Forest cover estimation in Ireland using radar remote sensing: a comparative analysis of forest cover assessment methodologies

Quantification of spatial and temporal changes in forest cover is an essential component of forest monitoring programs. Due to its cloud free capability, Synthetic Aperture Radar (SAR) is an ideal source of information on forest dynamics in countries with near-constant cloud-cover. However, few studies have investigated the use of SAR for forest cover estimation in landscapes with highly sparse and fragmented forest cover. In this study, the potential use of L-band SAR for forest cover estimation in two regions (Longford and Sligo) in Ireland is investigated and compared to forest cover estimates derived from three national (Forestry2010, Prime2, National Forest Inventory), one pan-European (Forest Map 2006) and one global forest cover (Global Forest Change) product. Two machine-learning approaches (Random Forests and Extremely Randomised Trees) are evaluated. Both Random Forests and Extremely Randomised Trees classification accuracies were high (98.1–98.5%), with differences between the two classifiers being minimal (<0.5%). Increasing levels of post classification filtering led to a decrease in estimated forest area and an increase in overall accuracy of SAR-derived forest cover maps. All forest cover products were evaluated using an independent validation dataset. For the Longford region, the highest overall accuracy was recorded with the Forestry2010 dataset (97.42%) whereas in Sligo, highest overall accuracy was obtained for the Prime2 dataset (97.43%), although accuracies of SAR-derived forest maps were comparable. Our findings indicate that spaceborne radar could aid inventories in regions with low levels of forest cover in fragmented landscapes. The reduced accuracies observed for the global and pan-continental forest cover maps in comparison to national and SAR-derived forest maps indicate that caution should be exercised when applying these datasets for national reporting

Patterns in the Temporal Variability of Temperate Reef Fishes and the Implications for Sampling Frequency in Citizen Science Monitoring Programs

Ecological monitoring enables our understanding of ecosystem change and is fundamental to the process of developing sound management policies. One major gap in all current California kelp forest monitoring programs is the limited frequency at which kelp forest fishes are sampled. Citizen science has been identified as a valuable tool to help meet monitoring needs in the marine environment, most recently in the California Marine Life Protection Act (1999). Because the costs of citizen science programs are mitigated by the use of volunteers, they are more able to expand their monitoring efforts to capture seasonal variations than other professional programs. We evaluated the citizen-based Reef Check California (RCCA) for its potential to capture seasonal variations in kelp forest fishes by monitoring multiple times per year. We conducted diver surveys approximately once every four weeks from March 2009-July 2010 at MacAbee reef in Monterey, California using the RCCA fish survey protocol. We compared generalized linear models (GLM) using an Akaike’s Information Criteria (AIC) approach to examine the relationship between fish abundances and time. The results of this study show that the local abundance of selected species and/or species groups were subject to substantial temporal variation both within and among oceanographic seasons. The results of this study provide information on the temporal trends of species recorded via the RCCA protocol and indicate that RCCA could expand monitoring efforts to capture continuous seasonal patterns, change between oceanographic seasons, and within season variability. This information, combined with information from other professional organizations can ultimately better inform marine management decisions

Forest Clearing in the Pantropics: December 2005–August 2011- Working Paper 283

This report summarizes recent trends in large-scale tropical forest clearing identified by FORMA (Forest Monitoring for Action). Our analysis includes 27 countries that accounted for 94 percent of clearing during the period 2000–2005. We highlight countries with relatively large changes since 2005, both declines and increases. FORMA produces indicators that track monthly changes in the number of 1-sq.-km. tropical forest parcels that have experienced clearing with high probability. This report and the accompanying spreadsheet databases provide monthly estimates for 27 countries, 280 primary administrative units, and 2,907 secondary administrative units. Countries’ divergent experiences since 2005 have significantly altered their shares of global clearing in some cases. Brazil’s global share fell by 11.2 percentage points from December 2005 to August 2011, while the combined share of Malaysia, Indonesia, and Myanmar increased by 10.8. The diverse patterns revealed by FORMA’s first global survey caution against facile generalizations about forest clearing in the pantropics. During the past five years, the relative scale and pace of clearing have changed across regions, within regions, and within countries. Although the overall trend seems hopeful, it remains to be seen whether the decline in forest clearing will persist as the global economy recovers.

Digital natures: New ontologies, new politics?<strong><strong> </strong></strong>

Digital tools and practices are transforming societal relationships with non -human worlds — whether through smartphone apps that city dwellers use to navigate urban forests, robotic bees that pollinate crops, or webcams that livestream rare birds’ nests. Recent academic and popular interest in the coming together of digital and natural worlds has generated both creative and critical reflections on what the digital means for the very concept of nature, troubling the latter’s ontological stability. In this Introduction to the special issue Digital Natures: Reconfiguring Ontologies, Epistemologies, and Politics we claim that the digital, when considered beyond an epistemological register, is a productive and political force that is unsettling, rather than reinforcing, the boundaries between society and nature. We review the extensive body of work from across geography and the social sciences that is actively engaging with digital –nature intersections, and historicise current debates through reference to the figures of the cyborg, technonatures, biomimicry and digital organisms. Asking whether digitalized practices of sensing, abstraction and algorithmic recombination simply mirror a pre -existing and external Nature, or whether they advance a reconceptualization of nature, we set out to trace the progressive political potential of a digitally -entangled ontological redefinition of nature. We discuss how, within emerging digital natures , agencies are entangled in a reimagining of what both nature and society are about. Here, we argue, lies the transformative potential of digital natures —precisely in challenging and subverting the ontological place of an external Nature. The introduction finishes by simultaneously outlining a research agenda for digital natures and presenting the six papers that comprise the special issue

Transfer of Remote Sensing Computer Technology to the Developing World---Case Examples

Computerized image processing represents a level of technology sufficiently advanced that the Agency for International Development (AID) has had years of problems attempting to set up the necessary equipment support. The theory of pattern recognition and various software algorithms, such as maximum likelihood, kth nearest neighbor, and supervised clustering, are difficult to teach to remote sensing resource managers and technicians with limited education in mathematics. Computer hardware is relatively complex and, in addition to requiring programming skills, both procedural level, as well as operating systems, also requires training in electronic trouble-shooting and computer maintenance to keep systems in operation

Integrating Remote Sensing Techniques into Forest Monitoring: Selected Topics with a Focus on Thermal Remote Sensing

A sustainable management of natural resources, in particular of forests, is of great importance to preserve the ecological, environmental and economic benefits of forests for future generations. An enhanced understanding of the current situation and ongoing trends of forests, e.g. through policy interventions, is crucial to managing the forest wisely. In this context, forest monitoring is essential for collecting the base data required and for observing trends. Despite the wide range of approved methods and techniques for both close-range and satellite-based remote sensing monitoring, ongoing forest monitoring research is still grappling with specific and unresolved questions: The data acquired must be more reliable, in particular over a long-term period; costs need to be reduced through advancements in both methods and technology that offer easier and more feasible ways of interpreting data. This thesis comprises a number of focused studies, each with their individual and specific research questions, and aims to explore the benefits of innovative methods and technologies. The main emphasis of the studies presented is the integration of close-range and satellite-based remote sensing for enhancing the efficiency of forest monitoring. Manuscript I discusses thermal canopy photography, a new field of application. This approach takes advantage of the large differences in temperature between sky and non-sky pixels and overcomes the inconsistencies of finding an optimal threshold. For an unambiguously separation of “sky” and “non-sky” pixels, a global threshold of 0 °C was defined. Currently, optical or hemispherical canopy photography is the most widely used method to extract crown-related variables. However, a number of aspects, such as exposure, illumination conditions, and threshold definition present a challenge in optical canopy photography and dramatically influence the result; consequently, a comparison of the results from optical canopy photography at a different point in time derived is not advisable. For forest monitoring, where repeated measurements of the canopy cover on the same plots were undertaken, it is therefore of utmost importance to devise a standard protocol to estimate changes in and compare the canopy covers. This paper offers such a protocol by introducing thermal canopy photography. A feasible and accurate method that examines the strong correlation (R2 = 0.96) of canopy closure values derived from thermal and optical image pairs. Thermal photography, as a close-range remote sensing technique, also aids data collection and analysis in other contexts, for instance to expand our knowledge about bamboo tree species: Information about the maturity of bamboo culms is of utmost importance for managing bamboo stands because only then the process of lignification is finished and the culm is technically stronger and more resistant to insect and fungi attacks. The findings of a study (Manuscript III) conducted in Pereira, Colombia, show small differences in culm surface temperature between culms of different ages for the bamboo species Guadua angustifolia K., which may be a sign of maturity. The surface temperature of 12 culms was measured after sunrise using the thermal camera system FLIR 60Ebx. This study shows an innovative close-range remote sensing technique which may support researchers’ determination of the maturity of bamboo culms. This research is in its inception phase and our results are the first of this kind. In the context of analyzing, in particular of thermal imagery time-series data, Manuscript (IV) offers a new methodology using advanced statistical methods. Otsu Thresholding, an automatic segmentation technique is used in a first processing step. O’Sullivan penalized splines estimated the temperature profile extracted from the canopy leaf temperature. A final comparison of the different profiles is done by constructing simultaneous confidence bands. The result shows an approximately significant difference in canopy leaf temperature. For this study, we successfully cooperated with the Center for Statistics at Göttingen University (Prof. Kneib). The second close-range remote sensing technology employed in this thesis is terrestrial laser scanning which is used here to enhance our understanding about buttressed trees. Big trees with an irregular non-convex shape are important contributors to aboveground biomass in tropical forests, but an accurate estimation of their biomass is still a challenge and often remains biased. Allometric equations including tree diameter and height as predictors are currently used in tropical forests, but they are often not calibrated for such large and irregular trees where measuring the diameter is quite difficult. Against this background, Manuscript II shows the result of the 3D-analysis of 12 buttressed trees. This study was conducted in the Botanical Garden of Bogor, Indonesia, using a state-of-the-art terrestrial laser scanner. The findings allow for new insights into the irregular geometry of buttressed trees and the methodological approach employed in this paper will help to improve volume and biomass models for this kind of tree. The results suggest a strong relationship (R² = 0.87) between cross-sectional areas at diameter above buttress (DAB) height and the actual tree basal area measured at 1.3 m height. The accuracy of field biomass estimates is crucial if the data are used to calibrate models to predict the forest biomass on landscape level using remote sensing imagery. The linkage between technology and methodology in the context of forest monitoring remote sensing enhance our knowledge in extracting more reliable information on tree cover estimation. The pre-processing of satellite images plays a crucial role in the processing workflow and particularly the illumination correction has a direct effect on the estimated tree cover. Manuscript IV evaluates four DEMs (Pleiades DSM, SRTM30, SRTM V4.1 and SRTM-X) that are available for the area of Shitai County (Anhui Province, Southeast China) for the purpose of an optimized illumination correction and tree cover estimation from optical RapidEye satellite images. The findings presented in this study suggest that the change in tree cover is contingent on the respective digital elevation models used for pre-processing the data. Imagery corrected with the freely available SRTM30 DEM with 30 m resolution leads to a higher accuracy in the estimation of tree cover based on the high-resolution and cost intensive Pleaides DEM. These manuscripts eventually seek to resolve some of the issues and provide answers to some of the detailed questions that still persist at different steps of the forest monitoring process. In future, these new and innovate methods and technologies will maybe integrate into forest monitoring programs

Landsat archive holdings for Finland : opportunities for forest monitoring

There is growing interest in the use of Landsat data to enable forest monitoring over large areas. Free and open data access combined with high performance computing have enabled new approaches to Landsat data analysis that use the best observation for any given pixel to generate an annual, cloud-free, gap-free, surface reflectance image composite. Finland has a long history of incorporating Landsat data into its National Forest Inventory to produce forest information in the form of thematic maps and small area statistics on a variety of forest attributes. Herein we explore the spatial and temporal characteristics of the Landsat archive in the context of forest monitoring in Finland. The United States Geological Survey Landsat archive holds a total of 30 076 images (1972-2017) for 66 scenes (each 185 km by 185 km in size) representing the terrestrial area of Finland, of which 93.6% were acquired since 1984 with a spatial resolution of 30 m. Approximately 16.3% of the archived images have desired compositing characteristics (acquired within August 1 +/- 30 days,Peer reviewe