Papers by Yunden Bayarjargal
Communications earth & environment, Jun 25, 2024
In Mongolia, partners from national and aimag governments, academia and NGOs have developed regio... more In Mongolia, partners from national and aimag governments, academia and NGOs have developed regional conservation plans that balance the government commitment to protection of natural habitats with planned development of mineral resources and related infrastructure. A key input is a mapped classification of major habitat types, or ecosystems, to represent the range of natural habitats and function as a surrogate for biodiversity. We developed a GIS model to map ecosystems across the Mongolian Gobi Desert region by comparing the distribution of plant communities and major vegetation types, taken from field surveys and national maps, with patterns of above-ground biomass, elevation, climate and topography derived from remote sensing. The resulting mapped classification is organized as a hierarchy of 1) biogeographic regions, 2) terrestrial ecosystem types based on vegetation, elevation and geomorphology, and 3) landforms. This provides a firstiteration map to support landscape-level c...
In Mongolia, partners from national and aimag governments, academia and NGOs have developed regio... more In Mongolia, partners from national and aimag governments, academia and NGOs have developed regional conservation plans that balance the government commitment to protection of natural habitats with planned development of mineral resources and related infrastructure. A key input is a mapped classification of major habitat types, or ecosystems, to represent the range of natural habitats and function as a surrogate for biodiversity. We developed a GIS model to map ecosystems across the Mongolian Gobi Desert region by comparing the distribution of plant communities and major vegetation types, taken from field surveys and national maps, with patterns of above-ground biomass, elevation, climate and topography derived from remote sensing. The resulting mapped classification is organized as a hierarchy of 1) biogeographic regions, 2) terrestrial ecosystem types based on vegetation, elevation and geomorphology, and 3) landforms. This provides a firstiteration map to support landscape-level c...
In Mongolia, partners from national and aimag governments, academia and NGOs have developed regio... more In Mongolia, partners from national and aimag governments, academia and NGOs have developed regional conservation plans that balance the government commitment to protection of natural habitats with planned development of mineral resources and related infrastructure. A key input is a mapped classification of major habitat types, or ecosystems, to represent the range of natural habitats and function as a surrogate for biodiversity. We developed a GIS model to map ecosystems across the Mongolian Gobi Desert region by comparing the distribution of plant communities and major vegetation types, taken from field surveys and national maps, with patterns of above-ground biomass, elevation, climate and topography derived from remote sensing. The resulting mapped classification is organized as a hierarchy of 1) biogeographic regions, 2) terrestrial ecosystem types based on vegetation, elevation and geomorphology, and 3) landforms. This provides a first-iteration map to support landscape-level ...
In Mongolia, partners from national and aimag governments, academia and NGOs have developed regio... more In Mongolia, partners from national and aimag governments, academia and NGOs have developed regional conservation plans that balance the government commitment to protection of natural habitats with planned development of mineral resources and related infrastructure. A key input is a mapped classification of major habitat types, or ecosystems, to represent the range of natural habitats and function as a surrogate for biodiversity. We developed a GIS model to map ecosystems across the Mongolian Gobi Desert region by comparing the distribution of plant communities and major vegetation types, taken from field surveys and national maps, with patterns of above-ground biomass, elevation, climate and topography derived from remote sensing. The resulting mapped classification is organized as a hierarchy of 1) biogeographic regions, 2) terrestrial ecosystem types based on vegetation, elevation and geomorphology, and 3) landforms. This provides a first-iteration map to support landscape-level ...
The objective of this study was to examine the temporal trend of the Mongolian natural vegetation... more The objective of this study was to examine the temporal trend of the Mongolian natural vegetation phenology during 18 years between 1981 and 1999, in various ecosystems, by using two Pathfinder NOAA-AVHRR Land (PAL) products -- the Normalized Different Vegetation Index (NDVI) and Land Surface Temperature (LST). Mongolia was selected as a study area for implementing the above objectives since
International Journal of Remote Sensing, 2013
Space and ground observations were applied to explore the ability of remote sensing techniques to... more Space and ground observations were applied to explore the ability of remote sensing techniques to assess the effect of grazing on vegetation degradation. The steppe biome of Mongolia was used as the study area, in which several pairs of sites were investigated-each pair comprised an ungrazed (fenced-off) area and a heavily grazed area. For each pair, the enhanced vegetation index (EVI), computed from Landsat-7 Enhanced Thematic Mapper Plus (ETM+) data, along with field-observed biophysical variables (e.g. plant density, species composite, above-ground biomass (AGB), and percentage cover) and plant spectral reflectance data were collected. As expected, plant density, AGB, and percentage cover values were significantly higher in the ungrazed areas than in the adjacent grazed ones. However, unexpectedly, the grazed areas had significantly higher EVI values than the ungrazed areas. It was found that unpalatable species had invaded into the grazed areas, substituting the native grasses. These invasive species, mostly characterized by denser leaf structure, induced higher spectral responses in the near infrared (NIR) region of the electromagnetic spectrum. EVI is the preferred vegetation index to use for detecting this phenomenon, since it is more sensitive to variations in leaf cellular structural as expressed in the NIR (rather than the red) portion of the spectrum. The current study contradicts the general assumption that the higher the vegetation index value, the better the grazing conditions.
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Conservation Science and Practice
Growing resource demands are driving rapid development to new frontiers in developing countries w... more Growing resource demands are driving rapid development to new frontiers in developing countries with important biological diversity. The mitigation hierarchy is a critical tool to manage the impacts of development projects on biodiversity, embedded into numerous government, lender, and corporate policies. However, implementation faces obstacles, in particular deciding when impacts should be avoided. Offset design, the last step, faces difficult questions about location of offsets relative to impacts and how to address uncertainty and conflicts with future development. Planning for conservation and development are typically separate processes, and environmental impact assessments are typically conducted on a project-by-project basis that does not consider the landscape context and cumulative impacts of multiple projects. Here we present a mitigation framework for Mongolia with an example from the Mongolian Gobi Desert, a landscape with globally significant biodiversity facing rapid development. This landscape-level planning approach has been replicated across Mongolia to produce a national level mitigation framework to guide both the government policy commitment to protect 30% of all natural lands and application of the mitigation hierarchy. This has led to protection of 177,000 km 2 in new national and local protected areas, and development of an offset design mechanism based on the conservation plans.
International Journal of Remote Sensing, 2006
The Vegetation Health index (VHI) is based on a combination of products extracted from vegetation... more The Vegetation Health index (VHI) is based on a combination of products extracted from vegetation signals, namely the Normalized Difference Vegetation Index (NDVI) and from the brightness temperatures, both derived from the NOAA Advanced Very High Resolution Radiometer (AVHRR) sensor. VH users rely on a strong inverse correlation between NDVI and land surface temperature, since increasing land temperatures are assumed to act negatively on vegetation vigour and consequently to cause stress. This Letter explores this hypothesis with data from Mongolia incorporating information from six different ecosystems. It was found that the northern ecosystems are characterized by positive correlations, implying that rising temperature favourably influences vegetation activity. It is concluded that the VHI should be used with caution, especially in high latitude regions.
International Journal of Applied Earth Observation and Geoinformation, 2004
Unsuccessful efforts to interpret and analyze several sets of images acquired over Israel by Land... more Unsuccessful efforts to interpret and analyze several sets of images acquired over Israel by Landsat-7 during the first 2 years of its operation (August 1999-August 2001 provided the motivation to examine the hypothesis that image data produced over the desert regions along the climatic transition zone of Israel were subject to radiometric saturation. The objectives of the current study are to characterize the saturation phenomenon, by inspecting different images of Landsat-7, and to suggest a statistic method for solution in the spectral domain. Entropy analysis was also performed on these images in order to compare the information content of the Landsat-7 Enhanced Thematic Mapper Plus (ETM+) sensor with that of the Landsat-5 Thematic Mapper (TM) over the desert environment before and after saturation correlation. The study reveals that radiometric saturation affected several ETM+ bands (especially band 3). Consequently, in terms of entropy, less information can be extracted from the saturated bands relative to equivalent bands of Landsat-5 TM. A statistical solution, based on multivariate correlation analysis among all spectral bands, is proposed to overcome the saturation problem. Satisfactory results were achieved by applying the statistical methods on several samples of saturated scenes. An operational revision in the spectral radiance range and the gain setting, applied to Landsat-7 ETM+ that is affected from July 1, 2000, has improved the saturation phenomenon over the region. The current proposed method can be applied for other climatic regions, such as scenes partially covered by snow, and other multi and hyper spectral sensors. (A. Karnieli). changes in the Earth's global environments including land, oceans, atmosphere, ice caps, as well as with life forms . The mission is accomplished through repetitive, synoptic coverage of continental surfaces. The sensor has six spectral bands in the visible, near-infrared, and shortwave infrared regions of the electromagnetic spectrum (at 30 m spatial resolution), one thermal infrared band (60 m and 120 m spatial resolution products), and one panchromatic band (at 15 m spatial resolution).
Remote Sensing of Environment, 2006
The objective of this study was to compare the spatial occurrences of droughts, detected by remot... more The objective of this study was to compare the spatial occurrences of droughts, detected by remotely sensed drought-indices over the desertsteppe and desert geo-botanical zones of Mongolia. All indices were derived from reflectance and thermal data sets, obtained from the NOAA-AVHRR data between 1982 and 1999. One group of the drought-indices is based on vegetation state derived from the reflective channels. This group includes the Normalized Difference Vegetation Index (NDVI), Anomaly of Normalized Difference Vegetation Index (NDVIA), Standardized Vegetation Index (SVI), and Vegetation Condition Index (VCI). Another group, based on surface brightness temperature derived from the thermal channel of NOAA-AVHRR, includes the Temperature Condition Index (TCI). The third group is based on combination between the reflective and thermal channels includes the ratio between Land Surface Temperature (LST) and NDVI (LST/NDVI), the Vegetation Health Index (VH), and the Drought Severity Index (DSI). Change detection procedure was performed by using the Change Vector Analysis in the temporal domain. Comparison analysis among the drought-indices reveals that there is no spatial coincidence between them, even when the vegetation growing period was divided into 2-month sub-periodsbeginning, middle, and end. Based on the statistical analysis, higher correlations were found among the reflective indices while lesser or no relationships were found between the thermal and combination of the thermal and reflective indices. Furthermore, no agreement was found between the spatial extent of the satellite-derived drought-indices and the meteorological-based Palmer Drought Severity Index (PDSI) and also between the traditional ground-observed drought-affected-areas (DAA) maps. It was found that the combination of satellite-derived drought-indices can identify wider drought-occurred areas rather than the PDSI and the DAA maps. In summary, this study concludes that it is difficult to point out the most reliable drought index, and that the ground observations cannot provide sufficient information for validation of satellite derived drought indices.
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Papers by Yunden Bayarjargal