Deep Learning on Synthetic Data Enables the Automatic Identification of Deficient Forested Windbreaks in the Paraguayan Chaco

Abstract: The Paraguayan Chaco is one of the most rapidly deforested areas in Latin America, mainly due to cattle ranching. Continuously forested windbreaks between agricultural areas and forest patches within these areas are mandatory to minimise the impact that the legally permitted logging has on the ecosystem. Due to the large area of the Paraguayan Chaco, comprehensive in situ monitoring of the integrity of these landscape elements is almost impossible. Satellite-based remote sensing offers excellent prerequisites for large-scale land cover analyses. However, traditional methods mostly focus on spectral and texture information while dismissing the geometric context of landscape features. Since the contextual information is very important for the identification of windbreak gaps and central forests, a deep learning-based detection of relevant landscape features in satellite imagery could solve the problem. However, deep learning methods require a large amount of labelled training data, which cannot be collected in sufficient quantity in the investigated area. This study presents a methodology to automatically classify gaps in windbreaks and central forest patches using a convolutional neural network (CNN) entirely trained on synthetic imagery. In a two-step approach, we first used a random forest (RF) classifier to derive a binary forest mask from Sentinel-1 and -2 images for the Paraguayan Chaco in 2020 with a spatial resolution of 10 m. We then trained a CNN on a synthetic data set consisting of purely artificial binary images to classify central forest patches and gaps in windbreaks in the forest mask. For both classes, the CNN achieved an F1 value of over 70%. The presented method is among the first to use synthetically generated training images and class labels to classify natural landscape elements in remote sensing imagery and therewith particularly contributes to the research on the detection of natural objects such as windbreaks

Mapping and Monitoring Forest Cover

This book is a compilation of six papers that provide some valuable information about mapping and monitoring forest cover using remotely sensed imagery. Examples include mapping large areas of forest, evaluating forest change over time, combining remotely sensed imagery with ground inventory information, and mapping forest characteristics from very high spatial resolution data. Together, these results demonstrate effective techniques for effectively learning more about our very important forest resources

Integrative Assessment and Modelling of the Non Timber Forest Products Potential in Nuba Mountains of Sudan by Field Methods, Remote Sensing and GIS

Pressure imposed at any one place or point in time results in a complexity of spatial and temporal interactions within topographical ecosystems. It can be propagated through the system and may have implications for future ecosystem functions over a wide array of various spatial and temporal scales. Under conditions of wars and other socio-economic conflicts, these processes are most forceful in developing countries amidst declining economic growth, lack of awareness, deterioration of ecosystem services, loss of existing traditional knowledge bases and weak governance structures. Forests are an essential part of ecosystem services, not only as a resource but as a contributor to biological systems as well. They represent one of the most important sectors in the context of Environmental Change (EC), both from the point of mitigation as well as adaptation. While forests are projected to be adversely impacted under EC, they are also providing opportunities to mitigate these changes. Yet this is one of the least understood sectors, especially at the regional level - many of its fundamental metrics such as mitigation potential, vulnerability and the likely impacts of EC are still not well understood until now. Thus, there is a need for research and field investigations into the synergy of mitigation and adaptation so that the cost of addressing EC impacts can be reduced and the co-benefits can be increased. The aim of this study is to focus particularly on forest-based ecosystem services and to use forests as a strategy for inducing environmental change within the Nuba Mountains in Sudan, specifically for systems in poor condition under EC, and furthermore to explore forests as an entry point for investigating the relationship between urban and rural development and ecosystem services. In addition, the aim is also to raise understanding of the relations between patterns of local-level economic and demographic changes, the nature and value of local ecosystem services, and the role of such services in increasingly interlinked urban and rural livelihood systems. The methodology applied in the current research is three-pronged: a formal literature review, a socio–economic survey (based on semi-structured interviews of household heads via Rapid Rural Appraisal (RRA), with a focus on group discussions, informal meetings, free listening and key informant techniques), and multitemporal optical satellite data analysis (i.e. Landsat and RapidEye). Landsat imagery was utilized to gather the spatial characteristics of the region and to study the Land Use/Land Cover (LU/LC) changes during the period from 1984 to 2014. Meanwhile, RapidEye imagery was used to generate the tree species distribution map. Qualitative and quantitative techniques were applied to analyze socio-economic data. Moreover, Food Consumption Score (FCS) was used to gauge both diversity and frequency of food consumption in surveyed areas. Geographic object-based image analysis (i.e. K-Nearest Neighbour classifier and knowledge-based classifiers) based on a developed model of integrated features (such as vegetation indices, DEM, thematic layers and meteorological information) was applied. Post Classification Analysis (PCA) as well as Post Change Detection (PCD) techniques were used. Hotspot analysis was conducted to detect the areas affected by deforestation. Furthermore, Ordinary Least Squares regression (OLS), Autocorrelation (Moran's) analysis, and Geographically Weighted Regression analyses (GWR) were applied to address the interaction of the different socioeconomic/ecological factors on Non Timber Forest Products (NTFPs) collection and to simulate the dependency scenarios of NTFPs along with their impact on poverty alleviation. Additionally, simulation was performed to estimate the future forest density and predict the dependency on forest services. An increasing impact of intensive interactions between the rural and urban areas has long been acknowledged. However, recent changes in the global political economy and environmental systems, as well as local dynamics of the study area driven by war, drought and deforestation, have led to an increasing rapidity and depth in rural transformation, as well as to a significant impact on urban areas. Like most environmental problems, the effects of these drivers are complex and are stressed diversely across different geographic regions by the socio-political processes that underlie recent economic and cultural globalization. These interactions and processes have increasingly brought rapid changes in land cover, social, institutional and livelihood transformation across broad areas of South Kordofan. Moreover, the study unveils new dynamics such as high rates of migration and mobility by the indigenous population and the increasing domination of market-centric livelihoods in many villages that were once dominated by rural agricultural and natural resourcesbased socio-economic systems. Furthermore, the research highlights the significant roles of NTFPs and trees in contributing to Nuba Mountains’ economic development, food security and environmental health, indicating which requirements need to be addressed in order to improve these potentials. The study proves that drawing on a wide range of these products for livelihood strengthens rural people’s ability to deal with and adapt to both EC and extreme events. Moreover, the results underline the importance of participatory approaches of rural women and their impact on NTFPs management with recommendations of more emphasis on potential roles and the ability of women to participate in public fora. Furthermore, the study shows that the use of high-resolution satellite imagery, integrated with model-based terrestrial information, provides a precise knowledge about the magnitude and distribution of LU/LC patterns. These methods can make an important contribution towards a better understanding of EC dynamics over time. The study reveals that more information exchange is needed to inform actors and decision makers regarding specific experiences, capacity gaps and knowledge to address EC. Subsequently, new policies and strategies are required to much more specifically focus on how to deal with consequences of longer-term EC rather than with the impacts of sudden natural disasters

Priority science can accelerate agroforestry as a natural climate solution

The expansion of agroforestry could provide substantial climate change mitigation (up to 0.31 Pg C yr−1), comparable to other prominent natural climate solutions such as reforestation. Yet, climate-focused agroforestry efforts grapple with ambiguity about which agroforestry actions provide mitigation, uncertainty about the magnitude of that mitigation and inability to reliably track progress. In this Perspective, we define agroforestry as a natural climate solution, discuss current understanding of the controls on farm-scale mitigation potential and highlight recent innovation on emergent, high-resolution remote sensing methods to enable detection, measurement and monitoring. We also assess the status of agroforestry in the context of global climate ambitions, highlighting regions of underappreciated expansion opportunity and identifying priorities for policy and praxis

Earth resources: A continuing bibliography with indexes (issue 60)

This bibliography lists 485 reports, articles, and other documents introduced into the NASA scientific and technical information system between October 1 and December 31, 1988. Emphasis is placed on the use of remote sensing and geophysical instrumentation in spacecraft and aircraft to survey and inventory natural resources and urban areas. Subject matter is grouped according to agriculture and forestry, environmental changes and cultural resources, geodesy and cartography, geology and mineral resources, oceanography and marine resources, hydrology and water management, data processing and distribution systems, and instrumentation and sensors

An exploratory investigation of low-altitude aerial image acquisition for land surface studies

In the context of environmental monitoring and sustainable land management this thesis seeks to evaluate the application of low-altitude remote sensing from a DIY perspective in the lower Ashburton River catchment. It seeks to demonstrate that the innovative synergistic use of airborne digital videography and CIR (colour infrared) 35mm photography can provide near real-time photomapping at local levels. These technologies are relatively inexpensive, easy-to-use and have proven successful in other countries. Used together with Desktop software systems for image processing, measurement and spatial calibration one can fulfil many community based environmental monitoring and sustainable land use management tasks. The concept of sustainable land use also implies we have an understanding of the landscape processes past and present that have occurred in the region. This is assessed using historical documents so that we may better appreciate the pace of rapid transformation. The role of GPS technology for the georeferencing of selected images into a GIS system is evaluated. The potential adoption of environmental monitoring index systems developed in Australia and Canada is investigated which would rely partly on the proposals recommended in this study

Calibration of DART Radiative Transfer Model with Satellite Images for Simulating Albedo and Thermal Irradiance Images and 3D Radiative Budget of Urban Environment

Remote sensing is increasingly used for managing urban environment. In this context, the H2020 project URBANFLUXES aims to improve our knowledge on urban anthropogenic heat fluxes, with the specific study of three cities: London, Basel and Heraklion. Usually, one expects to derive directly 2 major urban parameters from remote sensing: the albedo and thermal irradiance. However, the determination of these two parameters is seriously hampered by complexity of urban architecture. For example, urban reflectance and brightness temperature are far from isotropic and are spatially heterogeneous. Hence, radiative transfer models that consider the complexity of urban architecture when simulating remote sensing signals are essential tools. Even for these sophisticated models, there is a major constraint for an operational use of remote sensing: the complex 3D distribution of optical properties and temperatures in urban environments. Here, the work is conducted with the DART (Discrete Anisotropic Radiative Transfer) model. It is a comprehensive physically based 3D radiative transfer model that simulates optical signals at the entrance of imaging spectro-radiometers and LiDAR scanners on board of satellites and airplanes, as well as the 3D radiative budget, of urban and natural landscapes for any experimental (atmosphere, topography,…) and instrumental (sensor altitude, spatial resolution, UV to thermal infrared,…) configuration. Paul Sabatier University distributes free licenses for research activities. This paper presents the calibration of DART model with high spatial resolution satellite images (Landsat 8, Sentinel 2, etc.) that are acquired in the visible (VIS) / near infrared (NIR) domain and in the thermal infrared (TIR) domain. Here, the work is conducted with an atmospherically corrected Landsat 8 image and Bale city, with its urban database. The calibration approach in the VIS/IR domain encompasses 5 steps for computing the 2D distribution (image) of urban albedo at satellite spatial resolution. (1) DART simulation of satellite image at very high spatial resolution (e.g., 50cm) per satellite spectral band. Atmosphere conditions are specific to the satellite image acquisition. (2) Spatial resampling of DART image at the coarser spatial resolution of the available satellite image, per spectral band. (3) Iterative derivation of the urban surfaces (roofs, walls, streets, vegetation,…) optical properties as derived from pixel-wise comparison of DART and satellite images, independently per spectral band. (4) Computation of the band albedo image of the city, per spectral band. (5) Computation of the image of the city albedo and VIS/NIR exitance, as an integral over all satellite spectral bands. In order to get a time series of albedo and VIS/NIR exitance, even in the absence of satellite images, ECMWF information about local irradiance and atmosphere conditions are used. A similar approach is used for calculating the city thermal exitance using satellite images acquired in the thermal infrared domain. Finally, DART simulations that are conducted with the optical properties derived from remote sensing images give also the 3D radiative budget of the city at any date including the date of the satellite image acquisition

Micro-topography associated to forest edges

Forest edges are often defined as the discontinuity between the forest habitat and an adjacent open habitat, thus they are based on a clear difference in the structure of the dominant vegetation. However, beside this very general definition, in the field we can observe a large diversity of edges, with often different kinds of micro-topography features: bank, ditch, stone wall, path, etc. As these elements are rather common in many temperate forest edges, it seems important to start to characterize them more clearly and with consistency. From a set of observations in south-western France, we build a first typology of the micro-topographic elements associated to forest edges. For each of them we describe the process, natural or human induced, at their origin, and according to the literature available, we identify some of their key ecological roles. Banks, generated by the differential erosion between forest and crops along slopes, are especially analyzed since they are the most common micro-topographic element in our region. It offers many micro-habitat conditions in the soil used by a wide range of species, notably by several bee species. More research is required to study in details the importance of such micro-topographic elements

Operationalization of Remote Sensing Solutions for Sustainable Forest Management

The great potential of remote sensing technologies for operational use in sustainable forest management is addressed in this book, which is the reprint of papers published in the Remote Sensing Special Issue “Operationalization of Remote Sensing Solutions for Sustainable Forest Management”. The studies come from three continents and cover multiple remote sensing systems (including terrestrial mobile laser scanning, unmanned aerial vehicles, airborne laser scanning, and satellite data acquisition) and a diversity of data processing algorithms, with a focus on machine learning approaches. The focus of the studies ranges from identification and characterization of individual trees to deriving national- or even continental-level forest attributes and maps. There are studies carefully describing exercises on the case study level, and there are also studies introducing new methodologies for transdisciplinary remote sensing applications. Even though most of the authors look forward to continuing their research, nearly all studies introduced are ready for operational use or have already been implemented in practical forestry

Modelação geográfica da fragmentação e conectividade de habitats: casos de estudo nos padrões de distribuição local de espécies selvagens

Habitat fragmentation and the resultant reduction in connectivity are process of major importance in the persistence and patterns distribution of wildlife species. This thesis focuses on habitat fragmentation and connectivity, assessing their consequences on the local patterns distribution of wildlife species. The cases studies were published and conducted with monitoring data systematized using a common database. The case studies were located in the Alentejo region between the years of 1995 and 2005. The case studies are supported by examples of local impacts of fragmentation on the habitat connectivity of birds and reptile species patterns distribution. The observed pattern-process interactions are assessing by geographic modeling techniques. Methodologies were developed based on the innovative application of spatial statistical and networks analysis. The results show that the geographic modeling represents an added value to the understanding pattern-process interactions. The findings show how much the local distribution patterns of individuals are affected by habitat disturbances; RESUMO: A fragmentação dos habitats e a conectividade são processos de importância maior na persistência e nos padrões de distribuição das espécies selvagens. Esta tese centra -se na avaliação da fragmentação e conectividade dos habitats nos padrões locais de distribuição de espécies selvagens. Para tal foram realizados casos de estudo, com dados relativos a monitorizações efectuadas no Alentejo entre os anos de 1995 e 2005 e sistematizados numa base dados. Os casos de estudo foram publicados e são suportados por exemplos de impactes locais no padrão de distribuição de espécies de aves e réptil. Foram utilizadas técnicas de modelação geográfica na descrição e avaliação dos processos e padrões observados. Aplicadas e desenvolvidas metodologias inovadoras, com o suporte de técnicas de estatística espacial e análise de redes. Os resultados mostram que a modelação geográfica representa uma maisvalia para a compreensão da dinâmica entre padrões-processos. Os resultados revelam o quanto, os padrões de distribuição local dos indivíduos são afectados pelas alterações nos habitats