scholarly journals Modeling fragmentation probability of land-use and land-cover using the bagging, random forest and random subspace in the Teesta River Basin, Bangladesh

2021 ◽  
Vol 126 ◽  
pp. 107612
Author(s):  
Swapan Talukdar ◽  
Kutub Uddin Eibek ◽  
Shumona Akhter ◽  
Sk Ziaul ◽  
Abu Reza Md. Towfiqul Islam ◽  
...  
2017 ◽  
Vol 27 (1) ◽  
pp. 13-24 ◽  
Author(s):  
Fang Wang ◽  
Quansheng Ge ◽  
Qibiao Yu ◽  
Huaxin Wang ◽  
Xinliang Xu

2021 ◽  
pp. 70-77
Author(s):  
Т.К. МУЗЫЧЕНКО ◽  
М.Н. МАСЛОВА

В статье рассмотрено пространственное распределение типов земель в пределах трансграничного бассейна р. Раздольная. На основе дешифрирования космических снимков Sentinel-2 и Landsat 8 составлена карта пространственного распределения типов земель по состоянию на 2019 г. Исходя из геоэкологической классификации ландшафтов В.А. Николаева в данной работе было выделено 12 типов земель: используемые и неиспользуемые сельскохозяйственные земли, используемые и неиспользуемые рисовые поля, карьеры, леса, лесопосадки, рубки, луга, застроенные земли, водные объекты, а также кустарники и редколесья. Представлены абсолютные и относительные площади для каждого типа земель по трансграничному бассейну в целом, а также отдельно для его российской и китайской частей. По результатам дешифрирования данных дистанционного зондирования установлено, что российская и китайская части бассейна р. Раздольная имеют существенные трансграничные различия в структуре земель. На российской части бассейна лесами покрыто чуть более половины площади, но при этом значительные площади занимают сельскохозяйственные земли и луга. В некоторых местах луга и сельскохозяйственные земли преобладают в большей степени, чем леса. На китайской части лесные территории доминируют над другими типами земель. Сельскохозяйственные земли и луга образуют узкие и длинные полосы и имеют более мозаичное распространение, чем на российской части. Здесь заметно меньше площади застроенных земель, а площади рубок и лесопосадок больше, чем на российской части. Площади карьеров примерно равны в обеих частях бассейна. The transboundary Razdolnaya river basin is nearly evenly split up between Primorsky Krai of Russian Federation and Heilongjiang and Jilin provinces of People’s Republic of China. The Chinese and the Russian parts of the transboundary river have developed independently of each other. Therefore, the two have a different land cover and land use structure. The analysis of land cover and land use structure is of utmost importance for the understanding the modern state of land development and the possibilities of its future development. Using the remote sensing data, such as Sentinel-2 and Landsat 8 satellite imagery, the land cover and land use map of the Razdolnaya transboundary river basin for 2019 has been composed by means of the ArcMap 10.5 software package. According to V.A. Nikolaev’s geoecological classification of landscapes, we have identified 12 land types: forests, meadows, shrubs and woodlands, agricultural lands, unused agricultural lands, rice fields, unused rice fields, built-up areas, reforestation lands, logging, quarries, and bodies of water. We have provided area coverage for each type of land of the whole transboundary basin, and for the Russian and Chinese parts. According to the results of computer-aided visual deciphering and automatic deciphering, forests are the most common land use type in the basin. In the Chinese part of the basin, forests dominate over the other types of land. Agricultural lands and meadows have assumed narrow and linear shapes. Built-up areas have less coverage here than in the Russian part of the basin. However, the coverage of logging and reforestation lands is considerably larger than in the Russian part of the basin. In the Russian part of the basin, forests co-dominate with the agricultural lands and meadows. In some areas of this part of the basin forests disappear almost completely. The Russian part of the basin also has the larger coverage of shrubs and woodlands, unused agricultural lands, rice fields and unused rice fields. The coverage of quarries is roughly equal in both parts of the basin.


Author(s):  
Jiren Xu ◽  
Fabrice G. Renaud ◽  
Brian Barrett

AbstractA more holistic understanding of land use and land cover (LULC) will help minimise trade-offs and maximise synergies, and lead to improved future land use management strategies for the attainment of Sustainable Development Goals (SDGs). However, current assessments of future LULC changes rarely focus on the multiple demands for goods and services, which are related to the synergies and trade-offs between SDGs and their targets. In this study, the land system (combinations of land cover and land use intensity) evolution trajectories of the Luanhe River Basin (LRB), China, and major challenges that the LRB may face in 2030, were explored by applying the CLUMondo and InVEST models. The results indicate that the LRB is likely to experience agricultural intensification and urban growth under all four scenarios that were explored. The cropland intensity and the urban growth rate were much higher under the historical trend (Trend) scenario compared to those with more planning interventions (Expansion, Sustainability, and Conservation scenarios). Unless the forest area and biodiversity conservation targets are implemented (Conservation scenario), the forest areas are projected to decrease by 2030. The results indicate that water scarcity in the LRB is likely to increase under all scenarios, and the carbon storage will increase under the Conservation scenario but decrease under all other scenarios by 2030. Our methodological framework and findings can guide regional sustainable development in the LRB and other large river basins in China, and will be valuable for policy and planning purposes to the pursuance of SDGs at the sub-national scale.


2019 ◽  
Vol 10 (3) ◽  
pp. 212-235
Author(s):  
Fabiana da Silva Pereira ◽  
Ima Célia Guimarães Vieira

The objective of this paper was to evaluate the degree of anthropic transformation of a river basin in the Amazon region. We used the digital data of the TerraClass Project to calculate the Anthropic Transformation Index - ATI. In order to verify spatial and temporal changes along a decade in the Gurupi river basin, we used the database of the years 2004 and 2014. The results showed an increase of anthropic changes in the basin over a decade, as a result of forest cover conversion into agricultural and pastures areas. Although the Gurupi river basin remains at a regular level of degradation after a decade, the intensification of land use and land cover change is a threat to the few rainforest remnants of the river basin, which can lead the region to the next level of degradation, if effective forest protection, conservation and restoration actions are not implemented in the region.  


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