Detecting land-use change from seasonal vegetation dynamics on regional scale with MODIS EVI 250-m time-series imagery

2013 ◽  
Vol 9 (3) ◽  
pp. 304-330 ◽  
Author(s):  
Yudi Setiawan ◽  
Kunihiko Yoshino
Keyword(s):  
Land Use ◽  
Time Series ◽  
Land Use Change ◽  
Vegetation Dynamics ◽  
Regional Scale ◽  
Modis Evi

scholarly journals LAND USE ANALYSIS USING TIME SERIES OF VEGETATION INDEX DERIVED FROM SATELLITE REMOTE SENSING IN BRANTAS RIVER WATERSHED, EAST JAVA, INDONESIA

2017 ◽  
Vol 4 (2) ◽  
pp. 109
Author(s):  
Kunihiko Yoshino ◽  
Yudi Setiawan ◽  
Eikichi Shima
Keyword(s):  
Land Use ◽  
Time Series ◽  
Land Use Change ◽  
Land Use Planning ◽  
Vegetation Index ◽  
Tree Planting ◽  
River Watershed ◽  
Watershed Land Use ◽  
Modis Evi ◽  
Land Use Maps

In this study, time series datasets of MODIS EVI (Enhanced Vegetation Index) data from 2002 and 2011 in the Brantas River watershed located in eastern Java, Indonesia were analyzed and classified to make ten land use maps for each year, in order to support watershed land use planning which takes into account local land use and trends in land use change. These land use maps with eight types of main land use categories were examined. During the 10 years period, forested area has expanded, while upland, paddy rice field, mixed garden and plantation have decreased. One of the reasons for this land use change is ascribed to tree planting under the joint forest management system by local people and the state forest corporation.

Climate and land use change impacts on water resources in Sardinia (Italy)

2021 ◽  
Author(s):  
Dario Ruggiu ◽  
Salvatore Urru ◽  
Roberto Deidda ◽  
Francesco Viola
Keyword(s):  
Land Use ◽  
Water Resources ◽  
Land Use Change ◽  
Hydrological Cycle ◽  
Potential Evapotranspiration ◽  
Regional Scale ◽  
Annual Runoff ◽  
Annual Rainfall ◽  
Land Use Scenarios ◽  
Near Future

<p>The assessment of climate change and land use modifications effects on hydrological cycle is challenging. We propose an approach based on Budyko theory to investigate the relative importance of natural and anthropogenic drivers on water resources availability. As an example of application, the proposed approach is implemented in the island of Sardinia (Italy), which is affected by important processes of both climate and land use modifications. In details, the proposed methodology assumes the Fu’s equation to describe the mechanisms of water partitioning at regional scale and uses the probability distributions of annual runoff (Q) in a closed form. The latter is parametrized by considering simple long-term climatic info (namely first orders statistics of annual rainfall and potential evapotranspiration) and land use properties of basins.</p><p>In order to investigate the possible near future water availability of Sardinia, several climate and land use scenarios have been considered, referring to 2006-2050 and 2051-2100 periods. Climate scenarios have been generated considering fourteen bias corrected outputs of climatic models from EUROCORDEX’s project (RCP 8.5), while three land use scenarios have been created following the last century tendencies.</p><p>Results show that the distribution of annual runoff in Sardinia could be significantly affected by both climate and land use change. The near future distribution of Q generally displayed a decrease in mean and variance compared to the baseline.   </p><p>The reduction of  Q is more critical moving from 2006-2050 to 2051-2100 period, according with climatic trends, namely due to the reduction of annual rainfall and the increase of potential evapotranspiration. The effect of LU change on Q distribution is weaker than the climatic one, but not negligible.</p>

The Impacts of Different Land Use Patterns on Water Volume in the Xixian Watershed, China

2015 ◽  
Vol 737 ◽  
pp. 728-731 ◽  
Author(s):  
Yuan Yuan Han ◽  
Tao Cai
Keyword(s):  
Land Use ◽  
Time Series ◽  
Land Use Change ◽  
River Basin ◽  
Water Conservation ◽  
Swat Model ◽  
Water Volume ◽  
Huaihe River Basin ◽  
Huaihe River ◽  
Soil And Water

In this study, Soil and Water Assessment Tool (SWAT) model was used to simulate land-use change effects on water quantity in the upper Huaihe river basin above the Xixian hydrological controlling station with a catchment area of 10,190 km2 by the use of three-phase (1980s、1990s、2000s) land-use maps, soil type map (1:200000), 1980 to 2008 daily time series of rainfall from the upper Huaihe river basin. On the basis of the simulated time series of daily runoff, land-use change effects on spatio-temporal change patterns of runoff coefficients and runoff modules were investigated. The results revealed that under the same condition of soil texture and terrain slope the advantage for runoff generation and the sensitivity of rainfall-runoff relationship to rainfall descended by farmland, paddy field, woodland.The outputs could provide important references for soil and water conservation and river health protection in the upper stream of Huaihe river.

scholarly journals Representation of fire, land-use change and vegetation dynamics in the Joint UK Land Environment Simulator vn4.9 (JULES)

2019 ◽  
Vol 12 (1) ◽  
pp. 179-193 ◽  
Author(s):  
Chantelle Burton ◽  
Richard Betts ◽  
Manoel Cardoso ◽  
Ted R. Feldpausch ◽  
Anna Harper ◽  
...  
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Land Cover ◽  
Vegetation Cover ◽  
Land Surface ◽  
Vegetation Dynamics ◽  
Fire Disturbance ◽  
Substantial Contribution ◽  
Surface Model ◽  
The Impact

Abstract. Disturbance of vegetation is a critical component of land cover, but is generally poorly constrained in land surface and carbon cycle models. In particular, land-use change and fire can be treated as large-scale disturbances without full representation of their underlying complexities and interactions. Here we describe developments to the land surface model JULES (Joint UK Land Environment Simulator) to represent land-use change and fire as distinct processes which interact with simulated vegetation dynamics. We couple the fire model INFERNO (INteractive Fire and Emission algoRithm for Natural envirOnments) to dynamic vegetation within JULES and use the HYDE (History Database of the Global Environment) land cover dataset to analyse the impact of land-use change on the simulation of present day vegetation. We evaluate the inclusion of land use and fire disturbance against standard benchmarks. Using the Manhattan metric, results show improved simulation of vegetation cover across all observed datasets. Overall, disturbance improves the simulation of vegetation cover by 35 % compared to vegetation continuous field (VCF) observations from MODIS and 13 % compared to the Climate Change Initiative (CCI) from the ESA. Biases in grass extent are reduced from −66 % to 13 %. Total woody cover improves by 55 % compared to VCF and 20 % compared to CCI from a reduction in forest extent in the tropics, although simulated tree cover is now too sparse in some areas. Explicitly modelling fire and land use generally decreases tree and shrub cover and increases grasses. The results show that the disturbances provide important contributions to the realistic modelling of vegetation on a global scale, although in some areas fire and land use together result in too much disturbance. This work provides a substantial contribution towards representing the full complexity and interactions between land-use change and fire that could be used in Earth system models.

scholarly journals A Phenology-Based Method to Map Cropping Patterns under a Wheat-Maize Rotation Using Remotely Sensed Time-Series Data

2018 ◽  
Vol 10 (8) ◽  
pp. 1203 ◽  
Author(s):  
Jianhong Liu ◽  
Wenquan Zhu ◽  
Clement Atzberger ◽  
Anzhou Zhao ◽  
Yaozhong Pan ◽  
...  
Keyword(s):  
Land Use ◽  
Time Series ◽  
Vegetation Index ◽  
Agricultural Land ◽  
Threshold Model ◽  
Series Data ◽  
Cropping Pattern ◽  
Validation Data ◽  
Cropping Patterns ◽  
Modis Evi

Agricultural land use and cropping patterns are closely related to food production, soil degradation, water resource management, greenhouse gas emission, and regional climate alterations. Methods for reliable and cost-efficient mapping of cropping pattern, as well as their changes over space and time, are therefore urgently needed. To cope with this need, we developed a phenology-based method to map cropping patterns based on time-series of vegetation index data. The proposed method builds on the well-known ‘threshold model’ to retrieve phenological metrics. Values of four phenological parameters are used to identify crop seasons. Using a set of rules, the crop season information is translated into cropping pattern. To illustrate the method, cropping patterns were determined for three consecutive years (2008–2010) in the Henan province of China, where reliable validation data was available. Cropping patterns were derived using eight-day composite MODIS Enhanced Vegetation Index (EVI) data. Results show that the proposed method can achieve a satisfactory overall accuracy (~84%) in extracting cropping patterns. Interestingly, the accuracy obtained with our method based on MODIS EVI data was comparable with that from Landsat-5 TM image classification. We conclude that the proposed method for cropland and cropping pattern identification based on MODIS data offers a simple, yet reliable way to derive important land use information over large areas.

scholarly journals Thresholds definition in MOD13Q1 and VGT-S10 time series for coffee crop area estimation in Triângulo Mineiro/Alto Paranaíba

2019 ◽  
Vol 3 (2) ◽  
pp. 1-10
Author(s):  
Michel Eustáquio Dantas Chaves ◽  
Elizabeth Ferreira ◽  
Antonio Augusto Aguilar Dantas
Keyword(s):  
Land Use ◽  
Time Series ◽  
Large Scale ◽  
Agricultural Research ◽  
Regional Scale ◽  
Vegetation Indices ◽  
Seasonal Development ◽  
Land Use Classification ◽  
Crop Area ◽  
The Time Domain

In the last decades, remote sensing application in agricultural research has intensified to evaluate phenological cycles. Vegetation indices time series have been used to obtain information about the seasonal development of agricultural vegetation on a large scale. The multitemporal approach increases the gain of information coming from orbital images, an important factor for analysis of its spatial distribution. The objective of this study was to test the application of vegetation indices of the MODIS and SPOT-VEGETATION sensors to estimate the areas destined for coffee crops in the Triângulo Mineiro/Alto Paranaíba mesoregion. The results show that the vegetation indices NDVI and EVI of the product MOD13Q1 were more adequate for the estimation of land use over the time domain, especially NDVI. The best minimum threshold varies between 0.39 - 0.42 and the best maximum threshold varies between 0.71 - 0.74. The contribution of this work is that these thresholds can serve as subsidies for land use classification studies on a regional scale and for estimating areas for planting.

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