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

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.

Agronomy ◽  
2020 ◽  
Vol 10 (4) ◽  
pp. 478
Author(s):  
Ha Thi Thu Nguyen ◽  
Loc Van Nguyen ◽  
C.A.J.M (Kees) de Bie ◽  
Ignacio A. Ciampitti ◽  
Duc Anh Nguyen ◽  
...  

Land use maps specifying up-to-date acreage information on maize (Zea mays L.) cropping patterns are required by many stakeholders in Vietnam. Government statistics, however, lag behind by one year, and the official land use maps are only updated at 5-year intervals. The aim of this study was to apply the Savitzky–Golay algorithm to reconstruct noisy Enhanced Vegetation Index (EVI) time series (2003–2018) from Terra Moderate Resolution Imaging Spectroradiometer (MODIS) Vegetation Indices (MOD13Q1) to allow timely detection of changes in maize crop phenology, and then to employ a linear kernel Support Vector Machine (SVM) classifier on the reconstructed EVI time series to prepare the present-day maize cropping pattern map of Dak Lak province of Vietnam. The method was able to specify the spatial extent of areas cropped to maize with an overall map accuracy of 79% and could also differentiate the areas cropped to maize just once versus twice annually. The by-district mapped maize acreage shows a good agreement with the official governmental data, with a 0.93 correlation coefficient (r) and a root mean square deviation (RMSD) of 1624 ha.


2018 ◽  
Vol 10 (8) ◽  
pp. 1203 ◽  
Author(s):  
Jianhong Liu ◽  
Wenquan Zhu ◽  
Clement Atzberger ◽  
Anzhou Zhao ◽  
Yaozhong Pan ◽  
...  

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.


2013 ◽  
Vol 16 (1) ◽  
pp. 77-84
Author(s):  
Slamet Budi Yuwono ◽  
Naik Sinukaban ◽  
Kukuh Murtilaksono ◽  
Bunasor Sanim

Way Betung watershed is one of the important water resources in Lampung Province and it provides a clean water for Bandar Lampung City through a regional water supply company (PDAM). By the increase of population and economical activities of Bandar Lampung City, the need of clean water also increase, however by the time, the conditions of Way Betung watershed as water resources are declining. Therefore, to improve or to restore WayBetung watershed, a high cost is needed. The research was aimed: (a) to study the effects of Way Betung watershed land use change on the water resources of Bandar Lampung City, (b) to arrange the sustainable development of Way Betung watershed in order to maintain the availability of water resources. The sustainable developments of water resources of Way Betung watershed were arranged in five alternatives/scenarios and each alternative was related toits erosion (USLE method) and its run off volume (SCS method). The results showed that land use changes of Way Betung watershed (1991-2006) were likely to increase daily maximum discharge (Q max), to decrease daily minimum discharge (Q min), to increase fluctuation of river discharge, and to increase yearly run off coeffcient. The best sustainable development of water resources of Way Betung watershed, Lampung Province, was alternative/scenario-4 (forest as 30% of watershed areas + alley cropping in the mix garden). This alternative will decrease erosion to the level lower than tolerable soil loss and also decrease fluctuation of monthly run off.Keywords: Land use change, run off coefficient, water resources, watershed


2020 ◽  
Vol 12 (3) ◽  
pp. 478 ◽  
Author(s):  
Yuzhu Hao ◽  
Zhenjie Chen ◽  
Qiuhao Huang ◽  
Feixue Li ◽  
Beibei Wang ◽  
...  

High-precision information regarding the location, time, and type of land use change is integral to understanding global changes. Time series (TS) analysis of remote sensing images is a powerful method for land use change detection. To address the complexity of sample selection and the salt-and-pepper noise of pixels, we propose a bidirectional segmented detection (BSD) method based on object-level, multivariate TS, that detects the type and time of land use change from Landsat images. In the proposed method, based on the multiresolution segmentation of objects, three dimensions of object-level TS are constructed using the median of the following indices: the normalized difference vegetation index (NDVI), the normalized difference built index (NDBI), and the modified normalized difference water index (MNDWI). Then, BSD with forward and backward detection is performed on the segmented objects to identify the types and times of land use change. Experimental results indicate that the proposed BSD method effectively detects the type and time of land use change with an overall accuracy of 90.49% and a Kappa coefficient of 0.86. It was also observed that the median value of a segmented object is more representative than the commonly used mean value. In addition, compared with traditional methods such as LandTrendr, the proposed method is competitive in terms of time efficiency and accuracy. Thus, the BSD method can promote efficient and accurate land use change detection.


2018 ◽  
Vol 7 (10) ◽  
pp. 405 ◽  
Author(s):  
Urška Kanjir ◽  
Nataša Đurić ◽  
Tatjana Veljanovski

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.


2013 ◽  
Vol 39 (4) ◽  
pp. 59-70 ◽  
Author(s):  
Fredrick Ao Otieno ◽  
Olumuyiwa I Ojo ◽  
George M. Ochieng

Abstract Land cover change (LCC) is important to assess the land use/land cover changes with respect to the development activities like irrigation. The region selected for the study is Vaal Harts Irrigation Scheme (VHS) occupying an area of approximately 36, 325 hectares of irrigated land. The study was carried out using Land sat data of 1991, 2001, 2005 covering the area to assess the changes in land use/land cover for which supervised classification technique has been applied. The Normalized Difference Vegetation Index (NDVI) index was also done to assess vegetative change conditions during the period of investigation. By using the remote sensing images and with the support of GIS the spatial pattern of land use change of Vaal Harts Irrigation Scheme for 15 years was extracted and interpreted for the changes of scheme. Results showed that the spatial difference of land use change was obvious. The analysis reveals that 37.86% of additional land area has been brought under fallow land and thus less irrigation area (18.21%). There is an urgent need for management program to control the loss of irrigation land and therefore reclaim the damaged land in order to make the scheme more viable.


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