Monitoring land cover change of the dryland forest landscape of Central Chile (1975–2008)

Las figuras que contiene el documento se localizan al final del mismo.Land cover and its configuration in the landscape are crucial components in the provision of biodiversity and ecosystem services. In Mediterranean regions, natural landscapes mostly covered by evergreen vegetation have been to a large extent transformed into cultural landscapes since long time ago. We investigated land cover changes in Central Chile using multi-temporal satellite imagery taken in 1975, 1985, 1999 and 2008. The major trends in this highly dynamic landscape were reduction of dryland forest and conversion of shrubland to intensive land uses such as farmland. The average net annual deforestation rate was −1.7%, and shrubland reduction occurred at an annual rate of −0.7%; agriculture, urban areas and timber plantations increased at annual rates of 1.1%, 2.7% and 3.2%, respectively, during the 1975–2008 period. Total forest and shrubland loss rates were partly offset by passive revegetation. However, most of the areas that were passively revegetated remained as shrubland and did not turn into forests due to a low capacity of forest recovery. This resulted in a progressive loss and degradation of dryland forest over the entire region. Overall, the documented land cover changes increase provisioning services such as crops, cattle, and timber that are characteristic of cultural landscapes in the area but may cause an irreversible loss of biodiversity and a depletion of other ecological services provided by forests and shrubland. The implications for conservation of this area and the need for territorial planning and adapted land-use strategies are discussed

Empleo de la Teledetección en el análisis de la deforestación tropical : el caso de la reserva forestal de Ticoporo (Venezuela)

En este trabajo se ensaya una metodología sencilla de análisis multitemporal para el\ud seguimiento del proceso de deforestación en la Reserva de Ticoporo, Venezuela. Para llevar a cabo este estudio se ha utilizado una serie de fotografías aéreas (año 1962) y cuatro imágenes de satélite, procedentes de diversos sensores de alta resolución espacial (Landsat MSS y TM y SPOT-HRV), de los años 1972, 1989, 1993 y 1997. De la fotointerpretación del primer documento\ud se obtuvo un mapa de formaciones de vegetación, que posteriormente se reagrupó a dos únicas categorías, zonas forestales y agrícolas. Las imágenes se clasificaron en estas mismas categorías mediante el establecimiento de umbrales de sus respectivos índices de vegetación (NDVI). Se realizó una tabulación cruzada de cada par de imágenes clasificadas de fechas\ud consecutivas (1962-1972, 1972-1989, 1989-1993, y 1993-1997), así como de la primera y última fecha, para extraer las zonas de cambio y las estables durante ese intervalo de tiempo. La deforestación experimentada en esta zona puede cifrarse en unas 80.000 ha, lo que supone el 60% del área de estudio. La técnica se mostró de gran utilidad para el seguimiento de este\ud fenómeno, pudiendo ser utilizada por los órganos de gestión para paliar los efectos negativos asociados a los procesos de deforestación. Por último, se lleva a cabo un sencillo análisis de la evolución del patrón espacial del área de estudio en ese periodo. El análisis de los cambios\ud experimentados en las manchas (patches) del área de estudio, contabilizando el número de\ud polígonos, su densidad, tamaño promedio y diversidad, muestran una tendencia al aumento de la diversidad espacial (mayor fragmentación, pues el espacio original se parcela), pese a la pérdida de diversidad vegetal (reducción de las cubiertas forestales).This study presents a simple multi-temporal analysis methodology to monitor the deforestation\ud process in the Tipocoro Reserve (Venezuela). A series of air photos (1962) plus four satellite\ud images from 1972, 1989, 1993 and 1997 were used.\ud A vegetation type map was obtained from photo-interpretation, which was later reclassified\ud into just two categories: forests and crops. The satellite images were also classified into these two\ud same categories by establishing thresholds for each of their vegetation indices (NDVI). A cross\ud tabulation was carried out for each pair of classified images in chronological order (1962-1972,\ud 1972-1989, 1989-1993, and 1993-1997) plus a pair corresponding to the first and last date (1962-\ud 1997), in order to determine changes during this time period. The total deforestation can be\ud estimated in approximately 80,000 ha, which accounts for 60% of the study area.\ud The method used proved to be very useful for deforestation monitoring purposes and can be\ud implemented by forestry management officials to control its effects.\ud Finally, a simple analysis was carried out to study the spatial trends in the study area throughout\ud this period. Changes in the study area’s patches were analysed taking into account the number\ud of polygons, density, average size and diversity. Results showed that spatial diversity increased\ud (higher fragmentations, since the original area is parceled out), in spite of the decrease in\ud vegetation diversity resulting from losses in forested cover area

Optimal Landsat ETM+ band's combination for Colombian savannah discrimination

Resumen: Algunos autores han encontrado problemas de discriminación entre las clases de ocupación del suelo presentes en sabanas tropicales, al utilizar imágenes Landsat. Este trabajo de investigación indaga acerca de la combinación de bandas más apropiada, entre seis distintas, para diferenciar dichas clases en un sector de sabanas colombianas, utilizando una imagen Landsat ETM+. Las combinaciones incluyen las bandas espectrales no térmicas (combinación de referencia), a la que secuencial e individualmente se le adicionaba una imagen de entropía obtenida de la banda 4, el primer componente principal de todas las bandas, los componentes verdor y brillo de la transformación Tasseled Cap y el índice de vegetación NDVI. Inicialmente se utilizó análisis discriminante por pasos para clasificar los niveles digitales de 352 puntos distribuidos de forma aleatoria en la imagen, considerando las clases de cobertura y uso de la tierra presentes. Posteriormente se realizaron clasificaciones supervisadas, mediante el algoritmo de máxima probabilidad, utilizando las mismas combinaciones del análisis discriminante. Los resultados obtenidos, tanto en el análisis discriminante como en las clasificaciones supervisadas, dan cuenta que la mayor fiabilidad respecto a la combinación de referencia se logra adicionando la imagen de entropía a las bandas espectrales. Por tanto, el análisis discriminante permite seleccionar, entre muchas bandas, la combinación más adecuada para obtener la mejor discriminación. ABSTRACT. Some authors have found problems of discrimination among the land cover/use categories present on the tropical savannah, when using Landsat images. This research inquires about the more appropriate band's combination, using six different ones, to differentiate the land cover/use classes in a sector of Colombian savannahs, using an Landsat ETM+ image. The combinations include the spectral bands (combination of reference), to which sequential and individually was added an image of entropy obtained from band 4, the first principal component image obtained from all bands, the components Green and Brightness of the Tasseled CAP transformation and the NDV1. Initially a stepwise discriminant analysis was used to classify the digital number of 352 points randomly distributed in the image, considering the land cover/use classes of the savannah. Finally, several supervised classifications were made, by means of the Maximum Probability algorithm, using the same combinations of the discriminant analysis. The obtained results, in the discriminant analysis like as in the supervised classifications, give account that the greater accuracy with respect to the reference's combination was obtained adding the image of entropy to the spectral bands. Therefore, the discriminant analysis allows to select, between many bands, the most appropriated combination to obtain the best discrimination

Identifying Post-Fire Recovery Trajectories and Driving Factors Using Landsat Time Series in Fire-Prone Mediterranean Pine Forests

Wildfires constitute the most important natural disturbance of Mediterranean forests, driving vegetation dynamics. Although Mediterranean species have developed ecological post-fire recovery strategies, the impacts of climate change and changes in fire regimes may endanger their resilience capacity. This study aims at assessing post-fire recovery dynamics at different stages in two large fires that occurred in Mediterranean pine forests (Spain) using temporal segmentation of the Landsat time series (1994?2018). Landsat-based detection of Trends in Disturbance and Recovery (LandTrendr) was used to derive trajectory metrics from Tasseled Cap Wetness (TCW), sensitive to canopy moisture and structure, and Tasseled Cap Angle (TCA), related to vegetation cover gradients. Different groups of post-fire trajectories were identified through K-means clustering of the Recovery Ratios (RR) from fitted trajectories: continuous recovery, continuous recovery with slope changes, continuous recovery stabilized and non-continuous recovery. The influence of pre-fire conditions, fire severity, topographic variables and post-fire climate on recovery rates for each recovery category at successional stages was analyzed through Geographically Weighted Regression (GWR). The modeling results indicated that pine forest recovery rates were highly sensitive to post-fire climate in the mid and long-term and to fire severity in the short-term, but less influenced by topographic conditions (adjusted R-squared ranged from 0.58 to 0.88 and from 0.54 to 0.93 for TCA and TCW, respectively). Recovery estimation was assessed through orthophotos, showing a high accuracy (Dice Coefficient ranged from 0.81 to 0.97 and from 0.74 to 0.96 for TCA and TCW, respectively). This study provides new insights into the post-fire recovery dynamics at successional stages and driving factors. The proposed method could be an approach to model the recovery for the Mediterranean areas and help managers in determining which areas may not be able to recover naturally.Ministerio de Ciencia, Innovación y UniversidadesMinisterio de Economía y Competitivida

Assessing post-fire forest structure recovery by combining LiDAR data and Landsat time series in Mediterranean pine forests

Understanding post-fire recovery dynamics is critical for effective management that enhance forest resilience to fire. Mediterranean pine forests have been largely affected by wildfires, but the impacts of both changes in land use and climate endanger their capacity to naturally recover. Multispectral imagery is commonly used to estimate post-fire recovery, yet changes in forest structure must be considered for a comprehensive evaluation of forest recovery. In this research, we combine Light Detection And Ranging (LiDAR) with Landsat imagery to extrapolate forest structure variables over a 30-year period (1990?2020) to provide insights on how forest structure has recovered after fire in Mediterranean pine forests. Forest recovery was evaluated attending to vegetation cover (VC), tree cover (TC), mean height (MH) and heterogeneity (CVH). Structure variables were derived from two LiDAR acquisitions from 2016 and 2009, for calibration and independent spatial and temporal validation. A Support Vector Regression model (SVR) was calibrated to extrapolate LiDAR-derived variables using a series of Landsat imagery, achieving an R2 of 0.78, 0.64, 0.70 and 0.63, and a relative RMSE of 24.4%, 30.2%, 36.5% and 27.4% for VC, TC, MH and CVH, respectively. Models showed to be consistent in the temporal validation, although a wider variability was observed, with R2 ranging from 0.51 to 0.74. A different response to fire was revealed attending to forest cover and height since vegetation cover recovered to a pre-fire state but mean height did not 26-years after fire. Less than 50% of the area completely recovered to the pre-fire structure within 26 years, and the area subjected to fire recurrence showed signs of greater difficulty in initiating the recovery. Our results provide valuable information on forest structure recovery, which can support the implementation of mitigation and adaptation strategies that enhance fire resilience.Comunidad de Madri

Empleo de la Teledetección en el análisis de la deforestación tropical : el caso de la reserva forestal de Ticoporo (Venezuela)

En este trabajo se ensaya una metodología sencilla de análisis multitemporal para el seguimiento del proceso de deforestación en la Reserva de Ticoporo, Venezuela. Para llevar a cabo este estudio se ha utilizado una serie de fotografías aéreas (año 1962) y cuatro imágenes de satélite, procedentes de diversos sensores de alta resolución espacial (Landsat MSS y TM y SPOT-HRV), de los años 1972, 1989, 1993 y 1997. De la fotointerpretación del primer documento se obtuvo un mapa de formaciones de vegetación, que posteriormente se reagrupó a dos únicas categorías, zonas forestales y agrícolas. Las imágenes se clasificaron en estas mismas categorías mediante el establecimiento de umbrales de sus respectivos índices de vegetación (NDVI). Se realizó una tabulación cruzada de cada par de imágenes clasificadas de fechas consecutivas (1962-1972, 1972-1989, 1989-1993, y 1993-1997), así como de la primera y última fecha, para extraer las zonas de cambio y las estables durante ese intervalo de tiempo. La deforestación experimentada en esta zona puede cifrarse en unas 80.000 ha, lo que supone el 60% del área de estudio. La técnica se mostró de gran utilidad para el seguimiento de este fenómeno, pudiendo ser utilizada por los órganos de gestión para paliar los efectos negativos asociados a los procesos de deforestación. Por último, se lleva a cabo un sencillo análisis de la evolución del patrón espacial del área de estudio en ese periodo. El análisis de los cambios experimentados en las manchas (patches) del área de estudio, contabilizando el número de polígonos, su densidad, tamaño promedio y diversidad, muestran una tendencia al aumento de la diversidad espacial (mayor fragmentación, pues el espacio original se parcela), pese a la pérdida de diversidad vegetal (reducción de las cubiertas forestales).This study presents a simple multi-temporal analysis methodology to monitor the deforestation process in the Tipocoro Reserve (Venezuela). A series of air photos (1962) plus four satellite images from 1972, 1989, 1993 and 1997 were used. A vegetation type map was obtained from photo-interpretation, which was later reclassified into just two categories: forests and crops. The satellite images were also classified into these two same categories by establishing thresholds for each of their vegetation indices (NDVI). A cross tabulation was carried out for each pair of classified images in chronological order (1962-1972, 1972-1989, 1989-1993, and 1993-1997) plus a pair corresponding to the first and last date (1962- 1997), in order to determine changes during this time period. The total deforestation can be estimated in approximately 80,000 ha, which accounts for 60% of the study area. The method used proved to be very useful for deforestation monitoring purposes and can be implemented by forestry management officials to control its effects. Finally, a simple analysis was carried out to study the spatial trends in the study area throughout this period. Changes in the study area’s patches were analysed taking into account the number of polygons, density, average size and diversity. Results showed that spatial diversity increased (higher fragmentations, since the original area is parceled out), in spite of the decrease in vegetation diversity resulting from losses in forested cover area

Evolución de episodios pluviométricos en la Demarcación Hidrográfica del Júcar (1989-2016): del recurso al riesgo

Este trabajo aborda la clasificación y evolución diacrónica de los episodios de lluvia (1989-2016) en ambientes mediterráneos, en la Demarcación Hidrográfica del Júcar. En base a datos del SAIH, y siguiendo criterios hidrológicos, se seleccionan 698 episodios, que se caracterizan con indicadores de precipitación acumulada, intensidad y persistencia. Mediante un análisis cluster se identifican tres tipologías (episodios de recurso limitado, de gran recurso a largo plazo y de riesgo) y se analiza su evolución temporal, estableciendo diferencias entre los episodios de interior y de litoral. Los resultados muestran una tendencia hacia el incremento del riesgo en detrimento del recurso en los tres tipos, por descenso de los totales acumulados y aumento de las intensidades. Si bien la frecuencia anual de los eventos crece, la aportación de los de riesgo sube y la de los de recurso baja. Este comportamiento es más acusado en el interior que en la costa. Se apunta, además, un desplazamiento mensual de los tipos de episodios. Los que acumulan grandes totales se están trasladando de octubre a noviembre, donde pueden coincidir con los de riesgo que, a su vez, incrementan su probabilidad de ocurrencia. Esta sinergia entre sucesos copiosos e intensos supone un factor de riesgo añadido

Satellite Remote Sensing contributions to Wildland Fire Science and Management

No funding was received for this particular review, but support research was funded by the European Space Agency’s Climate Change Initiative Programme to Dr. Chuvieco.This paper reviews the most recent literature related to the use of remote sensing (RS) data in wildland fire management. Recent Findings Studies dealing with pre-fire assessment, active fire detection, and fire effect monitoring are reviewed in this paper. The analysis follows the different fire management categories: fire prevention, detection, and post-fire assessment. Extracting the main trends from each of these temporal sections, recent RS literature shows growing support of the combined use of different sensors, particularly optical and radar data and lidar and optical passive images. Dedicated fire sensors have been developed in the last years, but still, most fire products are derived from sensors that were designed for other purposes. Therefore, the needs of fire managers are not always met, both in terms of spatial and temporal scales, favouring global over local scales because of the spatial resolution of existing sensors. Lidar use on fuel types and post-fire regeneration is more local, and mostly not operational, but future satellite lidar systems may help to obtain operational products. Regional and global scales are also combined in the last years, emphasizing the needs of using upscaling and merging methods to reduce uncertainties of global products. Validation is indicated as a critical phase of any new RS-based product. It should be based on the independent reference information acquired from statistically derived samples. The main challenges of using RS for fire management rely on the need to improve the integration of sensors and methods to meet user requirements, uncertainty characterization of products, and greater efforts on statistical validation approaches.European Space Agenc

Characterizing global fire regimes from satellite-derived products

We identified four global fire regimes based on a k-means algorithm using five variables covering the spatial, temporal and magnitude dimensions of fires, derived from 19-year long satellite burned area and active fire products. Additionally, we assessed the relation of fire regimes to forest fuels distribution. The most extensive fire regime (35% of cells having fire activity) was characterized by a long fire season, medium size fire events, small burned area, high intensity and medium variability. The next most extensive fire regime (25.6%) presented a long fire season, large fire events and the highest mean burned area, yet it showed the lowest intensity and the least variability. The third group (22.07%) presented a short fire season, the lowest burned area, with medium-low intensity, the smallest fire patches and large variability. The fourth group (17.3%) showed the largest burned area with large fire patches of moderate intensity and low variability. Fire regimes and fuel types showed a statistically significant relation (CC = 0.58 and CC? = 0.67, p < 0.001), with most fuel types sustaining all fire regimes, although a clear prevalence was observed in some fuel types. Further efforts should be directed towards the standardization of the variables in order to facilitate comparison, analysis and monitoring of fire regimes and evaluate whether fire regimes are effectively changing and the possible drivers.Agencia Estatal de Investigació

Propuesta de un sistema espacialmente explícito para evaluar el peligro de incendios

Los incendios forestales suponen un factor muy destacado en la transformación ambiental de buena parte de los ecosistemas terrestres. Tienen impactos globales, afectando a la superficie forestal y a las emisiones de gases de efecto invernadero, y efectos locales, relacionados con la degradación de suelos, erosión, modificación de la dinámica de la vegetación y pérdida de recursos y de vidas humanas. La prevención de incendios resulta cada vez más crítica, para paliar los efectos negativos de los mismos. Se presentan en este trabajo las variables de entrada y el esquema de integración para estimar el peligro de ocurrencia de incendios que se desarrolló en el marco del proyecto Firemap. Se generó información de diversas fuentes, que hacen referencia a variables socio-económicas, así como al estado de los combustibles y las características del territorio, utilizando sistemas de información geográfica (SIG) e imágenes de satélite. Todas las variables se cartografiaron a una resolución espacial de un 1 km2 y se integraron en un servidor web, que estuvo operativo para su evaluación durante el verano de 2007. Se presenta la comparación entre la variación temporal de los índices generados y la ocurrencia observada en la Comunidad de Madrid, una de las regiones del estudio.Forest fires are a major factor of environmental transformation in several ecosystems. Fires have global impacts, affecting forested areas and having an important impact in greenhouse gas emissions. Additionally, fires have local impacts, associated to soil degradation, soil erosion, vegetation dynamics, and lost of lives and properties. Fire prevention is critical to reduce the negative impacts of fire. This paper presents the input variables and the integration scheme developed within the Firemap project (funded under the Spanish Ministry of Science and Technology) to map wildland fire occurrence probability. The project first generated fire risk variables related to several factors of fire ignition or propagation. They were generated from a wide variety of sources using geographic information systems and remote sensing technologies. All variables were mapped at 1 sq km spatial resolution, and were integrated into single indices. The risk system included the development of a dedicated web-mapping server to facilitate the access to the end-users. This service was tested in the summer of 2007 for semi-operational use. The paper presents the first validation results of the danger index, by comparing temporal trends of the different danger components to the fire occurrence in the Madrid region, one of the test sites