Improving the precision of sample-based forest damage inventories through two-phase sampling and post-stratification using remotely sensed auxiliary information

Roberge, Cornelia; Wulff, Sören; Reese, Heather; Ståhl, Göran

doi:10.1007/s10661-016-5208-4

Cited by 9 publications

(12 citation statements)

References 38 publications

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“…We used a quadrat-shaped area of interest (AOI) located in the Swedish county of Västernorrland (cf. Roberge et al 2016) to represent a typical municipality of 900 km 2 , divided into 1,200 × 1,200 grid-cells of 25 × 25 meters each. The AOI had a forest cover of 80% and comprised 13,870 forest stands in the segmented kNN-Sweden data (Reese et al 2003) used for simulating the damage populations ( Figure 1, Table 1).…”

Section: Methodsmentioning

confidence: 99%

“…The two baseline methods were compared with LPM, which uses multiple auxiliary data sources for the sample selection. 2PS has been frequently applied in forest damage inventories over the years (Lucas 2009, Roberge et al 2016. Both LPM and 2PS were based on an initial systematic sample of ݊ ଵ grid-cells spread in geographical (XY)…”

Section: Inventory Strategiesmentioning

confidence: 99%

“…Therefore, estimates based on designbased inference are often required (Ferretti, 2009). In a study by Roberge et al (2016) it was found that great gains in precision can be obtained with two-stage-sampling for stratification, using existing national forest inventory plots as a first phase. Moreover, using forest damage maps for poststratification improved the precision further.…”

Section: Introductionmentioning

confidence: 99%

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Forest damage inventory using the local pivotal sampling method

2017

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Specially designed forest damage inventories, directed to areas with potential or suspected damage, are performed in many countries. In this study, we evaluate a new approach for damage inventories in which auxiliary data are used for the sample selection with the recently introduced local pivotal sampling design. With this design, a sample that is well spread in the space of the auxiliary variables is obtained. We applied Monte Carlo sampling simulation to evaluate whether this sampling design leads to more precise estimates compared with commonly applied baseline methods. The evaluations were performed using different damage scenarios and different simulated relationships between the auxiliary data and the actual damages. The local pivotal method was found to be more efficient than simple random sampling in all scenarios, and depending on the allocation of the sample and the properties of the auxiliary data, it sometimes outperformed two-phase sampling for stratification. Thus, the local pivotal method may be a valuable tool to cost-efficiently assess the magnitude of forest damage once outbreaks have been detected in a forest region.

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Section: Methodsmentioning

confidence: 99%

Section: Inventory Strategiesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Forest damage inventory using the local pivotal sampling method

2017

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“…According to Bognola et al (2009), forest stands should be approached by sampling methods efficient in the representativeness of the current and temporal state of the population, so that it can provide accurate and low-cost data, being essential as a basis for management actions and forest planning. In this sense, the use of geostatistical interpolators has been consolidated as a viable alternative to obtain greater CFI accuracy (Kanegae Júnior et al, 2006;Guedes et al, 2012;Roberge et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

Eucalyptus spp. volume determined through geospatial interpolation

Neto¹,

Nogueira²,

Melo³

et al. 2019

Científica

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Planning and managing forest resources is fundamental for increasing the productivity of forest products and byproducts. This study evaluates the use of the ordinary kriging interpolator in the estimation of standing wood volume in Eucalyptus spp. plantations in Paragominas city, Pará State, Brazil. For this, we used data from the precut forest inventory, processed by the ordinary kriging method. Measurements took place in 27 georeferenced fields, with plots of 504 m², where trees were rigorously cubed. Geostatistical modeling was performed using ordinary kriging (spherical semivariogram model) with isotropic and anisotropic interpolators, seeking to map the volume of the area. To this end, experimental semivariograms were obtained through the Geostatistical Analyst tool of ArcGIS 10.1 software. Interpolation presented satisfactory results regarding plot volume mapping, in which the average volume fitted by ordinary kriging was statistically similar to the average volume obtained by the forest inventory, 11.3517 m³ and 11.3842 m³, respectively, showing efficiency with an adjusted coefficient of determination of 0.94. The use of ordinary kriging interpolation proved to be effective in plot volume estimation in the forest stands under study.

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“…A utilização de interpoladores geoestatísticos, para a estratificação dos povoamentos florestais, surge como alternativa para a obtenção de maior precisão do IFC (Kanegae Júnior et al, 2006;Guedes et al, 2012;Roberge et al, 2016), para eliminar a necessidade da realização do inventário pré-corte.…”

Section: Introductionunclassified

Estratificação de um povoamento de eucalipto por interpoladores geoestatísticos e sensoriamento remoto

Reis

Mello

Raimundo

et al. 2016

Pesq. agropec. bras.

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Resumo -O objetivo deste trabalho foi avaliar a utilização de interpoladores geoestatísticos e imagens de sensoriamento remoto, para a estratificação de povoamentos de Eucalyptus sp. em idade de corte. As estimativas da amostragem casual estratificada foram comparadas às estimativas da amostragem sistemática quanto à variável volume de madeira. A área de estudo correspondeu a um povoamento clonal de Eucalyptus sp. no Município de Lagoa Grande, MG. O inventário florestal foi realizado em 2011, em quatro situações de amostragem e diferentes números de parcelas. A estratificação da área foi feita por meio de krigagem da área basal (variável principal), da reflectância na banda TM5 (variável auxiliar) obtida em uma imagem Landsat 5 TM e com base na cokrigagem dessas variáveis. A área basal e a reflectância na banda TM5 apresentaram estrutura de dependência espacial. A estratificação reduziu o erro de amostragem em até 40%, em comparação ao erro da amostragem sistemática. As imagens de sensoriamento remoto e os interpoladores geoestatísticos krigagem e cokrigagem são eficientes na definição dos estratos em povoamentos de Eucalyptus sp., em decorrência da maior precisão dos estimadores da amostragem casual estratificada, que permitem estimativas volumétricas mais precisas do inventário florestal do que os da amostragem sistemática.Termos para indexação: Eucalyptus, cokrigagem, imagens, inventário florestal, krigagem. Stratification of an eucalyptus plantation through geostatistical interpolators and remote sensingAbstract -The objective of this work was to evaluate the use of geostatistical interpolators and remote sensing images for the stratification of Eucalyptus sp. stands, at harvesting age. Estimates by stratified random sampling and systematic sampling were compared for the timber volume variable. The study area was a clonal plantation of Eucalyptus sp. in the municipality of Lagoa Grande, in the state of Minas Gerais, Brazil. The forest inventory was performed in 2011, considering four sampling situations and different plot numbers. The area stratification was carried out based on kriging of the basal area (target variable), on the reflectance values in the TM5 band (auxiliary variable) extracted from a Landsat 5 TM image, and on the cokriging of these variables. Basal area and reflectance in the TM5 band showed a spatial dependence structure. Stratification reduced the sampling error up to 40%, in comparison with that generated from systematic sampling. Remote sensing images and kriging and cokriging interpolators are efficient to define the strata in Eucalyptus sp. stands, as a consequence of the higher precision of the stratified random sampling estimators, which allow more precise volume estimates of the forest inventory than those of systematic sampling.Index terms: Eucalyptus, cokriging, images, forest inventory, kriging. IntroduçãoO inventário florestal contínuo (IFC) é o sistema de amostragem mais utilizado no Brasil para acompanhar o crescimento da floresta. O IFC consiste de uma rede de parcelas perm...

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Improving the precision of sample-based forest damage inventories through two-phase sampling and post-stratification using remotely sensed auxiliary information

Cited by 9 publications

References 38 publications

Forest damage inventory using the local pivotal sampling method

Forest damage inventory using the local pivotal sampling method

Eucalyptus spp. volume determined through geospatial interpolation

Estratificação de um povoamento de eucalipto por interpoladores geoestatísticos e sensoriamento remoto

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