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:


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


• 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

Advance slide


• 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• Acreage in

Agricultural District LESA IAL

statewide:

759,534 acres

(estimate)

Percent LESA IAL:


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


• 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


ObjectivityMost objective

LCCLSB

Criteria clear/quantifiable for both

Less objectiveALISH

No standardized way to define “unique”

LeastLESA

Factors not clear, difficult to quantify & map


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


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


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”

Advance slide

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

sistem rating lahan pertanian

Documents

land types

soil properties

usda soil surveysoils

structure of soil

statewide usda

soil climatic conditionssystem

soil surveyssoil data

overall productivity