scholarly journals Wintering Habitat Use Pattern of Red-Crowned Cranes in the Korean Demilitarized Zone

2018 ◽  
Vol 4 (4) ◽  
pp. 58 ◽  
Author(s):  
Sang-Don Lee
Keyword(s):  
Land Cover ◽  
Habitat Use ◽  
Surface Area ◽  
Rice Paddies ◽  
Night Time ◽  
Grus Japonensis ◽  
Demilitarized Zone ◽  
Random Expectation ◽  
Wintering Habitat ◽  
Use Pattern

The study was the first attempt to identify the habitat use pattern of red-crowned cranes (Grus japonensis) around the demilitarized zone (DMZ) by overlapping coordinates with the land cover classification (LCC). Daily habitat use pattern was highly different (P = 0.000) between daytime (06:00–18:00) and nighttime (18:00–06:00). Cranes in Cheolwon used agricultural paddies more frequently in the daytime (P = 0.002), and forest areas at night and this indicated that cranes presumably use rice paddies for feeding and forests for resting, respectively. Cranes night time in Paju used wetlands more often than random expectation based on the available wetland surface area (P = 0.017). This indicated a different habitat use pattern between coastal (Paju) and inland (Cheolwon) areas. Securing agricultural paddies is important for providing crucial areas for feeding, and forests should be important for rest during the night time in Cheolwon, which support crane populations during their wintering migration in Korea.

scholarly journals Long-Term Land Cover Changes in the Western Part of the Korean Demilitarized Zone

Land ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 708
Author(s):  
Jae-Hyun Kim ◽  
Shinyeong Park ◽  
Seung-Ho Kim ◽  
Eun-Ju Lee
Keyword(s):  
Land Cover ◽  
Ecological Integrity ◽  
Land Cover Changes ◽  
Agricultural Activity ◽  
Civilian Control ◽  
Rice Paddies ◽  
Control Zone ◽  
Land Type ◽  
Demilitarized Zone ◽  
The Korean War

After the Korean War, human access to the Korean Demilitarized Zone (DMZ) was highly restricted. However, limited agricultural activity was allowed in the Civilian Control Zone (CCZ) surrounding the DMZ. In this study, land cover and vegetation changes in the western DMZ and CCZ from 1919 to 2017 were investigated. Coniferous forests were nearly completely destroyed during the war and were then converted to deciduous forests by ecological succession. Plains in the DMZ and CCZ areas showed different patterns of land cover changes. In the DMZ, pre-war rice paddies were gradually transformed into grasslands. These grasslands have not returned to forest, and this may be explained by wildfires set for military purposes or hydrological fluctuations in floodplains. Grasslands near the floodplains in the DMZ are highly valued for conservation as a rare land type. Most grasslands in the CCZ were converted back to rice paddies, consistent with their previous use. After the 1990s, ginseng cultivation in the CCZ increased. In addition, the landscape changes in the Korean DMZ and CCZ were affected by political circumstances between South and North Korea. Our results provide baseline information for the development of ecosystem management and conservation plans for the Korean DMZ and CCZ. Given the high biodiversity and ecological integrity of the Korean DMZ region, transboundary governance for conservation should be designed.

scholarly journals Continental-Scale Land Cover Mapping at 10 m Resolution Over Europe (ELC10)

2021 ◽  
Vol 13 (12) ◽  
pp. 2301
Author(s):  
Zander Venter ◽  
Markus Sydenham
Keyword(s):  
Land Cover ◽  
Atmospheric Correction ◽  
Google Earth ◽  
Tree Planting ◽  
Training Data ◽  
Classification Model ◽  
Night Time ◽  
Continental Scale ◽  
Land Cover Maps ◽  
Sentinel 2

Land cover maps are important tools for quantifying the human footprint on the environment and facilitate reporting and accounting to international agreements addressing the Sustainable Development Goals. Widely used European land cover maps such as CORINE (Coordination of Information on the Environment) are produced at medium spatial resolutions (100 m) and rely on diverse data with complex workflows requiring significant institutional capacity. We present a 10 m resolution land cover map (ELC10) of Europe based on a satellite-driven machine learning workflow that is annually updatable. A random forest classification model was trained on 70K ground-truth points from the LUCAS (Land Use/Cover Area Frame Survey) dataset. Within the Google Earth Engine cloud computing environment, the ELC10 map can be generated from approx. 700 TB of Sentinel imagery within approx. 4 days from a single research user account. The map achieved an overall accuracy of 90% across eight land cover classes and could account for statistical unit land cover proportions within 3.9% (R2 = 0.83) of the actual value. These accuracies are higher than that of CORINE (100 m) and other 10 m land cover maps including S2GLC and FROM-GLC10. Spectro-temporal metrics that capture the phenology of land cover classes were most important in producing high mapping accuracies. We found that the atmospheric correction of Sentinel-2 and the speckle filtering of Sentinel-1 imagery had a minimal effect on enhancing the classification accuracy (< 1%). However, combining optical and radar imagery increased accuracy by 3% compared to Sentinel-2 alone and by 10% compared to Sentinel-1 alone. The addition of auxiliary data (terrain, climate and night-time lights) increased accuracy by an additional 2%. By using the centroid pixels from the LUCAS Copernicus module polygons we increased accuracy by <1%, revealing that random forests are robust against contaminated training data. Furthermore, the model requires very little training data to achieve moderate accuracies—the difference between 5K and 50K LUCAS points is only 3% (86 vs. 89%). This implies that significantly less resources are necessary for making in situ survey data (such as LUCAS) suitable for satellite-based land cover classification. At 10 m resolution, the ELC10 map can distinguish detailed landscape features like hedgerows and gardens, and therefore holds potential for aerial statistics at the city borough level and monitoring property-level environmental interventions (e.g., tree planting). Due to the reliance on purely satellite-based input data, the ELC10 map can be continuously updated independent of any country-specific geographic datasets.

scholarly journals Evolution de l’occupation des sols dans la partie Nord du Dallol Bosso, départements de Filingué et Balleyara, région de Tillabéri-Niger

2018 ◽  
Vol 14 (30) ◽  
pp. 391
Author(s):  
Issoufou Maigary ◽  
Boureïma Ousmane ◽  
Ado Dankarami
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Climate Variability ◽  
Surface Area ◽  
Satellite Image ◽  
Total Surface Area ◽  
Land Use Land Cover ◽  
Climate Variability And Change ◽  
Natural Plant ◽  
Balanced Development

The departments of Filingué and Balleyara, which are our study area, are located in the northern part of Dallol Bosso, Tillabéri region in western Niger. This study area is circumscribed between 13 ° 35 'and 14 ° 40' north latitudes and 2 ° 50 'and 3 ° 30' East longitude. The effects of climate variability and change in the region since the 1970s have had significant impacts on ecosystems. This paper focuses on analyzing the dynamics of land use land cover in that area. The methodology based on the interpretation of the satellite image for 1972, 1987 and 2016 has led to important results. Thus, there is a notable decline in areas covered by natural plant formations (tiger bush and steppe). Indeed, they range from 28.79% in 1972 to 12.15% in 2016 of the total surface area of the study area. However, farmland increased from 164772 ha in 1972 to 200 697 ha in 2016, an increase of 22%. In addition, the bare spaces which were only 666 ha in 1972 moved to 4189 ha, an increase of more than 500%. Finally, the number of semi-permanent pools rose from 219 to 833 from 1972 to 2016, while the number of Koris increased from 280 to 1573 during the same period, an increase of more than 400%. It seems necessary to take urgent measures to safeguard the ecosystems of the region to allow a more balanced development of the area.

Forecasting future changes in Manzala Lake surface area by considering variations in land use and land cover using remote sensing approach

2018 ◽  
Vol 11 (5) ◽  
Author(s):  
Hickmat Hossen ◽  
Mona G. Ibrahim ◽  
Wael Elham Mahmod ◽  
Abdelazim Negm ◽  
Kazuo Nadaoka ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Surface Area ◽  
Lake Surface ◽  
Lake Surface Area

scholarly journals Impacts of Rapid Changes of Land Cover and Intensive Human Activities on Avarga Toson Lake Area, Mongolia

2020 ◽  
Vol 12 (15) ◽  
pp. 6070
Author(s):  
Urtnasan Mandakh ◽  
Danzanchadav Ganbat ◽  
Bayartungalag Batsaikhan ◽  
Sainbayar Dalantai ◽  
Zolzaya Adiya ◽  
...  
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Surface Area ◽  
Human Activities ◽  
Water Surface ◽  
Land Development ◽  
Water Area ◽  
Lake Area ◽  
Surrounding Area ◽  
Water Surface Area

Avarga Toson Lake and its surrounding area are very important for people, wildlife, and animals in Delgerkhaan Soum of Khentii Province in Eastern Mongolia. Some research has been conducted so as to explore the medical nature and characteristics of the lake and its surrounding area. However, the adverse effects of land use have neither been studied nor reported. The fact that the water catchment area is shrinking evidences clearly that findings of various real-time studies must be used effectively in the long-term by the local government and relevant authorities in order to take immediate remedial measures. Our study focused on land cover changes occurring as a result of human activities in the area, using a Landsat imageries and water indices approach to estimate the changes of land use and land cover. The aims of this study were to assess the land use and cover change that occurred between 1989 and 2018 and to define the impacting factors on the changes of water surface area in Avarga Toson Lake area, Mongolia. Findings revealed that the water surface area has decreased by 34.1% in the past 30 years. The lake water area had the weakest, positive correlation with temperature and precipitation. We did not find any indicators suggesting a relationship between lake area and climate variables. In contrast, the area was slightly correlated with socio-economic variables, such as Toson Lake area with the number of visitors (R2 = 0.89) and Burd Lake area the with number of livestocks (R2 = 0.75), respectively. Therefore, the main conclusion of this paper is that socioeconomic factors driven by land use change, policy, and institutional failure together with the existing pressure on the lake may amplify their effect of the water surface area decreasing. Additionally, even if policy adoption is relatively sufficient in the country, the public institutional capacity to implement a successful sustainable land management model regarding land access, land development, land resources protection, land market, and investments in infrastructure remains very limited.

scholarly journals Sex-related Differences in Habitat Use in Wintering American Kestrels

The Auk ◽  
2001 ◽  
Vol 118 (3) ◽  
pp. 746-750 ◽  
Author(s):  
Daniel R. Ardia ◽  
Keith L. Bildstein
Keyword(s):  
Logistic Regression ◽  
Habitat Use ◽  
Regression Models ◽  
Woody Vegetation ◽  
High Quality ◽  
Male And Female ◽  
Logistic Regression Models ◽  
American Kestrels ◽  
Wintering Habitat ◽  
Work Supports

AbstractWe investigated sex-related differences in habitat use in wintering American Kestrels (Falco sparverius) at two scales: within a 10 m radius and within a 100 m radius of perch sites. Female kestrels used areas containing a higher percentage of short vegetation (<0.25 m high) suitable for foraging than did males at both scales (100 m radius females 80%, males 69%; 10 m radius females 80%, males 73%). At both scales, females had more pasture (a high-quality foraging substrate) available than did males; areas within a 100 m radius of male perch sites contained more woodlot than did female perch sites. Logistic regression models indicated greater overlap between male and female habitat use on a 10 m radius scale than on a 100 m radius scale, suggesting that males may preferentially select smaller areas devoid of woody vegetation relative to what is available within 100 m radius of perch sites. Our results suggest that males may be constrained to winter in areas with lower overall foraging opportunities and possibly higher predation risk than areas used by females. Our work supports the hypothesis that males and female kestrels prefer open areas as wintering habitat.

scholarly journals Operational Large-Area Land-Cover Mapping: An Ethiopia Case Study

2020 ◽  
Vol 12 (6) ◽  
pp. 954
Author(s):  
Reza Khatami ◽  
Jane Southworth ◽  
Carly Muir ◽  
Trevor Caughlin ◽  
Alemayehu N. Ayana ◽  
...  
Keyword(s):  
Land Cover ◽  
Classification Accuracy ◽  
Landsat 8 ◽  
Large Area ◽  
National Scale ◽  
Night Time ◽  
Explanatory Variables ◽  
Image Compositing ◽  
Elevation Data ◽  
Multi Temporal

Knowledge of land cover and land use nationally is a prerequisite of many studies on drivers of land change, impacts on climate, carbon storage and other ecosystem services, and allows for sufficient planning and management. Despite this, many regions globally do not have accurate and consistent coverage at the national scale. This is certainly true for Ethiopia. Large-area land-cover characterization (LALCC), at a national scale is thus an essential first step in many studies of land-cover change, and yet is itself problematic. Such LALCC based on remote-sensing image classification is associated with a spectrum of technical challenges such as data availability, radiometric inconsistencies within/between images, and big data processing. Radiometric inconsistencies could be exacerbated for areas, such as Ethiopia, with a high frequency of cloud cover, diverse ecosystem and climate patterns, and large variations in elevation and topography. Obtaining explanatory variables that are more robust can improve classification accuracy. To create a base map for the future study of large-scale agricultural land transactions, we produced a recent land-cover map of Ethiopia. Of key importance was the creation of a methodology that was accurate and repeatable and, as such, could be used to create earlier, comparable land-cover classifications in the future for the same region. We examined the effects of band normalization and different time-series image compositing methods on classification accuracy. Both top of atmosphere and surface reflectance products from the Landsat 8 Operational Land Imager (OLI) were tested for single-time classification independently, where the latter resulted in 1.1% greater classification overall accuracy. Substitution of the original spectral bands with normalized difference spectral indices resulted in an additional improvement of 1.0% in overall accuracy. Three approaches for multi-temporal image compositing, using Landsat 8 OLI and Moderate Resolution Imaging Spectroradiometer (MODIS) data, were tested including sequential compositing, i.e., per-pixel summary measures based on predefined periods, probability density function compositing, i.e., per-pixel characterization of distribution of spectral values, and per-pixel sinusoidal models. Multi-temporal composites improved classification overall accuracy up to 4.1%, with respect to single-time classification with an advantage of the Landsat OLI-driven composites over MODIS-driven composites. Additionally, night-time light and elevation data were used to improve the classification. The elevation data and its derivatives improved classification accuracy by 1.7%. The night-time light data improve producer’s accuracy of the Urban/Built class with the cost of decreasing its user’s accuracy. Results from this research can aid map producers with decisions related to operational large-area land-cover mapping, especially with selecting input explanatory variables and multi-temporal image compositing, to allow for the creation of accurate and repeatable national-level land-cover products in a timely fashion.

Wintering habitat use by houbara bustard (Chlamydotis macqueenii) in steppes of Harat, central Iran

2010 ◽  
Vol 74 (8) ◽  
pp. 912-917 ◽  
Author(s):  
S. Aghainajafi-Zadeh ◽  
M.R. Hemami ◽  
M. Karami ◽  
P.M. Dolman
Keyword(s):  
Habitat Use ◽  
Central Iran ◽  
Wintering Habitat ◽  
Houbara Bustard

Comparative assessment of different methods for using land-cover variables for distribution modelling of Salamandra salamandra longirotris

2012 ◽  
Vol 40 (1) ◽  
pp. 48-59 ◽  
Author(s):  
DAVID ROMERO ◽  
JESÚS OLIVERO ◽  
RAIMUNDO REAL
Keyword(s):  
Land Cover ◽  
Surface Area ◽  
Single Type ◽  
Negative Effects ◽  
Distribution Modelling ◽  
Unique Type ◽  
Herbaceous Crops ◽  
Different Types ◽  
Salamandra Salamandra ◽  
Variable Analysis

SUMMARYPredictive models are frequently used to define the most suitable areas for species protection or reintroduction. Land-cover variables can be used in different ways for distribution modelling. The surface area of a set of land-cover classes is often used, each land-cover presence/absence or the distance to them from any point of the study area can be preferred; multiple types of land-cover variables may be combined to produce a single model. This paper assesses whether different approaches to using land-cover variables may lead to different ecological conclusions when interpreted for conservation by focusing on the distribution of the salamader Salamandra salamandra longirostris, an endangered amphibian subspecies in the south of the Iberian Peninsula. Twenty-eight land-cover classes and another 42 environmental variables were used to construct four different models. Three models used a unique type of land-cover variable: either the presence of each class, the surface area of each class or the distance to each class, with all three variable types jointly entered in a fourth model. All models attained acceptable scores according to some criteria (discrimination, descriptive and predictive capacities, classification accuracy and parsimony); however most of the assessment parameters computed indicated a better performance of the models using either the surface area of land classes or the distance to them from every sampled square, compared to the model using class presences. The best scores were obtained with the fourth model, which combined different types of land-cover variables. This model suggested that oak forest fragmentation in favour of herbaceous crops and pastures may have negative effects on the distribution of S. s. longirostris. This was only partially suggested by the first three models, which considered a single type of land-cover variable, demonstrating the importance of considering a multi-variable analysis for conservation planning.

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