Landsat-derived Normalized Difference Vegetation Index Research Articles

NEW MICROWAVE-BASED MISSIONS APPLICATIONS FOR RAINFED CROPS CHARACTERIZATION

A multi-temporal/multi-sensor field experiment was conducted within the Soil Moisture Measurement Stations Network of the University of Salamanca (REMEDHUS) in Spain, in order to retrieve useful information from satellite Synthetic Aperture Radar (SAR) and upcoming Global Navigation Satellite Systems Reflectometry (GNSS-R) missions. The objective of the experiment was first to identify which radar observables are most sensitive to the development of crops, and then to define which crop parameters the most affect the radar signal. A wide set of radar variables (backscattering coefficients and polarimetric indicators) acquired by Radarsat-2 were analyzed and then exploited to determine variables characterizing the crops. Field measurements were fortnightly taken at seven cereals plots between February and July, 2015. This work also tried to optimize the crop characterization through Landsat-8 estimations, testing and validating parameters such as the leaf area index, the fraction of vegetation cover and the vegetation water content, among others. Some of these parameters showed significant and relevant correlation with the Landsat-derived Normalized Difference Vegetation Index (R>0.60). Regarding the radar observables, the parameters the best characterized were biomass and height, which may be explored for inversion using SAR data as an input. Moreover, the differences in the correlations found for the different crops under study types suggested a way to a feasible classification of crops.

NEW MICROWAVE-BASED MISSIONS APPLICATIONS FOR RAINFED CROPS CHARACTERIZATION

Abstract. A multi-temporal/multi-sensor field experiment was conducted within the Soil Moisture Measurement Stations Network of the University of Salamanca (REMEDHUS) in Spain, in order to retrieve useful information from satellite Synthetic Aperture Radar (SAR) and upcoming Global Navigation Satellite Systems Reflectometry (GNSS-R) missions. The objective of the experiment was first to identify which radar observables are most sensitive to the development of crops, and then to define which crop parameters the most affect the radar signal. A wide set of radar variables (backscattering coefficients and polarimetric indicators) acquired by Radarsat-2 were analyzed and then exploited to determine variables characterizing the crops. Field measurements were fortnightly taken at seven cereals plots between February and July, 2015. This work also tried to optimize the crop characterization through Landsat-8 estimations, testing and validating parameters such as the leaf area index, the fraction of vegetation cover and the vegetation water content, among others. Some of these parameters showed significant and relevant correlation with the Landsat-derived Normalized Difference Vegetation Index (R>0.60). Regarding the radar observables, the parameters the best characterized were biomass and height, which may be explored for inversion using SAR data as an input. Moreover, the differences in the correlations found for the different crops under study types suggested a way to a feasible classification of crops.

Rice yield estimation using Landsat ETM + Data

Paddy rice areas in Larkana district in Sindh province, Pakistan, were mapped over eight years. Landsat 7 ETMþ satellite imagery was classified for rice areas using training data collected through visual interpretation and using a bagged decision tree approach. Within the rice areas, we estimated yield for the 2013 season using regression models based on Landsat-derived normalized difference vegetation index (NDVI) and ratio vegetation index (RVI) values against historic, reported yield values. The annual cropped rice area estimated from satellite imagery was between 19% and 24% lower than the area reported by the Crop Reporting Service, Sindh. A positive and strong relationship with coefficient of determination (R 2 ) of 0.94 was observed between the reported rice crop yield and NDVI at the peak of the growing season for the years 2006 to 2013. A fair relation (R 2 ¼ 0.875) between rice crop yield and RVI was observed for the same years. A strong relationship between observed and predicted rice production with model efficiency ¼ 0.925, mean bias error ¼ −85;016 t ,a ndRMSE ¼ 80;726 t was obtained. Thus, Landsat ETMþ has a high potential for estimating rice yield and production at the district level in Pakistan and elsewhere. © 2015 Society of Photo-Optical Instrumentation Engineers (SPIE) (DOI: 10.1117/1.JRS.9.095986)

Quantifying moderate resolution remote sensing phenology of Louisiana coastal marshes

Coastal ecosystems are under multiple stresses ranging from global climate change to regional hazardous weather and human interventions. Coastal marshes in Louisiana are inherently vulnerable to these threats because they are microtidal and inhabit a narrow portion of the intertidal zone. Phenological dynamics of the marshes offer valuable information on the stressors’ impacts, yet they have rarely been reported or compared. Here, we study the landscape-level phenologies of the marshes under different climatic conditions, using Landsat-derived Normalized Difference Vegetation Index (NDVI) records (30×30m2 spatial resolution) and a nonlinear mixed model that enables a quantitative analysis of nonlinear and piecewise functions involving repeated measures. In 2007 (a normal year), the Gaussian function was the best phenological model for Louisiana coastal marshes (pseudo R2 0.56–0.85), showing that: (1) NDVI of all marshes peaked within one month from late July to mid-August; (2) freshwater marshes had the highest peak NDVI, followed by intermediate, brackish, and saline marshes; and (3) saline marshes had the longest growth duration, followed by brackish, and then intermediate and freshwater marshes. Phenological shifts were found in years featuring extreme weather events: (1) a two-month delay in the peak NDVI day of saline marshes in 1999 (a drought year) compared to 2007; and (2) a shortening in growth duration of all marshes by approximately half in 2005 (a hurricane year). This work presents a methodgology to analyze and predict Louisiana coastal marshes' phenological dynamics in response to current and future stresses.

Inferring drought and heat sensitivity across a Mediterranean forest region in southwest Western Australia: a comparison of approaches

Changes in climate trends and extreme climatic events are increasingly impacting on forests around the world. In order to better understand how and where major ecological and climatic changes will affect our forested ecosystems, tools based on landscape sensitivity analysis need to be developed to help inform sustainable forest management. This study was undertaken in the Northern Jarrah Forest (NJF) region in the Mediterranean climate of southwest Western Australia. Extreme drought and multiple heatwaves in 2010/2011 resulted in large-scale tree canopy dieback in the NJF. In this study, we used Landsat satellite imagery to (1) accurately map the damaged areas, (2) produce a damage probability model and (3) compare the model with a probability model derived from data collected through an airborne flight survey. We found that the Landsat-derived Normalized Difference Vegetation Index was a good indicator of drought/heat induced damage in the NJF region. Both probability models identified the same set of topography and climate-related factors for determining the probability of drought/heat damage within the landscape. Extrapolation of the Landsat satellite method-based model, however, produced a more deterministic and useful drought/heat damage sensitivity map for the NJF region. The techniques and tools developed, and applied, in this study can readily be transferred to other regions around the world and can assist in the sustainable management and timely climate adaptation efforts to accommodate our future forests.

Mapping Wetland Areas Using Landsat-Derived NDVI and LSWI: A Case Study of West Songnen Plain, Northeast China

Increasing interest in wetlands for environmental management requires an understanding of the location, spatial extent, and configuration of the resource. The National Wetlands Inventory is the most commonly used data source for this information. However, its accuracy is limited in some contexts, such as agricultural and forested wetlands. An large number of studies have mapped wetlands worldwide from the perspective of land use and land cover change. However, information on the actual wetland planting areas annually is limited, which greatly impacts ongoing research. In this case study of the West Songnen Plain, we developed a simple algorithm for the quick mapping of wetlands by utilizing their unique physical features, such as annual display of phenological land-cover change of exposed soils, shallow flooding water, and plants from multi-temporal Landsat images. Temporal variations of the Normalized Difference Vegetation Index (NDVI) and Land Surface Water Index (LSWI) derived from Landsat images in 2010 for wetlands at different growth stages were analyzed. Results show that during the ante-tillering phase, the NDVI value (above zero) is lower than the LSWI value of paddies because of flooding of shallow water; during the reproductive and ripening phases, the NDVI value is higher than the LSWI value (above zero); and during the post-harvest wetland planting phase, the NDVI value is still higher than the LSWI value, but the LSWI value is negative. Wetland areas can be detected using one or two images in the optimum time window. The algorithm based on the difference of NDVI and LSWI values derived from Landsat images was used to extract the actual wetland planting area. Validated alongside statistical data, the algorithm showed high accuracy. Therefore, this algorithm highlights the unique features of wetlands and can help in mapping the actual wetland area annually on a regional scale. Results further indicate that the new method has a classification accuracy of 92 %. In comparison, two traditional methods based on Landsat-7/ETM registered accuracy rates of only 83 % and 87 % respectively.

Correlating Vegetation, Water Use, and Surface Temperature in a Semiarid City: A Multiscale Analysis of the Impacts of Irrigation by Single‐Family Residences

Urban heat islands (UHIs) and the vegetation that mitigates them vary across space and time, but little research has investigated this coupled natural–human system using both spatial and temporal analyses. Focusing on semiarid, water‐scarce Tucson, Arizona, we examined whether outdoor water use by residents of single‐family homes (a practice that uses close to half of residential water supplies) contributes to urban “greenness” and the mitigation of UHI effects. Specifically, we investigated how different types of residential development mediate vegetation–water use–temperature interactions. Our data sets include Landsat‐derived normalized difference vegetation index (NDVI) and surface temperatures, parcel‐level zoning and assessor data, and residential water use records at the quarter section level (0.63 km2). We analyzed these data at multiple spatial and temporal scales. Spatial analysis results demonstrate that cooling from vegetative evapotranspiration is mediated by development factors as well as by topography and wind patterns. Findings also suggest that outdoor water use aside from irrigation, particularly the use of swimming pools, promotes cooling without elevating the NDVI. Temporal analysis reveal that most residential areas maintained or increased greenness despite declining 1995–2008 water use due most likely to long‐term regional climate cycles. Only high‐density developments with little undeveloped ground cover and few natural drainage channels exhibit a strong relationship between household water use and NDVI trends. These results suggest that the preservation of natural drainage channels and limitation of impervious surfaces, as well as the siting of development in naturally cooled microclimates, may be sustainable strategies for UHI mitigation in water‐scarce regions.Análisis multi‐escalar de los impactos de riego en residencias unifamiliares: la correlación entre la vegetación, el uso del agua y la temperatura superficial en un área urbana semiáridaLas islas de calor urbano (urban heat islands‐UHIs) y las áreas con vegetación que ayudan a mitigarlas varían en su distribución especial y temporal. Sin embargo, existe relativamente poca investigación dedicada al análisis espacio‐temporal de este sistema acoplado humano‐ambiental urbano. El artículo examina la medida en la cual el uso de agua al aire libre por parte de residentes de viviendas unifamiliares (practica que consume mas de la mitad de los recursos hídricos) contribuye al “verdor” de áreas urbanas y a la mitigación de los efectos de las UHs. El área de estudio es Tucson, Arizona, una ciudad ubicada en un ambiente semiárido que sufre de escasez hídrica. En términos más concretos, los autores investigan cómo los diferentes tipos de desarrollos urbanos residenciales sirven de mediadores en las interacciones entre la vegetación, la temperatura y el uso del agua. Como datos se utilizaron índices de vegetación (Normalized difference vegetation index‐NDVI) y temperaturas superficiales derivados de imágenes Landsat. Así mismo se usaron datos catastrales a nivel de parcela de zonificación, y registros de uso residencial de agua a nivel de cuarto de sección (quarter‐section) (0,63 km2). Los datos fueron analizados a múltiples escalas espaciales y temporales. Los resultados de análisis espacial demuestran que el enfriamiento de la evapotranspiración vegetal está influenciado por los factores de desarrollo urbano residencial así como por los patrones topográficos y climáticos (viento). Los resultados también sugieren que los usos de agua al aire libre, aparte de riego, en particular el uso de las piscinas (o albercas), promueven el enfriamiento sin elevar el valor del NDVI. El análisis temporal revela que la mayoría de zonas residenciales mantuvieron o aumentaron el ‘verdor’ a pesar de la disminución del uso del agua entre 1995 y 2008, debido probablemente a los ciclos climáticos regionales de largo plazo. Únicamente las zonas urbanas de alta densidad con escasas áreas verdes y pocos canales naturales de drenaje muestran una fuerte relación entre el uso del agua residencial y las tendencias del NDVI. Estos resultados sugieren que la preservación de los canales de drenaje natural y la reducción de superficies impermeables, así como el emplazamiento del desarrollo urbano en áreas con microclimas naturalmente más fríos, pueden ser estrategias sostenibles para la mitigación de UHIs en regiones con escasez de agua.城市热岛与可缓解其效应的植被均随时间和空间变化，但鲜有研究从时空分析视角关注这一自然‐人文耦合系统。本文聚焦于半干旱、缺水的亚利桑那州图森市，主要调查独户家庭户外用水（其用水量大约是住宅供应水量的一半）是否对城市“绿化”和缓解城市热岛效应作出贡献。特别地，我们调查不同类型住宅开发是如何调节植物‐用水‐温度间的相互作用。数据集包括从美国陆地资源卫星获得的归一化植被指数（NDVI）和地表温度，地块区划和评估数据， 约160英亩（0.63 km2）用地面积的住户用水记录。我们从时空多尺度视角对这些数据进行了分析。空间分析结果表明，植被蒸散作用导致的降温不仅受开发因素也受地形和风模式的调节。同时也发现：包括灌溉的户外用水，尤其是泳池用水，在促进地表降温时并未促使归一化植被指数（NDVI）提高。时间分析揭示，大多数居住区即使在1995–2008用水减少的情况下仍保持和增加“绿化”，最可能归因于长期的区域气候循环。只是在植被覆盖和自然排水系统均很少的高密度开发地区，家庭用水与NDVI趋势上显示出强相关性。这些结果昭示保留自然排水系统和限制不透水地表，以及在具有自然降温作用的微气候上选址发展区，或许是缺水地区缓解热岛效应的可持续策略。

Implications of management strategies and vegetation change in the Mount St. Helens blast zone

The 1980 eruptions of Mount St. Helens provided an excellent opportunity for scientists to investigate the recovery of vegetation communities following a major geologic disturbance. An important and often overlooked aspect in these studies is the human factor in recovery processes, and specifically, the different management approaches taken towards re-establishment of vegetation on lands under the control of various owners. This study examines vegetation changes throughout the 1980 blast zone using a time series of Landsat-derived Normalized Difference Vegetation Index (NDVI) images and change detection methods to assess the changes over 25 years, from 1980 to 2005, as a function of human management combined with ecological factors. This long-term tracking of change indicates that differences in the speed of vegetation re-establishment and consequent rates of change substantially reflect human involvement and varying management strategies.