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Session Overview
211RB: Advances in land monitoring for sustainable development - Part B
Wednesday, 24/Apr/2019:
2:00pm - 3:30pm

Session Chair: Patrick Hostert
Session Chair: Veronique De Sy
Location: MB-220
Main Building, room 220, second floor, west wing, 154 (+22) seats
Session Topics:
What do people want from land?

Session Abstract

This session will explore the state-of-the-art in land monitoring, focussing on the use of freely available, global remote sensing data which can underpin land use assessments and contribute to solving pressing questions in the land use sector. The Paris Climate Agreement recognizes the importance of reducing emissions from deforestation and forest degradation, through the REDD+ results-based payments mechanism. Monitoring of forest cover and forest parameters (such as biomass) is an essential component. At the same time, increasing agricultural production is key in reaching the zero hunger SDG target, and, as well as increasing production (on existing agricultural land), area of land under agriculture is also expanding. Some monitoring needs related to agricultural land area and forest area can be potentially addressed by land cover change maps, which can provide information on for example conversions from forest to agriculture. This constantly evolving field (in terms of stakeholder demands, and available data from upcoming space missions and technology) calls for an expert-driven platform where researchers and other stakeholders can share knowledge, and work together to develop best-practices for land monitoring. GOFC-GOLD (Global Observation for Forest Cover and Land Dynamics) is currently supporting advances in the field and is developing guidance to overcome challenges including improving monitoring using interpretation of high-resolution satellite data for land cover (change) mapping and validation. Accurate, transparent and reproducible methods and results are required for monitoring purposes, and to enable decision makers (including forest managers, private sector, civil society and government agencies) to identify, plan and develop priority interventions and policies. This can also identify opportunities to reduce trade-offs from competing land-uses and to increase synergies, to achieve climate-smart land use.

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Full talk
ID: 711 / 211RB: 1
211R Advances in land monitoring for sustainable development
Keywords: Asia, forest degradation, SDG indicator, satellite remote sensing, Google Earth Engine.

Multi-scale monitoring of forest degradation using MODIS, Landsat and Sentinel data

Pinki Mondal1, Sonali McDermid2, Md. Abdul Q. Khan1

1University of Delaware, United States of America; 2New York University, United States of America

Sustainable Development Goal (SDG) indicator 15.1.1 proposes to quantify “Forest area as a proportion of total land area” in order to achieve SDG target 15.1. While, area under forest cover can provide useful information regarding discrete changes in forest cover, it does not provide any insight on subtle within-class changes, e.g. forest degradation. Continental or national-level studies, mostly utilizing coarse-scale satellite data, often fail to capture these changes due to the fine spatial and long temporal characteristics of forest degradation. Yet, these long-term changes affect forest structures, compositions and functions, thus ultimately limiting successful implementation of SDG targets.

Using a satellite-based monitoring approach, our goal is to provide a multi-scale satellite-based monitoring approach for South Asian forest ecosystem – spanning over Bangladesh, Bhutan, India, Nepal, Pakistan, and Sri Lanka for this study. We systematically analyze freely available remote sensing assets to provide a methodological framework for monitoring degradation and to evaluate the potential of multiple satellite data with different spatial resolutions for reporting forest degradation in this highly human-modified landscape. Taking a broad brush approach in step 1, we calculate trends in LP-DAAC’s MODIS data for Normalized Difference Vegetation Index (NDVI; rescaled to 1 km) during 2000-2016 in the context of weather variability, by combining NDVI data with the Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) rainfall trends over the same time-period. In step 2, we focus on two test cases for evaluating the potential of finer-resolution satellite data compared to MODIS, i.e. Landsat 8, Sentinel-1 and 2 (both optical and radar) data, for capturing forest degradation signals, which will ultimately contribute towards SDG indicators 15.1.1 and 15.1.2. We present evidence that utilizing higher-resolution satellite data (10- or 20-m) than those normally used for national-level studies might be crucial for reporting SDG indicator 15.2.1: “progress towards sustainable forest management”.

Full talk
ID: 737 / 211RB: 2
211R Advances in land monitoring for sustainable development
Keywords: Degradation, radar, ALOS, biomass, carbon stocks, miombo, mopane

Carbon losses from deforestation and widespread degradation offset by extensive growth in African woodlands

Casey M Ryan, Iain McNicol, Edward Mitchard

University of Edinburgh, United Kingdom

Land use carbon fluxes are major uncertainties in the global carbon cycle. This is because carbon stocks, the extent of deforestation and degradation, and biomass growth remain poorly resolved, particularly in the densely populated savannas which dominate the tropics. Here we quantify changes in aboveground woody carbon stocks from 2007-2010 in the world’s largest savanna – the southern African woodlands. We combine radar data from the Japanese ALOS PALSAR sensor with in situ field data to produce annual biomass maps of the region. Degradation is widespread, affecting 17.0% of the wooded area, and is the source of 55% of biomass loss (-0.075 PgC yr-1). Deforestation losses are lower (-0.038 PgC yr-1), despite deforestation rates being 5x greater than existing estimates. Gross carbon losses are therefore 3-6x higher than previously thought. Biomass gains occurred in 48% of the region and totalled +0.12 PgC yr-1. Region-wide stocks are therefore stable at ~5.5 PgC. We show that land cover in African woodlands is highly dynamic with globally high rates of degradation and deforestation, but also extensive regrowth. The methods employed here are widely applicable and we discuss a framework to implement pan-tropical degradation monitoring.

Full talk
ID: 560 / 211RB: 3
211R Advances in land monitoring for sustainable development
Keywords: Forest degradation, Tropical dry forests, Landsat time series, LandTrendr, Argentinean Dry Chaco

Relationships among forest disturbances, land use and woody cover patterns: an approach to forest degradation assessment in tropical dry forests

Teresa Rita De Marzo1, Matthias Baumann1, Philipp Gaertner2, Ignacio Gasparri2, Dirk Pflugmacher1, Eric Lambin3,4, Tobias Kuemmerle1

1Humboldt-Universität zu Berlin, Germany; 2Universidad Nacional de Tucumán - CONICET, Argentina; 3Université Catholique de Louvainé, Belgium; 4Stanford University, USA

Forest degradation has major impacts on ecosystems functioning and human livelihoods. Monitoring degradation is therefore important, but challenging for large areas. This is particularly so for the world’s tropical dry woodlands, which are characterized by high spatiotemporal variability in vegetation. Because many dry woodlands suffer from forest degradation, monitoring these ecosystems is a research priority.

We make full use of the entire Landsat image archive to detect abrupt and gradual forest change in the Dry Chaco in South America, a global deforestation hotspot. Specifically, we investigated the history and distribution of abrupt disturbances and long-term trends in the woodlands of the Argentinian Dry Chaco using mapped disturbances using LandTrendr temporal segmentation analyses for the time period 1987 to 2017 based on Tasseled Cap Wetness metrics. We then identified clusters of similar disturbances patterns using Self Organizing Maps and compared them with fractional woody cover components.

Our results highlight that in large areas across the Argentinean Dry Chaco, forest cover has been lost and remaining forest are affected by a range of disturbances likely reflecting degradation. Different land uses cause different vegetation signals, including regarding short-term disturbances (e.g. through selective logging) and regarding long-term trends (e.g. overgrazing in forests). This suggests potential of time series analyses to not only capture degradation signals, but also to attribute observed trends to land-use practices and actors. Protected areas exhibited generally less disturbances, but degradation often extended far into them. Comparing vegetation change metrics and distinct patches of contemporary tree and shrub cover indicated that degradation history is an important explanatory factor for contemporary woody cover in the Chaco.

More broadly, our work represents a step towards better understanding forest changes in the Dry Chaco and suggests considerable potential of Landsat time series for addressing and monitoring forest degradation in tropical dry forests.

Full talk
ID: 463 / 211RB: 4
211R Advances in land monitoring for sustainable development
Keywords: forest management impacts, climate change mitigation, land surface temperature, satellite remote sensing

Forest management in Europe and its local effect on land surface temperature (LST) – broadleaf tree cooling vs. dense forest cooling

Jonas Schwaab, Edouard Davin

ETH Zürich

Forest management (FM) influences climate by altering the concentration of CO2 or other atmospheric compounds (biogeochemical effects) and through its impact on albedo, evapotranspiration and surface roughness (biophysical effects). FM measures aiming at reducing or counteracting climate change need to account for both biogeochemical and biophysical effects. However, the biophysical climate effects of FM are not yet sufficiently understood and decision-makers lack scientific evidence when designing sustainable FM strategies. To enhance our understanding of the biophysical climate effect of FM and support decision-makers, we used two LST datasets over Europe (MODIS, LSA SAF) derived from satellite remote sensing observations and assessed the link between spatial patterns of LST and spatial patterns of forest structure and forest type (based on Copernicus "High Resolution Layers”).

Our results show that the two management strategies of increasing tree cover density and broadleaf tree fraction provide local cooling during the day in summer. During nights and in winter both FM strategies mainly cause warming. During the day an increased broadleaf tree fraction seems to provide cooling in the afternoon, while an increased tree cover density provides largest cooling at around noon. In mediterranean forests, the summer cooling caused by an increased tree cover density is more than two times higher than the one caused by an increased broadleaf tree fraction. In the boreal forest both strategies provide a cooling of similar magnitude. In boreal and alpine forests an increase in tree cover density and broadleaved tree fraction leads to an increase in yearly mean temperatures. However, for all regions we observe a reduction in maximum temperatures in summer and potentially during heatwaves.

Assessing the temperature effect of FM on high spatio-temporal resolution is a prerequisite for sustainable forest management and enhances our understanding of biophysical effects of FM.

Flash talk
ID: 868 / 211RB: 5
211R Advances in land monitoring for sustainable development
Keywords: Deforestation, forest loss, habitat loss, protected areas

Forest fragmentation and payment for ecosystem services in Mexico

Carlos Ramirez-Reyes1, Katharine R. E. Sims2, Peter Potapov3, Volker C. Radeloff1

1SILVIS Lab, Department of Forest and Wildlife Ecology, University of Wisconsin-Madison; 2Departments of Economics and Environmental Studies, Amherst College; 3Department of Geographical Sciences, University of Maryland

Forest fragmentation can lead to habitat reduction and exposure to disturbances. Payments for ecosystem services (PES) are becoming an important policy that could prevent such impacts in forests by offering compensation to landowners for environmental stewardship. Mexico was one of the first countries implementing a large-scale PES program, enrolling over 2.3 Mha by 2011, but it is not clear whether this program was successful in preventing forest fragmentation. We studied whether Mexican forests enrolled in the PES program had less forest fragmentation than those not enrolled, and if the PES effects varied among forest types, among socioeconomic zones, or compared to the protected areas system. We calculated forest fragmentation from 2000 to 2012 across Mexico using publicly available global forest cover maps. We investigated the possible causal impacts of the PES on forests across Mexico using matching analysis. We found that the area covered by forest in Mexico decreased by 3.4% from 2000 to 2012, resulting in 9.3% less forest core area. Change in forest cover was highest in the southern part of Mexico, and high-stature evergreen tropical forest lost the most core areas (-17%), while oak forest lost the least (-2%). Low-PES areas increased twice as much of the number of forest patches and forest edge compared to high-PES areas, offering a similar protection to that from protected areas. We conclude that the PES successfully slow forest fragmentation at the regional and country level. Global forest maps can be used to monitor the outcomes of forest protection programs including REDD+ and PES.

Flash talk
ID: 634 / 211RB: 6
211R Advances in land monitoring for sustainable development
Keywords: remote-sensing, rangelands, drylands, Participatory

Landscape-based vegetation monitoring to support participatory planning and management in dry rangelands

matteo jucker riva, Pascale Waelti, Joshua Scott Witshoe, Stefan Graf

HAFL-BFH, Switzerland

Dry rangelands around the world are under pressure because of the constraining abiotic conditions and anthropogenic pressure derived form land use. Last decades research and implementation around land use planning have stressed the importance of participatory methods – especially on collective lands - to ensure sustainable use of natural resources in the long term while maintaining productivity and sustaining livelihood. In particular, the Participatory Rangeland Management (PRM) framework has been adopted in many dry rangelands to design, implement and maintain sustainable rangeland use systems. To be effective, PRM requires a combination of scientific and lay knowledge, and a thorough understanding of the ecosystem state, evolution and impact of land use.

To substantiate the participatory decision-making, Wwe have developed a landscape-based approach for the analysis of remotely sensed dynamic of vegetation to provide land managers in data-scarce dry rangelands with spatially explicit, up-to-date information on the state of their land, the pressures driving land degradation, and the effectiveness of management, at a temporal and spatial scale fit to be used by land managers, supporting the following important steps of PRM:

1. Quantifying vegetation productivity across landscapes and grazing intensity levels, functional to the identification of rangeland resources

2. Discriminating land units with different trends and dynamics, facilitating planning and negotiation around natural resouce management e.g. grazing patterns

3. Monitoring the effectiveness of sustainable management practices, to help improve management practices and revise existing plans.

Along with the approach and indicators developed, we will present some insights on how remote sensing can be integrated in participatory land use planning, what tools and methods can be used. Moreover, we will propose ways to include stakeholder knowledge in remote-sensing based models and analysis to improve their accuracy and usability.

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