3S(GIS、GPS、DDS)技術在精準農業上之應用

Abstract

精準農業乃是針對農田及植栽的變異性給予最適當的耕作決策與處理，以減少資財之耗費，增加收益並減輕環境的衝擊。傳統之農耕方式將整個田區之作物、土壤等特性視為均一，故無論是灌溉水量、肥料或是農藥之施用量，均是針對整個田區施用。精準農業則針對田區間各種作物、土壤、環境因子具空間變異之特性，利用先進的電腦、通信與自動化科技，配合適當時間、空間尺度之田間調查作業及地理資訊系統、空間變異分析模式，以精確地且全面性地掌握田區作物、土壤與環境特性，進而經由作物模式、決策分析模式，以決定最佳之耕作策略及產量預測，並利用地理資訊系統建立各種空間分布圖層。 Agriculture is becoming more of a system and it is also becoming more of a business. As a system, the constituents involved with arid affected by precision agriculture are heading towards a direction of more directed interaction driven by the data which can be provided. The constituents of precision agriculture include the farmer, agribusiness, the agricultural equipment industry, university researcher, and the general public. As the process becomes more systems oriented, we can expect the data derived from precision agriculture to form the foundation some new opportunities including research. It is also reasonable to expect that these data will provide information for legal decisions, government regulation, and environmental accountability. Cultural practices will evolve from precision agriculture that provide more opportunities for changing the growth and development of the crop during the growing seasons. Crop models will serve as a “blueprint” for the potential growth and development of the crop at a point in time. Management models will be developed to perform whole-farm management, as a system of equipment, environmental factors, crops grown, and crop markets. To deal with variations prevailing in fields and crops of planted, precise agriculture provides the best approach decision-making of farm management to raise income, reduce cost waste as well as lessen the impact on the environment. In conventional agriculture, features of crop and soil in the field were frequently regarded as homogeneous; hence, irrigation, fertilizers and pesticides were applied very uniformly. While precision agriculture copes with spatial variations of crops, soil, and environment in field by technologies of computer, communication and automation. That is to incorporate the field survey of appropriate timing and space scale, geographic information system, and spatial variation analysis model. Thus, not only the best cultivation strategy and yield prediction but also various map layers of space distribution could be well made through crop model and decision analysis model. Eventually, the strategy can be carried out by satellite position and automatic technologies.