Monitoring Oil Exploitation Infrastructure and Dirt Roads with Object-Based Image Analysis and Random Forest in the Eastern Mongolian Steppe

Information on the spatial distribution of human disturbance is important for assessing and monitoring land degradation. In the Eastern Mongolian Steppe Ecosystem, one of the major driving factors of human-induced land degradation is the expansion of road networks mainly due to intensifications of oil exploration and exploitation. So far, neither the extents of road networks nor the extent of surrounding grasslands affected by the oil industry are monitored which is generally labor consuming. This causes that no information on the changes in the area which is affected by those disturbance drivers is available. Consequently, the study aim is to provide a cost-effective methodology to classify infrastructure and oil exploitation areas from remotely sensed images using object-based classifications with Random Forest. By combining satellite data with different spatial and spectral resolutions (PlanetScope, RapidEye, and Landsat ETM+), the product delivers data since 2005. For the classification variables, segmentation, spectral characteristics, and indices were extracted from all above mentioned imagery and used as predictors. Results show that overall accuracies of land use maps ranged 73%–93% mainly depending on satellites’ spatial resolution. Since 2005, the area of grassland disturbed by dirt roads and oil exploitation infrastructure increased by 88% with its highest expansion by 47% in the period 2005–2010. Settlements and croplands remained relatively constant throughout the 13 years. Comparison of multiscale classification suggests that, although high spatial resolutions are clearly beneficial, all datasets were useful to delineate linear features such as roads. Consequently, the results of this study provide an effective evaluation for the potential of Random Forest for extracting relatively narrow linear features such as roads from multiscale satellite images and map products that are possible to use for detailed land degradation assessments

Hyperspectral Data Analysis in R: The hsdar Package

Hyperspectral remote sensing is a promising tool for a variety of applications including ecology, geology, analytical chemistry and medical research. This article presents the new hsdar package for R statistical software, which performs a variety of analysis steps taken during a typical hyperspectral remote sensing approach. The package introduces a new class for efficiently storing large hyperspectral data sets such as hyperspectral cubes within R. The package includes several important hyperspectral analysis tools such as continuum removal, normalized ratio indices and integrates two widely used radiation transfer models. In addition, the package provides methods to directly use the functionality of the caret package for machine learning tasks. Two case studies demonstrate the package's range of functionality: First, plant leaf chlorophyll content is estimated and second, cancer in the human larynx is detected from hyperspectral data

Estimating Net Photosynthesis of Biological Soil Crusts in the Atacama Using Hyperspectral Remote Sensing

Biological soil crusts (BSC) encompassing green algae, cyanobacteria, lichens, bryophytes, heterotrophic bacteria and microfungi are keystone species in arid environments because of their role in nitrogen- and carbon-fixation, weathering and soil stabilization, all depending on the photosynthesis of the BSC. Despite their importance, little is known about the BSCs of the Atacama Desert, although especially crustose chlorolichens account for a large proportion of biomass in the arid coastal zone, where photosynthesis is mainly limited due to low water availability. Here, we present the first hyperspectral reflectance data for the most wide-spread BSC species of the southern Atacama Desert. Combining laboratory and field measurements, we establish transfer functions that allow us to estimate net photosynthesis rates for the most common BSC species. We found that spectral differences among species are high, and differences between the background soil and the BSC at inactive stages are low. Additionally, we found that the water absorption feature at 1420 nm is a more robust indicator for photosynthetic activity than the chlorophyll absorption bands. Therefore, we conclude that common vegetation indices must be taken with care to analyze the photosynthesis of BSC with multispectral data

Land Cover Change in the Andes of Southern Ecuador — Patterns and Drivers

In the megadiverse tropical mountain forest in the Andes of southern Ecuador, a global biodiversity hotspot, the use of fire to clear land for cattle ranching is leading to the invasion of an aggressive weed, the bracken fern, which is threatening diversity and the provisioning of ecosystem services. To find sustainable land use options adapted to the local situation, a profound knowledge of the long-term spatiotemporal patterns of land cover change and its drivers is necessary, but hitherto lacking. The complex topography and the high cloud frequency make the use of remote sensing in this area a challenge. To deal with these conditions, we pursued specific pre-processing steps before classifying five Landsat scenes from 1975 to 2001. Then, we quantified land cover changes and habitat fragmentation, and we investigated landscape changes in relation to key spatial elements (altitude, slope, and distance from roads). Good classification results were obtained with overall accuracies ranging from 94.5% to 98.5% and Kappa statistics between 0.75 and 0.98. Forest was strongly fragmented due to the rapid expansion of the arable frontier and the even more rapid invasion by bracken. Unexpectedly, more bracken-infested areas were converted to pastures than vice versa, a practice that could alleviate pressure on forests if promoted. Road proximity was the most important spatial element determining forest loss, while for bracken the altitudinal range conditioned the degree of invasion in deforested areas. The annual deforestation rate changed notably between periods: ~1.5% from 1975 to 1987, ~0.8% from 1987 to 2000, and finally a very high rate of ~7.5% between 2000 and 2001. We explained these inconstant rates through some specific interrelated local and national political and socioeconomic drivers, namely land use policies, credit and tenure incentives, demography, and in particular, a severe national economic and bank crisis

Ecophysiology and phylogeny of new terricolous and epiphytic chlorolichens in a fog oasis of the Atacama Desert

The Atacama Desert is one of the driest and probably oldest deserts on Earth where only a few extremophile organisms are able to survive. This study investigated two terricolous and two epiphytic lichens from the fog oasis “Las Lomitas” within the National Park Pan de Azúcar which represents a refugium for a few vascular desert plants and many lichens that can thrive on fog and dew alone. Ecophysiological measurements and climate records were combined with molecular data of the mycobiont, their green algal photobionts and lichenicolous fungi to gain information about the ecology of lichens within the fog oasis. Phylogenetic and morphological investigations led to the identification and description of the two new lichen species Ramalina reichenbergeri and Acarospora conafii as well as the lichenicolous fungi that accompanied them and revealed the trebouxioid character of all lichen photobionts. Their photosynthetic response during natural scenarios such as reactivation by high air humidity and in situ fog events were compared to elucidate the activation strategies of this lichen community. Epiphytic lichens showed photosynthetic activity that was rapidly induced by fog and additionally during high air humidity whereas terricolous lichens were only activated by fog

Estimating Net Photosynthesis of Biological Soil Crusts in the Atacama Using Hyperspectral Remote Sensing

Biological soil crusts (BSC) encompassing green algae, cyanobacteria, lichens, bryophytes, heterotrophic bacteria and microfungi are keystone species in arid environments because of their role in nitrogen- and carbon-fixation, weathering and soil stabilization, all depending on the photosynthesis of the BSC. Despite their importance, little is known about the BSCs of the Atacama Desert, although especially crustose chlorolichens account for a large proportion of biomass in the arid coastal zone, where photosynthesis is mainly limited due to low water availability. Here, we present the first hyperspectral reflectance data for the most wide-spread BSC species of the southern Atacama Desert. Combining laboratory and field measurements, we establish transfer functions that allow us to estimate net photosynthesis rates for the most common BSC species. We found that spectral differences among species are high, and differences between the background soil and the BSC at inactive stages are low. Additionally, we found that the water absorption feature at 1420 nm is a more robust indicator for photosynthetic activity than the chlorophyll absorption bands. Therefore, we conclude that common vegetation indices must be taken with care to analyze the photosynthesis of BSC with multispectral data

A simple, fast, and accurate method for land cover mapping in Mongolia

Low accuracy of global land cover (LC) products at local and regional scales is concerning, because of its huge impact on downstream applications. Therefore, developing a method for high accuracy LC maps at local and regional scale is of utmost importance. Taking Mongolia as a case study, we proposed a simple, fast, and accurate method to produce annual LC maps with 250 m spatial resolution from 2001 to 2020 using MODIS data. Our products have higher spatial resolution and higher accuracy (Overall Accuracy ∼90%) compared to MCD12Q1. These new maps are critical e.g., for land degradation research, and desertification/forest cover monitoring. Especially, information on grassland ecosystems is of utmost importance for Mongolia since more than half of the country economically depends on grassland resources. Therefore, Mongolia will benefit from the new dataset. Furthermore, due to the simplicity of the method, it can be easily applied and transferred to other regions

Conservation Value of Forests Attacked by Bark Beetles: Highest Number of Indicator Species is Found in Early Successional Stages

Heavy natural disturbance in large protected areas of former commercial forests increasingly evokes European parliaments to call for management intervention because a loss of habitats and species is feared. In contrast, natural early successional habitats have recently been recognised as important for conservation. Current knowledge in this field mostly results from studies dealing only with selected taxa. Here we analyse the success of species across 24 lineages of three kingdoms in the Bavarian Forest National Park (Germany) after 15 years of a European spruce bark beetle (Ips typographus L.) outbreak that led to rapid canopy opening. Using indicator species analysis, we found 257 species with a significant preference for open forests and 149 species with a preference for closed forests, but only 82 species with a preference for the stand conditions transitional between open and closed forests. The large number of species with a preference for open forests across lineages supports the role of this bark beetle as a keystone species for a broad array of species. The slowdown of the outbreak after 15 years in the core zone of the national park resulted in less than half of the area being affected, due to variability in stand ages and tree species mixtures. Our case study is representative of the tree species composition and size of many large protected montane areas in Central European countries and illustrates that (1) natural disturbances increase biodiversity in formerly managed forests and (2) a montane protected area spanning 10,000 ha of low range mountains is likely sufficient to allow natural disturbances without a biased loss of closed-forest species

The Green Desert of South America?

Der Nationalpark „Pan de Azúcar“ ist eine Nebeloase in der südlichen Atacama-Wüste Chiles. Er beherbergt eine Vielfalt an Cyanobakterien und Grünalgen, die insbesondere in Flechten vorkommen. Diversitätsaufnahmen und ökophysiologische sowie biochemische Untersuchungen zeigten, dass diese Lebewesen hervorragend an das Extremklima angepasst sind und schon bei geringsten Wassermengen aktiv werden können. Durch physikalische und chemische Veränderung ihrer Umwelt tragen sie damit zur Verwitterung von Gestein und Bodenbildung bei und sind an der Formung der Landschaft beteiligt.“Pan de Azúcar National Park” is a fog oasis in the southern Atacama Desert of Chile. It hosts a diversity of cyanobacteria and green algae, which can especially be found in lichens. Diversity surveys and eco-physiological and biochemical studies have shown that these organisms are excellently adapted to the extreme climate and can already become active even if the amount of water available is very low. By changing their environment physically and chemically, they contribute to the weathering of rocks and soil formation and are thus involved in shaping the landscape

Valleys are a potential refuge for the Amazon lowland forest in the face of increased risk of drought

Abstract The Amazon rainforest is home to an incredible variety of plant and animal species and plays a crucial role in regulating the Earth’s climate. Climate change and human activities are putting this important ecosystem at risk. In particular, increasing droughts are making it harder for certain organisms to survive. Here we analyse a satellite-based data set of fog/low-stratus (FLS) frequency and a spatio-temporal drought index. We show that vulnerable organisms may find refuge in river valleys where FLS provides a source of moisture. We find that these favourable microclimates exist throughout the Amazon basin, with the highest occurrence and stability in steep river valleys. We suggest that protecting these hygric climate change refugia could help preserve the biodiversity and functioning of the Amazon ecosystem in the face of future droughts. This would also help stabilise atmospheric moisture recycling, making the region more resilient to climate change