Use Of MODIS Data Research Articles

Applicability of MODIS land cover and Enhanced Vegetation Index (EVI) for the assessment of spatial and temporal changes in strength of vegetation in tropical rainforest region of Borneo

Rainforests in the equatorial tropical regions are facing severe changes in strength and distribution due to natural and anthropogenic activities. Climate change causes major issues in vegetation characteristics whereas logging and developmental activities destruct the natural characteristics of terrain and vegetation. In the present research, MODIS vegetation cover type and vegetation indices (Enhanced Vegetation Index –EVI) data were interpreted to assess the decade (2008–2017) variation in vegetation types and strength characteristics in the Baram River Basin (BRB) in Borneo. International Geosphere-Biosphere Programme (IGBP) based classification identified ten land cover types in the BRB and the mean EVI in most periods varies between −0.30 and greater than 0.80. Results showed spatial and temporal variation in the area covered by individual land cover during the period of analysis and the fluctuation in mean EVI values indicates variation in strength characteristics of land cover types in the region. Statistical analysis showed a significant correlation (r > 0.50) of mean EVI values between consecutive years of analysis. Though the IGBP classification scheme could not categorise the most dominant land use activities in the BRB i.e. logging and oil palm plantations, the findings of the present research validate the use of MODIS data in equatorial tropical rainforest regions for characterising the regional scale vegetation dynamics.

A Study of Spring Drought Using Terra MODIS Satellite Image

In 2015, drought was at the worst stage of devastation in Soyanggang Dam watershed. The purpose of this study is to trace the drought area around Soyanggang dam watershed by using Terra MODIS image because it has the ability of spatio-temporal dynamics. The MODIS indices, which included the enhanced vegetation index (NDVI), were extracted from MODIS product MOD13 16-day composite datasets with a spatial resolution of 250m from 2010.01.01 to 2015.06.30. We found that application of Vegetation Condition Index (VCI) and Standardized Vegetation Index (SVI) was suitable for monitoring the drought area. The result can be used to acquire the drought data scattered and demonstrate the potential for the use of MODIS data for temporal and spatial detection of drought effects.

Use of MODIS data to assess atmospheric aerosol before, during, and after community evacuations related to wildfire smoke

Wildfires can pose direct and indirect threats to public health via fire and smoke, respectively. Evacuations are used to manage both types of threat given situational information about fires and their behaviour. However, there has been limited documented use of objective remote sensing data to inform the decision-making process. We conduct a retrospective assessment of 41 smoke-related evacuations in Canada between 2000 and 2007 using smoke and cloud data from the Terra MODIS. Daily mean aerosol optical depth (AOD) measurements were used to represent smoke levels in the area surrounding each evacuation site. Time series of these data were plotted for the four days prior to evacuation, the evacuation date, and the four days following the evacuation. Daily AOD values were scaled using the daily cloud mask to crudely account for the fact that heavy aerosol can be classified as cloud. Time series plots and the percentage differences between pre- and post-evacuation AOD were used to contextualize each evacuation. Out of 41 cases, approximately half met each of the criteria used to assess public health protection: (1) post-evacuation AOD values over the risk threshold for sensitive populations; (2) peak AOD exposures occurring post-evacuation; and (3) mean AOD higher post-evacuation than pre-evacuation. Some evacuations did not meet any of these criteria. Although evacuation decisions would never be made in the absence of situational intelligence, we conclude that systematic use of objective and readily available remote sensing data can help to retrospectively evaluate smoke-related evacuations, and may be useful for prospective, real-time application with further development.

Complementarity of Two Rice Mapping Approaches: Characterizing Strata Mapped by Hypertemporal MODIS and Rice Paddy Identification Using Multitemporal SAR

Different rice crop information can be derived from different remote sensing sources to provide information for decision making and policies related to agricultural production and food security. The objective of this study is to generate complementary and comprehensive rice crop information from hypertemporal optical and multitemporal high-resolution SAR imagery. We demonstrate the use of MODIS data for rice-based system characterization and X-band SAR data from TerraSAR-X and CosmoSkyMed for the identification and detailed mapping of rice areas and flooding/transplanting dates. MODIS was classified using ISODATA to generate cropping calendar, cropping intensity, cropping pattern and rice ecosystem information. Season and location specific thresholds from field observations were used to generate detailed maps of rice areas and flooding/transplanting dates from the SAR data. Error matrices were used for the accuracy assessment of the MODIS-derived rice characteristics map and the SAR-derived detailed rice area map, while Root Mean Square Error (RMSE) and linear correlation were used to assess the TSX-derived flooding/transplanting dates. Results showed that multitemporal high spatial resolution SAR data is effective for mapping rice areas and flooding/transplanting dates with an overall accuracy of 90% and a kappa of 0.72 and that hypertemporal moderate-resolution optical imagery is effective for the basic characterization of rice areas with an overall accuracy that ranged from 62% to 87% and a kappa of 0.52 to 0.72. This study has also provided the first assessment of the temporal variation in the backscatter of rice from CSK and TSX using large incidence angles covering all rice crop stages from pre-season until harvest. This complementarity in optical and SAR data can be further exploited in the near future with the increased availability of space-borne optical and SAR sensors. This new information can help improve the identification of rice areas.

APPLICATION OF MODIS DATA TO ASSESS THE LATEST FOREST COVER CHANGES OF SRI LANKA

Abstract. Assessing forest cover of Sri Lanka is becoming important to lower the pressure on forest lands as well as man-elephant conflicts. Furthermore, the land access to north-east Sri Lanka after the end of 30 years long civil war has increased the need of regularly updated land cover information for proper planning. This study produced an assessment of the forest cover of Sri Lanka using two satellite data based maps within 23 years of time span. For the old forest cover map, the study used one of the first island-wide digital land cover classification produced by the main author in 1988. The old land cover classification was produced at 80 m spatial resolution, using Landsat MSS data. A previously published another study by the author has investigated the application feasibility of MODIS and Landsat MSS imagery for a selected sub-section of Sri Lanka to identify the forest cover changes. Through the light of these two studies, the assessment was conducted to investigate the application possibility of MODIS 250 m over a small island like Sri Lanka. The relation between the definition of forest in the study and spatial resolution of the used satellite data sets were considered since the 2012 map was based on MODIS data. The forest cover map of 1988 was interpolated into 250 m spatial resolution to integrate with the GIS data base. The results demonstrated the advantages as well as disadvantages of MODIS data in a study at this scale. The successful monitoring of forest is largely depending on the possibility to update the field conditions at regular basis. Freely available MODIS data provides a very valuable set of information of relatively large green patches on the ground at relatively real-time basis. Based on the changes of forest cover from 1988 to 2012, the study recommends the use of MODIS data as a resalable method to forest assessment and to identify hotspots to be re-investigated. It's noteworthy to mention the possibility of uncounted small isolated pockets of forest, or sub-pixel size forest patches when MODIS 250 m x 250 m data used in small regions.

RS를 이용한 홍수범람지역 탐지 정보화 기법 연구

2011년 태국 짜오프라야 강 유역에서 발생한 홍수에 의해 많은 피해가 발생했다. 본 연구에서는 홍수범람시 시공간적 침수상황이 파악 가능한 Terra MODIS 영상을 이용하여 태국 짜오프라야 강 유역의 홍수에 의한 침수지역을 추정하였다. 2011년 7월 29일에서 2012년 1월 9일까지의 500m 해상도인 MODIS product MOD09 8일 합성 영상을 수집하고 식생지수(EVI), 지표수분지수(LSWI)와 DVEL지수(식생지수와 지표수분지수의 차이)를 이용하여 홍수범람 지역과 수역관련 지역의 탐지 기법을 제시하였다. 본 연구의 결과는 홍수 범람지역의 자료를 정보화하고 그 결과를 정량적으로 제시하는 방법으로 활용될 수 있으며, MODIS 자료의 이용은 시공간적 하천 홍수범람지역 탐지의 가능성을 알 수 있었다. In 2011, floods were at the worst stage of devastation in Chao Phraya river basin of Thailand. The purpose of this study is to trace the flood inundation area around Chao Phraya river basin by using Terra MODIS image because it has the ability of spatiotemporal dynamics. The MODIS indices, which included the enhanced vegetation index(EVI), land surface water index(LSWI), and the difference in the values of EVI and LSWI(DVEL), were extracted from MODIS product MOD09 8-day composite datasets with a spatial resolution of 500m from Jul. 29, 2011 to Jan. 09, 2012. We found that combined application of EVI, LSWI, and DVEL was suitable for monitoring flood inundation. For the extracted flood inundation area and water-related area. The result can be used to acquire the flood inundation data scattered and demonstrate the potential for the use of MODIS data for temporal and spatial detection of flood effects.

Detecting the spatiotemporal changes of tidal flood in the estuarine wetland by using MODIS time series data

Summary This study was conducted to develop a novel technique of monitoring tidal floods and their spatiotemporal dynamics using a time series combination of the MODIS vegetation indices (VIs). The vegetation indices, which included the enhanced vegetation index (EVI), land surface water index (LSWI) and the difference in the values of EVI and LSWI (DVEL), were extracted from MODIS datasets with a spatial resolution of 500 m from 2001 to 2006. The technique first employed a wavelet-analysis to reduce the noise component of the time series of VIs, after which the smoothed time profiles were used to identify the spatiotemporal changes in tidal flood effects on estuarine wetland from islands to sea front. We found that combined application of EVI, LSWI and DVEL was suitable for monitoring flood inundation and recording flood dynamics and vegetation succession. Our approach takes advantage of both the flooded soils and canopy characteristics of vegetation during the tidal cycle and vegetation growth phases. The results of this study demonstrate the potential for the use of MODIS data for temporal and spatial detection of tidal flood effects in estuarine wetlands.

Класифікування земного покриття за супутниковими даними MODIS для моніторингу посівів озимих зернових у межах адміністративних районів Київської та Миколаївської областей України

Класифікування земного покриття за супутниковими даними MODIS для моніторингу посівів озимих зернових у межах адміністративних районів Київської та Миколаївської областей України

The use of MODIS data to derive acreage estimations for larger fields: A case study in the south-western Rostov region of Russia

Recent developments in remote sensing technology, in particular improved spatial and temporal resolution, open new possibilities for estimating crop acreage over larger areas. Remotely sensed data allow in some cases the estimation of crop acreage statistics independently of sub-national survey statistics, which are sometimes biased and incomplete. This work focuses on the use of MODIS data acquired in 2001/2002 over the Rostov Oblast in Russia, by the Azov Sea. The region is characterised by large agricultural fields of around 75ha on average. This paper presents a methodology to estimate crop acreage using the MODIS 16-day composite NDVI product. Particular emphasis is placed on a good quality crop mask and a good quality validation dataset. In order to have a second dataset which can be used for cross-checking the MODIS classification a Landsat ETM time series for four different dates in the season of 2002 was acquired and classified. We attempted to distinguish five different crop types and achieved satisfactory and good results for winter crops. Three hundred and sixty fields were identified to be suitable for the training and validation of the MODIS classification using a maximum likelihood classification. A novel method based on a pure pixel field sampling is introduced. This novel method is compared with the traditional hard classification of mixed pixels and was found to be superior.

Mapping regional land cover with MODIS data for biological conservation: Examples from the Greater Yellowstone Ecosystem, USA and Pará State, Brazil

The paper investigated the application of MODIS data for mapping regional land cover at moderate resolutions (250 and 500 m), for regional conservation purposes. Land cover maps were generated for two major conservation areas (Greater Yellowstone Ecosystem—GYE, USA and the Pará State, Brazil) using MODIS data and decision tree classifications. The MODIS land cover products were evaluated using existing Landsat TM land cover maps as reference data. The Landsat TM land cover maps were processed to their fractional composition at the MODIS resolution (250 and 500 m). In GYE, the MODIS land cover was very successful at mapping extensive cover types (e.g. coniferous forest and grasslands) and far less successful at mapping smaller habitats (e.g. wetlands, deciduous tree cover) that typically occur in patches that are smaller than the MODIS pixels, but are reported to be very important to biodiversity conservation. The MODIS classification for Pará State was successful at producing a regional forest/non-forest product which is useful for monitoring the extreme human impacts such as deforestation. The ability of MODIS data to map secondary forest remains to be tested, since regrowth typically harbors reduced levels of biodiversity. The two case studies showed the value of using multi-date 250 m data with only two spectral bands, as well as single day 500 m data with seven spectral bands, thus illustrating the versatile use of MODIS data in two contrasting environments. MODIS data provide new options for regional land cover mapping that are less labor-intensive than Landsat and have higher resolution than previous 1 km AVHRR or the current 1 km global land cover product. The usefulness of the MODIS data in addressing biodiversity conservation questions will ultimately depend upon the patch sizes of important habitats and the land cover transformations that threaten them.

ＷＷＷを利用したＴｅｒｒａ ＭＯＤＩＳデータ前処理システムの構築

Terra MODIS is one of the few space-borne sensors currently capable of acquiring radiometric data over the range of view angles. Institute of Industrial Science (ITS), University of Tokyo, has been receiving Terra MODIS data at the Komaba Campus station and at Asian Institute of Technology (AIT), Bangkok on direct broadcasting system since May 2001. The coverage includes whole East and South Asia and is expected to monitor environmental changes regularly such as deforestation, forest fires, floods and typhoon. Over eight hundred scenes have been archived in the storage system and they occupy 2 TB of disk space so far. In this study, MODIS data processing system on WWW is developed including following functions : spectral subset (250m, 500m and 1000m resolutions), radiometric correction to radiance, spatial subset of geo-referenced data as a rectangular area with latitude-longitude grid system in HDF format and generation of a quick look file in JPEG format. Users will be notified via e-mail just after all the processes have finished. Using this system enables us to process MODIS data on WWW with a few input parameters and download the processed data by FTP access. An easy to use interface is expected to promote the use of MODIS data. This system has been available via the Internet on the following URL since September 1 2002, “http: //webmodis.iis.u-tokyo.ac.jp/”.