Assess Land Use Research Articles

Plant Diversity in the Dynamic Mosaic Landscape of an Agricultural Heritage System: The Minabe-Tanabe Ume System

The Minabe-Tanabe Ume System in central Japan is defined as a Globally Important Agricultural Heritage System (GIAHS) by the United Nations Food and Agriculture Organization. This study examined relationships between parcel-level plant diversity and land use, management, and development in traditional sloped Ume (Japanese apricot; Prunus mume) orchards and adjoining level orchards recently developed through large-scale cut-fill land development. We constructed and overlaid past (1974) and present (2015) digital land-use maps to assess land use and topography. We conducted field vegetation surveys in land parcels with different development and management histories. Although 249 ha (4.6% of the total 2015 area) were developed using cut-fill methods, 5148 ha remain a traditional orchard surrounded by coppice forests. Vegetation surveys and a two-way indicator species analysis revealed that traditional orchards had more native species and a higher plant diversity index. Cut-fill orchards contained a higher proportion of alien species; however, the degree depended on parcel history and management. Overall, this area remains a dynamic mosaic landscape containing a core of long-standing Ume orchards. We suggest that biodiversity conservation in this area should focus on conservation measures such as indirect land-use regulations, including some acceptable landform transformations, to promote continued farming of this ecologically important area.

Assessment of sustainable land use: linking land management practices to sustainable land use indicators

ABSTRACT Land degradation threatens food production especially in smallholder farming systems predominant in sub-Saharan Africa. Monitoring the effects of agricultural land uses is critical to guide sustainable intensification (SI). There are various indicators of sustainable land use (SLU), but conventional methods to quantify their metrics are complex and difficult to deploy for rapid and large-scale assessments. Considering that SLU indicators are dependent on agricultural practices, which can be rapidly identified and quantified, we propose a framework for SLU assessment that includes indirect quantifications of prioritized indicators (crop productivity, soil organic carbon (SOC), acidification, erosion, nutrient balance) using agricultural practices; and a SLU index derived from the integration of these indicators. The application of the framework to a case study, consisting of 1319 farm plots in Tanzania, reveals that SOC and N balance were the main contributors to the SLU gap. Only 2.2% of the plots qualified as being used sustainably. The framework proved to be sensitive to practices commonly used by farmers, thus providing an opportunity to identify practices needed to revert land degradation. Further application of the framework as a decision-support tool can enhance the efficiency of SI investments, by targeting practices which effectively enhance food production and preserve land.

Assessment of land use and land cover changes in Kenya’s Mt. Elgon forest ecosystem

AbstractCurrent land‐use trends in Kenya's montane forest ecosystems show that land uses are changing fast due to natural and anthropogenic factors and these changes could have devastating effects on the environment. One such montane forest is the transboundary Mt. Elgon forest located in western Kenya. This study analysed trends in land use–land cover changes in Mt. Elgon forest ecosystem over the last 45 years. Landsat imageries downloaded from the United States Geological Survey archives were used to assess land use–land cover changes between 1973 and 2019 by applying supervised classification using Arc GIS 10.5. The IDRISI Selva 17.0 was used to calculate area under different land uses and generate change maps. The major Land Use–Land Cover (LULC) classified were mixed farming, natural forests, planted forests, bamboo forest, fallow land, tea plantation. The landsat images had an average overall classification accuracy of 87.12% and kappa coefficient (K) of 0.84. The kappa coefficient was rated as substantial and the classified images qualified for further analysis. Results established that there was an 18% decline in the natural forest cover between 1977 and 2019. There was a similar decline of 15.19% in bamboo forest cover. Plantation forests established in the 1990's also showed a 15.6% decline between 1999 and 2019. There was, however, a 29% increase in mixed farming, a 10% increase in fallow land and a 0.13% increase in tea plantations. These changes in land uses and land cover call for an urgent need to develop sustainable management plans to protect and conserve the Mt. Elgon forest ecosystem. Sustainable land management strategies to be used in the future may include education on the significance of the forest ecosystem, community participation in sustainable utilisation of forest eco‐services and the introduction of sustainable alternative sources of livelihoods, such as bee farming.

Toward regional hazard risk assessment: a method to geospatially inventory critical coastal infrastructure applied to the Caribbean

Hurricanes and sea level rise pose significant threats to infrastructure and critical services (e.g., air and sea travel, water treatment), and can hinder sustainable development of major economic sectors (e.g., tourism, agriculture, and international commerce). Planning for a disaster-resilient future requires high-resolution, standardized data. However, few standardized approaches exist for identifying, inventorying, and quantifying infrastructure lands at risk from natural hazards. This research presents a cost effective, standardized and replicable method to geospatially inventory critical coastal infrastructure land use and components, for use in risk assessments or other regional analyses. While traditional approaches to geospatial inventorying rely on remote sensing or techniques, such as object-based image analysis (OBIA) to estimate land use, the current approach utilizes widely available satellite imagery and a “standard operating procedure” that guides individual mappers through the process, ensuring replicability and confidence. As a pilot study to develop an approach that can be replicated for other regions, this manuscript focuses on the Caribbean. Small islands rely heavily on a small number of critical coastal infrastructure (airports, seaports, power plants, water and wastewater treatment facilities) and climate related hazards threaten sustainable development and economic growth. The Caribbean is a large and diverse area, and gaps exist between countries in the resources required for planning but much of the region lacks a comprehensive inventory of the land, infrastructure, and assets at risk. Identifying and prioritizing infrastructure at risk is the first step towards preserving the region’s economy and planning for a disaster resilient future. This manuscript uses high resolution satellite imagery to identify and geo-spatially classify critical infrastructure land area and assets, such as structures, equipment, and impervious surfaces. We identified 386 critical coastal infrastructure facilities across 28 Caribbean nations/territories, with over 19,000 ha of coastal land dedicated to critical infrastructure. The approach establishes a new standard for the creation of geospatial data to assess land use change, risk, and other research questions suitable for the regional scale, but with sufficient resolution such that individual facilities can utilize the data for local-scale analysis.

Proposing a set of indicators to evaluate the environmental efficiency of coastal land use towards sustainable development

The management of coastal land in Vietnam in recent years still has many shortcomings and limitations, such as the planning and management of construction investment according to planning has not meet development needs; there is a lack of public space for the community due to overwhelming approved coastal projects; soil environmental pollution is increasingly serious due to the lack of an effective mechanism for using and conserving the soil environment. Currently, Vietnam is applying many sets of indicators related to environmental performance assessment at national and sector levels, including several indicators related to soil environmental assessment. However, there is still no specific set of indicators on environmental performance assessment from sustainable coastal land use. Therefore, to improve the efficiency of coastal land use and well implement environmental objectives, it is necessary to develop a set of indicators on environmental efficiency assessment of coastal land use in the direction of sustainable development.

Assessing land use change in the context of climate change and proposing solutions: Case study in Gia Lai province, Vietnam

Assessing land use change in the context of climate change and proposing solutions: Case study in Gia Lai province, Vietnam

Using geographical information systems to measure accessibility of green areas in the urban center of Nevşehir, Turkey

The problem of how to ensure the accessibility of green areas is a significant issue for urban planners and leaders. Every segment of society should have access to green areas. The 2015 United Nations General Assembly Resolution indicated the necessity of ensuring that children, older adults, and disabled people have equal access to green areas.The Accessible Natural Greenspace Standard (ANGSt) was implemented in England in response to the United Nations 2015 Resolution. ANGSt states that housing developments needed to have a green space within 300 m in order to be identified as having adequate access to green space. Almost at the same time, Turkey has also identified increasing access to urban green spaces as a priority, which can be seen most directly in the 2014 Turkish Regulation on Spatial Planning. This document states that housing zones need to have a green space within 500 m to ensure that urban residents have sufficient access to green space. However, no specific suggestions or procedures have been provided on how to measure the accessibility of a city’s green areas. To fill this gap, this study developed a method for measuring the accessibility of green areas according to the standards outlined in the 2014 Turkish Regulation on Spatial Planning as well as the standards described in England’s ANGSt regulations. The accessibility of green areas in Nevşehir, Turkey was assessed using this method to demonstrate its utility.The method of Comber et al. (2008) and the grid method used in the GEOSTAT procedure were adapted for this study to assess the accessibility of green areas in Nevşehir, Turkey. In order to conduct this study, ArcGIS was used and analyses were performed grid method. As a result, this study identified housing zones that do not have access to a green space, both according to Turkish standards as well as English standards. Furthermore, this study also identified many green spaces that are not within an accessible distance from residential areas, indicating that a significant proportion of Nevşehir’s green spaces are being under-utilized.This study reveals that thus far, the planning approaches used in Nevşehir have not taken access to green spaces into consideration, particularly along the city’s borders. The center of the city has much more access to green areas, but it has the inverse problem of having green spaces that lack nearby residential areas, so they are not adequately utilized. This situation most likely arose due to reliance on the grid meter per capita standard for assessing green space rather than basing planning decisions on accessibility standards. Thus, this study provides important insights into Nevşehir’s current land use distribution that can be used to shape the future of urban planning in Nevşehir, while also providing a method for assessing land use distribution that can be used in a wide range of contexts to evaluate access to green spaces.

Land Use and Land Cover Change Assessment in the Context of Flood Hazard in Lagos State, Nigeria

Incessant flooding is a major hazard in Lagos State, Nigeria, occurring concurrently with increased urbanization and urban expansion rate. Consequently, there is a need for an assessment of Land Use and Land Cover (LULC) changes over time in the context of flood hazard mapping to evaluate the possible causes of flood increment in the State. Four major land cover types (water, wetland, vegetation, and developed) were mapped and analyzed over 35 years in the study area. We introduced a map-matrix-based, post-classification LULC change detection method to estimate multi-year land cover changes between 1986 and 2000, 2000 and 2016, 2016 and 2020, and 1986 and 2020. Seven criteria were identified as potential causative factors responsible for the increasing flood hazards in the study area. Their weights were estimated using a combined (hybrid) Analytical Hierarchy Process (AHP) and Shannon Entropy weighting method. The resulting flood hazard categories were very high, high, moderate, low, and very low hazard levels. Analysis of the LULC change in the context of flood hazard suggests that most changes in LULC result in the conversion of wetland areas into developed areas and unplanned development in very high to moderate flood hazard zones. There was a 69% decrease in wetland and 94% increase in the developed area during the 35 years. While wetland was a primary land cover type in 1986, it became the least land cover type in 2020. These LULC changes could be responsible for the rise in flooding in the State.

Assessing Land Use and Land Cover Change and Farmers’ Perceptions of Deforestation and Land Degradation in South-West Côte d’Ivoire, West Africa

Deforestation and land degradation remain two major economic and environmental threats in Côte d’Ivoire. This study assessed land use and land cover (LULC) change and farmers’ perceptions of the drivers and effects of deforestation and land degradation in south-western Côte d’Ivoire. We used remotely sensed data to determine LULC change trends, and a household survey to collect farmers’ perceptions of deforestation and land degradation. A total of 411 households were interviewed using a structured questionnaire and the focus group discussions involved 25 farmers. Landsat image analysis reported a drastic LULC change and a conversion of forestlands into agriculture from 1987 to 2015 at a rate of 1.44%/year and 3.44%/year for dense forests and degraded forests, respectively. The household survey revealed that the major causes of deforestation perceived by farmers included population growth (79.3%), extensive agriculture (72.9%), migration (54.2%) and logging (47.7%). Land degradation evolved, from a shortened fallow period (46.7%) and an inappropriate application of inputs (31.4%). The perceived major effects linked to deforestation encompassed land degradation (70.6%), loss of biodiversity (63.8%), global warming (56.9%) and loss of livelihood assets (54.3%). Therefore, this study recommends participatory landscape planning, reforestation and capacity building of stakeholders for sustainable intensification of the production systems to reduce LULC challenges for enhanced productive and protective functions of remaining forests.

Ecological impact assessment of land use in eco-industrial park based on life cycle assessment: A case study of Nanchang High-tech development zone in China

As the main unit of developing a circular economy, and an important way of realizing the ecological industry (eco-industry), the eco-industrial park (EIP) is the way forwards for industrial park development in China. As land is the carrier of industrial parks, the ecological effects brought about by its use patterns, and the evolution process play an important role in the sustainable park development. Based on 3S technology, using Nanchang High-tech Development Zone as a case-study, the life cycle assessment (LCA) is used to quantitatively analyze the ecological impact of land use change, and the characteristics of its evolution or laws at different stages of the EIP life cycle. The results showed the following: (1) In the life cycle development period, the annual average ecological effect was −2.15 × 104 CNY, and during the mature life cycle period, the value rose to −2.01 × 104 CNY, an increase of 6.44%; (2) During the mature period, as a result of changes in quantity and quality, the cultivated, forest, and unutilized land types, had all increased in both total value and annual average value of the ecological effect, showing an improvement in the overall ecological environment of the park. These three types of land were the main contributors to the improvement of the ecological effect. The contribution size was: forest land > cultivated land > unutilized land. On the contrary, the construction land and grassland showed negative ecological effects compared with the previous life cycle stage. Construction land was the main contributor to the decline in ecological park quality, and its negative ecological effect increased by 1.66 times; (3) In the two life cycle stages, amongst the ecological effects caused by the transformation of various land usees, only the conversion to forest land brought significant ecological benefits. Others showed either a certain degree of improvement, or the accumulation of negativizes in ecological effects. Therefore, the EIP generally showed the state of ecological destruction; (4) Finally, there is a relevant discussion about the applicability, scientificity, and innovation of the LCA applied to evaluate the ecological effects of industrial land.

Analysis of localized water chemistry and land use drivers of macroinvertebrate community structure in the Upper Ohio Watershed using multivariate modelling and ordination techniques.

An assessment of land use, water chemistry and macroinvertebrate community data was performed at 20 stream sites in southwestern Pennsylvania and West Virginia’s Northern Panhandle. Project sites were located on streams spanning six different watersheds from a variety of catchment sizes and land use characteristics. Macroinvertebrate community characteristics were analyzed using ordination techniques including Nonmetric Multidimensional Scaling (NMS) and hierarchical agglomerative cluster analysis, and predictive effects of ambient physicochemical stream conditions and watershed land use were evaluated using hierarchical modelling via Integrated Nested Laplace Approximation (INLA). Ordinations showed watershed development, shredder biomass, ambient annual turbidity, and riparian forest cover as primary drivers of dissimilarity between macroinvertebrate communities. INLA models identified significant negative relationships between macroinvertebrate community diversity and ambient annual conductivity, turbidity and watershed development. Results support regionwide water quality assessments citing conductivity and sedimentation as prevailing in-stream stressors, as well as land use characteristics as determining factors of water quality, even at localized scales.

Assessing Land Use Planning Tools to Mitigate Odour and Lighting Nuisance Related to Cannabis Production

Cannabis production has expanded significantly across southern Ontario with the legalisation of theindustry. Much of this expansion has occurred within the rural countryside, through the utilisation of existinggreenhouse infrastructure. While the growth of this sector provides economic benefits to rural communities, complaints from adjacent residents related to lighting and odour issues are common and mitigation of such issues is complex. Land use planning policies have been established across southern Ontario to manage the development of cannabis greenhouses; however, policies vary by region and countyand the appropriateness of these policies have not been tested. This study seeks to analyse municipalplanning policies that regulate cannabis production and understand the impacts of these policies on sector,adjacent land owners and rural communities. Planning policies will be analysed at the municipal, regional orcounty level, with the creation of a database to highlight consistency and differences between communities. Case studies will be utilised to gain better insights into the challenges and opportunities related to cannabis production and planning mitigation. This presentation will provide a summary of current research findings, including highlights of a municipal scan of zoning by-law policies and informalinsights into policy appeals in southern Ontario.

Legacy of historic land cover changes on sediment provenance tracked with isotopic tracers in a Mediterranean agroforestry catchment

A Compound Specific Stable Isotope (CSSI) sediment tracing approach is applied for the first time in a Mediterranean mountain agroforestry catchment subjected to intense land use changes in the past decades. Many Mediterranean mountain environments underwent conversion of rangelands into croplands during the previous centuries to increase agricultural production. Converted land has increased the risk of erosion and in some cases has led to loss of the entire fertile topsoil. After land abandonment the process was gradually reversed during the middle of the 20th century, allowing the recovery of natural land cover and reduction of soil erosion rates.The 13C abundance of long chain fatty acids was used as tracer to assess the contribution of soil under different vegetation covers in complex landscapes subjected to land use changes after land abandonment in a medium-sized Mediterranean catchment. A Bayesian mixing model (MixSIAR) was used for estimating the contribution of different land use types to suspended sediments. To this purpose, composite samples were collected over the four main land covers existing in the study area: cropland, Mediterranean forest, pine forest, scrubland, and two main geomorphic elements: highly disturbed areas such as exposed subsoil and channel banks. Suspended sediment traps were installed at three locations in the catchment to assess the variability of source contributions from the headwaters to the outlet of the catchment. At every sampling point three replicating traps integrated the suspended sediment per climatologic season during a one hydrological year. The fatty acids (FAs) content was significantly higher at the catchment outlet than at the headwaters. The δ13C signatures of the FAs were successful in discriminating between Mediterranean forest, scrubland, pine forest and both geomorphic elements. Overall, the model identified agricultural land as the largest contributing source for most of the sampled seasons. The inclusion of prior information with different informativeness produced variations in the model outputs and could represent an advantage as much as a disadvantage if priors are not used with caution and supported by robust evidence. The results of this study suggest that CSSI tracers are needed to correctly assess land use related sediment sources, while channel bank and subsoil contributions require geochemical tracers. The high agricultural apportionment despite its small coverage (16%) point out to the impact of human activities and the agriculture cycle on soil loss in these mountain agroforestry systems.

Decision-making algorithm based on the results of systematic monitoring of forested landscapes in the subsoil use territories of the Urals

Relevance of the study. Currently, information obtained during monitoring, including monitoring of forest lands, is of particular importance for making informed decisions on the development of natural potential. A feature of these works today is the lack of combination of data collection procedures, their processing with models of structural elements of forest lands, which requires a solution to the problem under consideration. The aim is to form, according to the results of system monitoring, a system of interconnected decision-making algorithms in the field of forest land use in industrial regions. The methodology for the formation of a system of interrelated decision-making algorithms in the field of forest land use in industrial regions is based on the use of mathematical models of natural objects of forest ecosystems, natural phenomena in them and forest-forming processes, on the procedures of a comprehensive assessment and optimization of forest land use in industrial regions in accordance with current provisions of the concept of environmentally sustainable development of territories. Results and their application. The algorithms for decision-making in the use of forest lands based on the results of system monitoring are considered: substantiation of strategic indicators of sustainable development of forest lands in industrial regions in the face of modern challenges and risks; comprehensive ecological and economic assessment of the natural resource potential of forest lands; determination of leeways of permissible use of forest lands in industrial regions in specific climatic and socio-economic conditions; coordination of individual interests of land users on forest lands with public preferences for the development of industrial regions; multi-criteria optimization of the use of forest lands in industrial regions. The main principles of forecasting the parameters of a comprehensive assessment of forest lands, the use of the indicator of consumption of net primary products of forest ecosystems, the sequence of greening the economy of the use of forest lands in industrial regions, justification of concessions to the extreme values of particular criteria in multi-criteria optimization are given. The proposed additional indicators of sustainable development of forest areas in the Middle Urals, the results of calculations on the change in the natural resource potential of forest lands in the subsoil use area are presented; the substantiation of the multicriteria optimization of the use of raw material resources of forest lands is given. Conclusions. The proposed decision-making algorithms in the field of systemic monitoring of forest lands are intellectual support for users in the analysis of information in the field of land relations. They provide a substantive dialogue that allows you to form the necessary information in a user-friendly form, adjust the data processing process and make decisions.

Assessing land use and land cover change in Los Molinos reservoir watershed and the effect on the reservoir water quality

Understanding and modelling land use and land cover (LULC) change have become one of the major subjects of interest for environmental management due to the negative effects that human activities generate on the normal functioning and dynamics of freshwater resources. Remote sensing and geographic information systems (GIS) are essential tools for assessing the drivers that cause LULC change and its relationship with lake and reservoir water quality. The objective of this study was to assess the spatial and temporal dynamics of LULC change in the watershed of Los Molinos reservoir (Argentina), and to investigate its relationship with the reservoir's water quality. Four Landsat imagery was used to analyse the LULC change in the studied watershed and in different buffer zones from 1990 to 2020. Further, the Normalized Difference Vegetation Index (NDVI) derived from a MODIS time-series dataset (2001–2020) was used to explain the effects of LULC change on the status of the reservoir. Results showed that the most significant LULC change started two decades ago and it has intensified during the last ten years. This change is related to the intensification of agriculture activities, and to the increasing conversion into urban areas, mainly on the shores of Los Molinos reservoir. During the period 2010–2020, urbanization located in the 1 km buffer zone defined from the shore of the reservoir increased at an annual rate of 18.02%. The degradation trend of LULC in Los Molinos watershed significantly contributed to the degradation of water quality of the reservoir. This was corroborated by analysing the MODIS NDVI time-series, which showed that since 2014 the NDVI trend-line presented an increasing behaviour and extreme values of NDVI, related to algal blooms, were more frequently observed.

Spatiotemporal assessment of land use/land cover change and associated carbon emissions and uptake in the Mekong River Basin

Land use and land cover (LULC) change caused by human activities is a major source of anthropogenic carbon emissions and a driver of climate change. The Mekong Region is highly dynamic, experiencing extensive LULC change in recent decades. This study provides a spatially and temporally continuous estimate of LULC change for the Mekong River Basin for 2001–2019 using time series analysis of MODIS data coupled with a spatiotemporal carbon bookkeeping model to track carbon losses and recovery. The LULC change product has an overall accuracy of 74.4 ± 1.9% (82.1 ± 1.7% after consolidating tree-dominated classes), including an increase of 5.6% after combining with existing MODIS products (referred to as the M-CCDC process). Two of the largest components of LULC change in the region are the establishment of plantations and agricultural expansion, which were estimated to be 33,617 ± 7342 km2 and 14,915 ± 4682 km2 between 2003 and 2014. We found that 82% of the deforested area was converted to tree plantations. Among all the newly added plantations, 86% replaced natural forests and 12% replaced agricultural land. In addition, existing maps of annual tree canopy cover (TCC) were used to assess forest disturbances that do not result in LULC conversions. The M-CCDC results combined with the forest disturbances derived from TCC maps were coupled to a spatiotemporal carbon bookkeeping model to estimate carbon emissions and uptake. Carbon emissions were 72.9 ± 6.2 Tg C yr−1 during 2001–2017; emissions increase to 102.8 ± 8.6 Tg C yr−1 if including carbon not yet released to the atmosphere in the form of decomposing slash and wood products. Carbon uptake for the same period was −35.5 ± 4.9 Tg C yr−1, with carbon uptake from new plantations offsetting almost half of the emissions from deforestation in this area. Assessment of post-deforestation land use is crucial for quantifying the short- and longer- term carbon consequences of LULC change.

Agricultural activities compromise ecosystem health and functioning of rivers: Insights from multivariate and multimetric analyses of macroinvertebrate assemblages.

Agricultural activities often lead to nutrient enrichment and habitat modification in rivers, possibly altering macroinvertebrate assemblages and hence ecosystem functioning. For the sake of environmental management and conservation, therefore, assessing the impacts of agricultural activities becomes indispensable, especially when these activities are predicted to be intensified in the future. In this study, the plain river network in the Lake Chaohu Basin was chosen to examine how agricultural activities influence the functioning of rivers by assessing land use, water quality, habitat condition and macroinvertebrate assemblages, followed by calculating the macroinvertebrate-based multimetric index (MMI) to indicate overall ecosystem health of the rivers. We found that agricultural activities lowered the diversity of macroinvertebrates (e.g. total number of taxa and Simpson index) primarily due to elevated ammonium concentrations in water and reduced microhabitat types, thereby impairing the habitat integrity and nutrient cycling of rivers. The macroinvertebrate-based MMI was positively correlated with increasing habitat quality but negatively with increasing nutrient concentrations, suggesting its high reliability for indicating the impacts of agricultural activities, which was further substantiated by classification and regression tree (CART) analysis. We recommend analyzing macroinvertebrate assemblages using both multivariate and multimetric approaches to offer a more comprehensive evaluation of the impacts of agricultural activities on ecosystem health. Some environmental (CODMn, NH4+-N and PO43--P) and biological parameters (total number of taxa), however, can be used as good proxies for MMI, when time and resources for gathering information to develop MMI are limited.

Response of local temperature variation to land cover and land use intensity changes in China over the last 30 years

In addition to land cover change (LCC), land use intensity change (LUIC) is another dominant pathway through which anthropogenic activities influence regional climate. Although the climatic effects of LCC have been investigated extensively, little is currently known about the effects of LUIC. In this study, we assess land use and cover change in China over the last three decades in terms of LCC and LUIC and investigate their climatic effects using the observation minus reanalysis method. Results indicate that nearly half of the stations have experienced LUIC, and the climatic response of these stations exhibit different or even opposite signals compared to those that have experienced LCC. With regard to LCC, it is found that urbanized stations generally exert a warming effect on local temperatures, whereas cropland expansion is likely to introduce a cooling effect. In the case of LUIC, the present study demonstrates that the intensification of grassland tends to lead to warming because of the decreased albedo. However, a cooling effect from the enhanced evapotranspiration (ET) dominates local temperature variations in intensified cropland stations. The absence of correlations between albedo/ET and land management changes in urban stations illustrates the inherent complexity of local climate change. The findings of the present study provide a deeper understanding of land–atmospheric interactions and could guide future land-use planning and management to achieve potential climatic benefits.

Suitability assessment of urban land use in Dalian, China using PNN and GIS

The suitability assessment of land use is crucial to avoid wasting land resources. However, the traditional methods with subjective weights are prone to reduce the reasonability and reliability of assessment. For filling this knowledge gap, the probability neural network (PNN) coupled with GIS was adopted to evaluate the land use suitability in this paper. According to the applications of the urban land resource, the land use was divided into three types (resident, industry and ecological reserve). Thus, the three different assessment criteria systems were built for the three land use types. The result of residential land use indicated that the most suitable, suitable and normal suitable residential land were 401, 272 and 12,406 km2 and mainly located in Changhai, Lvshun and Pulandian accordingly. The most suitable land for industry was in Ganjingzi, Jinzhou and Wafangdian and accounted for 22% of the total area. While the most suitable land for ecological reserve was in Pulandian and Zhuanghe with the area of 1967 km2. The results indicated that the south of Dalian was suitable for the residential land use, north of Dalian was suitable for the ecological land use and the central was suitable for industrial land use. The results were coincided to the actual spatial distribution of land use. The proposed PNN coupled with GIS assessment method in suitability of land use is conducted to provide a more reasonable assessment result that can be used by managers and regulators.

Identification of Dominant Warm-Season Latent Heat Flux Patterns in the Lower Mississippi River Alluvial Valley

Warm-season precipitation in the Lower Mississippi River Alluvial Valley (LMRAV) is heavily dominated by the rates of evapotranspiration and surface heat fluxes and is a primary water resource for agriculture. However, the stochastic nature of LMRAV warm-season thunderstorms makes precipitation forecasts challenging. The Weather Research and Forecasting Hydrologic (WRF-Hydro) model, coupled with the multi-parameter Noah land surface (Noah-MP) model, has improved estimates of important warm-season precipitation process. Given the widespread agriculture and dominance of crop and forested landscapes over the region, proper assessment of land use / land cover (LULC) is critical in predicting warm-season precipitation patterns. The objective of this study is to quantify simulated latent heat flux sensitivity (important for warm-season precipitation) to temporally updated LULC datasets. Both the model default and annually updated LULC conditions were used to initialize a 16-year WRF-Hydro simulation from which warm-season latent heat flux estimates were obtained. Annual root mean square difference was computed at each gridpoint. Cluster analysis preprocessed with kernel principal component analysis was used to identify spatial RMSD structures that quantified sensitivity to updated LULC conditions. Results showed the largest impacts occurred directly in the LMRAV and for points slightly east and revealed a meteorological link between these regions.