Evaluation of satellite based indices for gross primary production estimates in a sparse savanna in the Sudan

One of the more frequently applied methods for integrating controls on primary production through satellite data is the Light Use Efficiency (LUE) approach. Satellite indices such as the Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI) and the Shortwave Infrared Water Stress Index (SIWSI) have previously shown promise as predictors of primary production in several different environments. In this study, we evaluate NDVI, EVI and SIWSI derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite sensor against in-situ measurements from central Sudan in order to asses their applicability in LUE-based primary production modeling within a water limited environment. Results show a strong correlation between vegetation indices and gross primary production (GPP), demonstrating the significance of vegetation indices for deriving information on primary production with relatively high accuracy at similar areas. Evaluation of SIWSI however, reveal that the fraction of vegetation apparently is to low for the index to provide accurate information on canopy water content, indicating that the use of SIWSI as a predictor of water stress in satellite data-driven primary production modeling in similar semi-arid ecosystems is limited

How conflict affects land use: Agricultural activity in areas seized by the Islamic State

© 2017 The Author(s). Published by IOP Publishing Ltd.Socio-economic shocks, technogenic catastrophes, and armed conflicts often have drastic impacts on local and regional food security through disruption of agricultural production and food trade, reduced investments, and deterioration of land and infrastructure. Recently, more research has focused on the effects of armed conflict on land systems, but still little is known about the processes and outcomes of such events. Here we use the case of Syria and Iraq and the seizure of land by the Islamic State (IS) since 2014 as an example of armed conflict, where we investigate the effects on agricultural land use. We apply a reproducible approach using 250 m satellite-based time-series data to quantify the areas under cultivation from 2000 to 2015. Despite a common belief about widespread land abandonment in areas under conflict, results point to multiple trajectories regarding cropland cultivation in the IS seized area: (1) expansion of cropland to formerly un-cultivated areas, (2) cropland abandonment, and (3) decrease of high-intensity cropland. Our study highlights the need to understand these diverse conflict-related and context-dependent changes to the land system

Upscaling of methane exchange in a boreal forest using soil chamber measurements and high-resolution LiDAR elevation data

Forest soils are generally considered to be net sinks of methane (CH4), but CH4 fluxes vary spatially depending on soil conditions. Measuring CH4 exchange with chambers, which are commonly used for this purpose, might not result in representative fluxes at site scale. Appropriate methods for upscaling CH4 fluxes from point measurements to site scale are therefore needed. At the boreal forest research site, Norunda, chamber measurements of soils and vegetation indicate that the site is a net sink of CH4, while tower gradient measurements indicate that the site is a net source of CH4. We investigated the discrepancy between chamber and tower gradient measurements by upscaling soil CH4 exchange to a 100 ha area based on an empirical model derived from chamber measurements of CH4 exchange and measurements of soil moisture, soil temperature and water table depth. A digital elevation model (DEM) derived from high-resolution airborne Light Detection and Ranging (LiDAR) data was used to generate gridded water table depth and soil moisture data of the study area as input data for the upscaling. Despite the simplistic approach, modeled fluxes were significantly correlated to four out of five chambers with R>0.68. The upscaling resulted in a net soil sink of CH4 of -10 mu mol m(-2) h(-1), averaged over the entire study area and time period June-September, 2010). Our findings suggest that additional contributions from CH4 soil sources outside the upscaling study area and possibly CH4 emissions from vegetation could explain the net emissions measured by tower gradient measurements. (C) 2015 Elsevier B.V. All rights reserved

Carbon budget estimation of a subarctic catchment using a dynamic ecosystem model at high spatial resolution

A large amount of organic carbon is stored in high-latitude soils. A substantial proportion of this carbon stock is vulnerable and may decompose rapidly due to temperature increases that are already greater than the global average. It is therefore crucial to quantify and understand carbon exchange between the atmosphere and subarctic/arctic ecosystems. In this paper, we combine an Arctic-enabled version of the process-based dynamic ecosystem model, LPJ-GUESS (version LPJG-WHyMe-TFM) with comprehensive observations of terrestrial and aquatic carbon fluxes to simulate long-term carbon exchange in a subarctic catchment at 50 m resolution. Integrating the observed carbon fluxes from aquatic systems with the modeled terrestrial carbon fluxes across the whole catchment, we estimate that the area is a carbon sink at present and will become an even stronger carbon sink by 2080, which is mainly a result of a projected densification of birch forest and its encroachment into tundra heath. However, the magnitudes of the modeled sinks are very dependent on future atmospheric CO₂ concentrations. Furthermore, comparisons of global warming potentials between two simulations with and without CO₂ increase since 1960 reveal that the increased methane emission from the peatland could double the warming effects of the whole catchment by 2080 in the absence of CO₂ fertilization of the vegetation. This is the first process-based model study of the temporal evolution of a catchment-level carbon budget at high spatial resolution, including both terrestrial and aquatic carbon. Though this study also highlights some limitations in modeling subarctic ecosystem responses to climate change, such as aquatic system flux dynamics, nutrient limitation, herbivory and other disturbances, and peatland expansion, our study provides one process-based approach to resolve the complexity of carbon cycling in subarctic ecosystems while simultaneously pointing out the key model developments for capturing complex subarctic processes.For a previous discussion paper please see: http://hdl.handle.net/1957/56948. This is the publisher’s final pdf. The published article is copyrighted by the author(s) and published by Copernicus Publications on behalf of the European Geosciences Union. The published article can be found at: http://www.biogeosciences.net/home.html

Carbon budget estimation of a subarctic catchment using a dynamic ecosystem model at high spatial resolution

Large amount of organic carbon is stored in high latitude soils. A substantial proportion of this carbon stock is vulnerable and may decompose rapidly due to temperature increases that are already greater than the global average. It is therefore crucial to quantify and understand carbon exchange between the atmosphere and subarctic/arctic ecosystems. In this paper, we combine an arctic-enabled version of the process-based dynamic ecosystem model, LPJ-GUESS (version LPJG-WHyMe-TFM) with comprehensive observations of terrestrial and aquatic carbon fluxes to simulate long-term carbon exchange in a subarctic catchment comprising both mineral and peatland soils. The model is applied at 50 m resolution and is shown to be able to capture the seasonality and magnitudes of observed fluxes at this fine scale. The modelled magnitudes of CO₂ uptake generally follow the descending sequence: birch forest, non-permafrost Eriophorum, Sphagnum and then tundra heath during the observation periods. The catchment-level carbon fluxes from aquatic systems are dominated by CO₂ emissions from streams. Integrated across the whole catchment, we estimate that the area is a carbon sink at present, and will become an even stronger carbon sink by 2080, which is mainly a result of a projected densification of birch forest and its encroachment into tundra heath. However, the magnitudes of the modelled sinks are very dependent on future atmospheric CO₂ concentrations. Furthermore, comparisons of global warming potentials between two simulations with and without CO₂ increase since 1960 reveal that the increased methane emission from the peatland could double the warming effects of the whole catchment by 2080 in the absence of CO₂ fertilization of the vegetation. This is the first process-based model study of the temporal evolution of a catchment-level carbon budget at high spatial resolution, integrating comprehensive and diverse fluxes including both terrestrial and aquatic carbon. Though this study also highlights some limitations in modelling subarctic ecosystem responses to climate change including aquatic system flux dynamics, nutrient limitation, herbivory and other disturbances and peatland expansion, our application provides a mechanism to resolve the complexity of carbon cycling in subarctic ecosystems while simultaneously pointing out the key model developments for capturing complex subarctic processes.This discussion paper has been under review for the journal Biogeosciences (BG). Please refer to the corresponding final paper in BG. The published article is copyrighted by the author(s) and published by Copernicus Publications on behalf of the European Geosciences Union. The final revised paper is available at: http://hdl.handle.net/1957/5694

Estimating slope from raster data : A test of eight different algorithms in flat, undulating and steep terrain

Eight frequently used slope algorithms based on a DEM (Digital Elevation Model) have been compared in flat, gently sloping/undulating, and steep terrain in order to investigate differences in estimated results. The matter of scale/resolution has not been considered, and the focus has not been on comparing the estimates with "ground truth" data but on comparisons between the different algorithms. Pair-wise statistical tests have been carried out to detect significant differences between the methods in general, and also between different terrains. In this way, we make explanations and recommendations regarding these differences and "best practice" depending on data/terrain

Estimating surface flow over digital elevation models using a new improved form-based algorithm

This paper discusses new improvements of a form-based algorithm, which is used to estimate flow distribution over a continuous surface. In the new form- based algorithm (IFBFD), cells in a DEM are classified into five different classes. The classes are Peaks, Complicated, Sinks, Flats and Undisturbed cells. The method of how to estimate the flow distribution from each cell depends on its class. Estimating the flow distribution over flat area cells and sinks is done in an innovative way. The flow over a flat area can be either flow-out or flow-in. Flow-out occurs when one or more cells on the flat area border has an elevation lower than the flat area cells. The flat area is classified as 'flow-in' when all cells on the border of flat area have elevations higher than the flat area cells. The result is that the flow will be converged in the center of the flat area, and that cells will have no outflow (sink). Additionally, a culvert function is added to the new algorithm to enable the user to deal with man-made flow barriers like roads and railway lines. The new culvert function breaches the barrier and connects the flow between two defined points on both sides of it. The new algorithm is tested using the number of mathematical surfaces, as well as on a real DEM derived from LIDAR data. The results of comparing our new algorithm with some well-known algorithm used in most GIS programs shows that the IFBFD algorithm produces more realistic results than other algorithms. Tests show the capability of the new IFBFD algorithm to deal with different terrain types, flat areas and sinks, making it suitable for simulating the real flow distribution over any DEM without the need to e.g. fill sinks. Moreover, the IFBFD algorithm produces a convincing result when deriving the drainage network

Neural networks, multitemporal landsat thematic mapper data and topographic data to classify forest damages in the Czech republic

This study uses multitemporal Landsat Thematic Mapper data and topographic data for the purpose of classifying coniferous forest damage in the Czech Republic using an artificial neural network. Comparing the neural network-based classification with earlier studies and a multinominal logistic regression using identical training and test data indicates that the back propagation algorithm is comparable, but not superior, to conventional methods. The dependence on the randomly set input weights and the more time-consuming back propagation training make neural network less useful for classification of forest damages than conventional classification algorithms. However, the ability to integrate and extract information from multisource data with different or unknown distributions are advantages of neural networks

Lagring av geografiska data

Summary: Geografisk informationsbehandling baseras på insamling, lagring, analys och visualisering av geografiska data. Denna indelning utgör också grunden för bokens disposition. Boken är i första hand avsedd för introducerande kurser vid universitet och högskolor men vissa delar är lämpliga även på avancerad nivå. Den är också utmärkt för yrkesverksamma inom GIS som vill öka sina teoretiska kunskaper. Boken innehåller både teoretiska och praktiska delar, där de senare beskriver tillämpningar som exempelvis samhällsplanering, miljöövervakning och kommersiella tjänster. I insamlingsdelen beskrivs hur man anger en position genom att koppla ett koordinatsystem till jordytan. Därefter beskrivs de vanligaste metoderna att samla in geografiska data som satellitbaserade positioneringssystem, flygfotografering, satellitbaserad fjärranalys och laserskanning. Lagringsdelen behandlar hur dessa data lagras i databaser och distribueras via webben. Analysdelen innehåller beskrivningar av de vanligaste analysmetoderna samt kvalitetsfrågor. Resultatet av en geografisk analys visualiseras oftast i form av kartor, vilket är temat för den sista delen av boken. Denna sjunde upplaga har uppdaterats med nya aktuella tillämpningsexempel. Dessa är i denna upplaga beskrivna tillsammans med de teoretiska beskrivningarna för att stärka kopplingen mellan teori och tillämpningar. Dessutom har beskrivningen av webbtillämpningar utökats och utgör nu ett eget kapitel, och även texten om webbvisualiseringar har stärkts i kartografikapitlet. Vidare har det tillkommit beskrivningar av nya mättekniker samt texter om lagring, analys och visualisering av 3D geografiska data