Download - SISTEM RATING LAHAN PERTANIAN
SISTEM RATING LAHAN PERTANIAN
Earl Yamamoto, State Department of AgricultureFebruary 5, 2000
Deskripsi:– 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
Land Capability Classification - USDA 1972
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
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 forPine, sugar, vegetables, forage, grazing, orchard, timber
– Soil types drawn over aerial photos (variable scales)
• 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• Soils, climate, moisture supply, input use,
etc.,• Production-related factors generalized
Advance slide
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
ALISH : DOA/USDA, UH/CTAHR 1977-78
ALISH : DOA/USDA, UH/CTAHR 1977-78 • Acreage in
Agricultural District ALISH
statewide:
846,363 acres (estimate)
Percent ALISH:
45.8% of ag district
6.Strengths & weaknesses of ALISHStrengths
Criteria defined, can be reappliedNational standard: being used by USDA &
other states, basis for agricultural programs, ag grants & loans, & agricultural policy nationwide
Prime lands data is GIS-ready: surveyed, digitized, maintained by USDA, shared with State GIS
Takes into account local, unique crops: coffee, taro, watercress
WeaknessesUnique not as well-defined, no clear cut
criteriaMaps need updating to reflect urbanization &
current crop conditions & potential, e.g., papaya in Kapoho
• 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
LESA: LESA Commission 1983-86D.LESA Description
State of Hawaii Land Evaluation & Site Assessment Commission established by Act 273 of 1983 legislative session, to develop standards & criteria for identifying important agricultural lands, inventory of important agricultural lands
LESA systemBackground
Numerical land rating systemAdapted from USDA system,
initially developed to determine impact of federal activity on farmland
System can be used to identify lands or evaluate individual sites
• 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
3.Three componentsAgricultural production goalsLand evaluation, primarily
physical properties (soils, topography, climate)
Site assessment, relative quality of site or area based on non-physical properties like location, land use, to reflect agricultural viability
• 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
Advance slide
LESA: LESA Commission 1983-86
• 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
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LESA: LESA Commission 1983-86
• 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
Advance slide
LESA: LESA Commission 1983-86
LESA: LESA Commission 1983-86• Acreage in
Agricultural District LESA IAL
statewide:
759,534 acres
(estimate)
Percent LESA IAL:
41.1% of ag district
Strengths & weaknesses of LESAStrengths
Takes into account other land use policy considerationsAttempts at comprehensiveness with use of all indices for LE portionMost current in terms of existing conditions
WeaknessesMost complicated of systems
i. Lots of factors, variablesii. Score & methodology not easy to understandiii. Can result in multiple scores in large sites
Some of LE indices used are outdated, need to be reconstructed for current/future crops
Problems with SA criteriaiv. Some factors vague, difficult to definev. Subjectivity in assigning values & weight to factors: no two
people would necessarily interpret same way; open to manipulation
vi. Source data for mapping is of poor quality or not available; has yet to be mapped as required
vii.Tends to bias toward conversion of ag landAgricultural production goals:
viii.Limited to crop regime at one point in time; poor predictor of future opportunities, too many uncertainties (technological change, change in markets)
ix. Link to land requirements means that when ag land is converted to non-ag use, new land must be found to meet ag production goals
Not GIS-ready: Needs to be redigitized to reflect scores
• 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
Pembandingan Sistem-sistemCommon features
(For most part) Soils- or agronomy-based, soils data (soils, topography, climate), vary in degree to which other attributes like crop yield are consideredAll incorporate limitations to agricultural productivity in some form, but mostly physical and climatic limitationsAll are resident in some form on State GIS
Perbedaan yang utama:
– 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
Pembandingan Sistem-sistemB.Major differences
LE-only systems omit other factors related to ag profitability, like distance to markets, farm size, etc.
Determination of ag land requirementsLESA system unique in its use of
agricultural production goals to determine land requirements
Other systems do not predetermine land requirements; acreage limited only by lack of suitability for crop use
Incorporation of land use policy considerationsMajor component of LESA is
factoring in policy criteriaLand use factored in other systems
only by the exclusion of urbanized, built-up, subdivided land
Amount of land rated suitable for agriculture
LEAST
LCC 21% of ag district LSB 24%
LESA 41% ALISH 46%
MOST
Pembandingan Sistem-sistem
• 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
Pembandingan Sistem-sistem
• 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
Pembandingan Sistem-sistem
ObjectivityMost objective
LCCLSB
Criteria clear/quantifiable for both
Less objectiveALISH
No standardized way to define “unique”
LeastLESA
Factors not clear, difficult to quantify & map
Pembandingan Sistem-sistem
Objectivity1. Most objective:
LCC & LSB criteria clear/quantifiable
2. Less objective: ALISH because criteria for “unique” not clear
3. Least objective: LESA, factors not clear, difficult to quantify or map
• 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
Pembandingan Sistem-sistem
3. ConsistencyMost: LCC, LSBLess consistent: ALISH
Least: LESA, variability in interpreting, assigning values to factors
• Adaptability Most adaptable
• ALISH Criteria can be reapplied, accommodates unique crops
Less so• LCC
Criteria constant, least sensitive to local crop potential
• LSBDated, system indexed to sugar & pine & farm practices at time
Least• LESA
Components outdated; indexed to sugar & pine; productivity goals rigid; most difficult to update
Pembandingan Sistem-sistem4. Adaptability
Most: ALISH, criteria relatively constant, easy to reapply, allows for consideration of crops unique to Hawaii & diversified ag on less productive lands
Less:LCC, does not account for
unique local conditions, crops, improvements in ag management/inputs, otherwise, criteria fairly constant, can be reapplied
LSB, needs considerable reworking to update indicator crops for productivity
Least: LESA, lots of factors requiring update, remapping; some LE factors old, need to be reconstructed; productivity goals not flexible; keeping system current potentially involves reevaluating all factor scores for all soil mapping units statewide (time- & labor- intensive)
• GIS-readiness Most GIS-ready
• LCCUSDA NRCS maintains GIS soils data, source of State GIS data
• ALISHOn State GIS, USDA soils data for update available
Less so• LSB
On State GIS, data old Least GIS-ready
• LESAData on State GIS of questionable value/need to redigitize; problems encountered in mapping factors
Pembandingan Sistem-sistem
Advance slide
... good ag lands WITH irrigation
... without irrigation
Example of how one factor--irrigation--changes ratings
LSB
“C”“D”
ALISH
“Unique”
Two views of Lanai pineapple under different rating systems--
LSB “D” vs. ALISH “Unique”
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LSB
Two views of Hanalei Valley taro under different rating systems--
LSB “E” vs. ALISH “Unique”
ALISH “unique”
Advance slide
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
Summary1. Each of the systems has limitations in
application--none ideal
2. Ratings change with change in conditions or opportunities
• 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
CreditsDepartment of Agriculture
James Nakatani, DirectorEarl Yamamoto
State Office of Planning, DBEDTDavid Blane, Director
Ruby EdwardsChris Chung
Dennis Kim, State GIS Program