The Crystal Globe : A GIS-Based Operational Area Production Model

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The Crystal Globe : A GIS-Based Operational Area Production Model

Results and Discussiohs
The results of this research is a computer ILWIS batch file which includes all steps of the spatial APM. This model is based on the numerical model which was described earlier. This model was developed in GIS-ILWIS. In spite of the fact that the model is not difficult to use (e.g. it is fully automated), it is recommendable to get firstly knowledge of the assumptions of the model and how it is working.

Assumptiona
Every model will be an approach of the reality. It cannot take into account every variable factor of life which does influence the process of the model e.g. forest degradation. Therefore, it is important to know the assumptions of a model. In this model the following assumptions were made:

The most important assumption is that in this model the forest classes do not degrade after each other as in numerical APM. It is assumed that the forest classes can be degraded at the same time. Every pixel gets a value depending on: slope, distance from agricultural/village land, priority for forest classes of the rural people, population density and population growth. None of these is extra weighted nor does have a primary key. These factors were chosen their data were available in raster maps.
It is assumed that each of these factors has the following influence: The steeper the slope the slower the forest degradation and the higher the friction value; The greater the distance the slower the forest degradation and the higher the friction value; The higher the priority value the slower the forest degradation and the higher the friction value. Note that the highest priority means the lowest priority value, the higher the population growth the faster the forest degradation and the higher the starter value. The higher the population density the faster the forest degradation and the higher the starter value.
It is not clear whether it has to be assumed or not that it is possible for plantation forest to degrade into scrub. It was argued that plantation forest could in practice only be thinned or harvested. While this is still not clear, it has been made possible for the user to decide whether he/she want to have the plantation forest as degradable forest or not. If it is decided that the plantations are not degradable, it means that the user has to make an absolute barrier of these land use classes which could easily be done by giving the plantations a negative value in the priority table.
In the first instance, preference was set on using the real values of the input factors: slope, distance, priority, population growth and population pressure. This would guarantee a proper relation among the values within an input factor. But taken into account all these, two arguments plead for reclassification of the values of every input factor between 1 and 10. First of all, using the real values of an input factor give a weighting among the input factors. For example, using the real values would give a high weighting to the map slope distance (values 1-18825) and a low weighting to the population growth (values 1-5) .The second reason is that the real values of the input factors would, if you want to calculate the distances, result in values which exceed the maximum pixel value or the capacity of the computer.
Theoretically, forest degradation seems to start at the fringes of the scrub land. It is not clear whether the model is taking into account this theory. Therefore, it has been made possible for the user to chose whether forest degradation must start from the agricultural land or the existing scrub land or from both.
The process of forest degradation is simulated by creating a time-of-change-map. Firstly, this is done by calculating distances in a friction map in which each pixel has a weighting factor. This weighting factor includes the values of the DISTANCE, the SLOPE and the PRIORITY for change. This gives a direction to the forest degradation. Secondly, computing this map with the output of "population density (e.g. pressure) * population growth, creates the time-of-change-map.
It is assumed that the area of forest which will be degraded into scrub can be calculated in two steps. First, the future agricultural land is calculated with the help of the following formula:

N_a=B_a*(p/100)ⁿ
where:
N_a = Total agricultural area in the future year (ha),
B_a = Total begin agricultural area (ha)
p = Population growth (%), n = future years (years)
Second, the degraded area is calculated with the helpof the following formula:

N_a = X1 * (N_a)^1/2 -X2 * N_a -C
where:
N_a = Total scrub area in the future year (ha)
N_a = Total agricultural area in the -future (ha)
X1, X2, C = The coefficient of X1, X2, and the constant of the regression model between APM-predicted agricultural land and the real developed scrub land.

How is the new mode1 working in ILWIS-GXS
The new spatial APM working according to the following steps:

STEP 1. The model uses four input maps: General, Slope distance, Forest and Villages; and three tables: Priority, Population, and Year; Two batch files: Program.bat and Program1.bat; Twelve text files: FORMO.txt up to FORM9.txt, The DOS command file: ASK. corn.

STEP 2. Start ILWIS, then exit to Dos, change the directory to where the files of step 1 are loaded. The model will start by typing PROGRAM and then [ENTER]

STEP 3. The Model comes up with the tables population and Priority which can be altered by the user.

The table population contains information about the number of people, the surface of agricultural land and the population growth for each village. In FORMO.txt the user (s) alternations, the pressure on land, the Vilfact (e.g. village population) for each village and the maximum Vilfact are automatically stored and/or calculated in table POPNEW.

The table Priority contains information about the people's priority for transfer of a forest class. In FORM1.txt the user's alternations and the maximum priority are automatically stored and/or calculated. It must be noticed that a forest class with a negative value for its priority will be considered as an absolute barrier and will therefore not degrade into scrub.

STEP 4. In ILWIS-MCalc Form2.txt the map STARTER is realized. Each village owns apart of the agricultural land. This village land is given an integer value between 1 and 10 based on the Vilfact values of table population. With the help of the Distances Module in ILWIS a Thiessen map Thies is created. In Thies, this Vilfact value of each village land is extrapolated into the non-agricultural land use classes.

STEP 5. The user have to chose whether the process of forest degradation will start from the agricultural land or the scrub land or from both the agricultural and scrub land using the files FORM4_1.txt, FORM4_2.txt and FORM4_3.txt

STEP 6. In ILWIS-MCalc Form4 x.txt the map FRICTION is realized. Each pixel of a non-agricultural land use class has an integer value between 1 and 10. This value is based on the slope, distance from the village land and the priority. With the help of the ILWIS Distances Module the time of change into scrub land has been made visible in the friction map. The time of change depends on the roughness (e.g. friction value) of the area.

STEP 7 .In MAPOUT the time of change into scrub land has been weighted by the "Vilfact of each village. ;

STEP 8. The Histogram (Mapo) of the pixel values is derived from mapout in Histogram Form6 .txt .

STEP 9. The program comes up with table Year. The user has the possibility to change the begin area of agriculture, the percentage population growth and the future year for prediction. Based on these three values the total area of agricultural land for the future year is calculated (in Tabcalc Form7.txt), then transformed into a total needed area of scrub land and finally printed in table New year.

STEP 10. In ILWIS Tabcalc, the file Form8.txt, the total area of scrub land in the future year is translated into total needed pixels. If the cumulative number of pixels of table MAPO is lower than these needed pixels, then it will get a value of 23, otherwise it will get a value of 0. The result is printed in column (value) of table MAPON. The pixel groups with the value 23 will change into scrub land in the future. The other groups will not yet change.

STEP 11. Finally Map4 is constructed as follows: First, the pixels outside the area, the lake, the existed scrub land and the agricultural land use class will get the same value as the map Forest. Second, the pixel groups of table MAPO which has a value of 23 must be adjusted. These are the new developed scrub lands and will get a value of 23. Finally the rest pixels will also get the value of the map Forest.

References

De Gier A. and Hussin Y.A., (1993) Spatially Resolved Area Production Model in Kali Konto, Indonesia, GIS/LIS '93, Annual Conference and exposition, 31 Oct. -4 Nov., 1993, Minn, USA, Vol 1. 157-169 pp.
Hussin Y.A., A. de Gier and Hargyono (1994) Forest Cover Change Detection Analysis Using Remote Sensing: A test for the Spatially Resolved Area Production Model, Fifth European Conference and Exhibition on Geographic Information System, EGIS/MARI '94 Proceedings, Paris, France/Maroh, 29-April 1, 1994, Vol 111825-1834 pp.
FAO, (1986) Manual for using the area production model (APM), Case Studies, Asia-Pacific Region. GCP/RAS/106/JPN. Field Document 12:2, May, 1986. 99 pp.
FAO, (1986) Users guide to area production model (APM), Asia-Pacific Region. GCP/RAS/106/JPN. Field Document 12:1, May, 1986. 65 pp.
Hargyono, (1993) Occurrence and prediction of forest degradation, a case study of Upper Konto Watershed East Java Indonesia ,lTC, Enschede.
Palo M., M. KANNINEN, G.MERY and A. SELBY. 1986. Forest-based socio-economic development and deforestation in developing countries: A feasibility study for a major research project. Proceedings of IUFRO World Congress, Ljubljana, Yugoslavia.
World Bank, 1991, A world Bank Policy Paper, The Forest Sector, The World Bank, Washington DC.
Williams, D. H., (1987) LOTUS APM, version 1: A spreadsheet version of the area production model 1. Asian seminar on forest planning, Kuantaun, Malaysia. November 5-7, 1987. 12 pp.

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