Changes in land use associated with the suppression of native vegetation can greatly alter the landscape configuration, affecting biodiversity and environmental services availability. This study analyzes how changes i...Changes in land use associated with the suppression of native vegetation can greatly alter the landscape configuration, affecting biodiversity and environmental services availability. This study analyzes how changes in land use affect landscape patterns of vegetation remnant over a 10 year period. We quantified spatial landscape patterns throughout a hydrographic basin for the years 2002, 2008, 2010 and 2012, using nine landscape metrics. An indicator of integrity was used to details the transformation processes occurring in the basin that could be used to monitor the impact of landscape changes and its spatial patterning. Results showed that over this decade, extension of farming activities reduced the cover of native vegetation by 4.4%, with grassy-woody savanna, wooded savanna and forested savanna impacted especially strongly. Suppression of vegetation across this period reduced the size of fragments and their connectivity. The landscape fragmentation indicator indicated that the fragmentation pattern varied spatially, with the upland areas along river headwaters, being most fragmented. Areas of floodplains vegetation, belonged to the Pantanal Wetland, although in better integrity states, are the most threatened by current pressures of land use change. An intense recovery program for headwaters and aquifer recharge areas, as well as riparian forests, is recommended to avoid the future depletion of water production. Besides, we also recommend the maintenance and recovering of the connectivity of the current remaining patches of natural vegetation corridors and elaboration of specific laws that incoporate the consolidated scientific knowladge about wetland ecosystem functioning, like the Pantanal.展开更多
Moderate resolution imaging spectroradiometer (MODIS) time series (TS) have been widely applied for flood monitoring in large tropical wetlands. However, little systematic work is available on the influence of pixel q...Moderate resolution imaging spectroradiometer (MODIS) time series (TS) have been widely applied for flood monitoring in large tropical wetlands. However, little systematic work is available on the influence of pixel quality, vegetation cover, and the annual hydroclimatic cycle on classification performance. In this study, this issue is examined based on a six-year, 250 m resolution MOD13Q1 TS underpinned by extensive in situ measurements. The most parsimonious logistic regression model was obtained for land surface water index (LSWI) and enhanced vegetation index (EVI). The inclusion of the 500 m MCD12Q1 land cover Type 2 product improves accuracy. Performance markedly decreases for subsets that include pixels with a VI quality assurance (QA) level poorer than 0110 and/or a pixel reliability (PR) of three. When a Savitzky-Golay filter was used for TS reconstitution, performance is slightly lower than those obtained in a classification of a VI QA 0001 or PR = 0 level strata;moreover, these have the advantage of gap-free flood monitoring. The overall accuracy (OA) of the PR = 0 subset is better for grasslands, and slightly lower for Savannah, and for woodland and forests. The average OA is highest for the dry season, intermediate for the rainy/flooded season, and lowest for the transitional seasons, when the wetland becomes flooded or dries. Comparisons of internal, k-fold, and external validations indicate that only external validation enables a realistic assessment of flood-mapping performance. The complete substitution of PR = 3 pixels by filled-in values is recommended for operational flood monitoring, and it is concluded that the use of the simplified PR metrics as filtering criteria for gap filling and smoothing is sufficient for flood monitoring in the Pantanal. Classification metrics vary more strongly as a function of the hydrological period than by vegetation cover. MOD13Q1 users should be aware that OA in forest stands during the transition seasons are, on average, 25 p.p. lower than the average OAs obtained for the entire series.展开更多
文摘Changes in land use associated with the suppression of native vegetation can greatly alter the landscape configuration, affecting biodiversity and environmental services availability. This study analyzes how changes in land use affect landscape patterns of vegetation remnant over a 10 year period. We quantified spatial landscape patterns throughout a hydrographic basin for the years 2002, 2008, 2010 and 2012, using nine landscape metrics. An indicator of integrity was used to details the transformation processes occurring in the basin that could be used to monitor the impact of landscape changes and its spatial patterning. Results showed that over this decade, extension of farming activities reduced the cover of native vegetation by 4.4%, with grassy-woody savanna, wooded savanna and forested savanna impacted especially strongly. Suppression of vegetation across this period reduced the size of fragments and their connectivity. The landscape fragmentation indicator indicated that the fragmentation pattern varied spatially, with the upland areas along river headwaters, being most fragmented. Areas of floodplains vegetation, belonged to the Pantanal Wetland, although in better integrity states, are the most threatened by current pressures of land use change. An intense recovery program for headwaters and aquifer recharge areas, as well as riparian forests, is recommended to avoid the future depletion of water production. Besides, we also recommend the maintenance and recovering of the connectivity of the current remaining patches of natural vegetation corridors and elaboration of specific laws that incoporate the consolidated scientific knowladge about wetland ecosystem functioning, like the Pantanal.
文摘Moderate resolution imaging spectroradiometer (MODIS) time series (TS) have been widely applied for flood monitoring in large tropical wetlands. However, little systematic work is available on the influence of pixel quality, vegetation cover, and the annual hydroclimatic cycle on classification performance. In this study, this issue is examined based on a six-year, 250 m resolution MOD13Q1 TS underpinned by extensive in situ measurements. The most parsimonious logistic regression model was obtained for land surface water index (LSWI) and enhanced vegetation index (EVI). The inclusion of the 500 m MCD12Q1 land cover Type 2 product improves accuracy. Performance markedly decreases for subsets that include pixels with a VI quality assurance (QA) level poorer than 0110 and/or a pixel reliability (PR) of three. When a Savitzky-Golay filter was used for TS reconstitution, performance is slightly lower than those obtained in a classification of a VI QA 0001 or PR = 0 level strata;moreover, these have the advantage of gap-free flood monitoring. The overall accuracy (OA) of the PR = 0 subset is better for grasslands, and slightly lower for Savannah, and for woodland and forests. The average OA is highest for the dry season, intermediate for the rainy/flooded season, and lowest for the transitional seasons, when the wetland becomes flooded or dries. Comparisons of internal, k-fold, and external validations indicate that only external validation enables a realistic assessment of flood-mapping performance. The complete substitution of PR = 3 pixels by filled-in values is recommended for operational flood monitoring, and it is concluded that the use of the simplified PR metrics as filtering criteria for gap filling and smoothing is sufficient for flood monitoring in the Pantanal. Classification metrics vary more strongly as a function of the hydrological period than by vegetation cover. MOD13Q1 users should be aware that OA in forest stands during the transition seasons are, on average, 25 p.p. lower than the average OAs obtained for the entire series.
