Geotechnology on the spatial analysis of land use and vegetation changes in natural protected areas of the State of Mexico (2011-2021)

Quantifying the relative impacts of climate and human activities on vegetation changes at the regional scale

Challenges in the management of urban natural protected area systems and the conservation of ecosystem services in Guadalajara and Monterrey, Mexico

Para conocer el estado de conservación del Parque Nacional Nevado de Toluca (PNNT), se analizaron los cambios en el uso del suelo y vegetación ocurridos entre 1972 y el 2000. Para ello fue preciso obtener cartografía digital mediante procesos de digitalización y fotointerpretación. Los mapas obtenidos se basaron en el sistema de clasificación del INEGI, serie 1. La aplicación de un sistema de información geográfica (SIG) permitió obtener la densidad de la cobertura forestal y analizar el cambio de uso de suelo y vegetación, identificando los procesos de disminución y/o incremento en la densidad de las zonas forestales. En el periodo estudiado, poco más de 9 700 ha de bosques de pino, latifoliadas u oyamel, sufrieron pérdidas de densidad, esto representó 20% de la superficie del área natural protegida. Las zonas boscosas que mostraron incrementos apenas alcanzaron 4 800 ha. El enfoque metodológico adoptado resultó especialmente válido para obtener información detallada y con un alto nivel de precisión. Dicha información constituye un punto de partida para estudios a profundidad del parque nacional.

Photo-interpretation and diachronic analysis of land use and vegetation changes in the Baztan Valley (Navarre, Spain) between 1927 and 2019

The article presents the results of suitability analysis of land use records of agricultural and forest land from the Slovenian ministry responsible for agriculture, for the purpose of land use change monitoring in Slovenia. To date, these data are the only systematically gathered data concerning land use in the country. For qualitative land use change detection, the metadata of land use datasets are of crucial importance. In the article, the changing criteria for land use data acquisition of agricultural and forest land are exposed. For the case of the Pomurska Statistical Region, the analysis of land use change has been conducted based on land use data of the agricultural ministry in the period 2002–2011. The main objective has been to provide the basic information on the quality of used datasets in order to assist the critical and correct interpretation and use of land use data of the agricultural sector.

This study presents an in-depth analysis of land use and land cover change on the Kerch Peninsula over a period spanning three decades. Convolutional neural networks were employed in conjunction with satellite imagery analysis to map and quantify the changes in land use and cover. This revealed significant trends and transformations within the peninsula’s landscape. The analysis revealed a notable increase in urban expansion, particularly at the expense of natural ecosystems. Furthermore, there was a notable reversion of agricultural lands to grasslands, driven by economic downturns and reduced agricultural activity. These land cover changes underscore the urgency of implementing sustainable land management policies. The study recommends the establishment of conservation easements to protect remaining natural ecosystems, the initiation of reforestation programs to restore degraded lands, and the development of comprehensive water management strategies to address the peninsula’s hydrological challenges. Furthermore, the study underscores the pivotal importance of integrating change analysis and predictive modeling to anticipate future land cover scenarios and inform effective land management strategies. The model developed through this research, which employs advanced remote sensing and GIS technologies, provides a robust framework for understanding and managing land use and land cover change. This model can serve as a reference for similar regions globally, offering insights that can inform sustainable land use practices and policy decisions. The findings of this study have implications that extend beyond the Kerch Peninsula. They provide insights that can inform the management of land use changes and the conservation of natural landscapes in regions facing comparable socio-economic and environmental challenges.

O objetivo deste trabalho foi analisar o comportamento hidrológico em três sub-bacias da bacia hidrográfica do rio Carapá, localizadas no Departamento de Canindeyú, Paraguai em 1985, 1999 e 2007, através de análise multitemporal do uso do solo e análise da resposta hidrológica pelo método de Curva Número com ênfase no parâmetro de Coeficiente de escoamento superficial (CE). A metodologia de estudo foi dividida em duas etapas: classificação dos usos do solo e análise das mudanças da vegetação nativa e análise das classes geradas com adição de tipologias de solos para gerar os parâmetros hidrológicos nas três condições de umidade antecedente: normal (NII), seco (NI) e próximo da saturação (NIII). Os resultados indicaram diminuição da cobertura florestal nas três sub-bacias. Das três, o coeficiente de escoamento superficial nas três situações de umidade antecedente da sub-bacia 49 no período de 1985 e 1999 foi a mais alta (NI=6,42; NII=30,88; NIII=57,86) e a que indica maior possibilidade de degradação. No período de 2007, o coeficiente de escoamento superficial nas três situações de umidade antecedente da sub-bacia 01 foi a mais alta (NI=17,03; NII=45,18; NIII=69,32), indicando maior possibilidade de degradação na sub-bacia por conta da ação da erosão hídrica.Palavras-chave: Bacia hidrográfica; análise multitemporal; curva número; escoamento superficial. AbstractAnalysis of hydrologic characteristics of three sub-basins of Carapa River basin (Canindeyú, Paraguay) in relation to changes of plant cover. The objective of this study was to analyze the hydrological behavior in three sub-basins of the river basin, Carapa, located in the Department of Canindeyú, Paraguay in 1985, 1999 and 2007 through multitemporal analysis of land use and hydrologic response analysis method Curve Number with emphasis on parameter runoff coefficient (EC). The methodology was divided into two steps: classification of land use and analysis of changes in vegetation and analysis of the generated classes with the addition of soil types to generate the hydrological parameters in the three antecedent moisture conditions: normal (NII) cleaning (NI) and close to saturation (NIII). The results showed decrease in forest cover in the three sub-basins. From the three parameters, the runoff coefficient in three different moisture history of the sub-basin 49 between 1985 and 1999 was the highest (NI = 6.42, NII = 30.88, NIII = 57.86) and indicates a higher possibility of degradation. During 2007, the runoff coefficient in three different moisture history of the sub-basin 01 was the highest (NI = 17.03, NII = 45.18, NIII = 69.32), indicating a greater possibility of degradation the sub-basin due to the action of water erosion.Keywords: Hydrographic basin; multitemporal analysis; curve number; runoff.

Land use directly reflects degree of human development and utilization of land. Intensity analysis of land use is a quantitative method to analyze land use changes. In this paper, land use changes in Tianjin were studied using Thematic Mapper (TM) remote sensing images in 1995, 2000, 2005, 2010 and Operational Land Imager (OLI) remote sensing image in 2015. Land use information was extracted using decision tree classification method based on CART (Classification and Regression Trees) algorithm. This paper introduced land use intensity analysis to analyze its change intensity and stationarity, respectively at interval, category and transition levels. Based on the theory, new models were developed in the transition level to analyze land use change pattern. The analysis quantifies the contribution of a certain land categories to land use change during a specific time interval. The change of land use during 1995–2015 indicated that Tianjin experienced rapid urban development with the area of urban land increased by about 7.5%. This study provided a reference for the sustainable development of land use in Tianjin.

The paper aims to define a territorial analysis model for land use changes in multifunctional areas (MF) located near Florence in Tuscany region. Starting from existing project, Spatial Multicriteria Decision Analysis has been used with the aim of multifunctional degree definition of case study areas. Later land use changes have been performed by Artificial Neural Network model: using multitemporal analysis of land use, a non linear model Multi Layer Perceptron (MLP) neural network has been used in order to generate transition rules of land use and potential transition maps. Final step has generated a map of vulnerability to changes in MF areas.

Aquaculture is currently one of the fastest growing food production systems globally, and shrimp is considered one of the most highly valued products. Our study area is the lower Jaguaribe River sub-basin (LJRSB), located in the northeastern part of Ceará in Brazil. The aquaculture activity in this area began in the early 1990s and is currently one of the largest shrimp producers in Brazil. This study generated a spatial-temporal analysis of vegetation index and land use and land cover (LULC) using remote sensing images from Landsat satellites processed using geographic information systems (GIS). The findings showed an increase in the water bodies class where shrimp farms are found. In addition, to help us discuss the results, data from the Global Surface Water Explorer was also used to understand this change throughout intra and interannual water variability. Besides shrimp farms’ intensification, agricultural areas in the LJRSB also increased, mainly in the irrigated perimeter lands (IPLs), causing a loss in the Caatinga native vegetation. In summary, over recent years, significant changes have been noticeable in the LJRSB coastal region, caused by an increase in shrimp farms mainly located on the Jaguaribe River margins, destroying the native riparian forest.

Remote sensing and GIS have been widely employed to study temporal and spatial urban land use changes in southern and southeastern China. However, few studies have been conducted in northeastern regions. This study analyzed land use change and spatial patterns of urban expansion in the metropolitan area of Jilin City, located on the extension of Changbai Mountain, based on aerial photos from 1989 and 2005 Spot images. The results indicated that urban land and transportation land increased dramatically (by 94.04% and 211.20%, respectively); isolated industrial and mining land decreased moderately (by 29.54%); rural residential land increased moderately (by 26.48%); dry land and paddy fields increased slightly (by 15.68% and 11.78%, respectively); forest and orchards decreased slightly (by 5.27% and 4.61%, respectively); grasslands and unused land decreased dramatically (by 99.12% and 86.04%, respectively). Sloped dry land (more than 4 degrees) was mainly distributed on the land below 10 degrees with an east, southeastern and south sunny direction aspect, and most sloped dry land transformed to forest was located on an east aspect lower than 12 degrees, while forest changed to dry land were mainly distributed on east and south aspects lower than 10 degrees. A spatial dependency analysis of land use change showed that the increased urban land was a logarithmic function of distance to the Songhua River. This study also provided some data with spatial details about the uneven land development in the upstream areas of Songhua River basin.

The Citarum watershed is one of the priority watersheds due to problems of critical land, flooding, erosion, and sedimentation which continue to increase every year. As the main catchment area that contributes to maintaining the availability of water resources, the upstream Citarum watershed continues to experience a reduction in forest and an increase in built-up land. A research aimed to analyze land use changes to the hydrological characteristics was carried out at the Watershed. The methods used include interpretation of SPOT image data, analysis of land use changes, and determining the values of KRA and KAT. The results of the analysis of land use change conditions in 2009-2018 saw a reduction in forest area (-5.5%), rice fields (-17.4%), and shrubs (-60.8%). Land use increased in built up land (39.7%), dry land agriculture (13%), plantations (6.4%), and open land (95.5%). The highest discharge occurred in 2010 at 606,3 m3/second and the lowest discharge in 2012 was 4,3 m3/second. The KRA and KAT values of the Upper Citarum watershed were moderate and very high. The multiple linear regression model of the relationship between land use changes that affect river flow fluctuations is Y = 2380.5 + 0.9 rainfall -206.5 forest + 6.1 build-up area -31.8 dryland agriculture + e. Other factors that influence the increase in river discharge are the slope of land slopes, rainfall patterns, and inadequate land use methods. Keywords: hydrological characteristics, landuse change, Upper Citarum watershed

Kuswanda W, Sunandar AD. 2019. Analysis of land use change and its relation to land potential and elephant habitat at Besitang Watershed, North Sumatra, Indonesia. Biodiversitas 20: 350-358. Land use change from forest into plantation at a watershed could be detrimental both for humans and wildlife. This study was aimed to analyze land use change and its impact on the habitat potential of Sumatran elephant (Elephas maximus sumatranus Temminck, 1857) in the upstream of Besitang Watershed located at Gunung Leuser National Park (GLNP), North Sumatra, Indonesia. The study was conducted from April to November 2015. Data collection was made through land cover map analysis, ground check and vegetation analysis using strip transect method. Land use change was analyzed using ArcView 3.2 software, species diversity was calculated using Shannon-Weiner formula and community evenness indices. Based on map delineation, total extent of Besitang Watershed is about 95,428 hectares. The analysis results showed that, in the past 25 years, about 15,989 hectares of land was changed from forests and farms to monoculture plantations. These changes have caused conflicts and threatened elephant population. As many as 168 species of plants were identified during vegetation analysis in the three study locations, namely Bukit Mas primary forest (88 species), Sekundur mixed secondary forest (91 species) and Halaban secondary forest (68 species). Average Importance Value Index (IVI) was below 40% which indicates that there are no dominant plant species. Tree density was between 360 and 497,5 individual/ha, sapling density was between 2,640 and 4,680 individual/ha, and density of seedling and understory plants was between 27,750 and 38,500 individual/ha. Species diversity index for each plant growth stage was relatively high (H’>3) and the similarity of plant species across locations was generally low (IS = <50%). Analysis of the correlation between land cover differences and habitat features showed statistically significant effects on species density and frequency. The highest effect of land cover change is on species density with the correlation reaching 94.5%. Forests in GLNP will be able to regenerate naturally to reach a stable state if there is no more land clearing to raise plantations.

The transformation of Tirupati's landscape over the past two decades reflects the dynamic interplay between urbanization, agricultural expansion, and environmental degradation. Through a comprehensive analysis of land use and land cover (LULC) changes using satellite imagery and spatial analysis techniques, this study offers insights into the evolving socio-environmental dynamics of the region. The findings reveal significant increases in built-up areas and corresponding declines in agricultural lands and natural ecosystems, driven by population growth and economic development. Despite efforts to mitigate environmental degradation, challenges such as soil erosion, deforestation, and water scarcity persist. However, there are promising initiatives aimed at enhancing water security and ecosystem resilience. In statistical terms, the analysis of land use and land cover changes in Tirupati reveals compelling trends over the study period. Utilizing Landsat satellite data and Maximum Likelihood Estimation (MLE) techniques, significant shifts in urbanization, agricultural activity, and environmental degradation were quantitatively assessed. The results demonstrate a remarkable expansion of built-up areas, accompanied by a concerning decline in agricultural lands and natural vegetation cover. Moreover, buffer ring and directionality analyses elucidate spatial patterns of change, highlighting the concentrated urban growth in specific directions and the widespread degradation of natural habitats. These statistical insights underscore the urgency of implementing sustainable development strategies and conservation measures to address the socio-environmental challenges facing Tirupati and foster long-term resilience. The study underscores the importance of sustainable development strategies and conservation efforts to address these challenges and ensure the long-term sustainability of Tirupati and its surrounding areas.

Environmental problems in Jakarta, especially flooding problem, is strongly influenced by the condition of eight watersheds that flow into Jakarta Bay, namely Bekasi, Cisadane, Angke Pesanggrahan, Ciliwung, Krukut, Cakung, Buaran and Sunter. The center-periphery relationship between Jakarta and surrounding areas triggered significant land use changes in the watershed, especially in the upstream area. This study aims to analyze land use changes in eight watersheds that flow into Jakarta Bay in 2000, 2009 and 2017 as well as their effect on the distribution of the criticality level of the catchment area, using Geographic Information System (GIS) refers to Planning Procedures for Forest and Land Rehabilitation Engineering Watershed. The criticality map of the catchment area was created by overlay and scoring slope infiltration map, soil infiltration map and rainfall infiltration map. The results showed that there was a significant increase in built-up area of 14,33% in 2000-2009 and 10,42% in 2009-2017. In contrast, the area of dry land farming decreased significantly by 12,99% in 2000-2009 and 5.96% in 2009-2017. Based on the criticality analysis of the catchment area, land use changes in study area, mainly due to urban growth, has a significant effect on the criticality level of the catchment area.