Spatial Modeling on Coastal Land Use/Land Cover Changes and its Impact on Farmers

Coastal areas are an attractive place to live and/or to perform community activities, therefore coastal areas are vulnerable to both natural and artificial damage and destruction. This study presents the problem of changes in land cover/land use in coastal areas caused by humans. Rapid environmental change due to population growth will require food, shelter and other infrastructure. The 2010-2015 population growth rate of 1.37% or the population grew 6.86% from 2010. Population growth and industrial development increased demand for housing, roads and industrial infrastructure that encouraged land conversion. Agricultural land is the most converted land. Land use in 2000, for paddy fields area was 120,371 ha (62.83%) and pond area was 4,484 ha (2.34%). In 2015 paddy fields were degraded to 98.462 ha (51.41%), and pond area to 20,839 ha (10.88%). Markov modeling had a correlation of 97.72% “r” square value, indicated this modeling could be done to predict land cover change until 2031. In an effort to optimize irrigation field potential and increase of farmer's income, minapadi system (combined farming/fish kept in the paddy fields) was done by previous monoculture farmers to diversification system agriculture. This pattern could increase the productivity of the land and also could increase the diversity of agricultural produce, increase farmer income, increase soil fertility, and also reduce pest disease in rice plants. The purpose of this study is to model spatial changes in land cover/coastal land use and its effect on rice production, fish paddy field production and fishpond production in coastal habitat.


Introduction
Population growth in Karawang regency averages 1.37% per year.This population condition is followed by an increase in settlement infrastructure such as transportation facilities, fresh water and others. Settlement infrastructure and population growth have become triggers for the land conversion in coastal areas for settlements and other economic activities. Changes in agricultural land use and fisheries, identification of flood areas and estimates of agricultural production can be analysed using a remote sensing techniqueas one of the geospatial-based alternative approaches.
Presidential Decree no. 53 year 1989 about the industrial area directed development of industrial estate in Kabupaten Karawang, and it became the starting point of agricultural land conversion to industry. The paddy fields in Karawang regency in 2000 was 120,371 ha (62.83% of the regency), while in 2015 the remaining paddy fieldswas 98,462 ha (51.39%), meaning that in the period of 2000-2015 there has been conversion of paddy fields by 21,909 ha. From various land uses, the most converted one was paddy fields, especially around urban and settlement development centers [1]. In general, the paddy fields were transformed into settlements, ponds, urban areas and industries. A rapid pace of development programs and population increases led to rapid conversion of the rice fields.
When the aquaculture intensification program has improved and resulted in increased production and net income of farmers, there was an increase in demand for ponds in productive areas, therefore the selling price and the price of ponds became high [2]. The impact of expansion of ponds tended to shift natural ecosystems such as mangrove forests and paddy fields. Aquaculture is a maintenance activity and enlargement of aquatic biota in pond waters within a certain time to get the harvest. Changes land function in the area of mangrove and paddy fields to be ponds conducted by the surrounding community is to meet the needs of fish farmer life [3].
Another program conducted in coastal areas is called minapadi system (combined farming where fishes are kept in the paddy fields). For this system pond is made around a paddy field with a width of one meter and a depth of 60 centimeters, thus reducing area of the paddy field by about 10% to 20%. Although paddy fields are reduced for fish ponds, overall income is more favorable [4]. To recognize wetland as an indication of flood hazard areas, the Topographic Wetness Index (TWI) method was used. TWI was processed using TerraSAR-X DTM data. Flood hazard maps covered with land cover thematic maps would provide information on flood hazard areas that could have an economic impact on farmers. The Markov method was used to calculate the projection of land use degradation up to 2031. The purpose of this research was to analyze land use/land cover changes in coastal area and its effects on coastal habitat and existence of flood hazard.

Materials and Methods
The study was conducted in Karawang Regency, located in between107º02' -107º40' East and 5º56' -6º34'South. Location of the study is shown in Figure 1. Karawang regency is located in coastal zone having lowland morphologyandan average air temperature of 27ºC. Variations of slope in the region were between 0% to 2%, 2% to 15% and a small part with slope above 40%. Elevation of the northern region was between 0 to 25m mean sea level (msl), while a small part of the southern region had an elevation of 26m to 1200m msl, and the region had an annual mean rainfall of 728mm [5].   The landcover data was obtained from image enhancement using TCT (Tasseled Cap Transformation). Flood hazard areas were identified using TerraSAR-X DTM data using TWI (Topgraphic Wetness Index) method. The TWI analysis described an area with flood hazard potential or an area with flood potential that could be assumed to have a high probability of flooding [7]. Projected future land cover changes were made using the predicted changes in the present approach through spatial modeling ( Figure 2). The prediction model used CA-Markov to predict future land use changes by simulating land cover changes [8]. Degradation of paddy fields resulted in a lower rice production, and expansion of ponds on the other hand increased fishery production. Losses due to crop failures could be calculated based on the area of crop failure of rice or fish multiplied by productivity.

Data Analysis
Coastal Cultivation. The development of coastal aquaculture has given importance to fishery sector. The extent of the pond has increased its distribution and this can be observed spatially. Cultivation activities open employment and provide income to farmers and their families. The pond has become an important economic resource in coastal areas. The generally extensive coastal areas are suitable for expansion of ponds. Based on the results of the study on the physics -chemistry of waters, there was a tendency of excessive organic waste that could disrupt the aquaculture activities. However, in general the condition of both freshwater and marine waters in the coastal region of North Karawang was not too bad and therefore could be utilized for coastal aquaculture activities [9].
The study area is highly potential for rice cultivation and is a national rice barn located in coastal area. This area is also potential for terrestrial fisheries in minapadi system (combined farming / fish are kept in the paddy fields). Minapadi method is done by making a pond around the paddy field and use water in the fields as a medium for thefish. One week after fertilization of rice crops, the pond was filled with water up to a height of 50 cm, then the seeds of the fish were spread with a density of 3-4 fish/m 2 . Fish seeds used were tilapia (Oreochromisniloticus) ofsize 3-5 cm. The fish was harvested when its size reached 5-8 cm (phase of enlargement) or when the duration of fish nourishingwas 60 days [10] (Ashuri 2011).
Projected Population. Based on population data in 2010-2015, the average population growth rate (r) during 5 years was 1.37%. Using the Arithmetic Linear formula [5] and [7] (BPS 2016 and Riadi et al, 2017), projected population growth in the following years could be calculated with the following formula: Tasseled Cap Transformation (TCT) is a mathematical formula to calculate the levels of brightness, greenness, and moisture (wetness) of digital numbers in each band (band 1 to band 5 and band 7) on Landsat imagery. The mathematical formulation of third components TCT [11,7] are expressed in the following three equations for Landsat 8.

Identification of Flood Area.
TerraSAR-X signals have sensitivity to wet areas, thus an increase in wetness of an area may indicate a flood hazard area [12]. Terra SAR-X DEM data were analyzed using topographic Wetness index (TWI) method [13].The Topographic Wetness Index is a wetness index determined from the previously calculated surface variables with the following equation: = Where α = Flow Accumulation and tan β are slopes. In general, the delineation result of boundary areas of flood hazard needed to be generalized by conducting selection, simplification, merging, and magnification. Selection was done for objects that need to be eliminated and/or combined, because they did not meet geometry specifications or did not fit into the classification of elements that can be displayed on the map scale. Selection was done by removing and / or aggregating segments of polygon at least 0.5mm x 0.5mm [14]. TCT maps, when overlayed with TWI maps, will show the distribution of flood hazard areas. An area was considered having high flood hazard when the flooding frequency occured each year, inundation height was over 70 cm and flood duration was more than 7 days.
Land use/Land cover Modeling. Geographical Information System technology provides a number of spatial analyzes that can be used to determine trends in land cover changes in a region [15]. Projected future land cover changes are made with the predicted changes in the present approach through spatial modeling. The prediction model uses CA-Markov, to predict land use changes in 2031. This software has the ability to simulate land cover changes with Markov chain procedures [8].

Result
Coastal Cultivation. Aquaculture is one of the coastal fisheries businesses, such as shrimp cultivated commodity (Penaeusmonodon or Litopenaeusvannamei) and milkfish (Chanoschanos), with average management of 10 ha per fish farmer. Revenue earned by farmers was sufficient to meet the needs of family members, farmers became prosperous because the income and profit of the pond production was quite high [16]. Increased fishery swamp production (Table 1) indicated that pond farming had a high economic value for fish farmers. Pond cultivation was conducted on an area of 18,273 ha [5]. Source: [5] During rainy season Minapadi system gets more than enough fresh water from the rain, while during dry season the availability of fresh water is limited, so there are differences in fish production for different seasons.
Generally, economic analysis result shows that break event point value for paddy production and production of fish in paddy field obtained B/C ratio of 1.4(comparison between profit and business costs), whichmeans that every 1 (IDR) issued will get revenue of 1.4 (IDR). The results showed that the population density was unequally distributed and concentrated in urban areas with a density of > 1500 persons/km 2 (Figure 4.), population growth would require settlements and land adjacent to urban areas were paddy fields. Population and urban growth as one of the driving forces of land used change.
Land Used/Land Cover Change. From topography map extract, it was found that the area of Karawang regency was 191,577 hectares with paddy field area of 120,371 ha (62.83%) in 2000 ( Figure 3). Landsat TM image analysis for topographic map updated obtained information on paddy field area of 98,462ha (51.41%) in 2015. (Figure 4), more details are presented in Table 2.   Watering or damp land conditions give a white / sunny look, the darker the indication of dry land. The land with vegetation follows the density of the trees (tight trees look lighter because the soil is moist, the open areas will display darker shades)( Figure 5). Table 2.shows the results of the analysis, which showed that there was a decrease in wetland area from 2000 to 2015.Existing wetland area was 98,462 hectares in 2015.

Land Use/Land Cover Modeling.
To predict changes in land use/land cover in the next few years was done by CA-Markov modeling. The result of spatial modeling of land cover changes in 2015 (Figure 6) was validated by linear regression to measure whether the Markov modeling results were correlated with existing land cover or not (Table 3). To improve the accuracy of the modeling added parameters of road elements and population density, road elements will affect the accessibility of the population which will ultimately form the distribution pattern of settlement and distribution of population density.   Markov land cover modeling correlation resulted in a "R" square value of 0.9772 or 97.72% (Figure 7), it statedthat Y significantly affected X for further modeling for land cover change up to 2031 ( Figure 8).The variables used in this prediction were settlement, built up area, open area and paddy field. Up to 2031 the remaining paddy fields area was predicted to be 45.81% (88,007 ha) ( Table 4).

Identification of Flood Hazard Areas.
The flood hazard area analysis was done by integrating the spatial modeling data of TWI with historical data of flood events. The historical data parameters of flooding in paddy fields consisted of the frequency of flood occurance, the average height of the puddle, and the average length of the inundation.In the overlay. The TWI map was overlaid on the TCT map, by giving the attributes of each parameter in accordance with its influence. The result indicated that the flood hazard in Karawang regency occupied the paddy fields to parts of paddy fields flood area (Figure 9).
From the analysis results, areas with high flood hazard covered an area of 7,489 ha (7.61%), moderate flood hazard covered 19.188 ha (19.49%) and low flood hazard covered 1,689 ha (1.72%).Flood incidents recorded each year resulted in crop failure and decreased production of rice crops in Karawang regency (Riadi et al. 2017) as shown in Table 5. Source: [17,5] and The Calculation Results Pond area with medium potential flood prone was 14,058 Ha, and with high potential was 4,088 Ha(Agustini and Suratijaya, 2014).

Conclusions
Land cover/land use changes in Karawang regency were analyzed spatially indicating that there was degradation of paddy fields, and an increase in pond extent. From 2000 to 2015 degradation of paddy fields was 21,909 ha, while the expansion of pond area was 16,355 ha. Coastal areas are alluvial lands that are naturally flooded areas. Flooding that occurred in Karawang resulted in a loss of rice production by an average of 24,178 ha per year. Minapadi land in flood-hazard areas was 11,273 ha, ponds located in the area of moderate flood hazard was 14,058 ha while ponds with very high prone to flood was 4,088 ha. It was predicted that until 2031 the paddy fields will continue to degrade and the remaining is predicted 88,007 ha, the pond area will remain about 24,207 ha and the population will be 2,826,579 people. Assuming fixed rice production and population continues to increase, food security or rice needs in Karawang regency can still be met, but the surplus of rice for national food needs will decline. In accordance with the condition of pond habitat, fish farmers were predicted to keep working, considering its good income to support family life. However, wetland degradation tended to reduce minapadi business. The dynamics of coastal changes and the threat of floods to aquaculture led to the creativity of fish farmers in reducing business losses by placing nets around ponds to assure that fish was not washed away by the flood.
To prevent land use change can be done with several attempts (a) to protect paddy fields from the land conversion process; (b) restrict the conversion of productive agricultural land into residential or industrial areas; (c) restrict the conversion of paddy fields and ponds into non-agricultural activities and (d) any land use application is checked for compliance with Regional Regulation Number 2 of 2013 on Spatial Planning of Karawang Regency in 2011-2031.