ABSTRACT: The climate of Mongolia is a harsh continental climate with four distinctive seasons, high annual and diurnal temperature fluctuations, and low rainfall. Because of the country’s high altitude, it is generally colder than that of other countries in the same latitude. This study focuses on evaluating the suitability of two interpolation methods in terms of their accuracy at the air temperature data in Mongolia. Four data sets of air temperature from 1982 to 2019 in 60 meteorological stations located in Mongolia and elaborated from a 90 m resolution digital elevation model (DEM), latitude and longitude using two interpolation methods. ArcGIS is used to produce the spatially distributed air temperature data by using IDW and ordinary kriging. Three statistical methods are multiple regression, RMSE and bias, which showed that the IDW the best for this data from other methods by the results that have been obtained. Statistics on the latitude, longitude and surface elevation of each of the 37 years in Mongolia at 60 meteorological stations have been statistically valid with dependent coefficients at 95-99.9%. As the average air temperature, recorded at the meteorological stations, had a statistical correlation of -0.606 with latitude, 0.295 with longitude, and -0.432 with altitude, a multiple regression equation was developed and a highly accurate map for long terms air temperature covering 1982- 2019 using interpolation IDW and Kriging method. Also, the highest RMSE value for maps used IDW was 1.38 while the lowest and average values were 0.03 and 0.44, respectively, and the highest bias was 1.21, lowest 0.95, and average 1.01. As opposed to, highest RMSE value for maps that used Kriging, was 6.16, lowest 0.27 and average 1.08 while highest bias was 1.29 and lowest was 0.85, with 1.01 as average. This demonstrates that IDW offers much better accuracy as opposed to Kriging and shows less bias errors. When the air temperature map that used the IDW method is compared against the meteorological station data the significance was 0.98 and when compared against ERA5 model results, significance was 0.95 showing strong statistical significance. Also, a comparison of air temperature map, processed by Kriging method and the meteorological station data shows 0.97 statistical significance, and comparison with ERA5 model shows (validation) 0.94 significance, which is very high. The mean value of the calculated temperature regression model in Mongolia and the root mean square error 0.02-0.09 for each station indicates that the estimation method is good and can be used in the future.

ABSTRACT: Land degradation and desertification have been ranked as a major environmental issue for arid and semi-arid regions is a comprehensive concept that depends on many factors. Detecting early land degradation is a significant issue of social and environmental with geographical information system (GIS) and remote sensing methods has been used for the interpretation of spatial-temporal data. In this study, the assessment of the current state of land degradation is influenced by several complexes of the natural and anthropological causes. The results of land degradation assessment carried out for Bulgan province of Mongolia using multi-temporal resourced data as climate condition (vegetation growing season of temperature and precipitation), land use type (density of seasonal camps of herder households, roads, cropland, settlements) and MODIS vegetation product data were used to estimate land degradation change period from 2000 to 2018 and accessed it’s for effecting on degradation over last 19 years. We obtained a prediction of land degradation integrated with indicators and based on the spatial pattern of human influence. One of the main indicators for land degradation was land use type as pasture usage of livestock husbandry in Bulgan province, overgrazing is the most widespread cause of land degradation, particularly around permanent location of herders and livestock affecting about moderately and slightly degraded land is 72.78% of study total area.

Биеийн ерөнхий шинжүүд: Биеийн урт нь 0.2-3 мм хэмжээтэй усны доод хавчнууд хойд сэрүүн бүсийн сэрүүн бүсийн хавчны нэг зүйл Leptodora kindtii 1.8 см хүрдэг. Олонхи бүлгийн төлөөлөгчид биеийнхээ гадуур хатуу хавтасаар бүрхэгдсэн байдаг. Хоёр нимгэн хавхлаг нь нурууны дунд хэсэгт нийлж хуяг үүсгэн, толгойн сегментийн төгсгөл хэсгээс биеийн ханыг 2 хажуу талаар хучиж, цээж болон хөлнүүдийг бүрхэн, шахагдсан мэт хэлбэртэй байдаг (зураг 1, 2). Махчин зүйлүүдийн хавхлаг нь зөвхөн нурууны өндөг агуулах хэсгийг бүрдэг нь хөдөлгөөнийг чөлөөтэй байлгахад зохилджээ. Бие нь бусад хавч хэлбэртэн шиг үелэгдээгүй, цээж, толгой, хэвлий гэсэн 3 хэсэгт хуваагдсан, нэг нийлмэл нүднээс гадна жижиг энгийн нүдтэй, мэдрэх эрхтэнцэрийн үүрэгтэй 1-р антенн нь богино, 2-р антенн нь урт байх ба хөдөлгөөний (сэлэх) гол эрхтэнцэр юм. Амны бүтцэд эрүү болон дээд, доод уруул байдаг ба эрүү нь том, булчингийн аппараттай, дээд уруул нь жижиг хоол тэжээлийг шүүдэг, доод уруул нь үлдэгдэл төдий болсон байдаг. Ихэнхи хавч нь жижиг нарийхан 1-р антеннтай байна.

ABSTRACT: The climate of Mongolia is a harsh continental climate with four distinctive seasons, high annual and diurnal temperature fluctuations, and low rainfall. Because of the country’s high altitude, it is generally colder than that of other countries in the same latitude. This study focuses on evaluating the suitability of two interpolation methods in terms of their accuracy at the air temperature data in Mongolia. Four data sets of air temperature from 1982 to 2019 in 60 meteorological stations located in Mongolia and elaborated from a 90 m resolution digital elevation model (DEM), latitude and longitude using two interpolation methods. ArcGIS is used to produce the spatially distributed air temperature data by using IDW and ordinary kriging. Three statistical methods are multiple regression, RMSE and bias, which showed that the IDW the best for this data from other methods by the results that have been obtained. Statistics on the latitude, longitude and surface elevation of each of the 37 years in Mongolia at 60 meteorological stations have been statistically valid with dependent coefficients at 95-99.9%. As the average air temperature, recorded at the meteorological stations, had a statistical correlation of -0.606 with latitude, 0.295 with longitude, and -0.432 with altitude, a multiple regression equation was developed and a highly accurate map for long terms air temperature covering 1982- 2019 using interpolation IDW and Kriging method. Also, the highest RMSE value for maps used IDW was 1.38 while the lowest and average values were 0.03 and 0.44, respectively, and the highest bias was 1.21, lowest 0.95, and average 1.01. As opposed to, highest RMSE value for maps that used Kriging, was 6.16, lowest 0.27 and average 1.08 while highest bias was 1.29 and lowest was 0.85, with 1.01 as average. This demonstrates that IDW offers much better accuracy as opposed to Kriging and shows less bias errors. When the air temperature map that used the IDW method is compared against the meteorological station data the significance was 0.98 and when compared against ERA5 model results, significance was 0.95 showing strong statistical significance. Also, a comparison of air temperature map, processed by Kriging method and the meteorological station data shows 0.97 statistical significance, and comparison with ERA5 model shows (validation) 0.94 significance, which is very high. The mean value of the calculated temperature regression model in Mongolia and the root mean square error 0.02-0.09 for each station indicates that the estimation method is good and can be used in the future.

ABSTRACT: The climate of Mongolia is a harsh continental climate with four distinctive seasons, high annual and diurnal temperature fluctuations, and low rainfall. Because of the country’s high altitude, it is generally colder than that of other countries in the same latitude. This study focuses on evaluating the suitability of two interpolation methods in terms of their accuracy at the air temperature data in Mongolia. Four data sets of air temperature from 1982 to 2019 in 60 meteorological stations located in Mongolia and elaborated from a 90 m resolution digital elevation model (DEM), latitude and longitude using two interpolation methods. ArcGIS is used to produce the spatially distributed air temperature data by using IDW and ordinary kriging. Three statistical methods are multiple regression, RMSE and bias, which showed that the IDW the best for this data from other methods by the results that have been obtained. Statistics on the latitude, longitude and surface elevation of each of the 37 years in Mongolia at 60 meteorological stations have been statistically valid with dependent coefficients at 95-99.9%. As the average air temperature, recorded at the meteorological stations, had a statistical correlation of -0.606 with latitude, 0.295 with longitude, and -0.432 with altitude, a multiple regression equation was developed and a highly accurate map for long terms air temperature covering 1982- 2019 using interpolation IDW and Kriging method. Also, the highest RMSE value for maps used IDW was 1.38 while the lowest and average values were 0.03 and 0.44, respectively, and the highest bias was 1.21, lowest 0.95, and average 1.01. As opposed to, highest RMSE value for maps that used Kriging, was 6.16, lowest 0.27 and average 1.08 while highest bias was 1.29 and lowest was 0.85, with 1.01 as average. This demonstrates that IDW offers much better accuracy as opposed to Kriging and shows less bias errors. When the air temperature map that used the IDW method is compared against the meteorological station data the significance was 0.98 and when compared against ERA5 model results, significance was 0.95 showing strong statistical significance. Also, a comparison of air temperature map, processed by Kriging method and the meteorological station data shows 0.97 statistical significance, and comparison with ERA5 model shows (validation) 0.94 significance, which is very high. The mean value of the calculated temperature regression model in Mongolia and the root mean square error 0.02-0.09 for each station indicates that the estimation method is good and can be used in the future.

ABSTRACT: Land degradation and desertification have been ranked as a major environmental issue for arid and semi-arid regions is a comprehensive concept that depends on many factors. Detecting early land degradation is a significant issue of social and environmental with geographical information system (GIS) and remote sensing methods has been used for the interpretation of spatial-temporal data. In this study, the assessment of the current state of land degradation is influenced by several complexes of the natural and anthropological causes. The results of land degradation assessment carried out for Bulgan province of Mongolia using multi-temporal resourced data as climate condition (vegetation growing season of temperature and precipitation), land use type (density of seasonal camps of herder households, roads, cropland, settlements) and MODIS vegetation product data were used to estimate land degradation change period from 2000 to 2018 and accessed it’s for effecting on degradation over last 19 years. We obtained a prediction of land degradation integrated with indicators and based on the spatial pattern of human influence. One of the main indicators for land degradation was land use type as pasture usage of livestock husbandry in Bulgan province, overgrazing is the most widespread cause of land degradation, particularly around permanent location of herders and livestock affecting about moderately and slightly degraded land is 72.78% of study total area.

ABSTRACT: Land degradation and desertification have been ranked as a major environmental issue for arid and semi-arid regions is a comprehensive concept that depends on many factors. Detecting early land degradation is a significant issue of social and environmental with geographical information system (GIS) and remote sensing methods has been used for the interpretation of spatial-temporal data. In this study, the assessment of the current state of land degradation is influenced by several complexes of the natural and anthropological causes. The results of land degradation assessment carried out for Bulgan province of Mongolia using multi-temporal resourced data as climate condition (vegetation growing season of temperature and precipitation), land use type (density of seasonal camps of herder households, roads, cropland, settlements) and MODIS vegetation product data were used to estimate land degradation change period from 2000 to 2018 and accessed it’s for effecting on degradation over last 19 years. We obtained a prediction of land degradation integrated with indicators and based on the spatial pattern of human influence. One of the main indicators for land degradation was land use type as pasture usage of livestock husbandry in Bulgan province, overgrazing is the most widespread cause of land degradation, particularly around permanent location of herders and livestock affecting about moderately and slightly degraded land is 72.78% of study total area.

Биеийн ерөнхий шинжүүд: Биеийн урт нь 0.2-3 мм хэмжээтэй усны доод хавчнууд хойд сэрүүн бүсийн сэрүүн бүсийн хавчны нэг зүйл Leptodora kindtii 1.8 см хүрдэг. Олонхи бүлгийн төлөөлөгчид биеийнхээ гадуур хатуу хавтасаар бүрхэгдсэн байдаг. Хоёр нимгэн хавхлаг нь нурууны дунд хэсэгт нийлж хуяг үүсгэн, толгойн сегментийн төгсгөл хэсгээс биеийн ханыг 2 хажуу талаар хучиж, цээж болон хөлнүүдийг бүрхэн, шахагдсан мэт хэлбэртэй байдаг (зураг 1, 2). Махчин зүйлүүдийн хавхлаг нь зөвхөн нурууны өндөг агуулах хэсгийг бүрдэг нь хөдөлгөөнийг чөлөөтэй байлгахад зохилджээ. Бие нь бусад хавч хэлбэртэн шиг үелэгдээгүй, цээж, толгой, хэвлий гэсэн 3 хэсэгт хуваагдсан, нэг нийлмэл нүднээс гадна жижиг энгийн нүдтэй, мэдрэх эрхтэнцэрийн үүрэгтэй 1-р антенн нь богино, 2-р антенн нь урт байх ба хөдөлгөөний (сэлэх) гол эрхтэнцэр юм. Амны бүтцэд эрүү болон дээд, доод уруул байдаг ба эрүү нь том, булчингийн аппараттай, дээд уруул нь жижиг хоол тэжээлийг шүүдэг, доод уруул нь үлдэгдэл төдий болсон байдаг. Ихэнхи хавч нь жижиг нарийхан 1-р антеннтай байна.

Биеийн ерөнхий шинжүүд: Биеийн урт нь 0.2-3 мм хэмжээтэй усны доод хавчнууд хойд сэрүүн бүсийн сэрүүн бүсийн хавчны нэг зүйл Leptodora kindtii 1.8 см хүрдэг. Олонхи бүлгийн төлөөлөгчид биеийнхээ гадуур хатуу хавтасаар бүрхэгдсэн байдаг. Хоёр нимгэн хавхлаг нь нурууны дунд хэсэгт нийлж хуяг үүсгэн, толгойн сегментийн төгсгөл хэсгээс биеийн ханыг 2 хажуу талаар хучиж, цээж болон хөлнүүдийг бүрхэн, шахагдсан мэт хэлбэртэй байдаг (зураг 1, 2). Махчин зүйлүүдийн хавхлаг нь зөвхөн нурууны өндөг агуулах хэсгийг бүрдэг нь хөдөлгөөнийг чөлөөтэй байлгахад зохилджээ. Бие нь бусад хавч хэлбэртэн шиг үелэгдээгүй, цээж, толгой, хэвлий гэсэн 3 хэсэгт хуваагдсан, нэг нийлмэл нүднээс гадна жижиг энгийн нүдтэй, мэдрэх эрхтэнцэрийн үүрэгтэй 1-р антенн нь богино, 2-р антенн нь урт байх ба хөдөлгөөний (сэлэх) гол эрхтэнцэр юм. Амны бүтцэд эрүү болон дээд, доод уруул байдаг ба эрүү нь том, булчингийн аппараттай, дээд уруул нь жижиг хоол тэжээлийг шүүдэг, доод уруул нь үлдэгдэл төдий болсон байдаг. Ихэнхи хавч нь жижиг нарийхан 1-р антеннтай байна.