The spatial pattern of forest cover changes in Lithuania during the second half of the twentieth century

The trends of forest cover change in Lithuanian municipalities are introduced in the current paper. Two sources of information on the forest cover in 1950s and today (2013) were used in this study: (i) a geographic forest cover database developed using historical orthophotomaps based on aerial photography, which was carried out in the period just after the World War II, and (ii) the information originating from the State Forest Cadaster and referring to the year 2013. These two layers were compared using GIS overlay techniques. The data was made available for the analyses aggregated up to the municipality level. The Global Moran’s I statistic and Anselin Local Moran’s I were used to identify global and local patterns in the distribution of forest cover characteristics in Lithuanian municipalities, respectively. The main finding of this study was that the proportion of the forest cover in 1950 was 26.5%, i. e. notably differing from the official statistics – 19.7%. The proportion of the forest cover increased in all municipalities during the period 1950–2013. The largest increase in forest cover proportion was in the areas less suitable for agriculture. The relatively largest areas of new forests were identified in the south-eastern part of Lithuania, the deforestation was relatively slowest around less forested municipalities, while the afforestation was relatively slowest around the agricultural Pakruojis municipality. Deforestation was most commonly associated with the forest transformation into agricultural land, less often into scrublands or waters.

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Synthesizing published knowledge of boreal forest cover change for large-scale landscape dynamics modelling

The Forestry Chronicle ◽

10.5558/tfc79132-1 ◽

2003 ◽

Vol 79 (1) ◽

pp. 132-146 ◽

Cited By ~ 3

Author(s):

Dennis Yemshanov ◽

Ajith H Perera

Keyword(s):

Boreal Forest ◽

Large Scale ◽

Forest Canopy ◽

Forest Cover ◽

Forest Succession ◽

Simulation Models ◽

Limiting Factors ◽

Sources Of Information ◽

Forest Cover Change ◽

Discrete State

We reviewed the published knowledge on forest succession in the North American boreal biome for its applicability in modelling forest cover change over large extents. At broader scales, forest succession can be viewed as forest cover change over time. Quantitative case studies of forest succession in peer-reviewed literature are reliable sources of information about changes in forest canopy composition. We reviewed the following aspects of forest succession in literature: disturbances; pathways of post-disturbance forest cover change; timing of successional steps; probabilities of post-disturbance forest cover change, and effects of geographic location and ecological site conditions on forest cover change. The results from studies in the literature, which were mostly based on sample plot observations, appeared to be sufficient to describe boreal forest cover change as a generalized discrete-state transition process, with the discrete states denoted by tree species dominance. In this paper, we outline an approach for incorporating published knowledge on forest succession into stochastic simulation models of boreal forest cover change in a standardized manner. We found that the lack of details in the literature on long-term forest succession, particularly on the influence of pre-disturbance forest cover composition, may be limiting factors in parameterizing simulation models. We suggest that the simulation models based on published information can provide a good foundation as null models, which can be further calibrated as detailed quantitative information on forest cover change becomes available. Key words: probabilistic model, transition matrix, boreal biome, landscape ecology

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Spatial-Temporal Differentiation Analysis of Agricultural Land Use Intensity and Its Driving Factors at the County Scale: A Case Study in Hubei Province, China

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph17186910 ◽

2020 ◽

Vol 17 (18) ◽

pp. 6910

Author(s):

Li Yu ◽

Zhanqi Wang ◽

Hongwei Zhang ◽

Chao Wei

Keyword(s):

Land Use ◽

Agricultural Land ◽

Hubei Province ◽

Driving Factors ◽

The Other ◽

Moran’S I ◽

Agricultural Land Use ◽

Land Use Intensity ◽

Moran's I ◽

Continuous Growth

Scientifically characterizing the spatial-temporal distribution characteristics of agricultural land use intensity and analyzing its driving factors are of great significance to the formulation of relevant agricultural land use intensity management policies, the realization of food safety and health, and the achievement of sustainable development goals. Taking Hubei Province as an example, and taking counties as the basic evaluation unit, this paper establishes an agricultural land use intensity evaluation system, explores the spatial autocorrelation of agricultural land use intensity in each county and analyzes the driving factors of agricultural land use intensity. The results show that the agricultural land use intensity in Hubei Province increased as a whole from 2000 to 2016, and the spatial agglomeration about the agricultural land use intensity in Hubei Province experienced a process of continuous growth and a fluctuating decline; the maximum of the Global Moran’s I was 0.430174 (in 2007) and the minimum was 0.148651 (in 2001). In terms of Local Moran’s I, H-H agglomeration units were mainly concentrated in two regions: One comprising the cities of Huanggang, Huangshi and Ezhou, and the other the cities of Xiangyang and Suizhou; the phenomenon is particularly obvious after 2005. On the other hand, factors such as the multiple cropping index (MCI) that reflect farmers’ willingness to engage in agricultural production have a great impact on agricultural land use intensity, the influence of the structure of the industry on agricultural land use intensity varies with the degree of influence of different industries on farmers’ income, and agricultural fiscal expenditure (AFE) has not effectively promoted the intensification of agricultural land use. The present research has important significance for enhancing insights into the sustainable improvement of agricultural land use intensity and for realizing risk control of agricultural land use and development.

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The Trajectories of Perennial Crops Cover Change in Relationship with Forest Cover Change in Bao Lam District, Lam Dong Province

VNU Journal of Science Earth and Environmental Sciences ◽

10.25073/2588-1094/vnuees.4112 ◽

2018 ◽

Vol 34 (1) ◽

Author(s):

Le Quang Toan ◽

Pham Van Cu ◽

Bui Quang Thanh

Keyword(s):

Sustainable Development ◽

Forest Cover ◽

Forest Cover Change ◽

Perennial Crops ◽

Deforestation Rate ◽

Logistic Regression Models ◽

Blind Area ◽

Result Show ◽

Forest Cover Changes ◽

Negative Impacts

Abstract: The expansion of perennial crops area plays an important role for supporting the human livelihood in the Central Highlands, so have negative impacts on deforestation and sustainable development. Remote sensing and GIS were used to analyze the trajectories of perennial crops cover change in relationship with deforestation. The Logistic regression models were used to analyze proximate reasons and spatial changing determinants of main land cover changes for the period 2004-2016 of Bảo Lâm district. The result show that the perennial crops changes are indicator for deforestation in Bảo Lâm district with high deforestation rate 0,8% per year caused by the expansion of annual crops, blind area and the expansion of perennial crops. The facile accessed forest and suitable forest area for perennial crops have more destroyed. The trajectories of perennial crops and forest cover changes are important scientific towards sustainable development.

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Migration, Remittances, and Forest Cover Change in Rural Guatemala and Chiapas, Mexico

Land ◽

10.3390/land9030088 ◽

2020 ◽

Vol 9 (3) ◽

pp. 88 ◽

Cited By ~ 1

Author(s):

Arild Angelsen ◽

Mariel Aguilar-Støen ◽

John Ainembabazi ◽

Edwin Castellanos ◽

Matthew Taylor

Keyword(s):

Remote Sensing ◽

Rural Communities ◽

Forest Cover ◽

Agricultural Land ◽

Remote Sensing Data ◽

Forest Loss ◽

Household Surveys ◽

Forest Cover Change ◽

Household Members ◽

Migration Flows

This article investigates how migration and remittances affect forest cover in eight rural communities in Guatemala and Chiapas, Mexico. Based on household surveys and remote sensing data, we found little evidence to support the widespread claim that migration takes pressure off forests. In the Chiapas sites, we observed no significant changes in forest cover since 1990, while in the Guatemalan sites, migration may have increased demand for agricultural land, leading to an average annual forest loss of 0.73% during the first decade of the millennium. We suggest that when attractive opportunities exist to invest in agriculture and land expansion, remittances and returnee savings provide fresh capital that is likely to increase pressure on forests. Our study also has implications for the understanding of migration flows; in particular, migration has not implied an exodus out of agriculture for the remaining household members nor for the returning migrants. On the contrary, returning migrants are more likely to be involved in farming activities after their return than they were before leaving.

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Landslide risk trends in the Kivu Rift and the impact of environmental and societal dynamics

10.5194/egusphere-egu21-8927 ◽

2021 ◽

Author(s):

Arthur Depicker ◽

Liesbet Jacobs ◽

Nicholus Mboga ◽

Benoît Smets ◽

Anton Van Rompaey ◽

...

Keyword(s):

Forest Cover ◽

Agricultural Land ◽

Landslide Hazard ◽

Aerial Photographs ◽

Primary Forest ◽

Landslide Risk ◽

Sudden Increase ◽

Forest Cover Changes ◽

Societal Dynamics ◽

The Impact

On the nexus of humans and their environment, landslide risk is in essence dynamic. In mountainous areas over the world, the need for agricultural land incites people to settle on steeper (more landslide-prone) terrain at the expense of ecosystems. At the same time, the degradation of ecosystems, for example through deforestation, leads to a considerable increase in landslide hazard. Although the link between deforestation and landslide hazard/risk has been widely recognized, it remains poorly quantified. This is especially the case in the Global South where historical land cover and landslide records are scarce. &#160;In this study, we investigate 58 years of forest cover changes, population dynamics, and landslide risk in the Kivu Rift. This mountainous region presents similar geomorphic and climatic conditions across three countries: Burundi, the eastern part of the Democratic Republic of the Congo (DRC), and Rwanda. First, we use contemporary landslide and deforestation data (2000-2016) to explicitly quantify the interactions between these two processes. Second, we reconstruct the annual forest cover changes between 1958 and 2016 by means of a cellular automaton of which the output converges to four forest cover products (1958, 1988, 2001, 2016). We derive the 1958 forest data from an inventory of nearly 2,400 panchromatic aerial photographs, available at the Royal Museum for Central Africa. The forest data for 1988, 2001, and 2016 are readily available and derived from satellite imagery. Next, we estimate the yearly historical landslide hazard dynamics by applying the contemporary deforestation-landslide relationship to the historical forest cover changes. Finally, an approximation of the landslide risk (expected fatalities per 100,000 inhabitants), is calculated for four epochs (1975, 1990, 2000, 2015) and derived from the product of the corresponding hazard map and population density grids.During our entire period of observation, the landslide risk is higher in the DRC than in Rwanda and Burundi. While the risk in Rwanda and Burundi displays a slightly decreasing trend, the risk seems more volatile in the DRC. Here, the initial risk in 1975 is high due to the concentration of a small population along the steep northwestern coast of Lake Kivu. In the following 15 years, the risk in the DRC decreases sharply, only to soar again in the nineties. This sudden increase in risk can be linked to two factors: demographic changes and environmental degradation. During the nineties, the location of the Congolese people shifted towards steeper terrain. This shift is explained by the relocation of hundreds of thousands of Rwandan refugees and internally displaced people following the First and Second Congo War, but also by the economic opportunities provided by the booming, often informal, mining industry. Deforestation has also contributed to the higher landslide risk in the DRC, as large parts of the primary forest have been cut to satisfy the land and fuelwood demand of the fast-growing population.With our analysis, we demonstrate that a landslide risk assessment is more than the reflection of the current environmental conditions. The legacy of environmental and societal dynamics resonates in contemporary landslide risk.

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Forest Cover Change and the Effectiveness of Protected Areas in the Himalaya since 1998

Sustainability ◽

10.3390/su12156123 ◽

2020 ◽

Vol 12 (15) ◽

pp. 6123

Author(s):

Changjun Gu ◽

Pei Zhao ◽

Qiong Chen ◽

Shicheng Li ◽

Lanhui Li ◽

...

Keyword(s):

Protected Areas ◽

Forest Cover ◽

Forest Degradation ◽

Google Earth ◽

Forest Cover Change ◽

Natural Conditions ◽

Positive Role ◽

Forest Cover Changes ◽

Matched Samples ◽

The Himalaya

Himalaya, a global biodiversity hotspot, has undergone considerable forest cover fluctuation in recent decades, and numerous protected areas (PAs) have been established to prohibit forest degradation there. However, the spatiotemporal characteristics of this forest cover change across the whole region are still unknown, as are the effectiveness of its PAs. Therefore, here, we first mapped the forest cover of Himalaya in 1998, 2008, and 2018 with high accuracy (>90%) using a random forest (RF) algorithm based on Google Earth Engine (GEE) platform. The propensity score matching (PSM) method was applied with eight control variables to balance the heterogeneity of land characteristics inside and outside PAs. The effectiveness of PAs in Himalaya was quantified based on matched samples. The results showed that the forest cover in Himalaya increased by 4983.65 km2 from 1998 to 2008, but decreased by 4732.71 km2 from 2008 to 2018. Further analysis revealed that deforestation and reforestation mainly occurred at the edge of forest tracts, with over 55% of forest fluctuation occurring below a 2000 m elevation. Forest cover changes in PAs of Himalaya were analyzed; these results indicated that about 56% of PAs had a decreasing trend from 1998 to 2018, including the Torsa (Ia PA), an area representative of the most natural conditions, which is strictly protected. Even so, as a whole, PAs in Himalaya played a positive role in halting deforestation.

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TIPOLOGI PERUBAHAN TUTUPAN HUTAN DI KABUPATEN KUBU RAYA KALIMANTAN BARAT

Wahana Forestra Jurnal Kehutanan ◽

10.31849/forestra.v14i1.2460 ◽

2019 ◽

Vol 14 (1) ◽

pp. 63-69

Author(s):

Hanifah Ikhsani

Keyword(s):

Forest Cover ◽

Driving Forces ◽

Driving Factors ◽

Forest Cover Change ◽

Forest Change ◽

West Kalimantan ◽

Forest Cover Changes ◽

Clustering Approach ◽

Euclidean Distances ◽

The Village

Forest cover changes were influenced by many factors, some of which were biophysical characteristics, socio-economic conditions, and community cultural. The behavior of forest cover changes in each of Indonesia's regions varied, either its rate or its driving factors. The establishment of village typologies to categorize village administrative areas becomes important to see the driving factors that trigger forest change in each typology. The objective of this study was to develop the village typology and to identify the driving forces of forest cover change in each village in Kubu Raya Regency, West Kalimantan. The development of village typology was done by applying the clustering approach with standardized euclidean distances. Based on the proportion of forest in 2015, the study found that there are two village typologies within the study area with 81% OA. The study also recognized that the most significant driving forces of forest cover change in T1 were the distance from rivers (X2) and settlements (X3), whereas in T2 were the distance from roads (X1) and the edge of forest in 2015 (X9). The study concludes that the proximity from the center of the human activities holds a significant influence on the behavior of forest cover changes.

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Priestorová analýza dát z povrchového zberu na lokalite Vráble-Fidvár

Musaica Archaeologica ◽

10.46283/musarch.2021.1.2.03 ◽

2021 ◽

Vol 6 (1-2) ◽

pp. 35-50

Author(s):

Dominik Drozd

Keyword(s):

Spatial Analysis ◽

Spatial Pattern ◽

Spatial Patterns ◽

Interpolation Method ◽

Objective Evaluation ◽

Moran’S I ◽

Sampled Data ◽

Moran's I ◽

Geostatistical Interpolation ◽

Global And Local

The goal of this study is to introduce selected methods of spatial analysis and their contribution to evaluation of fieldwalking data. Spatial analysis encompasses various methods suitable for identification, objective evaluation and visualization of spatial patterns which are present in obtained data. This article primarily deals with sampled data, collected during a 2007 fieldwalking campaign. The dataset consisting of potsherds was spatially autocorrelated, using the global and local Moran’s I coefficient, which was used to identify clusters of finds. Spatial pattern of the settlement was visualised by geostatistical interpolation method – kriging.

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The Spatial Distribution Characteristics of Carbon Emissions at County Level in the Harbin−Changchun Urban Agglomeration

Atmosphere ◽

10.3390/atmos12101268 ◽

2021 ◽

Vol 12 (10) ◽

pp. 1268

Author(s):

Yixia Wang

Keyword(s):

Spatial Distribution ◽

Carbon Emissions ◽

Carbon Emission ◽

Urban Agglomeration ◽

Moran’S I ◽

County Level ◽

Distribution Characteristics ◽

Moran's I ◽

Spatial Distribution Characteristics ◽

Global And Local

China has clearly put forward the strategic goals of reaching the “Carbon Emission Peak” by 2030, and achieving “Carbon Neutrality” by 2060. To achieve these goals, it is necessary to precisely understand the spatial distribution characteristics of historical carbon emissions in different regions. This paper has selected a representative national-level urban agglomeration in China, the Harbin−Changchun urban agglomeration, to study the temporal and spatial distribution characteristics of carbon emissions in its counties. This paper has constructed global and local Moran’s I indexes for the 103 counties in this urban agglomeration by using the carbon emission values reflected by night light data from 1997 to 2017 to perform global and local autocorrelation analysis on a spatial level. The results show that: (1) the main characteristic of carbon emission clustering in the Harbin−Changchun urban agglomeration is similar clustering; (2) the changes in carbon emissions of the Harbin−Changchun urban agglomeration have a strong correlation with relevant policies. For example, due to the impact of the “Twelfth Five-Year Plan” policies, in 2013, the global county-level Moran’s I index of the carbon emissions in the Harbin−Changchun urban agglomeration decreased by 0.0598; (3) the areas where high carbon emission values cluster together (“High−High Cluster”) and low carbon emission values cluster together (“Low−Low Cluster”) in the Harbin−Changchun urban agglomeration are highly concentrated, and the clusters are closely related to the development level of different regions.

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Hyperendemicity, heterogeneity and spatial overlap of leprosy and cutaneous leishmaniasis in the southern Amazon region of Brazil

Geospatial health ◽

10.4081/gh.2020.892 ◽

2020 ◽

Vol 15 (2) ◽

Author(s):

Amanda Gabriela De Carvalho ◽

João Gabriel Guimarães Luz ◽

João Victor Leite Dias ◽

Anuj Tiwari ◽

Peter Steinmann ◽

...

Keyword(s):

Spatial Distribution ◽

Spatial Autocorrelation ◽

Cutaneous Leishmaniasis ◽

Urban Areas ◽

Neglected Tropical Diseases ◽

Scan Statistics ◽

Moran’S I ◽

Moran's I ◽

Mato Grosso ◽

Global And Local

Neglected tropical diseases characterized by skin lesions are highly endemic in the state of Mato Grosso, Brazil. We analyzed the spatial distribution of leprosy and Cutaneous Leishmaniasis (CL) and identified the degree of overlap in their distribution. All new cases of leprosy and CL reported between 2008 and 2017 through the national reporting system were included in the study. Scan statistics together with univariate Global and Local Moran’s I were employed to identify clusters and spatial autocorrelation for each disease, with the spatial correlation between leprosy and CL measured by bivariate Global and Local Moran’s I. Finally, we evaluated the demographic characteristics of the patients. The number of leprosy (N = 28,204) and CL (N = 24,771) cases in Mato Grosso and the highly smoothed detection coefficients indicated hyperendemicity and spatial distribution heterogeneity. Scan statistics demonstrated overlap of high-risk clusters for leprosy (RR = 2.0; p <0.001) and CL (RR = 4.0; p <0.001) in the North and Northeast mesoregions. Global Moran’s I revealed a spatial autocorrelation for leprosy (0.228; p = 0.001) and CL (0.311; p = 0.001) and a correlation between them (0.164; p = 0.001). Both diseases were found to be concentrated in urban areas among men aged 31-60 years, of brown-skinned ethnicity and with a low educational level. Our findings indicate a need for developing integrated and spatially as well as socio-demographically targeted public health policies.

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