Martin Herold

Martin Herold
Helmholtz-Zentrum Potsdam - Deutsches GeoForschungsZentrum GFZ | GFZ · Division of Remote Sensing

PhD

About

465
Publications
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Introduction
Martin Herold is head of the Remote Sensing and Geoinformatics section at GFZ Potsdam and full professor of Remote Sensing at University of Potsdam.

Publications

Publications (465)
Article
Full-text available
Calibration and validation of aboveground biomass (AGB) (AGB) products retrieved from satellite-borne sensors require accurate AGB estimates across hectare scales (1 to 100 ha). Recent studies recommend making use of non-destructive terrestrial laser scanning (TLS) based techniques for individual tree AGB estimation that provide unbiased AGB predic...
Article
Full-text available
The sustainable management of aquatic resources requires spatially explicit information on the water and vegetation presence of aquatic ecosystems. Previous Global Aquatic Land Cover (GALC) mapping has been focused on water bodies while lacking information on vegetation, and aquatic types have always been characterized by low accuracies in global l...
Article
Full-text available
National forest inventories (NFIs) are a reliable source for national forest measurements. However, they are usually not developed for linking with remotely sensed (RS) biomass information. There are increasing needs and opportunities to facilitate this link toward better global and national biomass estimation. Thus, it is important to study and un...
Data
The document provides information for transparency and reproducibility of the study according to the standard for species distribution modeling (ODMAP protocol) from Zurrell et al. (2020). Additional information reported include: (1) implementation strategy and results of spatial filtering operation, (2) hyperparameter space for model optimization...
Article
Full-text available
This paper describes a data-driven framework based on spatiotemporal machine learning to produce distribution maps for 16 tree species (Abies alba Mill., Castanea sativa Mill., Corylus avellana L., Fagus sylvatica L., Olea europaea L., Picea abies L. H. Karst., Pinus halepensis Mill., Pinus nigra J. F. Arnold, Pinus pinea L., Pinus sylvestris L., P...
Preprint
Full-text available
This paper describes a data-driven framework based on spatiotemporal machine learning to produce distribution maps for 16 tree species (Abies alba Mill., Castanea sativa Mill., Corylus avellana L., Fagus sylvatica L., Olea europaea L., Picea abies L. H. Karst., Pinus halepensis Mill., Pinus nigra J. F. Arnold, Pinus pinea L., Pinus sylvestris L., P...
Article
The backscattered power recorded by a spaceborne scatterometer operating at C-band is sensitive to land surface parameters and is operationally used by some global remote sensing services, e.g., to estimate soil moisture. The estimation of forest variables, in particular above-ground biomass (AGB), from scatterometer data instead was seldom explore...
Article
Full-text available
An increase in the frequency and severity of disturbances (such as forest fires) is putting pressure on the resilience of the Amazon tropical forest; potentially leading to reduced ability to recover and to maintain a functioning forest ecosystem. Dense and long-term satellite time series approaches provide a largely untapped data source for charac...
Poster
Full-text available
The poster describes a data-driven framework based on spatio-temporal ensemble machine learning to produce distribution maps for 16 tree species at high spatial resolution (30m). Tree occurrence data for a total of 3 million of points was used to train different Machine Learning (ML) algorithms: random forest, gradient-boosted trees, generalized li...
Conference Paper
Land use/cover change is central to understanding the global sustainability challenges of climate change, biodiversity loss, and food security. Yet, while the magnitude of global land use has often been studied, little is known about land use transitions and their drivers, and how these vary across the world. A major obstacle has been the lack of c...
Article
Full-text available
Tree restoration is an effective way to store atmospheric carbon and mitigate climate change. However, large-scale tree-cover expansion has long been known to increase evaporation, leading to reduced local water availability and streamflow. More recent studies suggest that increased precipitation, through enhanced atmospheric moisture recycling, ca...
Article
Full-text available
Over the past decade, several global maps of above-ground biomass (AGB) have been produced, but they exhibit significant differences that reduce their value for climate and carbon cycle modelling, and also for national estimates of forest carbon stocks and their changes. The number of such maps is anticipated to increase because of new satellite mi...
Article
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Analysis of forest disturbance patterns in relation to precipitation seasonality is important for understanding African tropical forest dynamics under changing climate conditions and different levels of human activities. Newly available radar-based forest disturbance information now enables an investigation of the intra-annual relationship between...
Article
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Two novel satellite LiDAR missions —GEDI and ICESat-2— are currently operational and combined provide near-global measurements of forest height and structure. Such data underpin a new era of large-area approaches for measuring forest height in regrowing forests of different ages and assessing associated regrowth rates. Two LiDAR missions further al...
Article
Full-text available
Spatially explicit monitoring of tropical forest aboveground carbon is an important prerequisite for better targeting and assessing forest conservation efforts and more transparent reporting of carbon losses. Here, we combine near-real-time forest disturbance alerts based on all-weather radar data with aboveground carbon stocks to provide carbon lo...
Article
Full-text available
Urbanization as a global phenomenon is a multifaceted process. Here we do the first global attempt to characterize the complexity of urbanization from 1975 to 2015 in terms of population, built-up structure, and greenness per 5 × 5 km² grid covering global inhabited areas, using Earth Observation data sources. Our results emphasize the multifaceted...
Article
Full-text available
Accurately quantifying tree and forest structure is important for monitoring and understanding terrestrial ecosystem functioning in a changing climate. The emergence of laser scanning, such as Terrestrial Laser Scanning (TLS) and Unoccupied Aerial Vehicle Laser Scanning (UAV-LS), has advanced accurate and detailed forest structural measurements. TL...
Article
Full-text available
One of the most fundamental questions in ecology is how many species inhabit the Earth. However, due to massive logistical and financial challenges and taxonomic difficulties connected to the species concept definition, the global numbers of species, including those of important and well-studied life forms such as trees, still remain largely unknow...
Article
Full-text available
Several forest change detection algorithms are available for tracking and quantifying deforestation based on dense Landsat and Sentinel time series satellite data. Only few also capture regrowth after clearing in an accurate and continuous way across a diversity of forest types (including dry and seasonal forests) and are thus suitable to address t...
Article
Full-text available
One of the most fundamental questions in ecology is how many species inhabit the Earth. However, due to massive logistical and financial challenges and taxonomic difficulties connected to the species concept definition, the global numbers of species, including those of important and well-studied life forms such as trees, still remain largely unknow...
Article
Full-text available
For monitoring and reporting forest carbon stocks and fluxes, many countries in the tropics and subtropics rely on default values of forest aboveground biomass (AGB) from the Intergovernmental Panel on Climate Change (IPCC) Guidelines for National Greenhouse Gas (GHG) Inventories. Default IPCC forest AGB values originated from 2006, and are relativ...
Article
Full-text available
Comparing the performance of different satellite sensors in global land cover change (LCC) monitoring is necessary to assess their potential and limitations for more accurate and operational LCC estimations. This paper aims to examine and compare the performance in LCC monitoring using three satellite sensors: PROBA-V, Landsat 8 OLI, and Sentinel-2...
Preprint
Full-text available
Land use efficiency, energy efficiency, and air quality are key indicators when assessing urban-related Sustainable Development Goals (SDGs), yet recent trends and trade-offs in and around urban areas worldwide remain largely unknown. We use an Earth Observation approach to map the land-energy-air sustainability nexus and highlight distinct urban-r...
Article
Full-text available
Annual global land cover maps (GLC) are being provided by several operational monitoring efforts. However, map validation is lagging, in the sense that the annual land cover maps are often not validated. Concurrently, users such as the climate and land management community require information on the temporal consistency of multi-date GLC maps and s...
Article
Full-text available
Remote Sensing-based global Forest/Non-Forest (FNF) masks have shown large inaccuracies in tropical wetland areas. This limits their applications for deforestation monitoring and alerting in which they are used as a baseline for mapping new deforestation. In radar-based deforestation monitoring, for example, moisture dynamics in unmasked non-forest...
Article
Full-text available
The monitoring of Global Aquatic Land Cover (GALC) plays an essential role in protecting and restoring water-related ecosystems. Although many GALC datasets have been created before, a uniform and comprehensive GALC dataset is lacking to meet multiple user needs. This study aims to assess the effectiveness of using existing global datasets to devel...
Article
Full-text available
Tropical forests store 40-50% of terrestrial vegetation carbon. Spatial variations in aboveground live tree biomass carbon (AGC) stocks remain poorly understood, in particular in tropical montane forests. Because of climatic and soil changes with increasing elevation, AGC stocks are lower in tropical montane compared to lowland forests. Here we ass...
Article
Full-text available
Tropical forests store 40–50 per cent of terrestrial vegetation carbon1. However, spatial variations in aboveground live tree biomass carbon (AGC) stocks remain poorly understood, in particular in tropical montane forests2. Owing to climatic and soil changes with increasing elevation3, AGC stocks are lower in tropical montane forests compared with...
Article
Full-text available
BFAST Lite is a newly proposed unsupervised time series change detection algorithm that is derived from the original BFAST (Breaks for Additive Season and Trend) algorithm, focusing on improvements to speed and flexibility. The goal of the BFAST Lite algorithm is to aid the upscaling of BFAST for global land cover change detection. In this paper, w...
Article
Full-text available
Like many other tropical countries, the Philippines has suffered from decades of deforestation and forest degradation during and even after the logging era. Several open access Earth Observation (EO) products are increasingly being used for deforestation analysis in support of national and international initiatives and policymaking on forest conser...
Article
Full-text available
The paper evaluates Deep neural network architectures that account for either (a) spatial-temporal information, i.e., Hybrid Recurrent convolutional neural network, 3D-convolutions, ConvLSTM, and the novel CNN + Multi Head Self-Attention model, or (b) only spatial information, i.e., 2D-convolutions, (c) only temporal information, i.e.,Long short te...
Conference Paper
Maps of above-ground biomass (AGB) using remote sensing (RS) are valuable to countries like the Philippines for multi-purposes including national greenhouse gas reporting, carbon accounting and even reforestation monitoring. As RS data increase, both optical and radar satellite data have been combined to produce higher quality AGB maps, rather than...
Article
Full-text available
Estimates of the area of land cover classes or land change are frequently calculated from land cover classification maps by counting the pixels labeled as each class in the map. This procedure is known to produce biased estimates of area for many widely used classification algorithms, including random forests. Poststratification estimation using th...
Article
Full-text available
Forest monitoring is the recurrent measurement of forest parameters to identify changes over time. There is currently a rising demand for monitoring, as well as growing capacities for it. This study identifies recent research on tropical forest monitoring using a systematic literature review. The research explores whether the location of these stud...
Article
Currently most global land cover maps are produced with discrete classes, which express the dominant land cover class in each pixel, or a combination of several classes at a predetermined ratio. In contrast, land cover fraction mapping enables expressing the proportion of each pure class in each pixel, which increases precision and reduces legend c...
Article
Full-text available
Four workshops and a webinar series were organized, with the aim of building capacity in countries to use Earth Observation Remote Sensing data to monitor forest cover changes and measure emissions reductions for REDD+ results-based payments. Webinars and workshops covered a variety of relevant tools and methods. The initiative was collaboratively...
Article
Full-text available
Accurate sub-annual detection of forest disturbance provides timely baseline information for understanding forest change and dynamics to support the development of sustainable forest management strategies. Traditionally , Landsat imagery was widely used to monitor forest disturbance, but the low temporal density of Landsat observations limits the t...
Article
Full-text available
Quantifying the dynamics of land use change is critical in tackling global societal challenges such as food security, climate change, and biodiversity loss. Here we analyse the dynamics of global land use change at an unprecedented spatial resolution by combining multiple open data streams (remote sensing, reconstructions and statistics) to create...
Article
Full-text available
Globally, countries report forest information to the Food and Agriculture Organization (FAO) of the United Nations Global Forest Resources Assessments (FRA) at regular intervals. While the status and trends of national forest monitoring capacities have been previously assessed for the tropics, this has not been systematically done worldwide. In thi...
Conference Paper
Full-text available
Land use change is a major contributor to greenhouse gas emissions and biodiversity loss and, hence, a key topic for current sustainability debates and climate change mitigation. To understand its impacts, accurate data of global land use change and an assessment of its extent, dynamics, causes and interrelations are crucial. However, although nume...
Article
Full-text available
Tropical forest disturbances linked to fire usage cause large amounts of greenhouse gas (GHG) emissions and environmental damages. Supporting precise GHG estimations and counteracting illegal fire usages in the tropics require timely and thematically detailed large-scale information on fire-related forest disturbances. Multi-sensor optical and rada...
Article
Full-text available
Disturbed African tropical forests and woodlands have the potential to contribute to climate change mitigation. Therefore, there is a need to understand how carbon stocks of disturbed and recovering tropical forests are determined by environmental conditions and human use. In this case study, we explore how gradients in environmental conditions and...
Article
Full-text available
Managing forests for climate change mitigation requires action by diverse stakeholders undertaking different activities with overlapping objectives and spatial impacts. To date, several forest carbon monitoring systems have been developed for different regions using various data, methods and assumptions, making it difficult to evaluate mitigation p...
Article
Full-text available
A humid tropical forest disturbance alert using Sentinel-1 radar data is presented for the Congo Basin. Radar satellite signals can penetrate through clouds, allowing Sentinel-1 to provide gap-free observations for the tropics consistently every 6-12 days at 10 m spatial scale. In the densely cloud covered Congo Basin, this represents a major advan...
Book
Full-text available
the full text can be found at: https://lpvs.gsfc.nasa.gov/PDF/CEOS_WGCV_LPV_Biomass_Protocol_2021_V1.0.pdf
Article
Full-text available
The terrestrial forest carbon pool is poorly quantified, in particular in regions with low forest inventory capacity. By combining multiple satellite observations of synthetic aperture radar (SAR) backscatter around the year 2010, we generated a global, spatially explicit dataset of above-ground live biomass (AGB; dry mass) stored in forests with a...
Article
Deep learning (DL) has proven to be a suitable approach for despeckling synthetic aperture radar (SAR) images. So far, most DL models are trained to reduce speckle that follows a particular distribution, either using simulated noise or a specific set of real SAR images, limiting the applicability of these methods for real SAR images with unknown no...
Preprint
Full-text available
Deep learning (DL) has proven to be a suitable approach for despeckling synthetic aperture radar (SAR) images. So far, most DL models are trained to reduce speckle that follows a particular distribution, either using simulated noise or a specific set of real SAR images, limiting the applicability of these methods for real SAR images with unknown no...