Area In Different Years Research Articles

ТАРИХИ КАРТАЛАРДАҒЫ АРАЛ ТЕҢІЗІ АКВАТОРИЯСЫНЫҢ ДИНАМИКАСЫ

The global environmental crisis of the Aral Sea has garnered the attention of researchers in recent decades, leading to an increase in studies on changes in the water area and its environmental impact. While most research on the Aral Sea focuses on the past fifty years, there is a lack of information on quantitative changes from its inception to becoming an environmental disaster. Our aim is to utilize historical maps to examine the Aral Sea's area in different years and trace its evolution before the environmental crisis. By reviewing scientific papers and maps using international search engines and electronic resources, we analyzed the area of the Aral Sea on historical maps with the ArсGIS 10.4.1 GIS program. The data from 1716 to 1967 reveals that the area was 10 320 km2 in 1716, expanding to 20 538 km2 in 1742 and reaching a peak of 71 009 km2 in 1848-1849. Subsequently, the area decreased slightly to 63 691 km2 by 1907 before rising again to 66 836 km2 by 1967. It is worth noting that pre-1848-1849 historical maps may have more inaccuracies due to limited scientific knowledge and mapping techniques.

Fauna and bird population of the basin of the middle reaches of the Kara River (Polar Urals, Bolshezemelskaya tundra) based on to the results of expedition studies in 2017 and 2023

The article presents the results of ornithological studies carried out in the basin of the middle reaches of the Kara River on the border of the Polar Urals and the Bolshezemelskaya tundra in the field seasons of 2017 and 2023. The routes covered a part of the valley of the middle reaches of the Kara River, sections of the valleys of the Halmershor 2nd, Lyadheyakha, Nyarmayakha, Yunyakha, Nerusaveyakha, Silovayakha, Halmer-Yu rivers and adjacent sections of the plakors. The relevance of the work is due to the fragmentary study of the territory and the need for monitoring to better identify the avifauna of a relatively inaccessible area of the Subarctic. During the research, 70 species of birds were recorded, 53 of which were breeding or likely to breed. The results of the work made it possible to carry out an inventory of the avifauna of the middle reaches of the Kara River basin, which had not previously been fully surveyed. Regular nesting in the tundra zone was confirmed down to the subzone of typical tundra, the steppe arrier Circus macrourus and the Siberian curlew Prunella montanella. The stability of the populations of the species included in the Red Book of the Russian Federation is demonstrated: the peregrine falcon Falco peregrinus and the little swan Cygnus bewickii. The revealed difference in the fauna and population of birds in the same area in different years with similar weather conditions confirms the necessity of monitoring these indicators in the Arctic and Subarctic.

Evaluation System of Light Pollution Risk Index Based on Entropy Weight Method

In recent years, the issue of light pollution has garnered widespread attention. To address this concern, the state of California in the United States has developed a grading format to regulate lighting areas for light pollution protection. In order to further study this problem, we have selected six factors related to light pollution, namely population density, per capita gross regional product, total passenger transport, industrial electricity consumption, real estate development investment, and green area of built-up areas in different years in each prefecture-level city in China. Based on the VIKOR model, we have established a light pollution risk assessment system using the obtained compromise value as an assessment index for light pollution levels in different regions. The results have been analyzed using VIIRS satellite remote sensing images, and the average error is 5.24%, indicating good sensitivity to the system. Finally, we have analyzed the assessment results to show that over-development of areas can seriously exacerbate the risk level of light pollution. Therefore, development should be planned rationally to reduce the impact of light pollution.

Rice Planting Area Identification Based on Multi-Temporal Sentinel-1 SAR Images and an Attention U-Net Model

Rice is one of the most important food crops for human beings. The timely and accurate understanding of the distribution of rice can provide an important scientific basis for food security, agricultural policy formulation, and regional development planning. As an active remote sensing system, polarimetric synthetic aperture radar (PolSAR) has the advantage of working both day and night and in all weather conditions and hence plays an important role in rice growing area identification. This paper focuses on the topic of rice planting area identification using multi-temporal PolSAR images and a deep learning method. A rice planting area identification attention U-Net (RIAU-Net) model is proposed, which is trained by multi-temporal Sentinel-1 dual-polarimetric images acquired in different periods of rice growth. In addition, considering the diversity of the rice growth period in different years caused by the different climatic conditions and other factors, a transfer mechanism is investigated to apply the well-trained model to monitor the rice planting areas in different years. The experimental results show that the proposed method can significantly improve the classification accuracy, with 11–14% F1-score improvement compared with the traditional methods and a pleasing generalization ability in different years. Moreover, the classified rice planting regions are continuous. For reproducibility, the source codes of the well-trained RIAU-Net model are provided.

Flood Hazard Assessment of the Bangshi River Floodplain using an Integrated 1D/2D Coupled Hydraulic Model

In the present study, the flood hazard of the Bangshi River, located in the Savar Industrial Area of Dhaka District, has been evaluated. The historical flood extent analysed from the Landsat satellite images suggests that most parts of the study area were flooded during the major flood events in Bangladesh. The flood flow data were fitted with different analytical frequency distribution functions, and it is found that the Pearson III distribution function best fits with the observed data based on the Chi-Squared statistical test. Then, the flood flow model of the Bangshi River as well as the surrounding floodplain area was developed using the HEC-RAS 1D-2D coupled hydraulic model. The model was simulated with an estimated flow of 100-year and 500-year return periods. The analysis of the historical flood data shows that the water level exceeds the danger level at the nearby monitoring station of the study area in different years. In the study area, devastating floods occurred in the years 1988 and 1998. The maximum flood level was 9.9 m during the flood event of 1988. The analysis of Landsat satellite images also shows that about 69% and 58% of the study area were flooded during the floods of 1988 and 1998, respectively. The roadways provide flood protection barriers in the western side of the study area for the flood water coming from the Bangshi River system unless the road is overtopped. The simulated result shows that about 68% and 79% of the study area will be inundated for the 100-year and 500-year return periods, respectively. The simulated maximum flood velocity for the 100-year and 500-year return period is 2.31 m/s and 4.52 m/s, and the flood duration for the same return periods is about 32.5 days and 48.95 days, respectively. The simulated flood depth, duration, and velocity maps can be used for any development activities within the study area. The Dhaka University Journal of Earth and Environmental Sciences, Centennial Special Volume June 2022: 167-186

The Arctic tern Sterna paradisaea: consistency and variability in spatial use at a global oceanographic scale

Elucidating the ecological factors underpinning migratory strategies of seabirds is necessary for understanding resilience to environmental change. Arctic terns Sterna paradisaea breed in the Northern Hemisphere and are unique for the global scale of their migration. Geolocator data from 37 Arctic terns breeding in a low-latitude colony, 10 of which were re-tagged in successive years, were analysed to characterise their migratory behaviour and to test the hypothesis that individuals have repeatable migration strategies. Seawater immersion data suggested a fly-forage strategy, with birds remaining on the wing at night and only foraging during daylight. Southward movement was focused initially along Atlantic eastern-boundary upwelling systems. Most terns then reoriented eastwards, crossing the southern Indian Ocean before moving south to the Antarctic. Foraging intensity differed between migration phases. Indian Ocean foraging locations were diverse, and less frequent over deep ocean basins. Foraging intensity was highest in the later stages of return migration, particularly in and around the Azores Confluence Zone. High movement speeds and foraging intensity on return migration may be adaptations to optimise reproductive success. Some aspects of migration phenology were repeatable between years, but trajectories were displaced by wind. Repeat birds did not use the same foraging areas in different years, and their trajectories across the Indian Ocean also differed. The results of this study suggest that the Indian Ocean crossing is a behaviour pattern, surviving since the last ice age, enabling Arctic terns breeding at low-latitude northwest European colonies to arrive at fragmenting Antarctic sea ice when foraging conditions are suitable.

A cost-effective method to monitor vegetation changes in steppes ecosystems: A case study on remote sensing of fire and infrastructure effects in eastern Mongolia

Land degradation is a major environmental and social issue in temperate steppes. It is commonly determined from vegetation cover using remote sensing techniques. Steppes in eastern Mongolia are subject to resource extraction activities, such as mining and oil extraction, which affect land degradation. Recent technological progress in remote sensing has facilitated the acquirement of high-resolution data by, for example, the CubeSat satellite or unmanned aerial vehicles (UAV), providing data for detailed maps of vegetation cover and plant functional groups (PFGs). Traditional methods for monitoring vegetation cover often face typical scale issues, such as the upscaling of vegetation parameters if plot-scale field measurements are integrated to satellite data. Here, we studied the spatial distribution of PFG using machine learning and a combination of field measurements, UAV imagery (spatial resolution: 2 cm), and PlanetScope multi-temporal imagery. We provide two products at two spatial resolutions: one for UAV data, which is restricted to comparatively small areas around field measurements, and one for PlanetScope, which covers large parts of northeastern Mongolia. The results showed that the overall accuracies of UAV classification were 91–95%, whereas those of PlanetScope were 78–95%. In integrating the classified UAV data to the PlaneScope data, our proposed model minimized the scale issue that often impedes classification. Importantly, our findings revealed that the ecological effects of dirt road and railroad extended up to 60–120 m into the adjacent, otherwise less degraded steppe vegetation. A comparison between burned and unburned areas in different years indicates that wildfires affect the composition of PFG in reducing the fractional cover of graminoids and forbs, and that increasing cover of bare ground leads to a distinct and patchy mosaic of different vegetation types.

Spatiotemporal Characteristics of Vegetation Net Primary Productivity on an Intensively-Used Estuarine Alluvial Island

Net Primary Productivity (NPP) can effectively reflect the characteristics and strength of the response to external disturbances on estuarine alluvial island ecosystems, which can provide evidence for regulating human development and utilization activities and improving blue carbon capacity. However, there are a few studies on NPP of estuarine alluvial islands. We established a model based on a Carnegie–Ames–Stanford Approach (CASA) to estimate NPP on Chongming Island, a typical estuarine alluvial island, by considering the actual ecological characteristics of the island. The NPP of different land-cover types and protected areas in different years and seasons were estimated using Remote Sensing and Geographic Information System as the main tools. Correlations between NPP and Remote Sensing-based spatially heterogeneous factors were then conducted. In the last 30 years, the mean NPP of Chongming Island initially increased and then slowly decreased, while total NPP gradually increased. In 2016–2017, Chongming Island total NPP was 422.32 Gg C·a−1, and mean NPP was 287.84 g C·m−2·a−1, showing significant seasonal differences. NPP showed obvious spatial differentiation in both land-cover and protected area types, resulting from joint influences of natural and human activities. Chongming Island vegetation growth status and cover were the main factors that positively affected NPP. Soil surface humidity increased NPP, while soil salinity, surface temperature, and surface aridity were important NPP limiting factors.

A study on the evolution mechanism of agricultural landscape pattern of Dadu River Valley in Danba Region

Taking the Dadu River Basin in the Danba area of Ganzi Prefecture, Sichuan Province as the research area, based on the 2013 and 2016 Landsat8 remote sensing images, the temperature vegetation drought index (TVDI) method is used to divide the Dadu River dry valley into 6 arid gradient regions. Using ArcGIS10.5 software and Fragstats4.2 software to calculate the landscape pattern index of different arid gradient areas in different years, combined with the survey results of agricultural policies, development models, and agricultural landscape patterns in key regions, analyze the evolution of agricultural landscape patterns under different drought gradients. The results show that, except for other forestlands, the degree of landscape fragmentation is decreasing year by year on the gradient of light and moderate drought, and the degree of spatial heterogeneity is higher. On the gradient of extreme drought, the degree of landscape fragmentation is higher, and the degree of spatial heterogeneity is lower.

Analysis of Soil retention service function in the North Area of Guangdong based on the InVEST model

Based on the InVEST model, the spatial and temporal evolution trends of water and soil conservation service functions in northern Guangdong in the three periods from 2000 to 2018 were evaluated, and the factors affecting the changes and spatial distribution of soil conservation time were further analyzed. The results indicate: (1) The average soil erosion per unit area in the study area in different years is 5.9∼7.6 t/ha•a, 81∼87% of the study area is mild erosion. (2) The amount of soil retention per unit area in the study area increased firstly and then decreased, reaching a maximum of 68.87 t/ha•a in 2010. This change was mainly caused by the difference in rainfall erosivity caused by precipitation. (3) The low-value areas of soil retention in the study area are mainly distributed in the central urban areas of Shaoguan, Qingyuan, Nanxiong Basin and Wengjiang Basin. The high-value areas are mainly distributed in the mountainous areas, such as Dadong Mountain, Qiweishan Mountain, Luoke Mountain, Huashui and Huangsi-nao Mountain. (4) The main factors affecting the spatial difference of soil retention in the study area are land use type, altitude, and slope. Under different land use types, the amount of soil retention per unit area from large to small is woodland> grassland> water area> cultivated land> construction land.

The Analysis of the Urban Sprawl Measurement System of the Yangtze River Economic Belt, Based on Deep Learning and Neural Network Algorithm.

In the context of rapid urbanization, the spread of cities in the Yangtze River Economic Belt is intensifying, which has an impact on the green and sustainable development of these cities. It is necessary to establish an accurate urban sprawl measurement system. First, the regulation theory of urban sprawl is explained. According to the actual development situation of cities in the Yangtze River Economic Belt, smart growth theory is selected as the basic regulation method of urban sprawl. Second, the back propagation neural network (BPNN) algorithm under deep supervised learning is applied to construct a smart evaluation model of land use growth. Finally, based on the actual development of cities in the Yangtze River Economic Belt, the quantitative growth measurement method is selected to construct a measurement system of urban sprawl in the Yangtze River Economic Belt, and the empirical analysis is carried out. The training results show that the proposed BPNN smart growth evaluation model, based on deep supervised learning, has good evaluation accuracy, and the error is within the preset range. The analysis of the quantitative growth-based measurement system in the increase of urban construction land shows that the increase in urban construction land area of the Yangtze River Economic Belt from 2014 to 2019 was 78.67 km2. Meanwhile, the increases in urban construction land area in different years are different. The empirical results show that the population composition of the Yangtze River Economic Belt and the urban construction area between 2005 and 2019 show a trend of increasing annually; at the same time, urban sprawl development shows a staged characteristic. It is of great significance to apply deep learning fusion neural network algorithm in the construction of the urban sprawl measurement system, which provides a quantitative basis for the in-depth analysis and discussion of urban sprawl.

Meteorological conditions and their associations with the productive performance of wheat

This study aimed at assessing the effect of the photothermal quotient, meteorological variables and their effects on the grain production and yield of the wheat cultivars in terms of hectoliter mass in Santa Maria, Rio Grande do Sul state, Brazil. The experiments were carried out in the same experimental area in different years. Four experiments were performed in the experimental field during the agricultural years of 2013 (10 cultivars), 2014 (16 cultivars), 2015 (15 cultivars) and 2016 (15 cultivars) with the principal cultivars in the Rio Grande do Sul state, during each of these years. The meteorological factors (mean air temperature, solar radiation, insolation and accumulated precipitation) showed wide fluctuations over these years. They induced instability in the production. The grain yield and the hectoliter mass were compared in each of the agricultural years (Scott-Knott, α≤0.05) and are related in dispersion plots according to the climatic variables for the set of years and cultivars (regression analysis). The available solar radiation (number of sunshine hours), quality (photothermal quotient) and average air temperature were the determinant factors for wheat productivity. However, the hectoliter mass was influenced more by the effect of genetic variability, lack of precipitation during crop maturation, and photothermal quotient around the time of anthesis. Wheat crop investments can be expanded to maximize wheat grain yield when average cycle temperatures remain near 16.5 oC, high solar radiation and low rainfall. Better quality trains (hectoliter mass) will be obtained when smaller precipitations are observed at harvest and higher photothermal quotient.

Annual and Seasonal Variation in Artemia Population in Relation to Water Quality Parameters in Lake Galgas in Crimea, Russia

Aim: To study seasonal changes of hydrological parameters of the water and Artemia population status in the hypersaline Galgas Lake in the period of 2017-2019.
 Study Area and Duration: The study was carried out in the Crimea, a peninsula on the northern coast of the Black Sea in Eastern Europe in 2017-2019.
 Methodology: Water (brine) and Artemia samples were collected monthly from the lake located at the coastal line of the Black Sea. The parameters namely temperature, pH, salinity, Eh, and oxygen concentration of were determined in the water. Artemia population including the developmental stages and the cysts hatching rate of the cysts were measured in different seasons in the study period. The differences in hydrochemical characteristics of the study area in different years and seasons were observed.
 Results: The results showed that the hydrochemical characteristics of the study area varied with the climate peculiarities. In summer months 2017, the lake was dried out. In the hot period, the temperature of the air and water was above +30°C, the pH ranged insignificantly, and the oxygen concentration was low. Artemia cysts were found throughout the year, however the nauplii were mostly available during spring and autumn seasons, while the adults were found in spring and summer months.
 Conclusion: The study concluded that the changes of the water parameters depended on season and especially on air temperature. The changes of Artemia population were different in examined years and depended on the water characteristics and especially on temperature and oxygen concentration. The obtained results could be helpful for the local climate changes consequences studies and their influence on aquatic biota.

Challenges in the conservation of wide‐ranging nomadic species

Abstract Conservation of nomadic species presents significant conservation challenges because of unpredictability in their movements and space use. Long‐term studies on nomadic species offering insights into the variability in space use within and between years are largely missing but are necessary to develop effective conservation strategies. We examined the temporal variability in space‐use of Mongolian gazelle, a nomadic species. We tracked 22 individuals for 1–3 years with GPS and used the resulting movement patterns to evaluate conservation strategies associated with their nomadic movements in the intact open plain grasslands of Mongolia. Individuals exhibited a high degree of variability in space use within and between years, often using different wintering areas in different years. The individual range size varied as much as threefold between years, with an estimated average annual individual range size of ~19,000 km2 and a lifetime range of ~100,000 km2. Comparing simulated and empirical GPS trajectories for the Mongolian gazelle showed that they avoided disturbed areas (e.g. oil fields) and did not prefer protected areas. Importantly, no single protected area in the region was large enough to cover the annual range of any of the tracked gazelle. Because of their wide‐ranging movements, the presence of linear infrastructure and the resulting barrier effects are a particular concern. We found that fences along the national border were absolute barriers affecting movements of about 80% of all tracked individuals. When gazelle encounter the border fence, they moved a median distance of 11 km along fences, suggesting frequent crossing options are needed to make barriers permeable. Synthesis and applications. We show that for nomadic species whose space use varies greatly across years, multiyear movement data are essential for sound conservation planning. We emphasize that place‐based approaches alone are insufficient to conserve wide‐ranging nomadic species and that linear infrastructure, including fences, highways and railroads, is of particular concern. Because nomadic species lack defined movement corridors, we advocate integrated land use planning that prioritizes permeability across the entire landscape and facilitates long‐distance movements. We suggest that conservation strategies for nomadic species in arid and semi‐arid regions be reconsidered based on multiyear connectivity assessments at the landscape scale.

Status Assessment of Agricultural Drainage Ditches

Abstract. Poor maintenance, environmental concerns, land use changes, and adaptation to climate change are creating a growing need for better agricultural drainage. The objectives of this study were to identify ditch properties that can be evaluated visually on-site and related soil erosion processes, and to define parameters requiring more intensive study and estimate these using simplified methods. The study included surveys of ditches in various soils using MADRAS (Minnesota Agricultural Ditch Research Assessment for Stability) to classify ditch status. To explain why some ditch segments were in poor condition, additional field and laboratory studies were carried out. Soil samples were taken for analysis of particle size distribution, unsaturated direct shear strength, and critical stress for erosion. The HEC-RAS data model was used for simulation of hydraulic forces acting at different flow rates. Digital maps of land use in the catchment area in different years were used to estimate changes in runoff conditions over time. MADRAS proved to be a suitable tool for rapid assessment of stability problems in ditches. The HEC-RAS simulations were a good complement to MADRAS in assessing how changes in land use affected the hydraulic load and in highlighting bottlenecks in the system. However, the hydraulic load did not adequately explain the degree of degradation in some ditch segments. Measurements of soil shear strength were a good aid to understanding existing degradation. Thus, assessment of soil erodibility and bank stability is essential in anticipating the risk of future erosion processes in ditches. Keywords: Cohesive strength meter, HEC-RAS, MADRAS, Unsaturated direct shear strength.

An approach to evaluating ecological status of populations in forest-nesting birds (Passeriformes and Piciformes)

A 13-year study of forest-nesting birds (orders Passeriformes and Piciformes) has been conducted at five constant census areas in European Russia, Caucasus, and the mountains of Southern Siberia. The nesting individuals are mapped at each census area for two or more nesting periods. The nesting densities for each species are estimated. Raster maps of spatial allocation (MSA) at the scale of the raster grid of 50 × 50 m are obtained for each species. The degree of spatial conservatism (DSC) for each local population is inferred from the pairwise comparisons of the specific MSAs obtained at the same area in different years with the use of the Gamma rank correlation method. This index characterizes the connection of population with the habitat. Based on 5-year observations at that particular census area, the areas of habitats are estimated (Y) and mean DSC values (X) are obtained for all 18 model species. Using the regression model (Y = 117–103.5X; R = 0.84; p < 0.01), it is demonstrated that, under conditions of almost complete saturation, when a population uses almost the entire area of available habitats and maximum carrying capacity of habitat is almost achieved, the total area occupied by the individual nesting home ranges of the particular species is in an inverse linear relationship with the DSC estimates. Based on this model, it is possible to calculate the maximum carrying capacity of habitat for each species from its DSC value. Maximum nesting density for each species at a particular census area is calculated based on its DSC values and mean size of its nesting home range. The ratio between observed and maximum nesting densities allows estimating the degree of saturation of carrying capacity of habitat and the population status of a particular species under different environmental conditions.

Quantifying the influences of various ecological factors on land surface temperature of urban forests

Identifying factors that influence the land surface temperature (LST) of urban forests can help improve simulations and predictions of spatial patterns of urban cool islands. This requires a quantitative analytical method that combines spatial statistical analysis with multi-source observational data. The purpose of this study was to reveal how human activities and ecological factors jointly influence LST in clustering regions (hot or cool spots) of urban forests. Using Xiamen City, China from 1996 to 2006 as a case study, we explored the interactions between human activities and ecological factors, as well as their influences on urban forest LST. Population density was selected as a proxy for human activity. We integrated multi-source data (forest inventory, digital elevation models (DEM), population, and remote sensing imagery) to develop a database on a unified urban scale. The driving mechanism of urban forest LST was revealed through a combination of multi-source spatial data and spatial statistical analysis of clustering regions. The results showed that the main factors contributing to urban forest LST were dominant tree species and elevation. The interactions between human activity and specific ecological factors linearly or nonlinearly increased LST in urban forests. Strong interactions between elevation and dominant species were generally observed and were prevalent in either hot or cold spots areas in different years. In conclusion, quantitative studies based on spatial statistics and GeogDetector models should be conducted in urban areas to reveal interactions between human activities, ecological factors, and LST.

Monitor and Study Horizontal and Verticals Changes at Land Surface in Wen Chuan Area from 1974 to 2010 Using Remote Sensing and GIS Technology

Wenchuan area has been one of the seismically active regions. The occurrences of earthquakes are largely controlled by active faults .The results showed that in Wenchuan area, movements of plate tectonic were not in the same direction in recent 40 years and when there was a change in the direction of plate tectonics there was an earthquake in Sichuan, or on Tibet plate, but most of the earthquakes were in the region between plate Sichuan and Tibet plate. The idea is to compare between images from the same satellite for same area in different years by using remote sensing and GIS technology. The result will become better if there are images of the same area every year. The satellite images were used from 1974-1976 land sat-1,2 ,1989-1996 land sat-4,1999-2005 land sat -7, Google earth images 2005-2008 after and before the earthquake Wenchuan 2008, Geomorphic features are extracted from the Shuttle Radar Topography Mission (SRTM) DEM data 2002 and 2010, SRTM DEM and Land sat data were used to extract the geo morphometric Features and structures. The relationship between the topography and tectonics is assessed to understand the evolution mode.

Characteristics Analysis and Classification of Crop Harvest Patterns by Exploiting High-Frequency MultiPolarization SAR Data

At harvest season, crops are often harvested using various methods at different times. Mapping and monitoring of the patterns of croplands during the harvest period provide information for farmers to help guide the harvest practices that are time critical and to support early warning of threats to food security. This study discusses the feasibility of high-frequency (C/X) polarimetric synthetic aperture radar (PolSAR) for the discrimination of crop patterns during harvest. The polarimetric signals gathered from a farmland area during harvest in Inner Mongolia, China, have been evaluated to investigate the properties of different harvest patterns by using the fully polarimetric Radarsat-2 and dual-pol TerraSAR-X images. A set of polarimetric parameters were derived from the datasets to interpret the radar signatures. The statistics show the sensitivity of the polarimetric parameters to the properties of the harvest patterns. The crop type, biomass, water content held by plants, crop swath direction, and crop state make a large contribution to the fluctuation of the polarimetric scattering characteristics. By exploring the polarimetric characteristics across different harvest patterns, a new method of mapping the harvest state is proposed by utilizing the decision tree algorithm. In the proposed method, GIS data are exploited to avoid the confusion of similar harvest patterns for different species. The harvest pattern mapping results by using the multipolarimetric data acquired over the study area in different years, demonstrate the feasibility and potential of polarimetric data of short wavelength for harvest pattern monitoring during harvest.

Obligate and facultative migration in birds: ecological aspects

This paper is concerned mainly with the differences between obligate and facultative migration in birds. Obligate migration is considered “hard-wired”, in that the bird seems pre-programmed to leave its breeding area at a certain time each year, and to return at another time. Timing, directions and distances are relatively constant from year to year. This type of migration is thus characterised by its regularity, consistency and predictability. It is found in both short-distance and long-distance migrants, but mainly in the latter. In contrast, facultative migration is considered optional, occurring in response to conditions at the time. Individuals may migrate in some years but not in others, depending on the prevailing food supplies or weather conditions. The timing of autumn migration, and the distance travelled, can be highly variable between individuals and, at the population level, between years. Facultative migration is typical of many partial migrants, but is found in its most extreme form in so-called irruptive migrants. While individual obligate migrants typically return to the same breeding localities year after year, and sometimes also to the same wintering localities, individual irruptive migrants typically breed or winter in widely separated areas in different years, wherever conditions are favourable. It is suggested that these two types of migration are best considered not as distinct, but as lying at opposite ends of a continuum of variation in bird migratory behaviour. Both systems are adaptive; one to conditions in which resource levels vary regularly and predictably in space and time, and the other to conditions in which resource levels vary unpredictably. Suggestions are made for experimental work on captive irruptive species.