한국농림기상학회지 (Korean Journal of Agricultural and Forest Meteorology)

  • 제21권4호
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  • Pages.286-296
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  • 2019
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  • 1229-5671(pISSN)
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  • 2288-1859(eISSN)
한국농림기상학회 (Korean Society of Agricultural and Forest Meteorology)
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토양 및 기후정보 통합 최대저해인자법에 의한 복숭아와 포도의 적지 평가

The maximum limiting characteristic method-based land suitability assessment for peaches (Prunus persica) and grapes (Vitis vinifera L.) using rasterized data of soil and climate on agricultural land in South Korea

  • Kim, Hojung (National Institute of Agricultural Sciences, Rural Development Administration) ;
  • Koo, Kyung-Ah (Environmental Policy Research Group, Korea Environment Institute) ;
  • Shim, Kyo-Moon (National Institute of Agricultural Sciences, Rural Development Administration)
  • 투고 : 2019.09.11
  • 심사 : 2019.11.25
  • 발행 : 2019.12.30
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초록

본 논문에서는 남한지역을 대상으로 토양학적 그리고 기후학적 적지 기준을 통합하여 최대저해인자 방법으로 과수 2종(복숭아와 포도)에 대해서 재배적지를 구분하였다. 복숭아는 최적지 2.21%, 적지 19.21%, 가능지(저위생산지 포함) 12.07%, 부적지 66.52%로 구분되었고, 포도는 최적지 3.65%, 적지 17.98%, 가능지(저위생산지 포함) 11.85%, 부적지 66.52%로 구분되었다. 토양과 기후 조건의 통합에 의해 구분한 복숭아와 포도의 적지는 토양 조건만으로 구분한 적지와 유사한 것으로 분석되었고, 토양 조건에 의한 구분한 적지(최적지 포함) 면적이 기후 조건에 의해 구분한 면적보다 적은 것으로 분석되어서 토양 조건이 적지구분의 저해인자로 확인되었다. 어떤 행정구역(도)에서 적지(최적지 포함)로 구분된 면적이 많으면 많을수록 더많은 과수가 재배될 것이라는 가정 하에, 행정구역별 복숭아와 포도의 실재 재배면적 비율과 토양 및 기후 조건 통합의 최대저해인자법에 의해 구분한 적지면적과 비교하였을 때, 실재 과수 재배면적의 비율이 적은 행정구역에서는 해당 과수의 재배면적 확대를 고려할 필요가 있을 것이다. 다만, 과수 적지구분의 정확도 향상을 위해서는 분석적 계층화법(AHP)과 같은 개선된 방법과 농장단위의 과수 생산량과 수익자료를 추가하여 비교 분석할 필요가 있다.

Land suitability assessments have been a crucial issue for enhancing productivity in agriculture and conserving agricultural lands. Based on soil and climate information, land suitability assessment for peaches (Prunus persica) and grapes (Vitis vinifera L.) were conducted using the maximum limiting characteristic method (MLCM) in South Korea. In peaches, S1 (highly suitable) exists on 2.21% of the land, S2 (moderately suitable) on 19.20%, N1 (currently not suitable) on 12.07%, and N2 (permanently not suitable) on the remaining 66.52%. In grapes, 3.65% of the land is classified as S1, 17.98% as S2, 11.85% as N1 and 66.52% as N2. In both fruit trees, the results acquired from soil and climatic information were similar to those from soil information alone. The data also suggest that the grades by soil information were relatively low over the land. With the assumption that the more suitable area a province has, the more will be cultivated for the fruit trees, we compared the percentages of area for peach and grape farming per province with the results by MLCM, and suggested that some provinces with a small percentage of farm can be encouraged to plant more in suitable areas as dictated by MLCM for the species. In the near future, we plan to use an advanced method such as analytic hierarchy process (AHP) to conduct similar tests, in which having reference data of yields or benefits per farm can efficiently increase the accuracy of the measurements.

키워드

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