Measuring the Loss of Arable and Rural Lands on the Maltese Islands through Satellite Images

2020 ◽  
Vol 4 (1) ◽  
pp. 52-68
Author(s):  
Steve Zerafa
Keyword(s):  
Land Use ◽  
Urban Growth ◽  
Rural Areas ◽  
Satellite Images ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Agricultural Land ◽  
Water Flooding ◽  
Vegetation Density ◽  
Maltese Islands

The Maltese Islands went through a rapid urban growth and increase in population. Such trends normally contribute to the loss of agricultural land, trees, soil and rural land. Urban growth is often responsible for a variety of urban environmental issues: Decreased air quality, increased runoff and subsequent water flooding, increased local temperature, losses of agricultural land and deterioration of water table. During such times, it is crucial to monitor the use of land resources, understand the changes of biodiversity and ecosystems, and ensure the long-term productive potential of soil, land and plants. Although the islands are small in size, such a monitoring task is quite challenging due to the effects of weather on the islands, the dynamics of the vegetation, and the continued activities of locals all across the islands. In this context, geospatial technologies and remote sensing techniques could serve as an essential tool for the analysis of land use and detecting changes occurring within the ecosystems. This study attempts to assess the land use change detection at a pixel level and highlight the vegetation density, and workout the loss of vegetative in arable and rural areas across the islands during the years 2015 to 2019. The created models are derived from the observation of the Normalized Difference Vegetation Index (NDVI) as obtained by Sentinel-2 satellite images. The results showed that from Spring 2017 to Spring 2019, the islands experienced a 2.45km² reduction of green vegetation colour. Over a period of 4 years the islands experienced a 1.25km² erosion of arable and rural lands. Among other reasons, this loss is the result of more development and the extension of the urbanization zones.

scholarly journals Sentinel-2 Based Temporal Detection of Agricultural Land Use Anomalies in Support of Common Agricultural Policy Monitoring

2018 ◽  
Vol 7 (10) ◽  
pp. 405 ◽  
Author(s):  
Urška Kanjir ◽  
Nataša Đurić ◽  
Tatjana Veljanovski
Keyword(s):  
Land Use ◽  
Time Series ◽  
Agricultural Policy ◽  
Common Agricultural Policy ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Agricultural Land ◽  
Agricultural Land Use ◽  
Land Use Control ◽  
Sentinel 2

The European Common Agricultural Policy (CAP) post-2020 timeframe reform will reshape the agriculture land use control procedures from a selected risk fields-based approach into an all-inclusive one. The reform fosters the use of Sentinel data with the objective of enabling greater transparency and comparability of CAP results in different Member States. In this paper, we investigate the analysis of a time series approach using Sentinel-2 images and the suitability of the BFAST (Breaks for Additive Season and Trend) Monitor method to detect changes that correspond to land use anomaly observations in the assessment of agricultural parcel management activities. We focus on identifying certain signs of ineligible (inconsistent) use in permanent meadows and crop fields in one growing season, and in particular those that can be associated with time-defined greenness (vegetation vigor). Depending on the requirements of the BFAST Monitor method and currently time-limited Sentinel-2 dataset for the reliable anomaly study, we introduce customized procedures to support and verify the BFAST Monitor anomaly detection results using the analysis of NDVI (Normalized Difference Vegetation Index) object-based temporal profiles and time-series standard deviation output, where geographical objects of interest are parcels of particular land use. The validation of land use candidate anomalies in view of land use ineligibilities was performed with the information on declared land annual use and field controls, as obtained in the framework of subsidy granting in Slovenia. The results confirm that the proposed combined approach proves efficient to deal with short time series and yields high accuracy rates in monitoring agricultural parcel greenness. As such it can already be introduced to help the process of agricultural land use control within certain CAP activities in the preparation and adaptation phase.

scholarly journals Impacts of Urbanization on Land Use Pattern and Environment: A Case Study of Ajmer City, Rajasthan

2019 ◽  
Vol 8 (1) ◽  
pp. 87-91
Author(s):  
Bhanu Priya Chouhan ◽  
Monika Kannan
Keyword(s):  
Land Use ◽  
Urban Growth ◽  
Land Degradation ◽  
Satellite Images ◽  
Agricultural Land ◽  
Population Pressure ◽  
Geographical Information ◽  
Land Use Patterns ◽  
Use Patterns ◽  
The Impact

The world is undergoing the largest wave of urban growth in history. More than half of the world’s population now lives in towns and cities, and by 2030 this number will swell to about 5 billion. ‘Urbanization has the potential to usher in a new era of wellbeing, resource efficiency and economic growth. But due to increased population the pressure of demand also increases in urban areas’ (Drakakis-Smith, David, 1996). The loss of agricultural land to other land uses occasioned by urban growth is an issue of growing concern worldwide, particularly in the developing countries like India. This paper is an attempt to assess the impact of urbanization on land use and land cover patterns in Ajmer city. Recent trends indicate that the rural urban migration and religious significance of the place attracting thousands of tourists every year, have immensely contributed in the increasing population of city and is causing change in land use patterns. This accelerating urban sprawl has led to shrinking of the agricultural land and land holdings. Due to increased rate of urbanization, the agricultural areas have been transformed into residential and industrial areas (Retnaraj D,1994). There are several key factors which cause increase in population here such as Smart City Projects, potential for employment, higher education, more comfortable and quality housing, better health facilities, high living standard etc. Population pressure not only directly increases the demand for food, but also indirectly reduces its supply through building development, environmental degradation and marginalization of food production (Aldington T, 1997). Also, there are several issues which are associated with continuous increase in population i.e. land degradation, pollution, poverty, slums, unaffordable housing etc. Pollution, formulation of slums, transportation congestion, environmental hazards, land degradation and crime are some of the major impacts of urbanization on Ajmer city. This study involves mapping of land use patterns by analyzing data and satellite imagery taken at different time periods. The satellite images of year 2000 and 2017 are used. The change detection techniques are used with the help of Geographical Information System software like ERDAS and ArcGIS. The supervised classification of all the three satellite images is done by ERDAS software to demarcate and analyze land use change.

scholarly journals Integrating an Expert System, GIS, and Satellite Remote Sensing to Evaluate Land Suitability for Sustainable Tea Production in Bangladesh

2020 ◽  
Vol 12 (24) ◽  
pp. 4136
Author(s):  
Animesh Chandra Das ◽  
Ryozo Noguchi ◽  
Tofael Ahamed
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Satellite Remote Sensing ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Agricultural Land ◽  
Multicriteria Analysis ◽  
Land Evaluation ◽  
Land Policy ◽  
Tea Production

Land evaluation is important for assessing environmental limitations that inhibit higher yield and productivity in tea. The aim of this research was to determine the suitable lands for sustainable tea production in the northeastern part of Bangladesh using phenological datasets from remote sensing, geospatial datasets of soil–plant biophysical properties, and expert opinions. Sentinel-2 satellite images were processed to obtain layers for land use and land cover (LULC) as well as the normalized difference vegetation index (NDVI). Data from the Shuttle Radar Topography Mission (SRTM) were used to generate the elevation layer. Other vector and raster layers of edaphic, climatic parameters, and vegetation indices were processed in ArcGIS 10.7.1® software. Finally, suitability classes were determined using weighted overlay of spatial analysis based on reclassified raster layers of all parameters along with the results from multicriteria analysis. The results of the study showed that only 41,460 hectares of land (3.37% of the total land) were in the highly suitable category. The proportions of moderately suitable, marginally suitable, and not suitable land categories for tea cultivation in the Sylhet Division were 9.01%, 49.87%, and 37.75%, respectively. Thirty-one tea estates were located in highly suitable areas, 79 in moderately suitable areas, 24 in marginally suitable areas, and only one in a not suitable area. Yield estimation was performed with the NDVI (R2 = 0.69, 0.66, and 0.67) and the LAI (R2 = 0.68, 0.65, and 0.63) for 2017, 2018, and 2019, respectively. This research suggests that satellite remote sensing and GIS application with the analytical hierarchy process (AHP) could be used by agricultural land use planners and land policy makers to select suitable lands for increasing tea production.

scholarly journals Land Use Change in Buffer Zone of Chitwan National Park, Nepal between 1978 and 1999

1970 ◽  
Vol 16 ◽  
pp. 79-86 ◽  
Author(s):  
N. G. Baidya ◽  
D. R. Bhuju ◽  
P. Kandel
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
National Park ◽  
Vegetation Index ◽  
Agricultural Land ◽  
Buffer Zone ◽  
Community Forest Management ◽  
Vegetation Density ◽  
Chitwan National Park ◽  
Total Study Area

Land use dynamics in the Buffer Zone of Chitwan National Park was assessed by integrated use of Remote Sensing and Geographic Information System covering 1978, 1992 and 1999. Among all land-use type, forest was the most dominating land-use in 1978 covering 45.33% of total study area. However, the agricultural land became the most dominating land-use since 1992. The study found that since 1978 to 1999 there was increase in agricultural land by 67.28 km2, built-up area by 0.81 km2 and shrub-land by 7.68 km2. Whereas, the forest decreased by 62.23 km2, grassland by 11.38 km2 and water bodies by 2.16 km2. Vegetation density analysis using Normalized Difference Vegetation Index (NDVI) revealed that the densely vegetated area decreased by 5.03 km2 in a time-span of less than 10 years. Despite the successful community forest management in the BZ of CNP, this study showed a decline in densely forested area. Key words: GIS, Land use types, management, Remote sensing, Vegetation. DOI: 10.3126/eco.v16i0.3478ECOPRINT 16: 79-86, 2009

scholarly journals ANALISIS KERAPATAN VEGETASI UNTUK AREA PEMUKIMAN DENGAN MEMANFAATAN CITRA SATELIT LANDSAT DI KOTA TASIKMALAYA

2019 ◽  
Vol 8 (2) ◽  
pp. 78
Author(s):  
Miftah Kurnia Hayu ◽  
Riki Ridwana
Keyword(s):  
Land Use ◽  
Global Warming ◽  
Human Activity ◽  
Rural Areas ◽  
Urban Areas ◽  
Vegetation Index ◽  
Human Life ◽  
Vegetation Density ◽  
Urban And Rural Areas ◽  
High Level

Global warming is an important issue to discuss because it is very impactful to human life, one of the factors influencing increase global warming is decreasing the green vegetation continuously that exist in both urban and rural areas. Especially in urban areas because it is the center of human activity. The high level of human activity centered in the city leads to an increase in the need for land use which will lead to reduced vegetation density levels. Utilization of remote sensing images can be used to determine the density of vegetation in an area. Vegetation density analysis can be done by means of digital imagery intrepetation using the transformation of NDVI (Normalized Different Vegetation Index). The purpose of this research is to know the land use through the calculation of vegetation index of residential area in Tasikmalaya city.

scholarly journals Aplicação do Índice da Vegetação por Diferença Normalizada (NDVI) à Análise Multitemporal da Dinâmica de Áreas Agrícolas no Alto Curso da Bacia do Rio Uberabinha, Minas Gerais Application of the (...)

2015 ◽  
Vol 25 (44) ◽  
pp. 149-164
Author(s):  
Vanderlei De Oliveira Ferreira ◽  
Mirella Velluma Portilho Magalhães
Keyword(s):  
Land Use ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Agricultural Land ◽  
Agricultural Land Use ◽  
Visual Interpretation ◽  
Land Occupation ◽  
Reconstruction Process ◽  
Seasonal Scale ◽  
Agricultural Areas

O mapeamento do uso do solo é essencial para acompanhamento do processo de reconstrução continuada da paisagem, sendo útil para definição de estratégias de utilização dos recursos naturais. O presente artigo relata pesquisa dedicada a inventariar e compreender a dinâmica do uso agrícola do solo sob uma perspectiva multitemporal (escala sazonal) no alto curso da bacia do rio Uberabinha, no Triângulo Mineiro, a montante da sede municipal de Uberlândia. Utilizou-se a técnica do NDVI (Normalized Difference Vegetation Index) devido à sua aptidão para levantamento de áreas agrícolas. O mapeamento foi elaborado por meio da interpretação visual, recorrendo-se às imagens do sensor LANDSAT 5 e ResourceSat-1, com a composição colorida 4R5G3B. Foi possível diferenciar os diversos estádios fenológicos da cobertura vegetal, percebendo situações de manejo e forma de ocupação do solo em diferentes épocas do ano. Observa-se, por exemplo, que não há recorrência ao pousio da terra entre uma cultura e outra. Os produtores adotam o método de plantio direto, intercalando culturas, além de forrageiras e leguminosas para melhorar a qualidade nutricional do solo.Palavras chave: Mapeamento; Sensoriamento Remoto; Uso agrícola do solo; Escala sazonal.AbstractThe mapping of the land use is essential for accompaniment of the reconstruction process continued of landscape, being useful for define strategies of utilization of the natural resources. This article reports the research dedicated to inventory and understand the dynamics of agricultural land use under a multitemporal perspective (seasonal scale) in the high course of the basin of the Uberabinha river, in the Triângulo Mineiro, the upstream of the municipal headquarters of Uberlândia. We used the technique of NDVI (Normalized Difference Vegetation Index) due to its aptitude for survey of agricultural areas. The mapping was prepared by visual interpretation, resorting to images of the sensor LANDSAT 5 and ResourceSat-1, with colorful makeup 4R5G3B. It was possible to differentiate the several phenological stages of the vegetation cover, realizing management situations and forms of land occupation in differents epochs of the year. It is observed that there is no recurrence to fallow of the land between one culture and another. The producers adopt the method of tillage, interspersing cultures, besides forages and legumes for improve the nutritional quality of the soil. Keywords: Mapping; Remote Sensing; Agricultural land use; Seasonal scale. 

scholarly journals Geospatial Analysis of Land Use/Land Cover Dynamics on Lake Abaya-Chamo Wetland in Southern Rift-Valley of Ethiopia

2021 ◽  
Author(s):  
Tariku Zekarias ◽  
Vanum Govindu ◽  
Yechale Kebede ◽  
Abren Gelaw
Keyword(s):  
Land Use ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Agricultural Land ◽  
Anthropogenic Factors ◽  
Southern Ethiopia ◽  
Water Index ◽  
Normalized Difference Water Index ◽  
Change Matrix ◽  
The Impact

Abstract Wetlands worldwide and in Ethiopia have long been subject to severe degradation due to anthropogenic factors. This study was aimed at analyzing the impact of land use/cover dynamics on Lake Abaya-Chamo wetland in 1990–2019. Data were acquired via Landsat TM of 1990, ETM + of 2000, and OLI of 2010 and 2019 images plus using interview. Unsupervised and supervised classifications (via ERDAS14 and ArcGIS10.5) were applied to detect land use/cover classes. Normalized difference vegetation index, normalized difference water index, change matrix model and Kappa coefficients were used for analysis of the land use/cover dynamics in the lake-wetland. It was found that forest; water, shrub land, agricultural land, settlement and swamp area were the main land use/cover classes. While ‘settlement’ and ‘water body’ of the lake-wetland increased at progressively increasing magnitudes of changes in three periods within 1990–2019, ‘shrub land’ and ‘swamp’ declined at progressively increasing magnitudes of loss in the same periods. The NDWI result revealed that ‘swamp’ area shrank by 48.9% (2,991 ha) due to siltation-led expansion of the lake-water in three decades. Siltation, rapid population growth-led expansion of settlement and irrigation-based farming were the main drivers of the land use/cover dynamics and degradation of the lake-wetland. Thus, consistent mapping and integrated actions should be taken to curb the threats on the sustainability of the lake-wetland in Southern Ethiopia.

TEMPERATURA DE SUPERFÍCIE E A RELAÇÃO COM O ÍNDICE DE VEGETAÇÃO POR DIFERENÇA NORMALIZADA (NDVI) NA MICROBACIA DO RIO DA BATATEIRAS, CRATO-CE

2019 ◽  
Vol 21 (2) ◽  
pp. 1310-1320
Author(s):  
Cícera Celiane Januário da Silva ◽  
Vinicius Ferreira Luna ◽  
Joyce Ferreira Gomes ◽  
Juliana Maria Oliveira Silva
Keyword(s):  
Remote Sensing ◽  
Surface Temperature ◽  
Temperature Measurement ◽  
Rainy Season ◽  
Satellite Images ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Landsat 8 ◽  
Low Density ◽  
Difference Map

O objetivo do presente trabalho é fazer uma comparação entre a temperatura de superfície e o Índice de Vegetação por Diferença Normalizada (NDVI) na microbacia do rio da Batateiras/Crato-CE em dois períodos do ano de 2017, um chuvoso (abril) e um seco (setembro) como também analisar o mapa de diferença de temperatura nesses dois referidos períodos. Foram utilizadas imagens de satélite LANDSAT 8 (banda 10) para mensuração de temperatura e a banda 4 e 5 para geração do NDVI. As análises demonstram que no mês de abril a temperatura da superfície variou aproximadamente entre 23.2ºC e 31.06ºC, enquanto no mês correspondente a setembro, os valores variaram de 25°C e 40.5°C, sendo que as maiores temperaturas foram encontradas em locais com baixa densidade de vegetação, de acordo com a carta de NDVI desses dois meses. A maior diferença de temperatura desses dois meses foi de 14.2°C indicando que ocorre um aumento da temperatura proporcionado pelo período que corresponde a um dos mais secos da região, diferentemente de abril que está no período de chuvas e tem uma maior umidade, presença de vegetação e corpos d’água que amenizam a temperatura.Palavras-chave: Sensoriamento Remoto; Vegetação; Microbacia.                                                                                  ABSTRACTThe objective of the present work is to compare the surface temperature and the Normalized Difference Vegetation Index (NDVI) in the Batateiras / Crato-CE river basin in two periods of 2017, one rainy (April) and one (September) and to analyze the temperature difference map in these two periods. LANDSAT 8 (band 10) satellite images were used for temperature measurement and band 4 and 5 for NDVI generation. The analyzes show that in April the surface temperature varied approximately between 23.2ºC and 31.06ºC, while in the month corresponding to September, the values ranged from 25ºC and 40.5ºC, and the highest temperatures were found in locations with low density of vegetation, according to the NDVI letter of these two months. The highest difference in temperature for these two months was 14.2 ° C, indicating that there is an increase in temperature provided by the period that corresponds to one of the driest in the region, unlike April that is in the rainy season and has a higher humidity, presence of vegetation and water bodies that soften the temperature.Key-words: Remote sensing; Vegetation; Microbasin.RESUMENEl objetivo del presente trabajo es hacer una comparación entre la temperatura de la superficie y el Índice de Vegetación de Diferencia Normalizada (NDVI) en la cuenca Batateiras / Crato-CE en dos períodos de 2017, uno lluvioso (abril) y uno (Septiembre), así como analizar el mapa de diferencia de temperatura en estos dos períodos. Las imágenes de satélite LANDSAT 8 (banda 10) se utilizaron para la medición de temperatura y las bandas 4 y 5 para la generación de NDVI. Los análisis muestran que en abril la temperatura de la superficie varió aproximadamente entre 23.2ºC y 31.06ºC, mientras que en el mes correspondiente a septiembre, los valores oscilaron entre 25 ° C y 40.5 ° C, y las temperaturas más altas se encontraron en lugares con baja densidad de vegetación, según el gráfico NDVI de estos dos meses. La mayor diferencia de temperatura de estos dos meses fue de 14.2 ° C, lo que indica que hay un aumento en la temperatura proporcionada por el período que corresponde a uno de los más secos de la región, a diferencia de abril que está en la temporada de lluvias y tiene una mayor humedad, presencia de vegetación y cuerpos de agua que suavizan la temperatura.Palabras clave: Detección remota; vegetación; Cuenca.

scholarly journals Forage Production of the Argentine Pampa Region Based on Land Use and Long-Term Normalized Difference Vegetation Index Data

2009 ◽  
Vol 62 (2) ◽  
pp. 163-170 ◽  
Author(s):  
Carlos M. Di Bella ◽  
Ignacio J. Negri ◽  
Gabriela Posse ◽  
Florencia R. Jaimes ◽  
Esteban G. Jobbágy ◽  
...  
Keyword(s):  
Land Use ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Forage Production ◽  
Index Data ◽  
Pampa Region

scholarly journals Modeling Past, Present, and Future Urban Growth Impacts on Primary Agricultural Land in Greater Irbid Municipality, Jordan Using SLEUTH (1972–2050)

2021 ◽  
Vol 10 (4) ◽  
pp. 212
Author(s):  
Rana N. Jawarneh
Keyword(s):  
Land Use ◽  
Growth Model ◽  
Urban Growth ◽  
Agricultural Land ◽  
Urban Land Use ◽  
Agricultural Area ◽  
Grand Challenge ◽  
Negative Consequences ◽  
Urban Growth Model ◽  
Rate Of Increase

Urban expansion and loss of primarily agricultural land are two of the challenges facing Jordan. Located in the most productive agricultural area of Jordan, Greater Irbid Municipality (GIM) uncontrolled urban growth has posed a grand challenge in both sustaining its prime croplands and developing comprehensive planning strategies. This study investigated the loss of agricultural land for urban growth in GIM from 1972–2050 and denoted the negative consequences of the amalgamation process of 2001 on farmland loss. The aim is to unfold and track historical land use/cover changes and forecast these changes to the future using a modified SLEUTH-3r urban growth model. The accuracy of prediction results was assessed in three different sites between 2015 and 2020. In 43 years the built-up area increased from 29.2 km2 in 1972 to 71 km2 in 2015. By 2050, the built-up urban area would increase to 107 km2. The overall rate of increase, however, showed a decline across the study period, with the periods of 1990–2000 and 2000–2015 having the highest rate of built-up areas expansion at 68.6 and 41.4%, respectively. While the agricultural area increased from 178 km2 in 1972 to 207 km2 in 2000, it decreased to 195 km2 in 2015 and would continue to decrease to 188 km2 by 2050. The district-level analysis shows that from 2000–2015, the majority of districts exhibited an urban increase at twice the rate of 1990–2000. The results of the net change analysis of agriculture show that between 1990 and 2000, 9 districts exhibited a positive gain in agricultural land while the rest of the districts showed a negative loss of agricultural land. From 2000 to 2015, the four districts of Naser, Nozha, Rawdah, and Hashmyah completely lost their agricultural areas for urbanization. By 2050, Idoon and Boshra districts will likely lose more than half of their high-quality agricultural land. This study seeks to utilize a spatially explicit urban growth model to support sustainable planning policies for urban land use through forecasting. The implications from this study confirm the worldwide urbanization impacts on losing the most productive agricultural land in the outskirts and consequences on food production and food security. The study calls for urgent actions to adopt a compact growth policy with no new land added for development as what is available now exceeds what is needed by 2050 to accommodate urban growth in GIM.

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