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GIS Applications. Faculty of Computer Science University of Indonesia Dr. Aniati Murni. Contoh Aplikasi. Agriculture Precision Farming Electricity Distribution Network Forest Fire. GIS in Agriculture Application (Source: GIS AsiaPacific, February/March 1998).
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GIS Applications Faculty of Computer Science University of Indonesia Dr. Aniati Murni
Contoh Aplikasi • Agriculture Precision Farming • Electricity Distribution Network • Forest Fire
GIS in Agriculture Application(Source: GIS AsiaPacific, February/March 1998) Faculty of Computer Science University of Indonesia Dr. Aniati Murni
Aspects of Agriculture Application • Aspects of applications • Crop location and area estimation; • Yield prediction; • Diseases monitoring; and • Precision Farming. • Required information • Identification of crop type; Measurement of crop area; • Determination of crop boundaries; Estimates of yield and production; • The determination of crop health and stress; and • The measurements of in-field variation (good and bad crops).
Data Capture Technology(Pengaruh Image Resolution) • High resolution optical remote sensing sensor (SPOT, three times/year) • Synthetic Aperture Radar (SAR) sensor • High resolution image for precise farming: resolution-size vs error
Location and Area Estimation • Colors in optical sensor images can identify crop/vegetation type, different health and maturity, growing season and harvesting season (using multitemporal data); • Crop boundaries, image pixel size, and information from the grower can be used for area estimation. • Areas declared as potatoes areas is combined with the declared location and area of planted potatoes to get a map of growing potatoes. • Later, the field supervisor can use this map to record the planting returns and to process only the growing potatoes area with no corresponding planting returns.
Yield Prediction • Compare the probable crop yield at a detailed level and the product estimation; • Predict the surpluses or shortages to support price prediction and stabilization effort at national level; • Improve logistics planning for the harvest, transportation, storage and processing of seasonal crops.
Disease Monitoring • The healthy and unhealthy crops can be differentiated using false color optical sensor SPOT data where healthy trees are red and unhealthy trees are pink and purples. • This information can be used to estimate the impact on the production and model of the epidemic (in terms of extent, severity, spreading time). Red = healthy vigorous crops Pink/Purple = unhealthy or blighted crops
Precision Farming(Lower Cost but More Competitive) • The type and structure of soil or unsuited to the crop type; • Different nutrient availability or non-uniform of seed distribution; • Germination; and Uneven irrigation. Sources/Causes of in-field variation (good and bad crops): The usefulness of multitemporal analysis: • Is there any repeatable variation? • Then it can be solved by fertilizing (use only if it is required / reduce fertilizer use, efisien / saving money, avoid run-off chemical polluted water); and additional / better irrigation. • Can predict crop yield and help farmer to improve farming efficiency.
Vigorous Crops Recognition by Vegetation Index • Healthier crops higher vegetation index: ; Vegetation Index Measures High NDVI
GIS in Electricity Distribution Network(Source: GIS AsiaPacific, June/July 1998) Faculty of Computer Science University of Indonesia Dr. Aniati Murni
The Objective of the GIS Project • distribution network technical information base; • customer connection database; • and decision support systems. To improve the reliability and accessibility of the power company’s:
Information Requirements • An accurate register of geographic position of distribution system assets for valuation and financial performance reporting purposes; • The capacity and geographic location of each customer connection points to the network to be used as an input parameter in the determination of charges for line function services; • This meant that the management should be able to derive (a) an electrical schematic of the network for analysis and planning purposes; (b) an asset inventory with location attributes for system maintenance.
Steps to achieve the objective • Assess the existing information contained in database; • Conduct a survey on information requirements; • Design and implement a strategy to obtain all necessary information; • Coordinate all information into a central database of a GIS; • Develop operational processes and procedures to automate up-to-date data maintenance; • Expand access to and operations of the GIS throughout the functional units of the organization.
Identification of data requirements • No previous database or records of individual poles and structures; • Records on rural lines were limited to large scale hard copy maps (1:10.000), so that the line position information is inaccurate and no detail attributes; • Records on urban lines and cables were in the A1 paper of 1:10.000 scale and could be directly digitized using CAD system; • A number of text data should be entered including the code numbers of computerized transformer and substations;
Identification of data requirements (continuation) • Incomplete records of existing transformers and substation records without or with wrong transformer data; • The database was based on customer account which is related to a single meter installation, in fact one customer may have more than one meter installations, meaning may have more than one customer accounts; • The database could be based on customer connection points but there was no information on their load capacity; • The database for street lights was in text describing the attribute of location name.
Data Capture Strategy • Data of geographic position and load capacity of each customer network connection points; • Geographic position and attributes of substation, lines, cables, switchgear, and streetlights; • Data collection is divided into urban and rural data collection; • Rural data collection is divided into ground mapping / survey and aerial mapping; • Geographic position is measured using GPS (Global Positioning System).
Ground Mapping • A roving crew consists of one lineman and one surveyor, visits all rural transformer sites and all their connected customer NCPs. • The surveyor made a field sketch book of the layout of 400V lines from each transformer, detail 400V conductors, substation code numbers, GPS (geographic) positions. • The lineman affixed the NCP identification number plate. • At the end of each day, the GPS waypoint files were down loaded to CAD system, and the field sketch book was transferred to CAD mapping.
Aerial Mapping • The survey involved a low-level helicopter flyover of all rural high voltage lines; • A video camera is mounted at the helicopter and recorded the view of the overhead lines; • Each high voltage line connection is marked and its position is recorded and stored in the GPS file. • At the end of each day, the data is down loaded to CAD system to provide input data for high voltage line connection database.
Urban Data Collection • The existing urban power map of 1:1.000 scale is used in the survey as the field sketch map where additional customer NCPs information is added to the map; • The urban power lines include under-ground cable and above-ground poles; • The data of above-ground line network includes the customer NCPs and the related NCP code number; • The NCP map is used by the lineman to add information of meter installation code number and its load capacity; • In the case of under-ground cable, the customer NCP is located at the service pillar box, so that it can be identified; • All the data then are digitized into the CAD maps.
System Map Production • This system produces an electronic map of all components of line network assets and entities such as transformers, NCPs, etc.; • The electronic map consists of sets of graphic entities which are geographically connected to each other; • Entity identifier is needed to relate the graphic entity to its attribute (table data) in the relational database; • The tolerable accuracy for rural and urban network is 10m - 15m and around 5m, respectively.
GIS Implementation • After the electronic maps are produced, then the GIS construction can be implemented; • The data coverage/layers include the theme of high voltage network, NCP network, switch gear network, etc.; • The relation between the graphic/spatial data and text/attribute/non-spatial data is also established; • The system is then extended as a multiuser system, so that each unit in the company can utilize the data; • In this way, the system has already been integrated to the network operational management system.
GIS in Fishermen, Farmers, Forest Change and Fire(Source: GIS AsiaPacific, February/March 1998) Faculty of Computer Science University of Indonesia Dr. Aniati Murni
DSWR (Danau Sentarum Kalimantan Wildlife Reserve) Data Area : 132,000 ha Population : 6000 - 8000 Feature : Swamp Forest Fauna : Rare Red Asian Arowana Proboscis Monkey, Orang Utan Stakeholders : Muslim Melayu (fishermen, traders, timber concessionaires, timber workers, conservation agency and local government officials) Christian and Animist Iban (shifting cultivators)
DSWR Conservation Project (1992 - 1997) • Funded by British Conservation Project between Government of Indonesia and UK Tropical Forest Management Programme (ITFMP); • Implemented based on Participatory and Community Management Plan in collaboration with the Ministry of Forestry’s Directorate General of Forest Protection and Nature Conservation; • Using the remote sensing technology and GIS (Geographic Information System) to produce 1:50,000 map scale; • Thematic Legend: vegetation, burned areas, regenerating areas, reserved villages (the local community decides its village boundary), socio-economic data, forest use status, administrative boundaries, geology data, logging concession boundaries, and spatial planning status.
Landsat TM of D. Sentarum (August 1990) Red = burned forest Green = forest Forest Burned Forest
Images of D. Sentarum Danau Sentarum in Wet Season Burned Swamp Forest
Joint Research between Conservation Project and CIFOR (The Center for International Forestry Research) • Forest Cover Change Analysis: using Landsat TM and MSS to produce base map of 1:50,000 scale. Aerial photo is used to digitize forest boundary on the base map. • Stakeholder activities: shifting cultivation (dry and wet land), hunting, fishing, harvest rattan, honey, firewood and timber from the forest. • During the period of 1973-1990, the swamp forest area was reduced from 4000 ha to 3444 ha; and the burned swamp forest was increased from 59 ha to 239 ha. Research on the Criteria and Indicator for Sustainable Forest Management System - Forest Change, Shifting Cultivator, Fisherfolks
Joint Research between Conservation Project and CIFOR (continuation) • The cause of forest fire could be physical (natural) or anthropogenic (the human) but it is sure not caused by shifting cultivation. • The hill and dry land forest (non-swamp forest) was also reduced from 1089 ha to 884 ha due to shifting cultivation activities. The remaining dry land forest was regenerated forest or non-cleared forest which is used for funeral. • Fishery could sustain the swamp forest, but some are also burned. The majority of the burned swamp forest are the dwarf and stunted (pohon-pohonnya kecil karena tidak subur) swamp forest.
Conclusions • Forest damages in non-reserved area have experienced greater loss in forest cover than that in reserved area. Most of the cause is fire. • Swamp forest damages in shifting cultivation areas are not always worse than that in fishery areas. • The remote sensing and GIS technologies are potential for sustainable forest management. • The socioeconomic data, ethnographic data and forest classification data could be used to obtain the cause of forest fire. • The shared claim zones consistently show forest decrease, often as a result of burning. Focusing on conflict resolution between the major stakeholders in these areas may lead to less burning. • The study of deforestation shows a complex analysis which need to examine conditions historically.