Land Use Conditions Research Articles

Study on the Value of Ecosystem Services and Land Use Change in the Area North of the Tianshan Mountains from 2000 to 2020

The northern Tianshans region in the arid zone of northwestern China plays a key role in promoting high-quality development of the ecological environment. In recent years, ecological environmental protection in this region has encountered major challenges due to the dual impacts of human activities and natural changes. In order to accurately assess the current status of the ecological environment in the northern Tianshans, this study analyzed the spatial and temporal changes in land use and ecological and environmental effects using land use data from 2000 to 2020 and explored the current status of land use, land use dynamic process, and ecosystem service value (ESV) in the region. Two-factor spatial autocorrelation analysis revealed the spatio-temporal characteristics of the value changes over the 20-year period as well as their spatial heterogeneity. The results show that: (1) land use changes are dominated by increases in cultivated land, forest land, watershed, and wetland, and decreases in grassland, glacier snow, and bare land. Of these changes, the expansion of cultivated land area is the most significant, showing a total increase of 1136.13 × 103 hm2. (2) The ESV increased and then decreased, reaching the highest value in 2005 and the lowest in 2020. The value of individual ecosystem services is dominated by regulating services, accounting for about 67% of the total value. (3) The overall regional balance of ecological environment quality and the contribution rate of the conversion from bare land to other land types is as high as 82.7986%, constituting the main factor in regional ecological environment improvement. The spatial distribution pattern exhibits the characteristic of “high in the northeast and low in the southwest”. (4) There is a positive correlation between the ESV, the Normalized Difference Vegetation Index (NDVI), and the Anthropogenic Impact Composite Index, with the NDVI being the main cause of spatial heterogeneity in the ESV. The research results provide a scientific basis for ecological protection, land management, and policy formulation in the northern foothills of the Tianshan Mountains and are of great significance for promoting regional sustainable development.

Origin of land status and history of land use of large oil palm plantation in PT PSM, West Kalimantan Province

Origin of land status and history of land use of large oil palm plantation in PT PSM, West Kalimantan Province

Tree species-mediated soil properties shape soil fauna community structure more strongly in the soil layer: Evidence from a common garden experiment

Soil fauna plays a crucial role in the soil biogeochemical cycles of forest ecosystems, with tree species composition regulating their diversity and functionality through alterations in habitat conditions and nutrient availability. However, identifying the impacts of tree species on soil faunal communities remains challenging due to the difficulty in distinguishing the effects of tree species-induced habitat changes from those of historical environmental conditions. Here, we conducted a field study in a common garden established in 2015, with consistent climate, soil, and land-use conditions to clarify the response of the soil faunal community to changes in tree species. After 5 years of plantation growth, we evaluated the differences in tree species identities and soil faunal community structures between the litter and soil layers in four closed-canopy broadleaf forests (Cinnamomum septentrionale, Cinnamomum camphora, Cinnamomum longepaniculatum and Toona sinensis). We found that the soil faunal communities differed significantly among the four broad-leaved tree species, with 18.7 % being dominated by Collembola and 67.2 % by Acari, with a relatively high proportion of microbivores (65.5 %). Compared with that of the other stands, the C. longepaniculatum stand had the most notable differences in taxa composition, while the T. sinensis stand exhibited the greatest soil biological quality, with a QBS value 1.25 times greater than that of other stands. The greatest total soil faunal abundance was observed in C. camphora, and this high abundance was due to a greater proportion of microbivores (75.4 %), whereas the detritivores, herbivores, and predators exhibited greater abundance in T. sinensis than in the other stands due to the high-quality litter input (low C/P and C/N ratios) and low tree biomass. The distribution of soil fauna across the habitat layers was significantly influenced by tree species changes, with the most pronounced differences occurring in the soil layer rather than in the litter layer. Finally, soil properties, rather than litter and plant conditions, were the primary factors explaining interspecific variations in total abundance and total diversity of the soil fauna and the QBS index, accounting for 61.6 %, 71.7 %, and 34.4 % of the variation, respectively. The results from the common garden experiment suggest that the change in the soil faunal community due to tree species identity was greater in the soil layer than in the litter layer, with the crucial determinant being tree-species-mediated soil properties. These insights enhance our understanding of the effect of tree species on soil faunal communities, which is essential for biodiversity conservation in artificial forests and for guiding tree species selection.

Spatiotemporal and vertical variability of water quality in lentic small water bodies: implications of varying rainfall and land use conditions.

Lentic small water bodies (LSWBs) deteriorate owing to anthropogenic activities, such as untreated domestic and agricultural waste disposal. Moreover, different turnover mechanisms occur during different seasons, contributing to nutrient enrichment and consequent degradation of LSWBs. However, understanding their spatial, temporal, and vertical variations during different seasons is understudied. In addition, studies on the variation in water quality under varying rainfall and land-use conditions are limited. Therefore, in this study, three LSWBs located in Northern India were studied during the pre-monsoon and monsoon seasons (December 2022 to October 2023). Total nitrogen (TN), chlorophyll-a (Chl-a), total phosphorus (TP), temperature, pH, dissolved oxygen (DO), total dissolved solids (TDS), chemical oxygen demand (COD),secchi disk depth (SDD), and water level (WL) were measured monthly. Sentinel-2 and CHIRPS pentad data were used for land use, land cover classification, and rainfall analysis. The spatial analysis indicates that the seasonal shift affects the water quality distribution, especially near the inlets and at the edges. The overall concentrations of TN and TP decreased during the monsoon season; however, they increased significantly at the inlets of the LSWBs. On the other hand, the Chl-a concentration shifted towards the edges due to the inflow during the monsoon. Temporal analysis also suggests that the arrival of the monsoon lowers pH, DO, and TDS. However, the concentrations of TN and TP increased because of agricultural runoff. Chl-a and COD show distinct variations due to the individual LSWBs' local conditions. Vertical variability analysis demonstrated pH, temperature, and TN stratification during the pre-monsoon period. However, during the monsoon, stratification is less significant due to intermixing. Redundancy analysis (RDA) showed that land use and rainfall patterns affected the water quality of LSWB 1, 2, and 3 by 53.49%, 81.62%, and 92.64%, respectively. This shows that land use, land cover, and rainfall changes affect the water quality of LSWBs. This study highlights the negative impact of runoff from agricultural land use as the main factor responsible for increased nutrient levels in the LSWBs.

Land-Use Feedback under Global Warming—A Transition from Radiative to Hydrological Feedback Regime

Abstract This study examines the effects of land-use (LU) change on regional climate, comparing historical and future scenarios using seven climate models from phase 6 of Coupled Model Intercomparison Project–Land Use Model Intercomparison Project experiments. LU changes are evaluated relative to land-use conditions during the preindustrial climate. Using the Community Earth System Model, version 2–Large Ensemble (CESM2-LE) experiment, we distinguish LU impacts from natural climate variability. We assess LU impact locally by comparing the impacts of climate change in neighboring areas with and without LU changes. Further, we conduct CESM2 experiments with and without LU changes to investigate LU-related climate processes. A multimodel analysis reveals a shift in LU-induced climate impacts, from cooling in the past to warming in the future climate across midlatitude regions. For instance, in North America, LU’s effect on air temperature changes from −0.24° ± 0.18°C historically to 0.62° ± 0.27°C in the future during the boreal summer. The CESM2-LE shows a decrease in LU-driven cooling from −0.92° ± 0.09°C in the past to −0.09° ± 0.09°C in future boreal summers in North America. A hydroclimatic perspective linking LU and climate feedback indicates LU changes causing soil moisture drying in the midlatitude regions. This contrasts with hydrology-only views showing wetter soil conditions due to LU changes. Furthermore, global warming causes widespread drying of soil moisture across various regions. Midlatitude regions shift from a historically wet regime to a water-limited transitional regime in the future climate. This results in reduced evapotranspiration, weakening LU-driven cooling in future climate projections. A strong linear relationship exists between soil moisture and evaporative fraction in midlatitudes. Significance Statement Land–atmosphere feedback involving soil moisture can increase local temperature and affect how land-use (LU) change impacts manifest in a warming climate. Conversely, an increased surface reflectance due to LU change can decrease local temperature in the midlatitude regions. Further, the LU change signal is often mixed with the internal climate variability, making it harder to separate. This study uses a novel technique to separate LU change impact from other climate forcing in the latest generation of climate and Earth system models. In the future climate, soil moisture drying lessens the cooling impact. A large-ensemble climate experiment analysis confirms a significant weakening of the LU-driven cooling impact in the midlatitudes. Both LU and climate changes exacerbate soil moisture drying, leading to a shift toward a water-limited system where hydrological feedback becomes more influential than radiative feedback.

Integrated hydrological modeling and water resource assessment in the Mayurakshi River Basin: A comprehensive study from historical data to future predictions

This study employs the SWAT hydrologic model to integrate climatological and hydrological processes for an in-depth analysis of the Mayurakshi River Basin. Utilizing the Markov Chain Model, the study evaluates water availability, flow patterns, and the basin's response to various climatic and land-use scenarios. Over 30 years of daily observed river discharge data were rigorously calibrated, validated, and analyzed for uncertainty, with critical data from the Massanjore Dam and Tilpara Barrage gauge stations characterizing the river's hydrological behavior. The result suggests the watershed received an average annual precipitation of 1432.4 mm, with evapotranspiration accounting for 40% of total water loss (578.4 mm). Surface runoff constituted over 90% of the total discharge, highlighting its importance for agricultural practices, particularly during the dry season. However future projections (2021-2031) indicate a significant decrease in mean annual precipitation (1404.7 mm) and a drop in evapotranspiration (542.1 mm or 38% of mean precipitation), attributed to reduced vegetation cover and increased settlement, leading to enhanced surface runoff. By quantifying internal renewable blue water, evapotranspiration, and soil water, this research provides crucial data for long-term water resource planning and assessment. The findings are valuable for national, regional, and transboundary water management agencies, offering insights into sustainable water resource management under changing climatic and different land-use conditions.

ANADEM: A Digital Terrain Model for South America

Digital elevation models (DEMs) have a wide range of applications and play a crucial role in many studies. Numerous public DEMs, frequently acquired using radar and optical satellite imagery, are currently available; however, DEM datasets tend to exhibit elevation values influenced by vegetation height and coverage, compromising the accuracy of models in representing terrain elevation. In this study, we developed a digital terrain model for South America using a novel methodology to remove vegetation bias in the Copernicus DEM GLO-30 (COPDEM) model using machine learning, Global Ecosystem Dynamics Investigation (GEDI) elevation data, and multispectral remote sensing products. Our results indicate considerable improvements compared to COPDEM in representing terrain elevation, reducing average errors (BIAS) from 9.6 m to 1.5 m. Furthermore, we evaluated our product (ANADEM) by comparison with other global DEMs, obtaining more accurate results for different conditions of vegetation fraction cover and land use. As a publicly available and open-source dataset, ANADEM will play a crucial role in advancing studies that demand accurate terrain elevation representations at large scales.

Contextualizing willingness to pay for sustainable management of agroecosystem services in a rapidly transforming landscape: Insights from the interdunal wetlands of Medinipur Coastal Plain, India

Interdunal wetlands of the Medinipur coastal plain provide various agroecosystem services (AES). Local populace had been found to utilize these wetlands for subsistence livelihood since time immemorial. However, many of these wetlands have become degraded by extensive land use conversions along with increasing apathy among young farmers to continue wetland based traditional livelihood practices in the recent years. In this regard, the present study attempts to assess the willingness to pay (WTP) of the local wetland dependent populace towards restoration and management of the various AES of a regional interdunal wetland complex using contingent valuation (CV) method. The CV survey was conducted among 229 households from 14 villages associated to the wetland complex. Four Landsat images from 1990 to 2020 and several ancillary spatial datasets were analysed to detect the current as well as future status (2030) of land use covers using the artificial neural network algorithm. Results showed that socio-economic factors such as age, level of education, monthly income per person, ownership of wetlands, and availability of AES primarily determined the average WTP (US$ 0.30 per month) of surveyed households. Thus, the total economic value of the wetland complex, calculated as the aggregate WTP, was remarkably as low as US$ 11568.64 per year, thereby indicating towards lesser environmental awareness and widespread poverty among the respondents. This perilous condition is also manifested in the present and future projected LULC patterns from 1990 to 2030. If the same trend of mismanagement prevails in the imminent years, a drop of more than 50% in areal coverage of interdunal wetlands is anticipated. Based on the findings, it was suggested that the vicious cycle of ‘lesser awareness-low WTP-wetland loss-degrading provision of AES’ could only be replaced through a three-pronged approach comprising environmental education, technological dissemination, and legislative cum ecotourism interventions.

ABNet: An Aggregated Backbone Network Architecture for Fine Landcover Classification

High-precision landcover classification is a fundamental prerequisite for resource and environmental monitoring and land-use status surveys. Imbued with intricate spatial information and texture features, very high spatial resolution remote sensing images accentuate the divergence between features within the same category, thereby amplifying the complexity of landcover classification. Consequently, semantic segmentation models leveraging deep backbone networks have emerged as stalwarts in landcover classification tasks owing to their adeptness in feature representation. However, the classification efficacy of a solitary backbone network model fluctuates across diverse scenarios and datasets, posing a persistent challenge in the construction or selection of an appropriate backbone network for distinct classification tasks. To elevate the classification performance and bolster the generalization of semantic segmentation models, we propose a novel semantic segmentation network architecture, named the aggregated backbone network (ABNet), for the meticulous landcover classification. ABNet aggregates three prevailing backbone networks (ResNet, HRNet, and VoVNet), distinguished by significant structural disparities, using a same-stage fusion approach. Subsequently, it amalgamates these networks with the Deeplabv3+ head after integrating the convolutional block attention mechanism (CBAM). Notably, this amalgamation harmonizes distinct scale features extracted by the three backbone networks, thus enriching the model’s spatial contextual comprehension and expanding its receptive field, thereby facilitating more effective semantic feature extraction across different stages. The convolutional block attention mechanism primarily orchestrates channel adjustments and curtails redundant information within the aggregated feature layers. Ablation experiments demonstrate an enhancement of no less than 3% in the mean intersection over union (mIoU) of ABNet on both the LoveDA and GID15 datasets when compared with a single backbone network model. Furthermore, in contrast to seven classical or state-of-the-art models (UNet, FPN, PSPNet, DANet, CBNet, CCNet, and UPerNet), ABNet evinces excellent segmentation performance across the aforementioned datasets, underscoring the efficiency and robust generalization capabilities of the proposed approach.

ASSESSMENT OF THE QUALITY OF LAND IN THE SARATOV TRANS-VOLGA REGION WHEN INVOLVING UNUSED ARABLE LAND IN PRODUCTION

ASSESSMENT OF THE QUALITY OF LAND IN THE SARATOV TRANS-VOLGA REGION WHEN INVOLVING UNUSED ARABLE LAND IN PRODUCTION

Wilding cities for biodiversity and people: a transdisciplinary framework.

Accelerating urbanisation and associated lifestyle changes result in loss of biodiversity and diminished wellbeing of people through fewer direct interactions and experiences with nature. In this review, we propose the notion of urban wilding (the promotion of autonomous ecological processes that are independent of historical land-use conditions, with minimal direct human maintenance and planting interventions) and investigate its propensity to improve biodiversity and people-nature connections in cities. Through a large interdisciplinary synthesis, we explore the ecological mechanisms through which urban wilding can promote biodiversity in cities, investigate the attitudes and relations of city dwellers towards urban wild spaces, and discuss the integration of urban wilding into the fabric of cities and its governance. We show that favouring assembly spontaneity by reducing planting interventions, and functional spontaneity by limiting maintenance practices, can promote plant diversity and provide ecological resources for numerous organisms at habitat and city scales. These processes could reverse biotic homogenisation, but further studies are needed to understand the effects of wilding on invasive species and their consequences. From a socio-ecological perspective, the attitudes of city dwellers towards spontaneous vegetation are modulated by successional stages, with grassland and woodland stages preferred, but dense shrubby vegetation stages disliked. Wild spaces can diversify physical interactions with nature, and enrich multi-sensory, affective and cognitive experiences of nature in cities. However, some aspects of wild spaces can cause anxiety, feeling unsafe, and the perception of abandonment. These negative attitudes could be mitigated by subtle design and maintenance interventions. While nature has long been thought of as ornamental and instrumental in cities, urban wilding could help to develop relational and intrinsic values of nature in the fabric of cities. Wildness and its singular aesthetics should be combined with cultural norms, resident uses and urban functions to plan and design urban spatial configurations promoting human-non-human cohabitation. For urban wilding to be socially just and adapted to the needs of residents, its implementation should be backed by inclusive governance opening up discussion forums to residents and urban workers. Scientists can support these changes by collaborating with urban actors to design and experiment with new wild spaces promoting biodiversity and wellbeing of people in cities.

Automatic calibration of SWMM parameters based on multi-objective optimisation model

Abstract To address the issue of low accuracy and inefficiency in the traditional parameter calibration methods for the SWMM model, this paper constructs an automatic parameter calibration model based on multi-objective optimisation algorithms. Firstly, the Sobol method and GLUE method are utilised to determine sensitive parameters and their ranges, aiming to narrow down the solution space and expedite the model-solving speed. Secondly, the NSGA-3 multi-objective optimisation algorithm based on the Pareto theory is applied for the optimisation and calibration of sensitive parameter sets. The model is validated in the rainwater drainage system with independent runoff in a residential area in a northwestern city in China. The results show that parameters such as N-Imperv and KSlope are highly sensitive to the model output under the land-use conditions of the study area. The simulation accuracy of the multi-objective continuous optimisation algorithm is significantly better than that of the single-objective genetic algorithm. The simulation results of the SWMM model under multi-objective optimisation demonstrate a certain level of reliability and stability. The research findings can provide technical support for the automatic calibration of SWMM model parameters, accurate model simulation, and application.

Anthropogenic climate and land-use change drive short- and long-term biodiversity shifts across taxa

Climate change and habitat loss present serious threats to nature. Yet, due to a lack of historical land-use data, the potential for land-use change and baseline land-use conditions to interact with a changing climate to affect biodiversity remains largely unknown. Here, we use historical land use, climate data and species observation data to investigate the patterns and causes of biodiversity change in Great Britain. We show that anthropogenic climate change and land conversion have broadly led to increased richness, biotic homogenization and warmer-adapted communities of British birds, butterflies and plants over the long term (50+ years) and short term (20 years). Biodiversity change was found to be largely determined by baseline environmental conditions of land use and climate, especially over shorter timescales, suggesting that biodiversity change in recent periods could reflect an inertia derived from past environmental changes. Climate–land-use interactions were mostly related to long-term change in species richness and beta diversity across taxa. Semi-natural grasslands (in a broad sense, including meadows, pastures, lowland and upland heathlands and open wetlands) were associated with lower rates of biodiversity change, while their contribution to national-level biodiversity doubled over the long term. Our findings highlight the need to protect and restore natural and semi-natural habitats, alongside a fuller consideration of individual species’ requirements beyond simple measures of species richness in biodiversity management and policy.

Evaluating relocation behavior of establishments: Evidence for the short-term effects of COVID-19

Due to the significant effects of establishments’ relocations on travel patterns and land-use conditions, investigating establishments’ relocation behavior is an important issue. In recent years, many establishments closed or relocated because of a downturn economy, health concerns, interrupted supply chains, and work-from-home caused by the pandemic. Hence, this study aims to propose a modeling approach to assess and compare the relocation behavior of establishments before, during, and after the pandemic. Establishments’ relocation behavior is modeled in two steps: relocation decision and relocation action. The former provides insights into behavioral factors associated with establishment relocation and the latter models likelihood of spatial relocation choice. Using the data collected from the state of Tennessee, USA, the Random Forest classification approach is incorporated to model both steps, where the model validation results showed the promising accuracy of this modeling approach. Moreover, statistical analyses are applied to evaluate the differences between the spatial relocation choices throughout the time. Results showed that in post-Covid conditions, the importance of establishment characteristics on relocation decisions was reduced by half and relocations occurred more due to office profile and accessibility. Results of modeling relocation action indicated the high importance of accessibility, even though the attractiveness of accessibility was reduced by 20.9% in post-Covid analysis. The findings of this study enrich the knowledge on establishment relocation behavior and provide valuable information regarding the effect of the pandemic, which can be used in policy development and travel behavior modeling by urban and transportation planners.

Enhanced future vegetation growth with elevated carbon dioxide concentrations could increase fire activity

Many regions of the planet have experienced an increase in fire activity in recent decades. Although such increases are consistent with warming and drying under continued climate change, the driving mechanisms remain uncertain. Here, we investigate the effects of increasing atmospheric carbon dioxide concentrations on future fire activity using seven Earth system models. Centered on the time of carbon dioxide doubling, the multi-model mean percent change in fire carbon emissions is 66.4 ± 38.8% (versus 1850 carbon dioxide concentrations, under fixed 1850 land-use conditions). A substantial increase is associated with enhanced vegetation growth due to carbon dioxide biogeochemical impacts at 60.1 ± 46.9%. In contrast, carbon dioxide radiative impacts, including warming and drying, yield a negligible response of fire carbon emissions at 1.7 ± 9.4%. Although model representation of fire processes remains uncertain, our results show the importance of vegetation dynamics to future increases in fire activity under increasing carbon dioxide, with potentially important policy implications.

МЕХАНІЗМ ДЕРЖАВНОГО РЕГУЛЮВАННЯ ПРОЦЕСІВ ЗЕМЛЕКОРИСТУВАННЯ

The article examines the peculiarities of the mechanism of state regulation of land use processes. Groups of social, ecological and economic aspects have been studied. It is emphasized that the regulation of economic processes of land use is impossible without reliable information about the qualitative characteristics of each specific plot, its economic and biological fertility, because ignoring or incorrect assessment of its potential can negate the results of planning, which is one of the main functions of management.
 By the economic aspects of land use, we primarily understand transferability as a property of a land plot, expressed in its ability to be freely alienated or transferred from one person to another in the order of universal legal succession or in another way; forms of ownership and management characterizing legal issues of land use, as well as organizational and technological conditions of agricultural production; the value of land resources as a measure of materialized labor necessary to support sustainable and effective development of agricultural production.
 Selected aspects of land use regulation formed the basis of the structural diagram of the mechanism of state regulation of land use processes presented by us and allow not only to clarify its content, but also directly determine its structure.
 It was determined that in the conditions of market relations, an important place in the system of state regulation of land use began to be assigned to the cadastral assessment of land plots. The content of the use of the land resource potential of the territorial formation is given.
 In the regulation structure, special attention should be paid to the issue of comprehensive assessment of the effectiveness of the use of land resources and the resulting need for further development of the methodological base for the assessment of land use.
 The key link in the process of state regulation should be the evaluation of the efficiency of land use, which is based on a system of quantitative parameters for the evaluation of the efficiency of the use of land resources.
 Land owners are mainly municipal authorities, enterprises (legal entities), citizens (individuals) or their associations (cooperatives, commercial firms, etc.).
 The denationalization of land ownership and the introduction of private land ownership on this basis, the privatization of land, the introduction of paid land use fundamentally changed the structure and content of land relations in the conditions of village land use, changed the structure, content and principles of planning land resource formations.
 The effective organization of state regulation of economic processes of land use has a significant impact on the process of creating the necessary organizational, territorial, legal and social conditions for full involvement in turnover, increasing the return of each hectare of land while preserving or reproducing soil fertility.

Land Use Land Cover Change Detection and Future Forecasting in Ningxia, China: A Random Forest and ANN-Based Approach for Sustainable Development

The accurate tracking and prediction of Land Use Land Change monitoring and prediction precision or accuracy are urgent for technological development and practical ecology management. This objective is pursued by understanding of the changing patterns of LULC temporally and spatially in Ningxia, China, a semi-arid region experiencing desertification and over-rapid urbanization. Therefore, one of the main objectives of this work is prediction for the future trends within this field of research. This research utilized the MODIS data taken from the satellite Moderate Resolution Imaging Spectroradiometer through remote sensing and advanced machine learning algorithms. During 2003 to 2023, the random forest classifier was used to monitor the LULC change in Ningxia, passing to different stage and increasingly affluent cities. These surveys predict the possible scenarios, including the rapid increase in desertification, urbanization side and erosion of the areas for agriculture, forestry and water-covered. A merging approach based on cellular automata and artificial neural network employed with the purpose of typing the future condition of land use and land cover. This approach relies on calibration to study future operations that remain unaffected by peoples’ choice. The calibrated version could be done to become tightly related to the spatial variables that heavily shift in time. The altered model achieved a great accuracy of 85% similarly the maximum value of 0.96 for the Kappa coefficient, which indicates the discovery of the ANN. Deserts and town are a few of the surfaces that have grown under science. As a result, wild animals’ facilities and natural flora have deteriorated, lowering agricultural output. (1) According to the transition probability matrix, this could be as high as 28% from agricultural land to desert. (2) One of the findings from spatial analytical trend analysis that I mentioned above, is also detected in terms of a distinct rise accumulation just for the desert category with respect to all other LULC types combined. (3) Thus, further increases in desert and artificial land might be coupled with urbanization (e. g.) to climate change.

Energy-Saving Method of Basic Tillage and Soil and Design for Its Implementation

The article is devoted to the analysis of mechanization tools for mineral fertilizer application systems of enterprises of various forms of ownership, which can be used for implementation into the production process. This will allow us to further develop a machine design that would be able to fully meet the initial agrotechnical requirements for working in conditions of limited land use. We conducted a patent search using publicly available tools.

ОСНОВНЫЕ ОПТИМАЛЬНЫЕ ПАРАМЕТРЫ ПРИРОДНО- КЛИМАТИЧЕСКОГО ПОТЕНЦИАЛА, ОПРЕДЕЛЯЮЩИЕ УСЛОВИЯ СЕЛЬСКОХОЗЯЙСТВЕННОГО ЗЕМЛЕПОЛЬЗОВАНИЯ СЕВЕРО-КАВКАЗСКОГО ЭКОНОМИЧЕСКОГО РАЙОНА

The article examines the optimal parameters of the natural and climatic potential that determine the conditions of agricultural land use in the North Caucasus Economic Region in order to achieve the goals set for the future. The practical side of effective and intensive turnover of agricultural land and ways to improve them in real use have been worked out. Depending on the ratio of indicators, optimal parameters of the natural and climatic potential for the involvement and expedient exploitation of land are built. Inefficient lands and methods of their use due to the use of highly effective agrotechnical innovations are considered. The analysis of the investment climate, key risks and adaptation to modern conditions is carried out. The key positions constraining the elimination of a number of problems are formulated. This is due to the risk of slowing down investment attractiveness and competitive advantage, taking into account the global economic context.

Overview of Environmental Conditions from Land Use Changes in Pesisir Selatan

Land use planning is the use of land for certain purposes. One issue that may arise during land planning is whether the land is appropriate or suitable for a particular purpose. For local governments, it is very important to know the income potential that exists through land use planning. One of the benefits of writing this article is to get an overview of environmental conditions and the efforts of the Pesisir Selatan Regency government in environmental management. With the increase in population, quality of life, and community welfare, land is needed to meet various needs and facilities. However, the amount of land is relatively fixed, which causes problems in land use in rural and urban areas. This study investigates the conditions of Land Use, Land Conversion, and Potential in Pesisir Selatan Regency. This research produces several conclusions, namely 1) Land in Pesisir Selatan Regency is very suitable for plantation cultivation because of its condition; and 2) Pesisir Selatan Regency has a lot of potential for mining, coastal and marine cultivation, mangroves, and coral reefs.