Dario Simonetti - Academia.edu (original) (raw)

Papers by Dario Simonetti

IEEE Geoscience and Remote Sensing Letters, 2015

Land, 2015

This study investigates how two existing pan-tropical above-ground biomass (AGB) maps can be comb... more This study investigates how two existing pan-tropical above-ground biomass (AGB) maps can be combined to derive forest ecosystem specific carbon estimates. Several data-fusion models which combine these AGB maps according to their local correlations with independent datasets such as the spectral bands of SPOT VEGETATION imagery are analyzed. Indeed these spectral bands convey information about vegetation type and structure which can be related to biomass values. Our study area is the island of Borneo. The data-fusion models are evaluated against a reference AGB map available for two forest concessions in Sabah. The highest accuracy was achieved by a model which combines the AGB maps according to the mean of the local correlation coefficients calculated over different kernel sizes. Combining the resulting AGB map with a new Borneo land cover map (whose overall accuracy has been estimated at 86.5%) leads to average AGB estimates of 279.8 t/ha and 233.1 t/ha for forests and degraded forests respectively. Lowland dipterocarp and mangrove forests have the highest

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2013

Forest monitoring from earth observation is crucial over tropical regions to assess forest extent... more Forest monitoring from earth observation is crucial over tropical regions to assess forest extent and provide up-to-date estimates of deforestation rates. Based on a systematic sample of 20x20 km size sites, a processing chain has been developed at the European Commission's Joint Research Centre (JRC) for producing deforestation estimates between years 1990, 2000 and 2005. Whereas this monitoring exercise was based on Landsat imagery, limitations in Landsat availability over Central Africa for year 2010 required alternative imagery such as the Disaster Monitoring Constellation (DMC). The classification module of the existing JRC processing chain is based on tasseled caps analysis (TCap-based). We adapted this module to DMC imagery by selecting the most suitable object-features through their assessments using a sub-sample of existing land-cover maps of years 1990 and 2000. The processing chain is adapted for the production of land-cover change maps between years 2000 and 2010. The accuracy of the land-cover maps produced for year 2010 with the two methods (original TCap-based and adapted Multi-Sensor)

Remote Sensing of Environment, 2011

The TREES-3 project of the Joint Research Centre aims at assessing tropical forest cover changes ... more The TREES-3 project of the Joint Research Centre aims at assessing tropical forest cover changes for the periods 1990-2000 and 2000-2010 using a sample-based approach. This paper refers to the 1990-2000 assessment. Extracts of Landsat satellite imagery (20 km× 20 km) are analyzed for these reference dates for more than 4000 sample sites distributed systematically across the tropical belt. For the processing and analysis of such a large amount of satellite imagery a robust methodological approach for forest mapping and change detection has been developed. This approach comprises two automated steps of multi-date image segmentation and object-based land cover classification (based on a supervised spectral library), followed by an intense phase of visual control and expert refinement. Image segmentation is done at two spatial scales, introducing the concept of a minimum mapping unit via the automated selection of a site-specific scale parameter. The automated segmentation of land cover polygons and the pre-classification of land cover types mainly aim at avoiding manual delineation and at reducing the efforts of visual interpretation of land cover to a reasonable level, making the analysis of 4000 sample sites feasible. The importance of visual control and correction can be perceived when comparing to the initial automatic classification result: about 20% of the polygon labels were changed through expert knowledge by visual interpretation. The component of visual refinement of the mapping results had also a notable impact on forest area and change estimates: for a set of sample sites in Southeast Asia (~90% of all sites of SE-Asia) the rate of change in tree cover (deforestation) was assessed at 0.9% and 1.6% before and after visual control, respectively.

PLoS ONE, 2013

There is an emerging consensus that protected areas are key in reducing adverse land-cover change... more There is an emerging consensus that protected areas are key in reducing adverse land-cover change, but their efficacy remains difficult to quantify. Many previous assessments of protected area effectiveness have compared changes between sets of protected and unprotected sites that differ systematically in other potentially confounding respects (e.g. altitude, accessibility), have considered only forest loss or changes at single sites, or have analysed changes derived from land-cover data of low spatial resolution. We assessed the effectiveness of protection in reducing land-cover change in Important Bird Areas (IBAs) across Africa using a dedicated visual interpretation of higher resolution satellite imagery. We compared rates of change in natural land-cover over a c. 20-year period from around 1990 at a large number of points across 45 protected IBAs to those from 48 unprotected IBAs. A matching algorithm was used to select sample points to control for potentially confounding differences between protected and unprotected IBAs. The rate of loss of natural land-cover at sample points within protected IBAs was just 42% of that at matched points in unprotected IBAs. Conversion was especially marked in forests, but protection reduced rates of forest loss by a similar relative amount. Rates of conversion increased from the centre to the edges of both protected and unprotected IBAs, but rates of loss in 20-km buffer zones surrounding protected IBAs and unprotected IBAs were similar, with no evidence of displacement of conversion from within protected areas to their immediate surrounds (leakage).

ISPRS Journal of Photogrammetry and Remote Sensing, 2011

In support to the Remote Sensing Survey of the global Forest Resource Assessment 2010, the TREES-... more In support to the Remote Sensing Survey of the global Forest Resource Assessment 2010, the TREES-3 project has processed more than 12,000 Landsat TM and ETM+ data subsets systematically distributed over the tropics. The project aims at deriving area estimates of tropical forest cover change for the periods 1990-2000-2005. The paper presents the pre-processing steps applied in an operational and robust manner to this large amount of multi-date and multi-scene imagery: conversion to top-of-atmosphere reflectance, cloud and cloud shadow detection, haze correction and image radiometric normalization. The results show that the haze correction algorithm has improved the visual appearance of the image and significantly corrected the digital numbers for Landsat visible bands, especially the red band. The impact of the normalization procedures (forest normalization and relative normalization) was assessed on 210 image pairs: in all cases the correlation between the spectral values of the same land cover in both images was improved. The developed automatic pre-processing chain provided a consistent multi-temporal data set across the tropics that will constitute the basis for an automatic object-based supervised classification. Ó

IEEE Transactions on Geoscience and Remote Sensing, 2000

set of spectral categories, has been downscaled to properly deal with spaceborne multispectral im... more set of spectral categories, has been downscaled to properly deal with spaceborne multispectral imaging sensors whose spectral resolution overlaps with, but is inferior to Landsat's, namely: 1) Satellite Pour l'Observation de la Terre (SPOT)-4/-5, Indian

IEEE Transactions on Geoscience and Remote Sensing, 2000

The increasing amount of remote sensing (RS) imagery acquired from multiple platforms and the rec... more The increasing amount of remote sensing (RS) imagery acquired from multiple platforms and the recent announcements that scientists and decision makers around the world will soon have unrestricted access at no charge to large-scale spaceborne multispectral (MS) image databases make urgent the need to develop easy-to-use, effective, efficient, robust, and scalable satellite-based measurement systems. In these scientific and industrial contexts, it is well known that, to date, the operational performance of existing stratified non-Lambertian (anisotropic) topographic correction (SNLTOC) algorithms has been limited by the need for a priori knowledge of structural landscape characteristics, such as surface roughness which is land cover class specific. In practice, to overcome the circular nature of the SNLTOC problem, a mutually exclusive and totally exhaustive land cover classification map of a spaceborne MS image is required before SNLTOC takes place. This system requirement is fulfilled by the original operational automatic two-stage SNLTOC approach presented in this paper which comprises, in cascade, 1) an automatic stratification first stage and 2) a second-stage ordinary SNLTOC method selected from the literature. The former combines 1) four subsymbolic digital-elevation-model-derived strata, namely, horizontal areas, self-shadows, and sunlit slopes either facing the sun or facing away from the sun, and 2) symbolic (semantic) strata generated from the input MS image by an operational fully automated spectral-rule-based decision-tree preliminary classifier recently presented in RS literature. In this paper, first, previous works related to the TOC subject are surveyed, and next, the novel operational two-stage SNLTOC system is presented. Finally, the original two-stage SNLTOC system is validated in up to 19 experiments where the system's capability of reducing within-stratum spectral variance while preserving pixel-based spectral patterns (shapes) is assessed quantitatively.

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IEEE Transactions on Geoscience and Remote Sensing, 2000

In our two-part paper [1], (this issue, pp. 1299-1354), there are two errors which we correct here.

Global Change Biology, 2014

We estimate changes in forest cover (deforestation and forest regrowth) in the tropics for the tw... more We estimate changes in forest cover (deforestation and forest regrowth) in the tropics for the two last decades (1990-2000 and 2000-2010) based on a sample of 4000 units of 10 910 km size. Forest cover is interpreted from satellite imagery at 30 9 30 m resolution. Forest cover changes are then combined with pan-tropical biomass maps to estimate carbon losses. We show that there was a gross loss of tropical forests of 8.0 million ha yr À1 in the 1990s and 7.6 million ha yr À1 in the 2000s (0.49% annual rate), with no statistically significant difference. Humid forests account for 64% of the total forest cover in 2010 and 54% of the net forest loss during second study decade. Losses of forest cover and Other Wooded Land (OWL) cover result in estimates of carbon losses which are similar for 1990s and 2000s at 887 MtC yr À1 (range: 646-1238) and 880 MtC yr À1 (range: 602-1237) respectively, with humid regions contributing two-thirds. The estimates of forest area changes have small statistical standard errors due to large sample size. We also reduce uncertainties of previous estimates of carbon losses and removals. Our estimates of forest area change are significantly lower as compared to national survey data. We reconcile recent low estimates of carbon emissions from tropical deforestation for early 2000s and show that carbon loss rates did not change between the two last decades. Carbon losses from deforestation represent circa 10% of Carbon emissions from fossil fuel combustion and cement production during the last decade (2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010). Our estimates of annual removals of carbon from forest regrowth at 115 MtC yr À1 (range: 61-168) and 97 MtC yr À1 (53-141) for the 1990s and 2000s respectively are five to fifteen times lower than earlier published estimates.

The Digital Observatory for Protected Areas (DOPA) is a biodiversity information system currently... more The Digital Observatory for Protected Areas (DOPA) is a biodiversity information system currently developed as a set of interoperable web services at the Joint Research Centre of the European Commission in collaboration with other international organizations, including GBIF, UNEP-WCMC, Birdlife International and RSPB. DOPA is not only designed to assess the state and pressure of Protected Areas (PAs) and to prioritize them accordingly, in order to support decision making and fund allocation processes, but it is also conceived as a monitoring and modelling service. To capture the dynamics of spatiotemporal changes in habitats and anthropogenic pressure on PAs, the automatic collection and processing of remote sensing data are at the heart of the system. The purpose of this paper is to highlight the variety of uses of remote sensing data by the DOPA, the integration with other data sources, the practical implementation according to an architecture grounded in international initiatives such as GEOSS, GSDI and INSPIRE, and applications in monitoring and ecological modelling.

… 2010, held 2-7 May …, May 1, 2010

Fire is an important ecological factor in many natural ecosystems. Without doubt one of the biome... more Fire is an important ecological factor in many natural ecosystems. Without doubt one of the biomes with the highest fire activity in the world is the African savannah. Savannahs have evolved with fires since climate in these regions is characterized by definite dry and wet seasons that ...

Time series of fire occurrence, derived from MODIS data, have been used to characterise the spati... more Time series of fire occurrence, derived from MODIS data, have been used to characterise the spatio-temporal distribution of fire events during the 2004-2009 period in 17 protected areas (PAs) of West and Central Africa, with particular attention to those of the SUN network in Senegal, Burkina Faso, Benin and Niger. The temporal distribution of the fire activity and the number of fire occurences are quite different inside the PAs and in their surrounding area. A progressive increase of the length of the burning season is observed in the West Africa PAs. Quantitatively, the general trend over the last five years is an increase of the fire density (+22%) inside the PAs and a decrease (−27%) outside.

– Research groups at the Joint Research Centre (JRC) have been heavily involved in the developmen... more – Research groups at the Joint Research Centre (JRC) have been heavily involved in the development of methods for monitoring forest cover resources in a global perspective. A JRC project aims at estimating forest cover changes for the periods 1990-2000-2005 based on a systematic sample of medium ,resolution satellite imagery from pan- tropical to sub-regional levels. The project is

IEEE Geoscience and Remote Sensing Letters, 2015

Land, 2015

This study investigates how two existing pan-tropical above-ground biomass (AGB) maps can be comb... more This study investigates how two existing pan-tropical above-ground biomass (AGB) maps can be combined to derive forest ecosystem specific carbon estimates. Several data-fusion models which combine these AGB maps according to their local correlations with independent datasets such as the spectral bands of SPOT VEGETATION imagery are analyzed. Indeed these spectral bands convey information about vegetation type and structure which can be related to biomass values. Our study area is the island of Borneo. The data-fusion models are evaluated against a reference AGB map available for two forest concessions in Sabah. The highest accuracy was achieved by a model which combines the AGB maps according to the mean of the local correlation coefficients calculated over different kernel sizes. Combining the resulting AGB map with a new Borneo land cover map (whose overall accuracy has been estimated at 86.5%) leads to average AGB estimates of 279.8 t/ha and 233.1 t/ha for forests and degraded forests respectively. Lowland dipterocarp and mangrove forests have the highest

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2013

Forest monitoring from earth observation is crucial over tropical regions to assess forest extent... more Forest monitoring from earth observation is crucial over tropical regions to assess forest extent and provide up-to-date estimates of deforestation rates. Based on a systematic sample of 20x20 km size sites, a processing chain has been developed at the European Commission's Joint Research Centre (JRC) for producing deforestation estimates between years 1990, 2000 and 2005. Whereas this monitoring exercise was based on Landsat imagery, limitations in Landsat availability over Central Africa for year 2010 required alternative imagery such as the Disaster Monitoring Constellation (DMC). The classification module of the existing JRC processing chain is based on tasseled caps analysis (TCap-based). We adapted this module to DMC imagery by selecting the most suitable object-features through their assessments using a sub-sample of existing land-cover maps of years 1990 and 2000. The processing chain is adapted for the production of land-cover change maps between years 2000 and 2010. The accuracy of the land-cover maps produced for year 2010 with the two methods (original TCap-based and adapted Multi-Sensor)

Remote Sensing of Environment, 2011

The TREES-3 project of the Joint Research Centre aims at assessing tropical forest cover changes ... more The TREES-3 project of the Joint Research Centre aims at assessing tropical forest cover changes for the periods 1990-2000 and 2000-2010 using a sample-based approach. This paper refers to the 1990-2000 assessment. Extracts of Landsat satellite imagery (20 km× 20 km) are analyzed for these reference dates for more than 4000 sample sites distributed systematically across the tropical belt. For the processing and analysis of such a large amount of satellite imagery a robust methodological approach for forest mapping and change detection has been developed. This approach comprises two automated steps of multi-date image segmentation and object-based land cover classification (based on a supervised spectral library), followed by an intense phase of visual control and expert refinement. Image segmentation is done at two spatial scales, introducing the concept of a minimum mapping unit via the automated selection of a site-specific scale parameter. The automated segmentation of land cover polygons and the pre-classification of land cover types mainly aim at avoiding manual delineation and at reducing the efforts of visual interpretation of land cover to a reasonable level, making the analysis of 4000 sample sites feasible. The importance of visual control and correction can be perceived when comparing to the initial automatic classification result: about 20% of the polygon labels were changed through expert knowledge by visual interpretation. The component of visual refinement of the mapping results had also a notable impact on forest area and change estimates: for a set of sample sites in Southeast Asia (~90% of all sites of SE-Asia) the rate of change in tree cover (deforestation) was assessed at 0.9% and 1.6% before and after visual control, respectively.

PLoS ONE, 2013

There is an emerging consensus that protected areas are key in reducing adverse land-cover change... more There is an emerging consensus that protected areas are key in reducing adverse land-cover change, but their efficacy remains difficult to quantify. Many previous assessments of protected area effectiveness have compared changes between sets of protected and unprotected sites that differ systematically in other potentially confounding respects (e.g. altitude, accessibility), have considered only forest loss or changes at single sites, or have analysed changes derived from land-cover data of low spatial resolution. We assessed the effectiveness of protection in reducing land-cover change in Important Bird Areas (IBAs) across Africa using a dedicated visual interpretation of higher resolution satellite imagery. We compared rates of change in natural land-cover over a c. 20-year period from around 1990 at a large number of points across 45 protected IBAs to those from 48 unprotected IBAs. A matching algorithm was used to select sample points to control for potentially confounding differences between protected and unprotected IBAs. The rate of loss of natural land-cover at sample points within protected IBAs was just 42% of that at matched points in unprotected IBAs. Conversion was especially marked in forests, but protection reduced rates of forest loss by a similar relative amount. Rates of conversion increased from the centre to the edges of both protected and unprotected IBAs, but rates of loss in 20-km buffer zones surrounding protected IBAs and unprotected IBAs were similar, with no evidence of displacement of conversion from within protected areas to their immediate surrounds (leakage).

ISPRS Journal of Photogrammetry and Remote Sensing, 2011

In support to the Remote Sensing Survey of the global Forest Resource Assessment 2010, the TREES-... more In support to the Remote Sensing Survey of the global Forest Resource Assessment 2010, the TREES-3 project has processed more than 12,000 Landsat TM and ETM+ data subsets systematically distributed over the tropics. The project aims at deriving area estimates of tropical forest cover change for the periods 1990-2000-2005. The paper presents the pre-processing steps applied in an operational and robust manner to this large amount of multi-date and multi-scene imagery: conversion to top-of-atmosphere reflectance, cloud and cloud shadow detection, haze correction and image radiometric normalization. The results show that the haze correction algorithm has improved the visual appearance of the image and significantly corrected the digital numbers for Landsat visible bands, especially the red band. The impact of the normalization procedures (forest normalization and relative normalization) was assessed on 210 image pairs: in all cases the correlation between the spectral values of the same land cover in both images was improved. The developed automatic pre-processing chain provided a consistent multi-temporal data set across the tropics that will constitute the basis for an automatic object-based supervised classification. Ó

IEEE Transactions on Geoscience and Remote Sensing, 2000

set of spectral categories, has been downscaled to properly deal with spaceborne multispectral im... more set of spectral categories, has been downscaled to properly deal with spaceborne multispectral imaging sensors whose spectral resolution overlaps with, but is inferior to Landsat's, namely: 1) Satellite Pour l'Observation de la Terre (SPOT)-4/-5, Indian

IEEE Transactions on Geoscience and Remote Sensing, 2000

The increasing amount of remote sensing (RS) imagery acquired from multiple platforms and the rec... more The increasing amount of remote sensing (RS) imagery acquired from multiple platforms and the recent announcements that scientists and decision makers around the world will soon have unrestricted access at no charge to large-scale spaceborne multispectral (MS) image databases make urgent the need to develop easy-to-use, effective, efficient, robust, and scalable satellite-based measurement systems. In these scientific and industrial contexts, it is well known that, to date, the operational performance of existing stratified non-Lambertian (anisotropic) topographic correction (SNLTOC) algorithms has been limited by the need for a priori knowledge of structural landscape characteristics, such as surface roughness which is land cover class specific. In practice, to overcome the circular nature of the SNLTOC problem, a mutually exclusive and totally exhaustive land cover classification map of a spaceborne MS image is required before SNLTOC takes place. This system requirement is fulfilled by the original operational automatic two-stage SNLTOC approach presented in this paper which comprises, in cascade, 1) an automatic stratification first stage and 2) a second-stage ordinary SNLTOC method selected from the literature. The former combines 1) four subsymbolic digital-elevation-model-derived strata, namely, horizontal areas, self-shadows, and sunlit slopes either facing the sun or facing away from the sun, and 2) symbolic (semantic) strata generated from the input MS image by an operational fully automated spectral-rule-based decision-tree preliminary classifier recently presented in RS literature. In this paper, first, previous works related to the TOC subject are surveyed, and next, the novel operational two-stage SNLTOC system is presented. Finally, the original two-stage SNLTOC system is validated in up to 19 experiments where the system's capability of reducing within-stratum spectral variance while preserving pixel-based spectral patterns (shapes) is assessed quantitatively.

[

IEEE Transactions on Geoscience and Remote Sensing, 2000

In our two-part paper [1], (this issue, pp. 1299-1354), there are two errors which we correct here.

Global Change Biology, 2014

We estimate changes in forest cover (deforestation and forest regrowth) in the tropics for the tw... more We estimate changes in forest cover (deforestation and forest regrowth) in the tropics for the two last decades (1990-2000 and 2000-2010) based on a sample of 4000 units of 10 910 km size. Forest cover is interpreted from satellite imagery at 30 9 30 m resolution. Forest cover changes are then combined with pan-tropical biomass maps to estimate carbon losses. We show that there was a gross loss of tropical forests of 8.0 million ha yr À1 in the 1990s and 7.6 million ha yr À1 in the 2000s (0.49% annual rate), with no statistically significant difference. Humid forests account for 64% of the total forest cover in 2010 and 54% of the net forest loss during second study decade. Losses of forest cover and Other Wooded Land (OWL) cover result in estimates of carbon losses which are similar for 1990s and 2000s at 887 MtC yr À1 (range: 646-1238) and 880 MtC yr À1 (range: 602-1237) respectively, with humid regions contributing two-thirds. The estimates of forest area changes have small statistical standard errors due to large sample size. We also reduce uncertainties of previous estimates of carbon losses and removals. Our estimates of forest area change are significantly lower as compared to national survey data. We reconcile recent low estimates of carbon emissions from tropical deforestation for early 2000s and show that carbon loss rates did not change between the two last decades. Carbon losses from deforestation represent circa 10% of Carbon emissions from fossil fuel combustion and cement production during the last decade (2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010). Our estimates of annual removals of carbon from forest regrowth at 115 MtC yr À1 (range: 61-168) and 97 MtC yr À1 (53-141) for the 1990s and 2000s respectively are five to fifteen times lower than earlier published estimates.

The Digital Observatory for Protected Areas (DOPA) is a biodiversity information system currently... more The Digital Observatory for Protected Areas (DOPA) is a biodiversity information system currently developed as a set of interoperable web services at the Joint Research Centre of the European Commission in collaboration with other international organizations, including GBIF, UNEP-WCMC, Birdlife International and RSPB. DOPA is not only designed to assess the state and pressure of Protected Areas (PAs) and to prioritize them accordingly, in order to support decision making and fund allocation processes, but it is also conceived as a monitoring and modelling service. To capture the dynamics of spatiotemporal changes in habitats and anthropogenic pressure on PAs, the automatic collection and processing of remote sensing data are at the heart of the system. The purpose of this paper is to highlight the variety of uses of remote sensing data by the DOPA, the integration with other data sources, the practical implementation according to an architecture grounded in international initiatives such as GEOSS, GSDI and INSPIRE, and applications in monitoring and ecological modelling.

… 2010, held 2-7 May …, May 1, 2010

Fire is an important ecological factor in many natural ecosystems. Without doubt one of the biome... more Fire is an important ecological factor in many natural ecosystems. Without doubt one of the biomes with the highest fire activity in the world is the African savannah. Savannahs have evolved with fires since climate in these regions is characterized by definite dry and wet seasons that ...

Time series of fire occurrence, derived from MODIS data, have been used to characterise the spati... more Time series of fire occurrence, derived from MODIS data, have been used to characterise the spatio-temporal distribution of fire events during the 2004-2009 period in 17 protected areas (PAs) of West and Central Africa, with particular attention to those of the SUN network in Senegal, Burkina Faso, Benin and Niger. The temporal distribution of the fire activity and the number of fire occurences are quite different inside the PAs and in their surrounding area. A progressive increase of the length of the burning season is observed in the West Africa PAs. Quantitatively, the general trend over the last five years is an increase of the fire density (+22%) inside the PAs and a decrease (−27%) outside.

– Research groups at the Joint Research Centre (JRC) have been heavily involved in the developmen... more – Research groups at the Joint Research Centre (JRC) have been heavily involved in the development of methods for monitoring forest cover resources in a global perspective. A JRC project aims at estimating forest cover changes for the periods 1990-2000-2005 based on a systematic sample of medium ,resolution satellite imagery from pan- tropical to sub-regional levels. The project is