Burnt area mapping in insular Southeast Asia using medium resolution satellite imagery

Burnt area mapping in humid tropical insular Southeast Asia using medium resolution (250-500m) satellite imagery is characterized by persisting cloud cover, wide range of land cover types, vast amount of wetland areas and highly varying fire regimes. The objective of this study was to deepen understanding of three major aspects affecting the implementation and limits of medium resolution burnt area mapping in insular Southeast Asia: 1) fire-induced spectral changes, 2) most suitable multitemporal compositing methods and 3) burn scars patterns and size distribution. The results revealed a high variation in fire-induced spectral changes depending on the pre-fire greenness of burnt area. It was concluded that this variation needs to be taken into account in change detection based burnt area mapping algorithms in order to maximize the potential of medium resolution satellite data. Minimum near infrared (MODIS band 2, 0.86μm) compositing method was found to be the most suitable for burnt area mapping purposes using Moderate Resolution Imaging Spectroradiometer (MODIS) data. In general, medium resolution burnt area mapping was found to be usable in the wetlands of insular Southeast Asia, whereas in other areas the usability was seriously jeopardized by the small size of burn scars. The suitability of medium resolution data for burnt area mapping in wetlands is important since recently Southeast Asian wetlands have become a major point of interest in many fields of science due to yearly occurring wild fires that not only degrade these unique ecosystems but also create regional haze problem and release globally significant amounts of carbon into the atmosphere due to burning peat. Finally, super-resolution MODIS images were tested but the test failed to improve the detection of small scars. Therefore, super-resolution technique was not considered to be applicable to regional level burnt area mapping in insular Southeast Asia.Laaja valikoima erilaisia maankäyttöluokkia, pilvisyys ja kosteikkoalueiden suuri määrä luovat erityispiirteet paloalueiden kartoitukselle Kaakkois-Aasian saariston kostean troppisissa olosuhteissa keskiresoluutioisilla (250m-500m) satelliittikuva-aineistoilla. Tämän tutkimuksen tavoitteena oli syventää ymmärrystä keskiresoluutioisen paloaluekartoituksen toteutukseen ja rajoituksiin Kaakkois-Aasian saaristossa vaikuttavista tekijöistä. Tutkimuksen tulokset paljastivat suurta vaihtelua tulipalojen aiheuttamissa heijastussäteilyn muutoksissa riippuen palaneen alueen vehreydestä ennen tulipaloa. Johtopäätöksenä todettiin että keskiresoluutioisten satelliittikuvien koko potentiaalin hyödyntämiseksi paloalueiden kartoituksessa tämä vaihtelu tulisi ottaa huomioon paloalueiden havainnointialgoritmeissa jotka perustuvat heijastussäteilyn muutosten seurantaan. Tähän ajatukseen perustuvaa paloalueiden kartoitusta myös kokeiltiin aineistoilla jotka oli tutkimuksissa todettu parhaiten tarkoitukseen sopiviksi. Paloalueiden muoto- ja kokojakauman analyysiin sekä käytännön testeihin perustuen keskiresoluutioinen paloalueiden kartoitus todettiin käyttökelpoiseksi Kaakkois-Aasian saariston kosteikkoalueilla. Muilla alueilla sen sijaan paloalueiden pieni koko uhkasi vakavasti sen käyttökelpoisuutta. Keskiresoluutioisten satelliittikuva-aineistojen käyttökelpoisuus paloalueiden kartoitukseen kosteikkoalueilla on kuitenkin merkittävää sillä viime aikoina Kaakkois-Aasian kosteikkoalueet ovat monilla tieteenaloilla nousseet kiinnostuksen kohteeksi vuosittain esiintyvien tulipalojen takia. Vuosittaiset tulipalot eivät ainoastaan heikennä näitä ainutlaatuisia ekosysteemejä vaan lähinnä palavan turpeen johdosta myös aiheuttavat pahoja alueellisia savusumuongelmia ja vapauttavat maailmanlaajuisesti merkittäviä määriä hiilidioksidia ilmakehään. Tämän tutkimuksen tulokset osaltaan luovat pohjaa yhä tarkempien alueellisten paloalueiden kartoitusmenetelmien kehittämiselle. Näillä menetelmillä kerättävä tieto paloalueiden laajuudesta ja sijainneista antaa muiden alojen tutkijoille yhä paremmat mahdollisuudet arvioida Kaakkois-Aasian saariston kosteikkoalueiden tulipalojen paikallisia, alueellisia ja maailmanlaajuisia vaikutuksia

Using New and Long-Term Multi-Scale Remotely Sensed Data to Detect Recurrent Fires and Quantify Their Relationship to Land Cover/Use in Indonesian Peatlands

Indonesia has committed to reducing its greenhouse gases emissions by 29% (potentially up to 41% with international assistance) by 2030. Achieving those targets requires many efforts but, in particular, controlling the fire problem in Indonesia’s peatlands is paramount, since it is unlikely to diminish on its own in the coming decades. This study was conducted in Sumatra and Kalimantan peatlands in Indonesia. Four MODIS-derived products (MCD45A1 collection 5.1, MCD64A1 (collection 5.1 and 6), FireCCI51) were initially assessed to explore long-term fire frequency and land use/cover change relationships. The results indicated the product(s) could only detect half of the fires accurately. A further study was conducted using additional moderate spatial resolution data to compare two years of different severity (2014 and 2015) (Landsat, Sentinel 2, Sentinel 1, VIIRS 375 m). The results showed that MODIS BA products poorly discriminated small fires and failed to detect many burned areas due to persistent interference from clouds and smoke that often worsens as fire seasons progress. Although there are unique fire detection capabilities associated with each sensor (MODIS, VIIRS, Landsat, Sentinel 2, Sentinel 1), no single sensor was ideal for accurate detection of peatland fires under all conditions. Multisensor approaches could advance biomass-burning detection in peatlands, improving the accuracy and comprehensive coverage of burned area maps, thereby enabling better estimation of associated fire emissions. Despite missing many burned areas, MODIS BA (MCD64A1 C6) provides the best available data for evaluating longer term (2001-2018) associations between the frequency of fire occurrence and land use/cover change across large areas. Results showed that Sumatra and Kalimantan have both experienced frequent fires since 2001. Although extensive burning was present across the entire landscape, burning in peatlands was ~5- times more frequent and strongly associated with changes of forest to other land use/cover classes. If fire frequencies since 2001 remain unchanged, remnant peat swamp forests of Sumatra and Kalimantan will likely disappear over the next few decades. The findings reported in this dissertation provide critical insights for Indonesian stakeholders that can help them to minimize impacts of environmental change, manage ecological restoration efforts, and improve fire monitoring systems within Indonesia

TOWARDS OBJECT-BASED EVALUATION OF INDIVIDUAL FIRES AT GLOBAL SCALES

Fire is a complex biophysical variable that has shaped the land surface for over 400 million years and continues to play important roles in landscape management, atmospheric emissions, and ecology. Our understanding of global fire patterns has improved dramatically in recent decades, coincident with the rise of systematic acquisition and development of global thematic products based on satellite remote sensing. Currently, there are several operational algorithms which map burned area, relying on coarse spatial resolution sensors with high temporal frequencies to identify fire-affected surfaces. While wildfires have been analyzed over large areas at the pixel level, object-based methods can provide more detailed attributes about individual fires such as fire size, severity, and spread rate. This dissertation evaluates burned area products using object-based methods to quantify errors in burn shapes and to extract individual fires from existing datasets. First, a wall-to-wall intercomparison of four publicly available burned area products highlights differences in the spatial and temporal patterns of burning identified by each product. The results of the intercomparison show that the MODIS Collection 6 MCD64A1 Burned Area product mapped the most burned area out of the four products, and all products except the Copernicus Burnt Area product showed agreement with regard to temporal burning patterns. In order to determine the fitness of the MCD64A1 product for mapping fire shapes, a framework for evaluating the shape accuracy of individual fires was developed using existing object-based metrics and a novel metric, the “edge error”. The object-based accuracy assessment demonstrated that MCD64A1 preserves the fire shape well compared to medium resolution data. Based on this result, an algorithm for extracting individual fires from MCD64A1 data was developed which improves upon existing algorithms through its use of an uncertainty-based approach rather than empirically driven approaches. The individual fires extracted by this algorithm were validated against medium resolution data in Canada and Alaska using object-based metrics, and the results indicate the algorithm provides an improvement over similar datasets. Overall, this dissertation demonstrates the capability of coarse resolution burned area products to accurately identify individual fire shapes and sizes. Recommendations for future work include improving the quality assessment of burned area products and continuing research into identifying spatiotemporal patterns in fire size distributions over large areas

Historical Fire Detection of Tropical Forest from NDVI Time-series Data: Case Study on Jambi, Indonesia

In addition to forest encroachment, forest fire is a serious problem in Indonesia. Attempts at managing its widespread and frequent occurrence has led to intensive use of remote sensing data. Coarse resolution images have been employed to derive hot spots as an indicator of forest fire. However, most efforts to verify the hot spot data and to verify fire accidents have been restricted to the use of medium or high resolution data. At present, it is difficult to verify solely upon those data due to severe cloud cover and low revisit time. In this paper, we present a method to validate forest fire using NDVI time series data. With the freely available NDVI data from SPOT VEGETATION, we successfully detected changes in time series data which were associated with fire accidents

Detection and Characterization of Low Temperature Peat Fires during the 2015 Fire Catastrophe in Indonesia Using a New High-Sensitivity Fire Monitoring Satellite Sensor (FireBird)

Vast and disastrous fires occurred on Borneo during the 2015 dry season, pushing Indonesia into the top five carbon emitting countries. The region was affected by a very strong El Nino-Southern Oscillation (ENSO) climate phenomenon, on par with the last severe event in 1997/98. Fire dynamics in Central Kalimantan were investigated using an innovative sensor offering higher sensitivity to a wider range of fire intensities at a finer spatial resolution (160 m) than heretofore available. The sensor is onboard the TET-1 satellite, part of the German Aerospace Center (DLR) FireBird mission. TET-1 images (acquired every 2-3 days) from the middle infrared were used to detect fires continuously burning for almost three weeks in the protected peatlands of Sebangau National Park as well as surrounding areas with active logging and oil palm concessions. TET-1 detection capabilities were compared with MODIS active fire detection and Landsat burned area algorithms. Fire dynamics, including fire front propagation speed and area burned, were investigated. We show that TET-1 has improved detection capabilities over MODIS in monitoring low-intensity peatland fire fronts through thick smoke and haze. Analysis of fire dynamics revealed that the largest burned areas resulted from fire front lines started from multiple locations, and the highest propagation speeds were in excess of 500 m/day (all over peat > 2m deep). Fires were found to occur most often in concessions that contained drainage infrastructure but were not cleared prior to the fire season. Benefits of implementing this sensor system to improve current fire management techniques are discussed. Near real-time fire detection together with enhanced fire behavior monitoring capabilities would not only improve firefighting efforts, but also benefit analysis of fire impact on tropical peatlands, greenhouse gas emission estimations as well as mitigation measures to reduce severe fire events in the future

The ecological effects of grazing by the White Rhino (Ceratotherium simum simum) at a landscape scale

In this thesis I generated hypotheses concerning the top down effect of grazing ungulates on grass communities and fire behavior from work done within grazing exclosures in Hluhluwe iMfolozi Park. White Rhino had a large influence in controlling grass biomass in Hluhluwe, a high rainfall mesic savanna. Other smaller species of grazers could not replicate the effect of White Rhino when their grazing was removed. In Umfolozi, a semi-arid savanna, other species of grazer could replace the effect of White Rhino grazing and exert a controlling influence on grass biomass. Hence the relative importance of different species of grazers changed along a rainfall gradient. When examined at a larger spatial scale I found that the removal of White Rhino led to a detectable change in grass biomass and in the grazing behavior of other species in the area of the removal. The effect that herbivores exerted on the grass layer also had consequences for the movement of fire through the landscape by reducing fuel loads. Burnt areas were larger and less patchy in areas from which White Rhino had been removed in comparison to control areas. This effect was larger in Hluhluwe but still significant in Umfolozi. I suggest that both fire and grazing are in competition for the same resource, grass, and that each results in conditions favorable to the recurrence of that event (fire or grazing). This allows the system to switch between mammal and fire dominated states. Rainfall shifts the balance of this competition and in mesic savannas White Rhino appear to be the only animal capable of competing successfully with fire. This work has application for the management of ecosystems that are influenced by top down control and for the maintenance of heterogeneity in mesic savannas

Cellular automata simulations of field scale flaming and smouldering wildfires in peatlands

In peatland wildfires, flaming vegetation can initiate a smouldering fire by igniting the peat underneath, thus, creating a positive feedback to climate change by releasing the carbon that cannot be reabsorbed by the ecosystem. Currently, there are very few models of peatland wildfires at the field-scale, hindering the development of effective mitigation strategies. This lack of models is mainly caused by the complexity of the phenomena, which involves 3-D spread and km-scale domains, and the very large computational resources required. This thesis aims to understand field-scale peatland wildfires, considering flaming and smouldering, via cellular automata, discrete models that use simple rules. Five multidimensional models were developed: two laboratory-scale models for smouldering, BARA and BARAPPY, and three field-scale models for flaming and smouldering, KAPAS, KAPAS II, and SUBALI. The models were validated against laboratory experiments and field data. BARA accurately simulates smouldering of peat with realistic moisture distributions and predicts the formation of unburned patches. BARAPPY brings physics into BARA and predicts the depth of burn profile, but needs 240 times more computational resources. KAPAS showed that the smouldering burnt area decreases exponentially with higher peat moisture content. KAPAS II integrates daily temporal variation of moisture content, and revealed that the omission of this temporal variation significantly underestimates the smouldering burnt area in the long term. SUBALI, the ultimate model of the thesis, integrates KAPAS II with BARA and considers the ground water table to predict the carbon emission of peatland wildfires. Applying SUBALI to Indonesia, it predicts that in El Niño years, 0.40 Gt-C in 2015 (literature said 0.23 to 0.51 Gt-C) and 0.16 Gt-C in 2019 were released, and 75% of the emission is from smouldering. This thesis provides knowledge and models to understand the spread of flaming and smouldering wildfires in peatlands, which can contribute to efforts to minimise the negative impacts of peatland wildfires on people and the environment, through faster-than-real-time simulations, to find the optimum firefighting strategy and to assess the vulnerability of peatland in the event of wildfires.Open Acces

Near-Real-Time Global Biomass Burning Emissions Product from Geostationary Satellite Constellation

Near-real-time estimates of biomass burning emissions are crucial for air quality monitoring and forecasting. We present here the first near-real-time global biomass burning emission product from geostationary satellites (GBBEP-Geo) produced from satellite-derived fire radiative power (FRP) for individual fire pixels. Specifically, the FRP is retrieved using WF_ABBA V65 (wildfire automated biomass burning algorithm) from a network of multiple geostationary satellites. The network consists of two Geostationary Operational Environmental Satellites (GOES) which are operated by the National Oceanic and Atmospheric Administration, the Meteosat second-generation satellites (Meteosat-09) operated by the European Organisation for the Exploitation of Meteorological Satellites, and the Multifunctional Transport Satellite (MTSAT) operated by the Japan Meteorological Agency. These satellites observe wildfires at an interval of 15–30 min. Because of the impacts from sensor saturation, cloud cover, and background surface, the FRP values are generally not continuously observed. The missing observations are simulated by combining the available instantaneous FRP observations within a day and a set of representative climatological diurnal patterns of FRP for various ecosystems. Finally, the simulated diurnal variation in FRP is applied to quantify biomass combustion and emissions in individual fire pixels with a latency of 1 day. By analyzing global patterns in hourly biomass burning emissions in 2010, we find that peak fire season varied greatly and that annual wildfires burned 1.33 × 1012 kg dry mass, released 1.27 × 1010 kg of PM2.5 (particulate mass for particles with diameter \u3c2.5 μm) and 1.18 × 1011kg of CO globally (excluding most parts of boreal Asia, the Middle East, and India because of no coverage from geostationary satellites). The biomass burning emissions were mostly released from forest and savanna fires in Africa, South America, and North America. Evaluation of emission result reveals that the GBBEP-Geo estimates are comparable with other FRP-derived estimates in Africa, while the results are generally smaller than most of the other global products that were derived from burned area and fuel loading. However, the daily emissions estimated from GOES FRP over the United States are generally consistent with those modeled from GOES burned area and MODIS (Moderate Resolution Imaging Spectroradiometer) fuel loading, which produces an overall bias of 5.7% and a correlation slope of 0.97 ± 0.2. It is expected that near-real-time hourly emissions from GBBEP-Geo could provide a crucial component for atmospheric and chemical transport modelers to forecast air quality and weather conditions

The potential of multi-sensor satellite data for applications in environmental monitoring with special emphasis on land cover mapping, desertification monitoring and fire detection

Unprecedented pressure on the physical, chemical and biological systems of the Earth results in environment problems locally and globally, therefore the detection and understanding of environmental change based on long-term environmental data is very urgent. In developing countries/regions, because the natural resources are depleted for development while environmental awareness is poor, environment is changing faster. The insufficient environmental investment and sometimes infeasible ground access make the environment information acquisition and update inflexible through standard methods. With the main advantages of global observation, repetitive coverage, multispectral sensing and low-cost implementation, satellite remote sensing technology is a promising tool for monitoring environment, especially in the less developed countries. Multi-sensor satellite images may provide increased interpretation capabilities and more reliable results since data with different characteristics are combined and can achieve improved accuracies, better temporal coverage, and better inference about the environment than could be achieved by the use of a single sensor alone. The objective of this thesis is to demonstrate the capability and technique of the multi-sensor satellite data to monitor the environment in developing countries. Land cover assessment of Salonga national park in the democratic republic of Congo of Africa, desertification monitoring in North China and tropical/boreal wildland fire detection in Indonesia/Siberia were selected as three cases in this study for demonstrating the potential of multi-sensor application to environment monitoring. Chapter 2 demonstrates the combination of Landsat satellite images, Global Position System (GPS) signals, aerial videos and digital photos for assessing the land cover of Salonga national park in Congo. The purpose was to rapidly assess the current status of Salonga national park, especially its vegetation, and investigated the possible human impacts by shifting cultivation, logging and mining. Results show that the forests in the Salonga national park are in very good condition. Most of the area is covered by undisturbed, pristine evergreen lowland and swamp forests. No logging or mining activity could be detected. Chapter 3 demonstrates the one full year time series SPOT VEGETATION with coarse resolution of 1 km and the ASTER images with higher resolution of 15 meters as well as Landsat images for land cover mapping optimised for desertification monitoring in North-China. One point six million km2 were identified as risk areas of desertification. Results show within a satellite based multi-scale monitoring system SPOT VEGETATION imagery can be very useful to detect large scale dynamic environmental changes and desertification processes which then can be analysed in more detail by high resolution imagery and field surveys. Chapter 4 demonstrates the detection of tropical forest fire and boreal forest fire. Firstly, the ENVISAT ASAR backscatter dynamics and ENVISAT full resolution MERIS characteristics of fire scars were investigated in Siberian boreal forest, and results show these two sensors are very useful for fire monitoring and impact assessment. Secondly, the general capability and potential of ENVISAT multi-sensor of MERIS, AATSR, ASAR as well as NOAA-AVHRR and MODIS for tropical forest fire event monitoring and impact assessment in tropical Indonesia were investigated, and results show the capability of ENVISAT to acquire data from different sensors simultaneously or within a short period of time greatly enhances the possibilities to monitor fire occurrence and assess fire impact. Finally, the multi-sensor technology was applied to the disastrous boreal forest fire event of 2003 around East and West Lake Baikal in Siberia, and results show that 202,000 km2 burnt in 2003 within the study area of 1,300,000 km2, which is more than the total burnt area between 1996-2002. 71.4% of the burnt areas were forests, and 11.6% were wetlands or bogs. In total 32.2% of the forest cover has been burnt at least once from 1996 to 2003, 14% of the area has been affected at least twice by fire. These demonstrations show that in spite of the two disadvantages of indirect satellite measurements and the difficulty of detecting the cause of environment change, multi-sensor satellite technology is very useful in environment monitoring. However more studies on multi-sensor data fusion methods are needed for integrating the different satellite data from various sources. The lack of personnel skilled in remote sensing is a severe deficiency in developing countries, so the technology transfer from the developed countries is needed