Vegetation mapping using global, vegetation index and weather data

Vegetation mapping using global, vegetation index and weather data

Yoshiaki Honda and Shunji murai
Institute of Industrial Science
University of Tokyo
7-22 Roppingi, Minato-Ku,
Tokyo 106 Japan

Abstract
Though Koppen's climatological map is widely known all over the world, a new climatological and ecological zoning system should be developed in order to monitor the global change of vegetation. A generation of a vegetation map based on Global Vegetation Index and weather data is presented in this paper. The typical patterns of monthly vegetation activity are analyzed from Global Vegetation Index and weather data, and various vegetation types with similar climatological and ecological characteristics are classified.

Introduction
Nowadays, the global change of the climate is one of the most important problems for the human society, and this change can be detected from the condition of the Earth's vegetation. Global Vegetation Index (GVI) indicates the weekly condition of the Earth's vegetation. GVI, which is produced from NOAA's (United States National Oceanic and Atmospheric Administration) AVHRR sensor (Advanced very High Resolution Radiometer), is used as a tool to study the continental patterns and global-scale patterns of the Earth's vegetation. The monthly change characteristic of the vegetation can be classified by dividing GVI into 5 typical vegetation patterns. A new vegetation map based on these vegetation patterns has been made.

Data and Methodology

Data
The data which has been used in this study consists of :

Monthly maximum value of GVI from January 1983 to December 1987. The original GVI data which indicates the weekly density and vigor of the green vegetation is the resampling data of the Normalized Vegetation Index (NVI) for the whole earth (except parts more than 75 degrees North latitude and 55 degrees South latitude). The NVI is determined by the following equation:

NVI= (Ch2- Ch1)/Ch2+Ch1)
Where Ch1 and Ch2 are the data from channel 1 (visible red band) and 2 (near infrared band) of the AVHRR. The spectral response of the five AVHRR channels is as follows:

Channel 1	0.58 to 0.68 micrometer
Channel 2	0.725 to 1.10 micrometer
Channel 3	3.55 to 3.93 micrometer
Channel 4	10.30 to 11.30 micrometer
Channel 5	11.50 to 12.50 micrometer

Monthly average values of temperature, rainfall and moisture from January 1983 to December 1987, provided by the Japanese Meteorological Agency, detected at 2344 observation stations all over the world.

Methodology
In climatology, the classification methods of the climate are as follows:
1. The method based on the climate factor
2. The method based on the characteristic of the climatological Index.
3. The method based on the vegetation
4. The method based on natural phenomena (except for the vegetation).
In this paper, the method based on the vegetation is used. Afore- Mentioned Koppen also used this method when he made his famous climatological map. In general, the 3rd method (the method based on the vegetation) to classify the types of vegetation is separated into:
1. A method based on 6the elements of the vegetation
2. A method based on the life forms of the main vegetation.
In case of the study of global -scale patterns of the vegetation, the second one is widely used and so also in this paper.

As the climate changes, the formation of vegetation also changes (i.e. forest è grassland èdesert). However, there is a difference in the pflanzenformation between group 1 and group 2 (Table 1). In this paper, grouping of the vegetation formation has been made in order to avoid the difference between group 1 and group 2. The formation of the vegetation has been classified into tropical rain forest, forest, grassland and desert.

Table 1 The difference of pflanzenformation

Figure 1. Flow chart
The outline of the method is (Fig. 1):

Ist Step:
Necessary NVI values at 2344 weather observation points (world weather information), are being picked out from the GVI data for a 5 year period (1983-1987). The NVI values can then be compared with the weather data for the same points.

2nd Step
The stabilities of the monthly vegetation changes are computed by using equation 1 below at each observation point.

Eq.1
S M V C : The stability of the monthly vegetation change
N V I : Average NVI for 5 years (1983~1987)
NVI_ym : Maximum NVI (Year:y, Month:m)

The first 30 % of the smallest computed data are being picked out. From this group of data, the monthly vegetation changes at 120 observation points (5 % of the total number of points) are taken randomly.

3rd Step :
The grouping is made by using the data from the second step. The grouping criteria depends on the maximum of the NVI data and the total number of months at each NVI level at each observation point. The result of this step is shown in Table 2. The figures inside Table 2 are the numbers of observation points which falls within that criteria change for example, at Benjamin Constant observation point in Brazil shown on the left side of Fig. 2-1, the maximum NVI are within the change of 0.3 0.3. Therefore this observation point is classified to be one of the 13 observation points in this group.

4th step :
Using table 2 and the weather data fro the classification. the points are classified into tropical rain forest. forest. grassland or insert 4 typical patterns of monthly vegetation change can finally be distinguished.

Results

4 typical patterns of monthly vegetation change
in Table 2, the more right in the table, the more dense the forest becomes. The lower in the table, the longer the period of vegetation becomes.

Table 2

N V I ranging	MAXIMUM NVI
N V I ranging	~0.1	0.1~0.2	0.2~0.3	0.3~0.4	0.4~
~0.1	37	20	11	1	1
0.1~0.2	0	11	8	5	2
0.2~0.3	0	0	5	13	1
0.3~0.4	0	0	0	4	1
0.4~	0	0	0	0	1

4 typical patterns of monthly vegetation change are shown in Figure 2. The vertical and horizontal axes in Figure 2 indicate the NVI and the months respectively.

The NVI curves in Figure 201 show the characteristics of tropical rain forest. The curves are almost constant at about NVI 0.3, so it is easy to classify them to be Af (tropical rain forest) in Koppen's climatologically map., The NVI curves in Figure 2-2 show the characteristics of dense forest consisting of evergreen leaved forest , deciduous leaved forest and otheras leaved forest and others. These NVI curves have only one peak of NVI per year. the NVI curves in Figure 2-3 show various patterns. These observation points are grassland in Koppen's climatologically map. The NIV curves in FIgures2-4 show the characteristics of desert. There is almost no vegetation and the curves show almost constant low NVI. They are BW (desert) in Koppen's climatologically map.

A new vegetation map
Figure 3 is generated based on the 4 typical monthly vegetation change patterns. Zone No. 1 is tropical rain forest, zone No. 2 is forest, zone No.3 is grassland, zone No. 4 is nearly desert and zone No. 5 desert. The border between grassland and desert runs parallel with the latitude.

Figure 2-1 Tropical rain forest

Figure 2-2 Forest

Figure 2-3 Grassland

Figure 2-4 Desert

( Figure 2 )

Conclusion
The results of this study leads to the conclusions:

It is easy to distinguish desert from other kinds of vegetation area.
It is easy to distinguish tropical rain forest from other kind of vegetation areas.
It is difficult of classify grassland into steppe, savanna prairie etc.

The further research will pay attention to the classification grassland into more categories.

Figure 3 A new vegetation map (1983)

References

Kuniji Yoshioka, Vegetation geography, Kyoritu publishing company 1973.
Masatoshi Yoshino. Climatology, Taimei-do, 1978
Noriyuki Nasu, Atmoshphere and Ocean, Japan broadcast publishing association, 1986.
Hideo Iwaki, Introduction of ecology, Japan broadcast publishing association , 1986.