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 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 Agroforestry Systems of the Tehuacán-Cuicatlán Valley: Land Use for Biocultural Diversity Conservation

Land ◽  
2019 ◽  
Vol 8 (2) ◽  
pp. 24
Author(s):  
Mariana Vallejo ◽  
M. Isabel Ramírez ◽  
Alejandro Reyes-González ◽  
Jairo López-Sánchez ◽  
Alejandro Casas
Keyword(s):  
Land Use ◽  
Agricultural Land ◽  
Agroforestry Systems ◽  
World Heritage Site ◽  
Biocultural Diversity ◽  
Semiarid Region ◽  
Agricultural Land Use ◽  
Visual Interpretation ◽  
Natural Ecosystems ◽  
Human Settlements

The Tehuacán-Cuicatlán Valley, Mexico, is the semiarid region with the richest biodiversity of North America and was recently recognized as a UNESCO's World Heritage site. Original agricultural practices remain to this day in agroforestry systems (AFS), which are expressions of high biocultural diversity. However, local people and researchers perceive a progressive decline both in natural ecosystems and AFS. To assess changes in location and extent of agricultural land use, we carried out a visual interpretation of very-high resolution imagery and field work, through which we identified AFS and conventional agricultural systems (CAS) from 1995 to 2003 and 2012. We analyzed five communities, representative of three main ecological and agricultural zones of the region. We assessed agricultural land use changes in relation to conspicuous landscape features (relief, rivers, roads, and human settlements). We found that natural ecosystems cover more than 85% of the territory in each community, and AFS represent 51% of all agricultural land. Establishment and permanence of agricultural lands were strongly influenced by gentle slopes and the existence of roads. Contrary to what we expected, we recorded agricultural areas being abandoned, thus favoring the regeneration of natural ecosystems, as well as a 9% increase of AFS over CAS. Agriculture is concentrated near human settlements. Most of the studied territories are meant to preserve natural ecosystems, and traditional AFS practices are being recovered for biocultural conservation.

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 Classifying multiyear agricultural land use data from Mato Grosso using time-series MODIS vegetation index data

2013 ◽  
Vol 130 ◽  
pp. 39-50 ◽  
Author(s):  
J. Christopher Brown ◽  
Jude H. Kastens ◽  
Alexandre Camargo Coutinho ◽  
Daniel de Castro Victoria ◽  
Christopher R. Bishop
Keyword(s):  
Land Use ◽  
Time Series ◽  
Vegetation Index ◽  
Agricultural Land ◽  
Agricultural Land Use ◽  
Mato Grosso ◽  
Index Data

scholarly journals USING LANDSAT 8 IMAGE TIME SERIES FOR CROP MAPPING IN A REGION OF CERRADO, BRAZIL

2016 ◽  
Vol XLI-B8 ◽  
pp. 845-850 ◽  
Author(s):  
H. Bendini ◽  
I. D. Sanches ◽  
T. S. Körting ◽  
L. M. G. Fonseca ◽  
A. J. B. Luiz ◽  
...  
Keyword(s):  
Land Use ◽  
Time Series ◽  
Vegetation Index ◽  
Agricultural Land ◽  
Vegetation Indices ◽  
Agricultural Land Use ◽  
Landsat 8 ◽  
Land Use Classification ◽  
Crop Mapping ◽  
Phenological Metrics

The objective of this research is to classify agricultural land use in a region of the Cerrado (Brazilian Savanna) biome using a time series of Enhanced Vegetation Index (EVI) from Landsat 8 OLI. Phenological metrics extracted from EVI time series, a Random Forest algorithm and data mining techniques are used in the process of classification. The area of study is a region in the Cerrado in a region of the municipality of Casa Branca, São Paulo state, Brazil. The results are encouraging and demonstrate the potential of phenological parameters obtained from time series of OLI vegetation indices for agricultural land use classification.

scholarly journals ANALYSIS OF AGRICULTURAL LAND USE AND EVALUATION OF IMPACT ON ECONOMIC DEVELOPMENT IN BIJNOR DISTRICT

2020 ◽  
Vol 8 (6) ◽  
pp. 121-125
Author(s):  
Rashmi Sharma Rawal ◽  
Naresh Kumar
Keyword(s):  
Land Use ◽  
Social Development ◽  
Rural Economy ◽  
Crop Production ◽  
Agricultural Land ◽  
Human Life ◽  
Agricultural Land Use ◽  
Agricultural System ◽  
Human Environment ◽  
Agricultural Areas

From the beginning of human life, in the gradual development of its culture, various types of enterprises, businesses, economic activities and social development and its basic needs are obtained from the land. The study of the effects on human behavior and human functioning, the distance of the market from agricultural areas, market prices and agricultural production, demand of agricultural areas as well as the capacity of production, land production, density of cropland etc. were the questions that were studied Studies the impacts on agricultural land from a human social point of view. Agriculture is the most important aspect of the rural economy. Agriculture is the backbone of the sustenance and social development of all living communities. Along with the special production method and social ecologies of the area, the agricultural system and farming community, land ownership, availability of resources, size of holdings, agricultural land use along with social change of human environment has also seen changes in the agricultural state. Researchers by evaluating the effects of agricultural land use on social development in their area of ​​study Bijnor district to maintain the quality of land under environmental balance through scientific techniques and green agricultural development for various long term agricultural needs. There is a need and the plains formed from the fertile land by the rivers Ramganga and Kho are important for agricultural land use and crop production..   Hindi: मानव आदिकाल से ही अपनी संस्कृति के क्रमिक विकास में विभिन्न प्रकार के उद्यम, व्यवसायों, आर्थिक क्रियाकलाप एवं सामाजिक विकास तथा अपनी मूलभूत आवश्यकताओं की पूर्ति भूमि से प्राप्त करता है। मानव व्यवहार एवं मानवीय कार्य प्रणाली पर होने वाले प्रभावों का अध्ययन कृषि क्षेत्रों से बाजार की दूरी ,बाजार का भाव एवं कृषि उत्पादन, कृषि क्षेत्रों की मॉंग के साथ-साथ उत्पादन क्षमता भूमि उत्पादन की क्षमता फसल भूमि की सघनता आदि ऐसे प्रश्न रहे जिनका अध्ययन मानव सामाजिक दृष्टि कोण से कृषि भूमि पर पड़ने वाले प्रभावों का अध्ययन करता है। कृषि ग्रामीण अर्थव्यवस्था का सबसे महत्वपूर्ण पक्ष है। कृषि समस्त जीव समुदाय का भरण-पोषण एवं सामाजिक विकास की रीढ़ होती है। फसलोत्पादन क्षेत्र विशेष उत्पादन विधि तथा वहाँ की सामाजिक पारिस्थितियों से कृषि व्यवस्था एवं कृषक समुदाय , भूमि स्वामित्व, संसाधनों की उपलब्धता, जोत का आकार, कृषि भूमि उपयोग को मानवीय वातावरण के सामाजिक परिवर्तन के साथ-साथ कृषि प्रदेश मे भी परिवर्तन देखा गया है। शोधार्थी अपने अध्ययन क्षेत्र बिजनौर जनपद में कृषि भूमि उपयोग का सामाजिक विकास पर प्रभावों का मूल्यांकन करके उसके भावी नियोजन की आवश्यकताओं को दीर्घकालीन विभिन्न कृषि भूमि उपयोग के वैज्ञानिक तकनीक एवं हरित कृषि विकास के माध्यम से वातावरण सन्तुलन के अन्तर्गत भूमि की गुणवत्ता को बनाये रखने की आवश्यकता है तथा रामगंगा और खो नदियों के द्वारा उपजाऊ भूमि से निर्मित मैदान कृषि भूमि उपयोग एवं फसल उत्पादन के लिये महत्वपूर्ण है।

scholarly journals USING LANDSAT 8 IMAGE TIME SERIES FOR CROP MAPPING IN A REGION OF CERRADO, BRAZIL

2016 ◽  
Vol XLI-B8 ◽  
pp. 845-850
Author(s):  
H. Bendini ◽  
I. D. Sanches ◽  
T. S. Körting ◽  
L. M. G. Fonseca ◽  
A. J. B. Luiz ◽  
...  
Keyword(s):  
Land Use ◽  
Time Series ◽  
Vegetation Index ◽  
Agricultural Land ◽  
Vegetation Indices ◽  
Agricultural Land Use ◽  
Landsat 8 ◽  
Land Use Classification ◽  
Crop Mapping ◽  
Phenological Metrics

The objective of this research is to classify agricultural land use in a region of the Cerrado (Brazilian Savanna) biome using a time series of Enhanced Vegetation Index (EVI) from Landsat 8 OLI. Phenological metrics extracted from EVI time series, a Random Forest algorithm and data mining techniques are used in the process of classification. The area of study is a region in the Cerrado in a region of the municipality of Casa Branca, São Paulo state, Brazil. The results are encouraging and demonstrate the potential of phenological parameters obtained from time series of OLI vegetation indices for agricultural land use classification.

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 Mapping Evapotranspiration of Agricultural Areas in Ghana

2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Kenneth Aidoo ◽  
Nana Ama Browne Klutse ◽  
Kofi Asare ◽  
Comfort Gyasiwaa Botchway ◽  
Samuel Fosuhene
Keyword(s):  
Land Use ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Environmental Changes ◽  
Hydrological Cycle ◽  
Remotely Sensed Data ◽  
Spatial Dimensions ◽  
Combined Estimation ◽  
Annual Water ◽  
Agricultural Areas

Climate change is having an adverse effect on the environment especially in sub-Sahara Africa, where capacity for natural resource management such as water is very low. The scope of the effect on land use types have to be estimated to inform proper remedy. A combined estimation of transpiration and evaporation from plants and soil is critical to determine annual water requirement for different land use. Evapotranspiration (ET) is a major component in the world hydrological cycle, and understanding its spatial dimensions is critical in evaluating the effects it has on regional land use. A measure of this component is challenging due to variation in rainfall and environmental changes. The mapping evapotranspiration with high resolution and internalized calibration (METRIC) method is employed to create evapotranspiration map for land use, using remotely sensed data by satellite, processed, and analyzed in ArcGIS. Normalized difference vegetation index (NDVI) was related to the availability of water for vegetation on different land use, and the results indicate a high evapotranspiration for vegetated land use with high NDVI than land use with low NDVI.

scholarly journals Comparing Sentinel-1 and -2 Data and Indices for Agricultural Land Use Monitoring

2020 ◽  
Vol 12 (18) ◽  
pp. 2919
Author(s):  
Ann-Kathrin Holtgrave ◽  
Norbert Röder ◽  
Andrea Ackermann ◽  
Stefan Erasmi ◽  
Birgit Kleinschmit
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Vegetation Index ◽  
Agricultural Land ◽  
Optical Data ◽  
Agricultural Land Use ◽  
Land Use Type ◽  
Auxiliary Data ◽  
Land Use Types ◽  
Sentinel 2

Agricultural vegetation development and harvest date monitoring over large areas requires frequent remote sensing observations. In regions with persistent cloud coverage during the vegetation season this is only feasible with active systems, such as SAR, and is limited for optical data. To date, optical remote sensing vegetation indices are more frequently used to monitor agricultural vegetation status because they are easily processed, and the characteristics are widely known. This study evaluated the correlations of three Sentinel-2 optical indices with Sentinel-1 SAR indices over agricultural areas to gain knowledge about their relationship. We compared Sentinel-2 Normalized Difference Vegetation Index, Normalized Difference Water Index, and Plant Senescence Radiation Index with Sentinel-1 SAR VV and VH backscatter, VH/VV ratio, and Sentinel-1 Radar Vegetation Index. The study was conducted on 22 test sites covering approximately 35,000 ha of four different main European agricultural land use types, namely grassland, maize, spring barley, and winter wheat, in Lower Saxony, Germany, in 2018. We investigated the relationship between Sentinel-1 and Sentinel-2 indices for each land use type considering three phenophases (growing, green, senescence). The strength of the correlations of optical and SAR indices differed among land use type and phenophase. There was no generic correlation between optical and SAR indices in our study. However, when the data were split by land use types and phenophases, the correlations increased remarkably. Overall, the highest correlations were found for the Radar Vegetation Index and VH backscatter. Correlations for grassland were lower than for the other land use types. Adding auxiliary data to a multiple linear regression analysis revealed that, in addition to land use type and phenophase information, the lower quartile and median SAR values per field, and a spatial variable, improved the models. Other auxiliary data retrieved from a digital elevation model, Sentinel-1 orbit direction, soil type information, and other SAR values had minor impacts on the model performance. In conclusion, despite the different nature of the signal generation, there were distinct relationships between optical and SAR indices which were independent of environmental variables but could be stratified by land use type and phenophase. These relationships showed similar patterns across different test sites. However, a regional clustering of landscapes would significantly improve the relationships.

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