APPLYING NIJOS LANDSCAPE INDICATORS
TO THE RIBATEJO E OESTE REGION [1]
By Rui Rosário (INIAP), Ana Antunes, Isabel Escada (GPPAA)
[1] Rosário, Rui; Ana Antunes e Isabel Escada, 2001. Elementos Paisagísticos do Ribatejo e Oeste, Estação Agronómica Nacional, Instituto Nacional de Investigação Agrária Introduction
Research project :
• to use GIS to produce information associated with land use
• integrate data obtained by photointerpretation of already existing digital orthophotomaps (CAP control system) Introduction
Strategy:
• launching a sample of territorial sections, based on statistical criteria
• data gathered using photointerpretation techniques validated through field work Indicators Framework
Agro-environmental indicators should: • have the ability to desaggregate values spatially - geographical scale
• have time scales associated with each particular issue - time scale
• identify trends and variation intervals for each indicator - the relative expression of an indicator is usually more important than its absolute value Project
• Team: 2.25 research units
• Duration: 18 months
• Variable cost: $19.000.00 (USD) Project Outline
Heterogeneous geographical area
Open land Small plots Project Outline
Open forest area Softwood forest with agriculture Project Outline
Urban settlements Mixed urban/rural settlements Project Methodology
• A non-stratified aligned systematic sample
• A methodology that allows an uniform coverage of the region
• Observation without any intervention at farm level Project Methodology Segment location and identification 221221 356356 Project Methodology
The sample:
• is made up of 483 segments of 25 hectares each
• segments are 5 Km from each other
• the total area sampled is 12.075 hectares
• the sampling rate is 1% Project Methodology Sample rate by municipality Photointerpretation
Photointerpretation techniques were used to identify plot structures
CPCP_P_POO • Parceling criteria URBURB_P_POOVV TLTL EstEst • Soil occupation CPCP_V_V classes EstEst CPCP_V_V TLTL Photointerpretation
Photointerpretation data was compared with field data in 80 segments corresponding to 520 plots
• 45% had been correctly classified
• 55% of the plots the initial parceling and classification criteria required revision : - by plot aggregation (less detailed) - by occupation reclassification Photointerpretation
FLFL TLTLTlTlssSS TlTlss TLS TLS TLTL TLTL TLTL Tls Sb_PasSb_PasTlTlss Tls TLTL TLTLSS
Initial parceling (6 plots) Final parceling (1 plot) Photointerpretation
After this work, the initial parceling and classification criteria were revised
With the new criteria the degree of precision reached 76% of the plots Photointerpretation
Persistent deviations were due to:
• differences between the time when aerial photographs were taken (1995) and when field data was collected (1999)
• highest effectiveness of this work was obtained in Agro-Forestry (93%) and Open Land (81%)
• a residual source of error (3 in 520 plots) was due to misunderstandings of occupation type Results
Soil Occupation Indicator Defined taking into account the type of occupation and the corresponding area in each segment
Ferreira do Zezere Ferreira do Zezere Vila Nova de Ourém Vila Nova de Ourém
Nazaré Tomar Nazaré Tomar Alcobaça Sardoal Alcobaça Sardoal
Torres Novas Torres Novas V. Nova da Barquinha Alcanena EntroncamV.ent Nova da Barquinha Alcanena Entroncamento Gavião Constância Abrantes Gavião Caldas da Rainha Constância Abrantes Caldas da Rainha Golegâ Óbidos Golegâ Óbidos Peniche Santarém Peniche Rio Maior Rio Maior Santarém Bombarral Bombarral Chamusca Lourinhã Chamusca Lourinhã Cadaval Alpiarça Cadaval Alpiarça
Permanent Crop-Vineyard Almeirim Cartaxo Almeirim Azambuja Cartaxo Azambuja Torres Vedras Alenquer Torres Vedras Alenquer
Salvaterra de Mag os Salvaterra de Mag os
Sobral de Monte Agraço Sobral deA Mrrountdae doAgsr Vaçinhoo s Mafra Arruda dos Vinhos Mafra Vila Franca de Xira Coruche Vila Franca de Xira Coruche
Benavente Loures Benavente Loures Sintra Sintra
Amadora AmadoraLisboa Cascais Lisboa Montijo Oeiras Alcochete Montijo Cascais Oeiras Alcochete Montijo Montijo Moita Almada Moita Almada Barreiro Barreiro Palmela Seixal Palmela Seixal
Setúbal Sesimbra Setúbal Sesimbra Results
Forestry Agro-Forestry
Ferreira do Zezere Ferreira do Zezere Ferreira do Zezere Vila Nova de Ourém Vila Nova de Ourém Vila Nova de Ourém
Tomar Tomar Nazaré Nazaré Nazaré Tomar Alcobaça Sardoal Alcobaça Sardoal Alcobaça Sardoal
Torres Novas Torres Novas Torres Novas V. Nova da Barquinha Alcanena V. Nova da Barq uinha EntroncamV.e ntNova da Barquinha Alcanena Alcanena Entroncamento Entroncamento Gavião Gavião Constância Abrantes Gavião Constância Abrantes Caldas da Rainha Constância Abrantes Caldas da Rainha Caldas da Rainha Golegâ Golegâ Óbidos Golegâ Óbidos Óbidos Peniche Santarém Peniche Santarém Peniche Rio Maior Rio Maior Rio Maior Santarém Bombarral Bombarral Bombarral Chamusca Chamusca Lourinhã Chamusca Lour inhã Lourinhã Cadaval Alpiarça Cadaval Alpiarça Cadaval Alpiarça
Almeirim Almeirim Cartaxo Almeirim Cartaxo Azambuja Cartaxo Azambuja Azambuja Torres Vedras Alenquer Torres Vedr as Torres Vedras Alenq uer Alenquer
Salvaterra de Magos Salvaterra de Magos Salvaterra de Magos
Sobral de Monte Agraço Sobral de Monte Ag raço Sobral deAr Mrountdae doAgsr Viaçnohos Arruda dos Vinhos Mafra Arruda dos Vinhos Mafra Mafra Vila Franca de Xira Coruche Vila Franca de Xira Coruche Vila Franca de Xira Coruche
Benavente Benavente Loures Benavente Loures Loures Sintra Sintra Sintra
Amadora Amadora AmadoraLisboa Lisboa Cascais Lisboa Montijo Montijo Oeiras Alcochete Montijo Cascais Oeiras Alcochete Cascais Oeiras Alcochete Montijo Montijo Montijo Moita Moita Almada Moita Almada Almada Barreiro Barreiro Barreiro Palmela Palmela Seixal Palmela Seixal Seixal
Setúbal Setúbal Sesimbra Setúbal Sesimbra Sesimbra Results
Diversity Indicator
Ferreira do Zezere Ferreira do Zezere Vila Nova de Ourém Vila Nova de Ourém
Nazaré Tomar Nazaré Tomar Alcobaça Sardoal NO Alcobaça Sardoal NO Torres Novas Torres Novas V. Nova da Barquinha Alcanena V. Nova da Barquinha Alcanena Entroncamento Entroncamento Diversity = Gavião Diversity = Constância Abrantes Gavião Caldas da Rainha Constância Abrantes Caldas da Rainha Golegâ Óbidos Golegâ Óbidos Peniche NS Peniche Rio Maior Santarém NS Rio Maior Santarém Bombarral Bombarral Chamusca Lourinhã Chamusca Lourinhã Cadaval Alpiarça Cadaval Alpiarça
Almeirim Cartaxo Almeirim Azambuja Cartaxo Azambuja Torres Vedras Torres Vedras Alenquer Alenquer
Salvaterra de Magos Salvaterra de Magos
Sobral de Monte Agraço Sobral de Monte Agraço Arruda dos Vinhos Mafra Arruda dos Vinhos NO - total number of different Ma fr a Vila Franca de Xira Coruche Vila Franca de Xira Coruche
Benavente occupations Loures Benavente Loures Sintra Sintra
Amadora Amadora Lisboa Cascais Lisboa Montijo NS - total number of segments Oeiras Alcochete Montijo Cascais Oeiras Alcochete Montijo Montijo
Moita Almada Moita Almada Barreiro Barreiro Palmela Seixal Palmela Seixal
Setúbal Sesimbra Setúbal Sesimbra Results
Landscape Structure Indicator or Perimeter/Area ratio
Ferreira do Zezere Vila Nova de Ourém
Nazaré Tomar EE Alcobaça Sardoal
Torres Novas ED = V. Nova da Barquinha ED = Alcanena Entroncamento Gavião Constância Abrantes Caldas da Rainha A Golegâ A Óbidos Peniche Rio Maior Santarém
Bombarral Chamusca Lourinhã Cadaval Alpiarça
Almeirim Cartaxo E - Total perimeter of the plots Azambuja Torres Vedras Alenquer
Salvaterra de Magos
A - Total area of the reference unit Sobral de Monte Agraço Arruda dos Vinhos Mafra Vila Franca de Xira Coruche
Benavente Loures Sintra
Amadora Lisboa Montijo Cascais Oeiras Alcochete Montijo
Moita Almada Barreiro Palmela Seixal
Setúbal Sesimbra Conclusions
Sampling:
• different sizes of segments in the stratified sample
• Progressive area frame sampling to adapt the sample to different landscape characteristics Conclusions
Photointerpretation techniques
are quite adequate when dealing with large groups of territorial occupation
the larger the scale of the photographic material, the more efficient the photointerpreting process with more detail nomenclature Thank you very much