Download or read book Leveraging Multi Sensor Time Series Datasets to Map Short and Long Term Forest Disturbances and Drivers of Change in the Colombian Andes written by Paulo Jose Murillo Sandoval and published by . This book was released on 2017 with total page 80 pages. Available in PDF, EPUB and Kindle. Book excerpt: The spatial distribution of forest disturbance is commonly calculated using a satellite imagery-driven bi- or tri-temporal change analysis. Working in Colombia’s Cordillera de los Picachos National Natural Park – a region of consistent cloud cover and dramatic topographic relief – a change assessment with such infrequent observations cannot capture long-term trends of vegetative decline (browning) or improvement (greening) nor the drivers associated with these changes. In recognition of the importance of spatio-temporally explicit information for assessing the effects of socio-environmental change and conservation strategy implementation, I developed a rigorous assessment of vegetation change using MODIS and Landsat time-series data and the Breaks For Additive Season and Trend (BFAST) algorithm to identify the timing, trends, and locations of change as well the associated drivers. First, I measured long-term vegetation trends from 2001-2015 using a Moderate Resolution Imaging Spectroradiometer (MODIS)-based 250m resolution Multi-Angle Implementation of Atmospheric Correction (MAIAC) time-series, and mapped short-term disturbances using all available Landsat images (149 dates from Landsat 5, 7, and 8). BFAST trends based on MAIAC data indicate a net greening in 6% of the park, with a net browning trend of 2.5% in the 10km-wide region surrounding the park. I also identified a 12,500 ha area within Picachos (4% of the park’s total area) that experienced a consecutive vegetative decline or browning during every year of study, a result corroborated with a BFAST Monitor assessment using finer 30m resolution Landsat data. With Landsat, I recorded 12,642 ha (±1440) of disturbed forest within the park at high spatial and temporal accuracy. Spatially, Landsat results had user’s and producer’s accuracies of 0.95±0.02 and 0.83±0.18, respectively. Temporally, a TimeSync-supported temporal validation assessment showed that 75% of Landsat-detected dates of disturbance events were accurate within ± 6 months. With disturbances identified, I characterized disturbances within Picachos’ southeastern foothills and associated drivers using a set of metrics related to the spectral, pattern and trend properties of disturbance patches derived from Landsat time-series data (1996-2015). A training dataset was initially developed to identify drivers of disturbances using Corine Land Cover maps and high-resolution imagery. A Random Forests classifier was used to attribute disturbances to specific drivers of forest cover change: conversion to pasture, conversion to subsistence agriculture, and non-stand replacing disturbance (i.e., thinning). Attribution of changes had high accuracy at patch and area levels with 1-5% commission and 2-14% omission errors, respectively, for regions that were converted to pasture or experienced thinning. Lower agreement was found for agricultural conversion with 43% omission and 9% commission errors. I found that conversion to pasture is the main cause of forest cover loss within Picachos at 9901 ha (±72) corresponding to 14.7% of Picachos’ foothills, and that subtle forest alteration contributed to 1327 ha (±92) of forest degradation. Recognizing the diversity of pressures facing conservation strategy implementation in the region, these results have direct relevance for anticipating future land use pressures within Colombia, as well as across similar regions in the Andes-Amazon transition area. Indeed, since these results reveal the possibility to uncover historical disturbances related to human-incursion in protected landscapes, the methods are well suited to enhancing landscape planning particularly where biodiversity richness is quickly diminishing due to anthropogenic presence.
Download or read book Mapping Forest Changes Using Multi temporal Remote Sensing Images written by Yanlei Chen and published by . This book was released on 2014 with total page 104 pages. Available in PDF, EPUB and Kindle. Book excerpt: We developed a semi-automatic algorithm named Berkeley Indices Trajectory Extractor (BITE) to detect forest disturbances, especially slow-onset disturbances such as insect mortality, from time series of Landsat 5 Thematic Mapper (TM) images. BITE is a streamlined process that features trajectory extraction and interpretation of multiple spectral indices followed by an integration of all indices. The algorithm was tested over Grand County in Colorado, located in the Southern Rocky Mountains Ecoregion, where forests dominated by lodgepole pine have been under mountain pine beetle attack since 2000. We produced a disturbance map using BITE with an identification accuracy of 94.7% assessed from 602 validation sample pixels. The algorithm shows its robustness in deriving forest disturbance type and timing with the presence of different levels of atmospheric conditions, noises, pixel misregistration and residual cloud/snow cover in the imagery. Outputs of the BITE algorithm could be used in studies designed to increase understanding of the mechanisms of mountain pine beetle dispersal and tree mortality, as well as other types of forest disturbances. Large remote sensing datasets, that either cover large areas or have high spatial resolution, are often a burden for information mining for scientific studies. Here, we present an approach that conducts clustering after gray-level vector reduction. In this manner, the speed of clustering can be considerably improved. The approach features applying eigenspace transformation to the dataset followed by compressing the data in the eigenspace and storing them in coded matrices and vectors. The clustering process takes advantage of the reduced size of the compressed data and thus reduces computational complexity. We name this approach Clustering Based on Eigen Space Transformation (CBEST). In our experiment with a subscene of Landsat Thematic Mapper (TM) imagery, CBEST was found to be able to improve speed considerably over conventional K-means as the volume of data to be clustered increases. We assessed information loss and several other factors. In addition, we evaluated the effectiveness of CBEST in mapping land cover/use with the same image that was acquired over Guangzhou City, South China and an AVIRIS hyperspectral image over Cappocanoe County, Indiana. Using reference data we assessed the accuracies for both CBEST and conventional K-means and we found that the CBEST was not negatively affected by information loss during compression in practice. We then applied CBEST in mapping the forest change from 1986-2011 for the entire state of California, USA with over 400 Landsat TM images. We discussed potential applications of the fast clustering algorithm in dealing with large datasets in remote sensing studies. We present an efficient approach for a practice of large-area mapping of forest changes based on the Clustering Based on Eigen Space Transformation (CBEST) algorithm using remote sensing. By analyzing 450 Landsat Thematic Mapper (TM) satellite images from 1986 to 2011 with a five-year interval covering the entire state of California, USA, we derived a forest change type map, a forest loss map and a forest gain map. Although California has 99.6 million acres land area in total and the spatial resolution of Landsat TM is 30m, the computing time of the task took only 10 hours in a computer with an Intel 2.8 Ghz i5 CPU and 8 Gigabytes RAM. The overall accuracy of the forest cover in year 2011 was reported as 92.9% " 1.6%. We found that the estimated forest area changed from 28.20 " 1.98 million acres to 28.05 " 1.98 million acres from 1986-2011. In particular, our rough estimate indicates that each year California's forest experienced loss of 92 thousand acres and recovery of 85 thousand acres, resulting in seven thousand acres forest loss per year. In addition, during 1986-2011, around 12% of the forestland experienced changes, in which the change was 4% each for deforestation, afforestation and deforestation then recovered respectively. We concluded that the forestland in California had been managed in a sustainable manner over the 25 years, since no significantly directional changes were observed. Our approach made a tighter estimate of the true canopy coverage such that 29% of land in California is forestland, comparing with the statistics of 33% and 40% made by previous studies that had lower spatial resolution and shorter temporal coverage.
Download or read book An Unsupervised Classification based Time Series Change Detection Approach for Mapping Forest Disturbance written by Ilia Parshakov and published by . This book was released on 2021 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Unsupervised Classification to Change (UC-Change) is a new remote sensing approach for mapping areas affected by logging and wildfires. It addresses the main limitations of existing image time-series change detection techniques, such as limited multi-sensor capabilities, use of purely spectral-based forest recovery metrics, and poor detection of salvage harvesting. UC Change detects disturbances and tracks forest recovery by analyzing changes in the spatial distribution of spectral classes over time. The algorithm detected approximately 85% and 70% of reference cutblock and fire scar pixels at a ±2-year temporal agreement, respectively, consistently outperforming existing algorithms across different biogeoclimatic zones of British Columbia, Canada. The results indicate an upper estimate of 7.5 million ha of forest cleared between 1984 and 2014, which is above estimates based on existing maps and databases (6.3 - 6.7 million ha). Also presented is a new framework for using open-access data for validation of change detection results.
Download or read book Leveraging High resolution Imagery and New Technologies in Machine Learning to Map Forest Disturbances written by Sarah Wegmueller and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Remotely sensed imagery, satellite and airborne, has great potential to provide increased monitoring and mapping capabilities for applications in forest health and management. In this dissertation, I investigated ways to leverage newly available satellite imagery, machine learning techniques, and recently collected ground data to develop new methods for monitoring and mapping forest health at various scales and for a range of purposes. The efforts my collaborators and I resulted in two new software programs, named Astrape and Tree Condition and Analysis Program (TreeCAP), that collectively map disturbances ranging from large, stand-replacing derechos to individual tree mortality in a mixed forest with accuracies typically over 80%. Both of these systems were designed to be scaled up for operational use across the contiguous US, and maybe internationally. Astrape is capable of using nearly any imagery source but was designed with Sentinel-2 imagery and Dove imagery. It implements a machine learning framework to produce thematic maps of damage severity in four classes (high severity, moderate severity, low severity, and little to no damage) with limited need for ground-truthing. TreeCAP was built to leverage the National Agricultural Imagery Program (NAIP) data that has a spatial resolution of 0.6-1 m, suitable for differentiating individual trees. TreeCAP uses a machine learning model to create thematic maps of healthy, morbid, and dead trees with high accuracy. Further, I pioneered a vital method to normalize the highly radiometrically variable Dove data called LOESS Radiometric Correction for Contiguous Scenes (LORACCS). The output of LORACCS can be used to create seamless Dove imagery mosaics that can then be used with the aforementioned systems, greatly expanding their temporal and spatial potential. Finally, I conducted a reinvestigating of oak wilt spread in Wisconsin using a time series of NAIP imagery and ground-confirmed incidents (courtesy of the Wisconsin Department of Natural Resources Forest Health Team). The results of this study indicate that oak wilt may be far more prevalent on the landscape than is currently known, highlighting the value of using remote sensing to better understand the patterns of insects and disease regionally.
Download or read book Multi Sensor Vegetation Index and Land Surface Phenology Earth Science Data Records in Support of Global Change Studies Data Quality Challenges and Data Explorer System written by Armando Barreto-Munoz and published by . This book was released on 2013 with total page 236 pages. Available in PDF, EPUB and Kindle. Book excerpt: Synoptic global remote sensing provides a multitude of land surface state variables. The continuous collection, for more than 30 years, of global observations has contributed to the creation of a unique and long term satellite imagery archive from different sensors. These records have become an invaluable source of data for many environmental and global change related studies. The problem, however, is that they are not readily available for use in research and application environment and require multiple preprocessing. Here, we looked at the daily global data records from the Advanced Very High Resolution Radiometer (AVHRR) and the Moderate Resolution Imaging Spectroradiometer (MODIS), two of the most widely available and used datasets, with the objective of assessing their quality and suitability to support studies dealing with global trends and changes at the land surface. Findings show that clouds are the major data quality inhibitors, and that the MODIS cloud masking algorithm performs better than the AVHRR. Results show that areas of high ecological importance, like the Amazon, are most prone to lack of data due to cloud cover and aerosols leading to extended periods of time with no useful data, sometimes months. While the standard approach to these challenges has been compositing of daily images to generate a representative map over a preset time periods, our results indicate that preset compositing is not the optimal solution and a hybrid location dependent method that preserves the high frequency of these observations over the areas where clouds are not as prevalent works better.
Download or read book Multi temporal and Multi sensor Monitoring of Forest Disturbance written by Suming Jin and published by . This book was released on 2005 with total page 196 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Assessing Local Expert Data Quality for Forest Monitoring written by E.B. Gebremeskel and published by . This book was released on 2014 with total page 51 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recent advancement in spatial data collection technologies dramatically increases the contribution of ordinary people to collect and disseminate geospatial data. At the same time, there is an increasing general agreement that community based forest monitoring can play a crucial role in producing and sharing information about the condition of forest resources in time and space. Despite the advantages of the community based monitoring, there are also doubts and concerns that existed in the scientific community related to the quality of the data. Therefore, this research is aiming to assess the quality of forest monitoring activity data sets, which is collected by local experts in Kafa Biosphere Reserve in Ethiopia. The research was conducted to test the quality of local experts data for REDD+ mechanism to track the forest change and carbon emissions. In this research, we examines the quality of local experts data relative to the reference data sets of remotes sensing time series images of 2005 to 2012, GIS data sets, and ground based validation measurements. The main variables are date of forest disturbances, size of the forest disturbance, drivers information, location and coverage of forest disturbances. The spatial variables of the local experts data were assessed using the spatial data quality parameters whereas the temporal variables were compared through BFAST monitoring on Landsat time series images and visual interpretations on high resolution images of Spot and Rapid Eye. The results show that the local experts can perform and produce quality data comparable to validation measurements by experts. We found a regression coefficient value of 0.84 for area/size estimation and ~65% of correctly classification accuracy of drivers information of forest disturbances. Furthermore, the result confirms that local experts have a short time delay in detecting forest disturbances compared to high resolution remote sensing time series data of Spot 5-Rapid Eye satellite images than of Landsat imagery. Based up on the findings of this study, we suggests that the local expert data can enhance the quality of forest monitoring data of remote sensing particularly in detecting near real time forest disturbances.
Download or read book Monitoring Long term Forest Dynamics Using Very Dense Landsat Time Series written by Adam Chlus and published by . This book was released on 2015 with total page 136 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Monitoring Dynamics of Semi arid Forests with Multi sensor Time Series written by Philipp Gärtner and published by . This book was released on 2017 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Forest Pathology and Plant Health written by Matteo Garbelotto and published by MDPI. This book was released on 2018-04-13 with total page 243 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a printed edition of the Special Issue "Forest Pathology and Plant Health" that was published in Forests
Download or read book Warfare Ecology written by Gary E. Machlis and published by Springer Science & Business Media. This book was released on 2011-05-29 with total page 303 pages. Available in PDF, EPUB and Kindle. Book excerpt: The purpose of this book is specific and ambitious: to outline the distinctive elements, scope, and usefulness of a new and emerging field of applied ecology named warfare ecology. Based on a NATO Advanced Research Workshop held on the island of Vieques, Puerto Rico, the book provides both a theoretical overview of this new field and case studies that range from mercury contamination during World War I in Slovenia to the ecosystem impacts of the Palestinian occupation, and from the bombing of coral reefs of Vieques to biodiversity loss due to violent conflicts in Africa. Warfare Ecology also includes reprints of several classical papers that set the stage for the new synthesis described by the authors. Written for environmental scientists, military and humanitarian relief professionals, conservation managers, and graduate students in a wide range of fields, Warfare Ecology is a major step forward in understanding the relationship between war and ecological systems.
Download or read book Peatlands mapping and monitoring written by The Food and Agriculture Organization of the United Nations and published by Food & Agriculture Org.. This book was released on 2020-03-01 with total page 100 pages. Available in PDF, EPUB and Kindle. Book excerpt: Integration of peatlands into land-use monitoring systems is central to the conservation of their carbon storage – be they conserved, degraded or restored. Healthy peatlands mitigate climate change, enhance adaptive capacity and maintain ecosystem services and biodiversity. Albeit peatlands are starting to receive a high level of attention and the scientific basis for their monitoring has quickly developed over the last few years. Robust and practical approaches and tools for developing and integrating peatland-monitoring into national monitoring and reporting frameworks is an important opportunity for countries to limit global warming to 2 °C.
Download or read book The United Nations World Water Development Report 2020 written by UNESCO and published by . This book was released on 2020-03-27 with total page 234 pages. Available in PDF, EPUB and Kindle. Book excerpt: The 2020 edition of the WWDR, titled Water and Climate Change illustrates the critical linkages between water and climate change in the context of the broader sustainable development agenda. Supported by examples from across the world, it describes both the challenges and opportunities created by climate change, and provides potential responses – in terms of adaptation, mitigation and improved resilience – that can be undertaken by enhancing water resources management, attenuating water-related risks, and improving access to water supply and sanitation services for all in a sustainable manner. It addresses the interrelations between water, people, environment and economics in a changing climate, demonstrating how climate change can be a positive catalyst for improved water management, governance and financing to achieve a sustainable and prosperous world for all. The report provides a fact-based, water-focused contribution to the knowledge base on climate change. It is complementary to existing scientific assessments and designed to support international political frameworks, with the goals of helping the water community tackle the challenges of climate change, and informing the climate change community about the opportunities that improved water management offers in terms of adaptation and mitigation.
Download or read book At Loggerheads written by Piet Buys and published by World Bank Publications. This book was released on 2007 with total page 309 pages. Available in PDF, EPUB and Kindle. Book excerpt: The report offers a simple framework for policy analysis by identifying three forest types: frontiers and disputed lands; lands beyond the agricultural frontier; and, mosaic lands where forests and agriculture coexist. It collates geographic and economic information for each type that will help formulate poverty-reducing forest policy.
Download or read book Ecological Informatics written by Friedrich Recknagel and published by Springer Science & Business Media. This book was released on 2002-12-11 with total page 440 pages. Available in PDF, EPUB and Kindle. Book excerpt: Ecological Informatics is defined as the design and application of computational techniques for ecological analysis, synthesis, forecasting and management. The book provides an introduction to the scope, concepts and techniques of this newly emerging discipline. It illustrates numerous applications of Ecological Informatics for stream systems, river systems, freshwater lakes and marine systems as well as image recognition at micro and macro scale. Case studies focus on applications of artificial neural networks, genetic algorithms, fuzzy logic and adaptive agents to current ecological management issues such as toxic algal blooms, eutrophication, habitat degradation, conservation of biodiversity and sustainable fishery.
Download or read book Optical Approaches to Capture Plant Dynamics in Time Space and Across Scales written by Eetu Puttonen and published by Frontiers Media SA. This book was released on 2018-08-17 with total page 173 pages. Available in PDF, EPUB and Kindle. Book excerpt: Quantifying temporal changes in plant geometry as a result of genetic, developmental, or environmental causes is essential to improve our understanding of the structure and function relationships in plants. Over the last decades, optical imaging and remote sensing developed fundamental working tools to monitor and quantify our environment and plants in particular. Increased efficiency of methods lowered the barrier to compare, integrate, and interpret the optically obtained plant data across larger spatial scales and across scales of biological organization. In particular, acquisition speed at high resolutions reached levels that allow capturing the temporal dynamics in plants in three dimensions along with multi-spectral information beyond human visual senses. These advanced imaging capabilities have proven to be essential to detect and focus on analyzing temporal dynamics of plant geometries. The focus of this Research Topic is on optical techniques developed to study geometrical changes at the plant level detected within the wavelength spectrum between near-UV to near infrared. Such techniques typically involve photogrammetric, LiDAR, or imaging spectroscopy approaches but are not exclusively restricted to these. Instruments operating within this range of wavelengths allow capturing a wide range of temporal scales ranging from sub-second to seasonal changes that result from plant development, environmental effects like wind and heat, or genetically controlled adaption to environmental conditions. The Research Topic covered a plethora of methodological approaches as suggestions for best practices in the light of a particular research question and to a wider view to different research disciplines and how they utilize their state-of-the-art techniques in demonstrating potential use cases across different scales.
Download or read book Our Common Future written by and published by . This book was released on 1990 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt:
