Satellite-based Machine Learning modelling of Ecosystem Services indicators: A review and meta-analysis

Satellite-based Machine Learning (ML) modelling has emerged as a powerful tool to understand and quantify spatial relationships between landscape dynamics, biophysical variables and natural stocks. Ecosystem Services indicators (ESi) provide qualitative and quantitative information aiding the assessment of ecosystems’ status. Through a systematic meta-analysis following the PRISMA guidelines, studies from one decade (2012–2022) were analyzed and synthesized. The results indicated that Random Forest emerged as the most frequently utilized ML algorithm, while Landsat missions stood out as the primary source of Satellite Earth Observation (SEO) data. Nonetheless, authors favoured Sentinel-2 due to its superior spatial, spectral, and temporal resolution. While 30% of the examined studies focused on modelling proxies of climate regulation services, assessments of natural stocks such as biomass, water, food production, and raw materials were also frequently applied. Meta-analysis illustrated the utilization of classification and regression tasks in estimating measurements of ecosystems' extent and conditions and findings underscored the connections between established methods and their replication. This study offers current perspectives on existing satellite-based approaches, contributing to the ongoing efforts to employ ML and artificial intelligence for unveiling the potential of SEO data and technologies in modelling ESi.info:eu-repo/semantics/publishedVersio

Banking on strong rural livelihoods and the sustainable use of natural capital in post-conflict Colombia

In post-conflict Colombia, the government has prioritized resettlement of displaced people through development of strong rural livelihoods and the sustainable use of natural capital. In this paper, we considered government proposals for expanding payment for ecosystem services (PES) and sustainable silvopastoral systems, and private-sector investment in habitat banking. We coupled the Integrated Economic-Environmental Model (IEEM) with spatially explicit land use and land cover change and ecosystem services models to assess the potential impacts of these programs through the lens of wealth and sustainable economic development. This innovative workflow integrates dynamic endogenous feedbacks between natural capital, ecosystem services and the economic system, and can be applied to other country contexts. Results show that PES and habitat banking programs are strong investment propositions (Net Present Value of US$4.4 and$4.9 billion, respectively), but only when moving beyond conventional economic analysis to include non-market ecosystem services. Where a portfolio investment approach is taken and PES is implemented with sustainable silvopastoral systems, investment returns would reach US$7.1 billion. This paper provides a detailed evaluation of the benefits of investing in rural livelihoods and enhancing Colombia’s natural capital base, with empirical evidence to inform the spatial targeting of policies to maximize economic, environmental and social outcomes. © 2023, The Author(s), under exclusive licence to Springer Nature B.V.This study was funded by the Inter-American Development Bank and the Department for Environment, Food and Rural Affairs (UK). Support for Kenneth J. Bagstad’s time was provided by the U.S. Geological Survey’s Land Change Science Program

Impacts of Land Cover Changes on Ecosystem Services Delivery in the Black Hills Ecoregion from 1950 to 2010

Environmental degradation generated by land use choices and human activities is the first driver of change in the provision of ecosystem goods and services. One of the challenges in ecosystem services research is to evaluate the contribution of each land cover unit to ecosystem services delivery while considering multiple services. In this thesis, I develop a framework to assess the capacity of many land covers to independently produce ecosystem services (i.e., potential production) and the capacity of the whole landscape to deliver multiple services to the population (i.e., potential supply). In the first part, this methodology is used to report on the change in ecosystem services delivery in the Black Hills ecoregion resulting from land cover modifications over a 60-year period. The trajectories of change in the Black Hills land cover are quantified using manual land cover mapping on aerial photographs from circa 1950 and circa 2010. In the second part, the same methodology is applied to the Black Hills National Forest, Custer State Park, and Wind Cave National park, in order to compare different management systems in the Black Hills and their implications for ecosystems services delivery over time. Although the trends of changes vary among the case studies following management directions and actions, most of the land cover conversions from 1950 and 2010 occurred on public land and affected ecosystem services delivery by the landscape. The three major net land cover changes were a loss of dense forest, a gain of medium and open forests, and a decrease in grassland/shrubland area. Even though the main drivers of change were not always human-induced, managers have been working to restore ecosystems, enhance their functionalities, and thus have been moving the landscape toward a higher level of ecosystems services delivery. By identifying the relationships between past and current land management, land cover changes and their drivers, and ecosystem services, this study contributes to a better understanding of land management results and their impacts upon Black Hills ecoregion sustainability and ecosystem services delivery

Analyzing spatial patterns and dynamics of landscapes and ecosystem services – Exploring fine-scale data and indicators

In den vergangenen Jahrzehnten hat der Einfluss des Menschen auf Ökosysteme stark zugenommen. Tendenzen der Landnutzungsänderung, darunter die Ausdehnung von Städten und die Intensivierung der Landwirtschaft als Folge des Bevölkerungsanstiegs und damit des Nahrungsmittel- und Energiebedarfs, führen zu Umweltproblemen wie dem Verlust von Lebensraum und biologischer Vielfalt. Die zunehmende Verfügbarkeit von Daten mit feiner räumlicher Auflösung kann die Analyse von Merkmalen und Prozessen in Landschaften mit Hilfe von räumlichen Metriken unterstützen. Das Ziel dieser Arbeit ist es, feinskalige Daten und räumliche Metriken zu integrieren, um Indikatoren zur Messung und Bewertung von Landnutzung, Ökosystemdienstleistungen und deren räumlichen Mustern zu entwickeln und folgende Fragen zu beantworten: Wie können Landnutzungsänderungen und Ökosystemleistungen einer Landschaft beschrieben und analysiert werden? Und, wie kann die Landschaftsperspektive zu unserem Verständnis von Landsystemen beitragen? In zwei verschiedenen Weltregionen werden Landschaften mit Hilfe von Hexagonen als räumliche Einheiten untersucht. Diese dienen zur Analyse von räumlichen Mustern und Beziehungen zwischen verschiedenen Indikatoren (z. B. Ökosystemdienstleistungen) und die Konzeptualisierung von Prozessen auf Landschaftsebene. Obwohl sich einige Phänomene auf feinen räumlichen Skalen manifestieren, ist es für die Operationalisierung und Überwachung dieser Prozesse notwendig, ‚herauszuzoomen‘. Der Landschaftsansatz im Zusammenhang mit Ökosystemleistungen bietet wichtige Perspektiven im Hinblick auf Umweltauswirkungen, die durch Landnutzungsänderungen verursacht werden. Dabei können Indikatoren, die die ökologische, ökonomische und soziale Dimension verknüpfen, dazu beitragen, regionalspezifisches Wissen über Landschaftsdynamiken zu erlangen und dieses Wissen an Entscheidungsträger weiterzugeben, um gezielte Maßnahmen für ein nachhaltiges Landmanagement zu entwickeln.Over the last decades, anthropogenic pressures on ecosystems have been increasing. Trends of land use change including urban expansion and agricultural intensification driven by population increase, and hence food and energy demand, cause environmental challenges including habitat and biodiversity loss. Analyzing major trends of land use change requires additional metrics to capture local processes on a landscape spatial scale. Increasing fine-scale data availability can support analyses of characteristics and processes of landscapes with the help of spatial metrics, e.g. distance or density measures. The aims of this thesis are to incorporate fine-scale data and spatial metrics to develop indicators to measure and assess land-use, ecosystem services (ESS) and their spatial patterns to answer the following questions: How can land use change and ecosystem services of landscapes be described and analyzed? And how can the landscape perspective contribute to our understanding of land systems? The thesis includes three case studies in two different world regions: 1) characteristics of land use within a peri-urban gradient in Dar es Salaam, Tanzania, 2) characteristics of agricultural landscapes in Brandenburg, Germany, and 3) ecosystem service relationships at different spatial units and scales. In both regions, landscapes are investigated with hexagons as spatial units for the analysis of spatial patterns and relationships among different indicators (i.e., ESS) and conceptualize processes on a landscape level. The landscape approach in context with ecosystem services offers important perspectives regarding environmental impacts caused by land use change. Thereby, metrics integrating the ecological, economic, and social dimensions can support obtaining region-specific knowledge on landscape dynamics and transferring this knowledge to decision-makers to design targeted measures towards sustainable land management

Forest Landscape Restoration and Ecosystem Services in A Luoi District, Thua Thien Hue Province, Vietnam

Abstract The Government of Vietnam has invested efforts to increase the forest cover, and to conserve biodiversity through different forest development projects and programs. Losing natural forests and landscapes in the context of the “exhaust” of ecosystem services has been seen as burden in many mountainous areas. The Decision No.16 on ecosystem restoration, which was adopted by the Conference of the Parties to the Convention on Biological Diversity (CBD) at the 11th meeting (December 5th, 2012) stated that ecosystem restoration requires the application of suitable technologies and the fully-effective participation of local entities. This serves to identify obstacles while attempting to restore, regenerate ecosystem services and biodiversity, which have been degraded and lost in the recent decades. Furthermore, Vietnam’s National Forest Development Strategy targeted to achieve a forest area of 16.2 million hectares by the year 2020. Local people living adjacent to forests depend on the forest ecosystem services supplied from various natural forest landscapes in the area. This holds true especially for the people of Central Vietnam where the terrestrial area is narrow due to the country shape. In this area, agriculture practices play an essential role although the agricultural land is very limited due to the topographic conditions. The distinct land-uses reflect the natural distribution of plant and animal species as well as human interventions. In Vietnam, the forest ecosystems have been classified into three categories according to their main functions: special-use forest for nature conservation; protection forest for the watershed and protective measures; and production forest for commercial operations. This study was conducted in the A Luoi District, Thua Thien Hue Province. Ground truth samples were inventoried in three forest types from 150 m to 1162 m above sea level (a.s.l.) and steep slopes from 5 to 48 degrees. The elevation range was divided into the lower elevation level H1 ranging from 150 m – 699 m and into the higher elevation level H2 from 700 m-1162 m a.s.l.. The slopes were stratified into level S1 from 5-20 degrees, and into S2 from 21-48 degrees. The forest cover was classified into the types: undisturbed forest (UF), low disturbed forest (LF), and heavily disturbed forest (DF). To strengthen the classification of forest types, a t-test of extracted vegetation indices between ground truth plots and training sample plots was done. Up to date, no remote sensing-based work on ecological stratification of the natural forest landscapes has been conducted. Finding the tree species distribution, species diversity, and species composition over the sub-stratification of the elevations, slopes, and the forest types - by applying remote sensing - are necessary to classify the land-use types and to map out the availability of natural resources, especially the ecosystem services supply and demand of local people. Land-use and forest type classification may contribute remarkably to long-term planning, which has been assigned to local authorities, and which should include local communities. The entire study consists of four main parts. The first part aimed at evaluating the influence of topography on tree species diversity, distribution, and composition of the forests in Central Vietnam. A significant difference of species richness and species diversity was found in shallower and steeper slopes (p < 0.05) and a relatively high correlation of the species distribution, the number of stems, and the number of tree families with the elevation factor was found. The lower elevation and shallower slope showed higher species richness (p < 0.05) but not a significant difference between the number of families and the evenness. The dominance and the abundance of tree species among the topographic attributes were significantly different (p < 0.05). Lower elevation and shallower slope showed higher species richness and species diversity than the higher elevation and steeper slope. The most dominant and abundant tree families from different elevations and slopes included the Myrtaceae, Dipterocarpaceae, Burseraceae, Fagaceae, Moraceae, Cornaceae, Apocynaceae, Sapindaceae, Cannabaceae, Juglandaceae, Lauraceae, Myristicaeae, Annonaceae, Ebenaceae, Meliaceae, Rubiaceae, and the Rosaceae. The second part aimed at assessing the soil qualities, which belong to the most essential elements for land-use planning and agricultural production. 155 soil samples from different land-use types and topographic aspects were collected in order to compare information on soil organic carbon (SOC), soil total nitrogen (STN), and soil acidity (pH) at two soil depths. The SOC of arable land and forest plantation land was found to be higher than those of grassland and of natural forests (p < 0.05). The total nitrogen in the natural forests was significantly less, compared to the other land-use types. No significant differences in the total nitrogen content (p < 0.05) were found among arable land, plantation forest, and grassland. The soil organic carbon and the total nitrogen were high in the upper soil and less downwards, within all land-use types. The soil pH in the plantation forest and the arable land-use types showed no significant change among soil depth categories. Significant differences were not found in topographic aspects and the soil organic carbon content; however, differing trends of soil organic carbon and land-use types and aspects were found. The impact of the slope, elevation, farming system and soil texture accounted for the main differences of soil indicators under varying land-use types in the A Luoi District. The third part of this study was designed to apply remote sensing data from Landsat-8 and Sentinel-2 sources in order to classify land-cover and land-use classes (including three forest types UF, LF, and DF) in the study area by using machine learning algorithms. Further, vegetation indices were applied to find possible correlations and regressions of both, vertical and horizontal structures of the dominant forest tree species within different forest types. It was found that the vegetation indices between the ground-truth plots and the training sample plots were significantly different (p<0.05). The most dominant and abundant tree families in the context of the vertical structure were the Dipterocaparceae, Combretaceae, Moraceae, Leguminosae, Burseraceae, and the Polygalaceae. These, in the context of the horizontal structure were the Fagaceae, Lauraceae, Leguminosae, Dipterocaparceae, Myrtaceae, Myristicaceae, Euphorbiaceae, and the Clusiaceae. The results of the land cover and the land-use classification of Sentinel-2 were found to be more precise than those of Landsat-8 with the Random Forest algorithm: (Sentinel-2 with out-of-bag error of 14.3%, overall accuracy of 85.7%, kappa of 83% and Landsat-8 with out-of-bag error 31.6%, overall accuracy of 68%, kappa of 67.5%). The study found relationships (from 43% up to 66%) between four (out of ten) vegetation indices within horizontal and vertical structures of the forest stands: the Enhanced Vegetation Index (EVI), the Difference Vegetation Index (DVI), the Perpendicular Vegetation Index (PVI), and the Transformed Normalized Difference Vegetation Index (TNDVI). The fourth part evaluated potential provisioning services of the current natural forests - apart from wood and timber supply. It (i) assessed and compared the amount of non-timber forest tree species (NTFP species) in the different investigated forest types and elevations as potential resources; explored (ii) the respective demands of local people and (iii) their personal views concerning the importance of natural forests and the satisfaction with their provisioning services; and finally (iv) gathered their awareness of limited consequences of former forest development and requirements for forest landscape restoration. Thirty-nine NTFP tree species were found for various uses such as food, medicine, and resin or oil. Random on-site interviews of 120 out of 627 local households were conducted in a commune with high dependency on local natural forest products. Their importance and satisfaction ranking of natural forests - considering different target groups with respect to gender, income, age-class, and education - was commenced. Multiple methods were used to assess an array of gathering information, which are related to (a) the forest resources importance and (b) the local people satisfaction. These were set into context with the involvement of non-timber forest goods extraction, landslides, goods declination, and the perception for natural forest landscapes restoration, in order to clarify perspectives on forest provisioning services. The results revealed remarkable differences among target groups, adjustment, perceptions. The insufficient supply of NTFPs, particularly profitable natural medicine provision, urges for adapted silvicultural measures. The results imply that NTFPs from natural forests are not only very important to the local communities, but also contribute to the enrichment of biodiversity. The participation of local people in practical forest management and forest improvement should be considered in the decision-making process for natural forest landscape restoration of remote mountainous areas. The findings of this study can support sustainable forest management; natural forest landscape restoration with the involvement of local communities; conservation practices of biodiversity, based on topographic conditions; land-use planning; identification of dominant tree species using vegetation indices’ values, and land cover and land-use classification using open source satellite images. This final component will be aided by application of machine learning algorithms in the current study area and in the central mountainous area of Vietnam.2021-07-2

Alien Planktonic Species in the Marine Realm: What Do They Mean for Ecosystem Services Provision?

Human well-being is significantly affected by the contributions provided by ecosystems, or ecosystem services. In this well-illustrated atlas, world-class experts identify and discuss key driving forces, trade-offs, and synergies of ecosystem services. Through interdisciplinary case studies varying across ecosystems and scales, this atlas narrows the knowledge gap between ecosystem services management and related fields of study. This atlas begins with conceptual background and proceeds to present drivers and their risks for ecosystems, their functions and services, and biodiversity. Trade-offs and synergies among ecosystem services and societal responses to the drivers and trade-offs are discussed. Sustainable land management and governance concepts are demonstrated throughout the atlas. Environmental scientists, practitioners and policy makers worldwide will appreciate the solutions and best practices identified throughout the chapters. Students of environmental sciences, socio-economics and landscape planning will find this atlas to be a valuable read, as well

A Field-Scale Decision Support System for Assessment and Management of Soil Functions

peer-reviewedAgricultural decision support systems (DSSs) are mostly focused on increasing the supply of individual soil functions such as, e.g., primary productivity or nutrient cycling, while neglecting other important soil functions, such as, e.g., water purification and regulation, climate regulation and carbon sequestration, soil biodiversity, and habitat provision. Making right management decisions for long-term sustainability is therefore challenging, and farmers and farm advisors would greatly benefit from an evidence-based DSS targeted for assessing and improving the supply of several soil functions simultaneously. To address this need, we designed the Soil Navigator DSS by applying a qualitative approach to multi-criteria decision modeling using Decision Expert (DEX) integrative methodology. Multi-criteria decision models for the five main soil functions were developed, calibrated, and validated using knowledge of involved domain experts and knowledge extracted from existing datasets by data mining. Subsequently, the five DEX models were integrated into a DSS to assess the soil functions simultaneously and to provide management advices for improving the performance of prioritized soil functions. To enable communication between the users and the DSS, we developed a user-friendly computer-based graphical user interface, which enables users to provide the required data regarding their field to the DSS and to get textual and graphical results about the performance of each of the five soil functions in a qualitative way. The final output from the DSS is a list of soil mitigation measures that the end-users could easily apply in the field in order to achieve the desired soil function performance. The Soil Navigator DSS has a great potential to complement the Farm Sustainability Tools for Nutrients included in the Common Agricultural Policy 2021–2027 proposal adopted by the European Commission. The Soil Navigator has also a potential to be spatially upgraded to assist decisions on which soil functions to prioritize in a specific region or member state. Furthermore, the Soil Navigator DSS could be used as an educational tool for farmers, farm advisors, and students, and its potential should be further exploited for the benefit of farmers and the society as a whole

A spatial decision support system for multifunctional landscape assessment: a transformative resilience perspective for vulnerable inland areas

The concept of transformative resilience has emerged from the recent literature and represents a way to interpret the potential opportunities for change in vulnerable territories, where a socioeconomic change is required. This article extends the perspective of transformative resilience to an assessment of the landscape multifunctionality of inland areas, exploring the potential of identifying a network of synergies among the different municipalities that is able to trigger a process of territorial resilience. A spatial decision support system (SDSS) for multifunctionality landscape assessment aims to help local actors understand local resources and multifunctional values of the Partenio Regional Park (PRP) and surrounding municipalities, in the South of Italy, stimulating their cooperation in the management of environmental and cultural sites and the codesign of new strategies of enhancement. The elaboration of spatial indicators according to Landscape Services classification and the interaction between the “Analytic Network Process” (ANP) method, spatial weighted overly and geographic information system (GIS) support the identification of a preferable scenario able to activate a transformative resilience strategy in selected vulnerable inland areas, which can be scaled up in other similar contexts

Mapping cropland in smallholder-Dominated Savannas: Integrating Remote Sensing Techniques

Traditional smallholder farming systems dominate the savanna range countries of sub-Saharan Africa and provide the foundation for the region’s food security. Despite continued expansion of smallholder farming into the surrounding savanna landscapes, food insecurity in the region persists. Central to the monitoring of food security in these countries, and to understanding the processes behind it, are reliable, high-quality datasets of cultivated land. Remote sensing has been frequently used for this purpose but distinguishing crops under certain stages of growth from savanna woodlands has remained a major challenge. Yet, crop production in dryland ecosystems is most vulnerable to seasonal climate variability, amplifying the need for high quality products showing the distribution and extent of cropland. The key objective in this analysis is the development of a classification protocol for African savanna landscapes, emphasizing the delineation of cropland. We integrate remote sensing techniques with probabilistic modeling into an innovative workflow. We present summary results for this methodology applied to a land cover classification of Zambia’s Southern Province. Five primary land cover categories are classified for the study area, producing an overall map accuracy of 88.18%. Omission error within the cropland class is 12.11% and commission error 9.76%