Knowledge of hydrologic connectivity is important to grasp the hydrological response at a basin scale, particularly as changes in connectivity can have a negative effect on the environment. In the context of a changing climate, being able to predict how changes in connectivity will affect runoff and sediment transport is particularly relevant for land-use planning. Many studies on hydrology, geomorphology and climatology have been conducted in the Lake Tana Basin in Ethiopia, which is undergoing rapid development and significant environmental changes.

This investigation aims to assess the changes of Land Use/Land Cover (LULC) and its impact on ecosystem services value in Damietta Governorate, Egypt. To fulfill this aim, Landsat data of TM5 in 2001, ETM in 2011 and OLI in 2021 were used. The Maximum Likelihood Classifier was employed to track the changes in LULC of the study area. Cellular automata (CA) and Markov model adopted from IDRISI software were used for accurate prediction of the LULC in 2031. The VALIDATE model in TerrSet was used to compare the predicted 2031 LULC with actual 2021 LULC to assess the accuracy of the model.

The knowledge about the spatial distribution of soil organic carbon stock (SOCS) helps in sustainable land-use management and ecosystem functioning. No such study has been attempted in the complex topography and land use of Himalayas, which is associated with great spatial heterogeneity and uncertainties. Therefore, in this study digital soil mapping (DSM) was used to predict and evaluate the spatial distribution of SOCS using advanced geostatistical methods and a machine learning algorithm in the Himalayan region of Jammu and Kashmir, India.

The scientific estimation of carbon budgets induced by land use and land cover change (LUCC) can improve the accuracy of carbon budget estimates for terrestrial ecosystems and deepen our understanding of the future carbon sink potential of these ecosystems. Previous studies have typically selected one of many LUCC-induced carbon budget methods and overlooked the differences in the results between the different methods.

Most cadastral systems today are coordinate-based and contain only a weak or no reference to measurements or the origin of the information. In some contexts, this is largely due to the transition of land data management and maintenance from an analogue to a digital environment. This study focuses on analysing the importance of the measurement-based cadastre and the digitisation process in North Macedonia and Slovenia. The survey-based boundary data and their integration into the digital environment were not considered in either case study.

The Colorado Plateau has abundant oil, gas, and alternative energy potential. This energy potential is scattered among a patchwork of land ownership, with private, tribal, and public lands being actively developed for energy extraction. Elements of biodiversity (e.g., listed and sensitive plant and animal species) are distributed among all land tenures, yet the laws protecting them can vary as a function of land tenure.

Land use and land cover change (LULC) is known worldwide as a key factor of environmental modification that significantly affects natural resources. The aim of this study was to evaluate the dynamics of land use and land cover in the Matenchose watershed from the years 1991, 2003, and 2020, and future prediction of land use changes for 2050. Landsat TM for 1991, ETM+ for 2003, and Landsat-8 OLI were used for LULC classification for 2020. A supervised image sorting method exhausting a maximum likelihood classification system was used, with the application using ERDAS Imagine software.

Pricing of direct industrial real estate (DIRE) has long been under-researched due to the paucity of analysable data. Compared to other types of real estate, DIRE has often been regarded as more inefficient because of information asymmetry amongst market players stemming from a lack of market transparency. Therefore, pricing of DIRE usually does not follow a random walk and should be more predictable than other types of real estate.

Rapid urbanization results in farmland loss, habitat fragmentation, biodiversity decrease, and greenhouse gas emissions. Land-use policies and planning as administrative means are used to guide sustainable urban development and to balance the location of urban expansion and agricultural activities. To better understand the future implications of a variety of land-use policies, we used a FUTURES model scenario analysis to analyze the potential future patterns of urban areas and the loss and fragmentation of farmland and natural resources at the local level for Xi’an.

The project-based construction land-use policy of ‘increasing versus decreasing balance’ (IVDB) is pivotal to easing the contradiction between urban and rural land in China. Understanding the relationship between the scale and revenue of the balanced quota is crucial for increasing the efficiency of quota-allocated, and further improving, IVDB performance. However, existing studies have rarely revealed the impact of the balanced quota’s scale on its revenue, supported through empirical evidence.

Controlling land use change in coastal areas is one of the world’s sustainable development goals and a great challenge. Existing research includes in-depth studies of land use change in relatively developed regions, but research on economically less developed but fast-growing regions is lacking. Since the reform and opening up in Vietnam, the influences of globalization have prompted the economy of the coastal area to develop rapidly, making it one of the less developed but rapidly developing regions where human activities and global changes vigorously interact.

As an important resource for human survival and development, the utilization efficiency of cultivated land is directly related to national food security and social harmony and stability. Based on the stochastic frontier production function, this paper estimated the cultivated land use efficiency of 342 prefecture-level administrative regions in China from 2003 to 2019 and used spatial autocorrelation analysis and the Gini coefficient decomposition model to explore the spatial agglomeration and spatial disequilibrium of cultivated land use efficiency in China.