1. Agricultural Land Rating Systems... for the Non-Soil Scientist Earl Yamamoto, State Department of Agriculture February 5, 2000 Advance slide 

2. Presentation  Overview of major rating systems  Comparison of systems  What approach? OVERVIEW Advance slide 

3. Four major systems  Land Capability Classification, USDA  Overall Productivity Rating, Land Study Bureau, UH  Agricultural Lands of Importance to the State of Hawaii (ALISH), DOA/USDA/CTAHR  Land Evaluation & Site Assessment (LESA) System, LESA Commission OVERVIEW Advance slide 

4. Land Capability Classification USDA 1972 Description  Statewide USDA & UH soil surveys Soil data used by all systems  Agricultural suitability as limited by soil & climatic conditions System favors mainland field crop & mechanization  8 Classes I-VIII, best to worse Effective cutoff=LCC Class IV  Productivity estimated only for limited crops Sugar, pine, pasture, woodland  Soils mapped statewide Advance slide 

5. Land Capability Classification USDA 1972 Acreage in Agricultural District  LCC I, II & III statewide: 381,609 acres (estimate)  Percent LCC I, II & III: 20.6% of ag district Advance slide 

6. Overall Productivity Ratings, Detailed Land Classification LSB, UH 1965-1972 Description  Developed concurrent with USDA soil survey  Soils grouped into land types based on soil & productive capabilities  Two sets of productivity ratings: Overall Productivity Rating- “A”, very good to “E”, not suitable Crop Productivity ratings for Pine, sugar, vegetables, forage, grazing, orchard, timber  Soil types drawn over aerial photos (variable scales) Advance slide 

7. Overall Productivity Ratings, Detailed Land Classification LSB, UH 1965-1972 Acreage in Agricultural District  LSB A-C statewide: 447,250 acres (estimate)  Percent LSB A-C: 24% of ag district Advance slide 

8. ALISH DOA/USDA, UH/CTAHR 1977-78 Description  Part of national effort (USDA) to inventory important farmlands  National criteria applied, adapted by USDA, CTAHR & DOA  Adopted by State Board of Agriculture, 1977  Broad range of factors considered S oils, climate, moisture supply, input use, etc., Production-related factors generalized Advance slide 

9. ALISH DOA/USDA, UH/CTAHR 1977-78 Description  3 classes of important agricultural lands Prime – Soils with best physical, chemical, & climatic properties for mechanized field crops – Excludes built-up land/urban, water bodies Unique – Land other than prime for unique high-value crops--coffee, taro, watercress, etc. Other important agricultural lands – State or local important lands for production, not prime or unique; needing irrigation or requiring commercial production management Advance slide 

10. ALISH DOA/USDA, UH/CTAHR 1977-78 Acreage in Agricultural District  ALISH statewide: 846,363 acres (estimate)  Percent ALISH: 45.8% of ag district Advance slide 

11. LESA LESA Commission 1983-86 Description  1983 State Land Evaluation & Site Assessment Commission (Act 273, Session Laws, 1983) Standards & criteria for identifying important agricultural lands Inventory of important agricultural land  LESA system Numeric scoring system USDA system to determine impact of federal activity on farmland Used to identify lands or evaluate individual sites Advance slide 

12. Description  Three components Agricultural production goals Land evaluation (LE) – Soils, topography, climate Site assessment (SA) – Non-physical properties (location, land use) LESA LESA Commission 1983-86 Advance slide 

13. Description  Ag production goals for crop acreage requirements Amount of land required to attain ag production objectives Estimates based on current & expected levels of production, population & per capita consumption Typical crops profiled: – Sugar, pine, mac nuts, coffee, local dairy, eggs/poultry Crop acreage used to set cutoff score for LESA IAL lands LESA LESA Commission 1983-86 Advance slide 

14. Description  Land Evaluation (LE) Combines 5 soil ratings into single score for land capability – LCC – ALISH – LSB – Modified Storie Index – Soil Potential Index LE score is weighted average LESA LESA Commission 1983-86 Advance slide 

15. Description  Site Assessment (SA) Based on USDA LESA manual, selected locational, environmental, operational factors 10 site factors; categories of factors: – Farm productivity/profitability – Land use potential/conflicting uses – Conformance with government programs/policies Soils rated for each criterion, weighted, summed  Final LESA rating= (LE rating+SA score) divided by 2  Threshold score for LESA IAL based on projected acreage  Mapping & GIS coverage limited LESA LESA Commission 1983-86 Advance slide 

16. LESA LESA Commission 1983-86 Acreage in Agricultural District  LESA IAL statewide: 759,534 acres (estimate)  Percent LESA IAL: 41.1% of ag district Advance slide 

17. Comparison of Systems Common features  Soils-based with factors for topography, climate Vary in consideration of other attributes like crop yield  Limitations to agricultural productivity considered in some form Mostly physical and climatic limitations  All are available on State GIS in some form Advance slide 

18. Comparison of Systems Major differences  Soils-based systems exclude other factors related to ag profitability  Determination of ag land requirements LESA system unique in its use of agricultural production goals Other systems do not predetermine land requirements  Incorporation of land use policy considerations LESA includes policy criteria Land use policy dealt with in other systems only by the exclusion of urbanized, built-up, subdivided land Advance slide 

19. Amount of land rated suitable for agriculture LEAST LCC21% of ag district LSB24% LESA41% ALISH46% MOST Comparison of Systems Advance slide 

20. Comparison of systems  LSB -- “A”-“C” lands  LCC -- Lands better than Class IV LCC LESALSB ALISH Advance slide  ALISH  “Prime” & “Other Important Ag” LESA  Lands above threshold IAL score

21. Comparison of Systems Evaluation criteria (based on CTAHR, 1990)  Ease of use Low cost, clear explanations, factors well-defined  Objectivity Measurable factors with quantifiable data  Consistency Scores would be same across individuals, clear definitions, interpretations consistent, no incentive for score manipulation  Adaptability Can be readily updated to reflect change  GIS-readiness Advance slide 

22. Comparison of Systems Ease of Use  Easiest LCC Straightforward use of soils data ALISH LSB Crop indices & inputs would need to be reassessed; more cost to State  Difficult LESA Most complex, scoring system is opaque, mapping problems; most costly to define & use Advance slide 

23. Comparison of Systems Objectivity  Most objective LCC LSB Criteria clear/quantifiable for both  Less objective ALISH No standardized way to define “unique”  Least LESA Factors not clear, difficult to quantify & map Advance slide 

24. Consistency  Most consistent LCC LSB Properties, criteria clear  Less so ALISH Both “unique” & “other” introduce variability  Least LESA Variability in interpreting, assigning values/weights to factors Comparison of Systems Advance slide 

25. Adaptability  Most adaptable ALISH Criteria can be reapplied, accommodates unique crops  Less so LCC Criteria constant, least sensitive to local crop potential LSB Dated, system indexed to sugar & pine & farm practices at time  Least LESA Components outdated; indexed to sugar & pine; productivity goals rigid; most difficult to update Comparison of Systems Advance slide 

26. GIS-readiness  Most GIS-ready LCC USDA NRCS maintains GIS soils data, source of State GIS data ALISH On State GIS, USDA soils data for update available  Less so LSB On State GIS, data old  Least GIS-ready LESA Data on State GIS of questionable value/need to redigitize; problems encountered in mapping factors Comparison of Systems Advance slide 

27. Closing Thoughts Summary 1. Each of the systems has limitations in application-- none ideal 2. Ratings change with change in conditions or opportunities Some examples... Advance slide 

28. Closing Thoughts  Example of how one factor-- irrigation--changes ratings Under LCC system, good ag lands WITHOUT irrigation Advance slide 

29. Closing Thoughts... good ag lands WITH irrigation... without irrigation  Example of how one factor-- irrigation--changes ratings Advance slide 

30. LSB “C” “D” ALISH “Unique” Closing Thoughts  Two views of Lanai pineapple under different rating systems-- LSB “D” vs. ALISH “Unique” Advance slide 

31. Closing Thoughts LSB  Two views of Hanalei Valley taro under different rating systems-- LSB “E” vs. ALISH “Unique” ALISH “unique” Advance slide 

32. Closing Thoughts 3. All need to be updated to reflect present conditions-- some more than others 4. In general, system is more robust if: Emphasis is on resource suitability System criteria are well-defined Summary 1. Each of the systems has limitations in application-- none ideal 2. Ratings change with change in conditions or opportunities Advance slide 

33. Closing Thoughts In considering a system...  Purpose of ratings: identify resource, system will be soils-based  Factors of land use policy more appropriate for public decision making process, creates problems if built into rating system  Must weigh value of additional time/money spent on development & maintenance of system Advance slide 

34. Credits Department of Agriculture James Nakatani, Director Earl Yamamoto State Office of Planning, DBEDT David Blane, Director Ruby Edwards Chris Chung Dennis Kim, State GIS Program