Spatial-Temporal Changes of Land Degradation Caused by Natural and Human Induced Factors: Case Study of Bulgan Province in Central Mongolia

Abstract

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.

Historical conservation of community forests in Guatemala: the case of the Asociación Parcialidad Indígena de Chuamazán

“…These measures favored the recovery of the forest in the following years when support from external institutions in the defense of natural assets began. These processes of reorganization and improvements in forest management offer elements that explain the NDVI values linked to dense vegetation for these years, since the forest, despite the problems described, remained, associating the interannual variation of this period with the process of forest recovery in the midst of the climatic anomalies mentioned above (Dalantai et al, 2021); (Yang et al, 2022). PERIOD 1993TO 2002 In this decade the index value ranges from 0.63 to 0.71.…”

“…Con el objetivo de reestablecer la organización comunitaria en 1985 se fundó el comité promejoramiento, retomando las reforestaciones anuales, los recorridos de vigilancia, la prevención de incendios y, se funda el vivero de la parcialidad; favoreciendo la recuperación del bosque en los años subsiguientes, cuando también inicia el apoyo de instituciones externas en el tema de la defensa de los bienes naturales. Estos procesos de reorganización y mejoras en la gestión del bosque ofrecen elementos que explican los valores de NDVI vinculados a una vegetación densa para estos años, pues el bosque a pesar de las problemáticas descritas permaneció asociándose la variación interanual de este periodo con el proceso de recuperación del bosque en medio de las anomalías climáticas mencionadas anteriormente (Dalantai et al, 2021); (Yang et al, 2022).…”

Assessment of Land Degradation at the Local Level in Response to SDG 15.3: A Case Study of the Inner Mongolia Region from 2000 to 2020

“…OV i,j − OV j,min / OV j,max − OV j,min , OV i,j ≥ 0 − OV i,j − OV j,min / OV j,max − OV j,min , OV i,j < 0 (10) where SDV i,j represents the standardized value of indicator j of land unit i; OV i,j represents the value of indicator j of land unit i; OV j,max and OV j,min represent the maximum and minimum absolute values of indicator j in all land units, respectively.…”

“…were determined based on expert experience, but there was no consistent standard to measure them. With the continuous development of GIS technology, the methods to assess land degradation gradually changed from subjective and qualitative to objective and quantitative [10,11]. In some studies, land cover changes were used for identifying land degradation [12][13][14], but this method was invalid when land degradation occurred without land cover change.…”

Simulation and Prediction of Land Use/Cover Changes Based on CLUE-S and CA-Markov Models: A Case Study of a Typical Pastoral Area in Mongolia

“…Local herders blindly pursue economic interests and ignore the rational use and distribution of land resources, resulting in serious imbalances in the ecosystem and the threat of land degradation (desertification). In the Gurvanbulag pastoral area, where the ecological environment is more sensitive in the southern part of the province, an increasing number of grassland, forest, and water-bodies (river, lake, wetland) are transformed into other land types (sandy, saline-alkali land) [27]. In this research, the pastoral area is studies using RS technology combined with driving factors, such as nature and social economy, to capture the future LUCC evolution trend in the pastoral area and to compare and analyze the simulation results of the two models.…”