••••••••
NDVI(1)NDVI(1)
NDVI dataset in 1984NDVI dataset in 1984
NDVI dataset in 1999NDVI dataset in 1999
………… Threshold Applying
Threshold Applying
Time Series Filtering
Time Series Filtering
Change PixelsChange Pixels
Change Pixel Detection FlowChange Pixel Detection Flow
Base Dataset
Change pixels during 1984-1988
Change pixels during 1989-1993
Change pixels during 1994-1997
Chang Pixels in Different PeriodsChang Pixels in Different Periods
NDVI Decreasing Trend
NDVI Increasing Trend
Change Pixel Distributions with Different TrendsChange Pixel Distributions with Different Trends
Special Modification by Forest Fire
No Trend
Grassland MonitoringGrassland Monitoring
Xilinhot
Haibei
Wetland MonitoringHabitats of Red-Crowned Cranes and Oriental White Storks
Circles show the sites where birds stayed more than 10 days.
Thank you!