Abstract: A process for locating real estate parcels for a user comprises accessing a library of parceled real estate image data to identify objects and features in a plurality of parcels identified by the user as having a feature of interest. A predictive model is constructed and applied to a geographic region selected by the user to generate a customized output of real estate parcels predicted to have the feature of interest, or, in some implementations, not to have the feature of interest.

Abstract: A process for locating real estate parcels for a user comprises accessing a library of parceled real estate image data to identify objects and features in a plurality of parcels identified by the user as having a feature of interest. A predictive model is constructed and applied to a geographic region selected by the user to generate a customized output of real estate parcels predicted to have the feature of interest.

Abstract: Methods and systems for automatic estimation of object characteristics from a digital image are disclosed, including a method comprising sub-dividing into two or more segments a digital image comprising pixels and depicting an object of interest, wherein each segment comprises two or more pixels; assessing content depicted in one or more of the segments for a predetermined object characteristic using machine learning techniques comprising General Image Classification of the one or more segments using a convolutional neural network, wherein the General Image Classification comprises analyzing the segment as a whole and outputting a general classification for the segment as a whole as related to the one or more predetermined object characteristic; and determining a level of confidence of one or more of the segments having the one or more predetermined object characteristic based on the General Image Classification assessment.

Abstract: A process for locating real estate parcels for a user comprises accessing a library of parceled real estate image data to identify objects and features in a plurality of parcels identified by the user as having a feature of interest. A predictive model is constructed and applied to a geographic region selected by the user to generate a customized output of real estate parcels predicted to have the feature of interest.

Abstract: Methods and systems for automated structure modeling form digital imagery are disclosed, including a method comprising receiving target digital images depicting a target structure; automatically identifying target elements of the target structure in the target digital images using convolutional neural network semantic segmentation; automatically generating a heat map model depicting a likelihood of a location of the target elements of the target structure; automatically generating a two-dimensional model or a three-dimensional model of the target structure based on the heat map model without further utilizing the target digital images; and extracting information regarding the target elements from the two-dimensional or the three-dimensional model of the target structure.

Abstract: Methods and systems for predicting well site production are disclosed, including a computer system comprising one or more processor and a non-transitory computer memory storing processor readable instructions that when executed by the one or more processor cause the one or more processor to receive image data of a geographic region around and including a well site; receive well site location data of a location of the well site; analyze well site data to determine well pad location data of a location of a well pad including an area of observation extending beyond and around a well site; determine pixel data of the well pad within the image data for a particular time from the well pad location data; and analyze the pixel data of the well pad for a particular time to determine a volume of flared gas based on the pixel data.

Abstract: Computer-implemented methods and systems for image analysis of multiband images of geographic regions are described, including a method by one or more computer executing executable instructions stored in one or more non-transitory, tangible, computer readable media, the method comprising: receiving one or more multiband image of a geographic region, the one or more multiband image having pixels; generating a grey level co-occurrence matrix for the pixels in the one or more multiband image; generating a surface index for the one or more multiband image containing information indicative of a surface type represented by one or more of the pixels in the one or more multiband image; and classifying the pixels of the one or more multiband image into one of a group of predefined land cover classes, based on the surface index in combination with the grey level co-occurrence matrix.

Abstract: A process for locating real estate parcels for a user comprises accessing a library of parceled real estate image data to identify objects and features in a plurality of parcels identified by the user as having a feature of interest. A predictive model is constructed and applied to a geographic region selected by the user to generate a customized output of real estate parcels predicted to have the feature of interest.

Abstract: A device includes an image data receiving component, a vegetation index generation component, a crop data receiving component, a masking component and a multivariate regression component. The image data receiving component receives image data of a geographic region. The vegetation index generation component generates an array of vegetation indices based on the received image data, and includes a plurality of vegetation index generating components, each operable to generate a respective individual vegetation index based on the received image data. The crop data receiving component receives crop data associated with the geographic region. The masking component generates a masked vegetation index based on the array of vegetation indices and the received crop data. The multivariate regression component generates a crop parameter based on the masked vegetation index.

Abstract: Methods and systems for automatic estimation of object characteristics from a digital image are disclosed, including a method comprising sub-dividing into two or more segments a digital image comprising pixels and depicting an object of interest, wherein each segment comprises two or more pixels; assessing content depicted in one or more of the segments for a predetermined object characteristic using machine learning techniques comprising General Image Classification of the one or more segments using a convolutional neural network, wherein the General Image Classification comprises analyzing the segment as a whole and outputting a general classification for the segment as a whole as related to the one or more predetermined object characteristic; and determining a level of confidence of one or more of the segments having the one or more predetermined object characteristic based on the General Image Classification assessment.

Abstract: Methods and systems for predicting well site production are disclosed, including a computer system comprising one or more processor and a non-transitory computer memory storing processor readable instructions that when executed by the one or more processor cause the one or more processor to receive image data of a geographic region around and including a well site; receive well site location data of a location of the well site; analyze well site data to determine well pad location data of a location of a well pad including an area of observation extending beyond and around a well site; determine pixel data of the well pad within the image data for a particular time from the well pad location data; and analyze the pixel data of the well pad for a particular time to determine a volume of flared gas based on the pixel data.

Abstract: Methods and systems for automatic estimation of object characteristics from a digital image are disclosed, including a method comprising sub-dividing into two or more segments a digital image comprising pixels and depicting an object of interest, wherein each segment comprises two or more pixels; assessing content depicted in one or more of the segments for a predetermined object characteristic using machine learning techniques comprising General Image Classification of the one or more segments using a convolutional neural network, wherein the General Image Classification comprises analyzing the segment as a whole and outputting a general classification for the segment as a whole as related to the one or more predetermined object characteristic; and determining a level of confidence of one or more of the segments having the one or more predetermined object characteristic based on the General Image Classification assessment.

Abstract: Computer-implemented methods and systems for image analysis of multiband images of geographic regions are described, including a method by one or more computer executing executable instructions stored in one or more non-transitory, tangible, computer readable media, the method comprising: receiving one or more multiband image of a geographic region, the one or more multiband image having pixels; generating a grey level co-occurrence matrix for the pixels in the one or more multiband image; generating a surface index for the one or more multiband image containing information indicative of a surface type represented by one or more of the pixels in the one or more multiband image; and classifying the pixels of the one or more multiband image into one of a group of predefined land cover classes, based on the surface index in combination with the grey level co-occurrence matrix.

Abstract: Methods and systems for predicting well site production are disclosed, including a computer system comprising one or more processor and a non-transitory computer memory storing processor readable instructions that when executed by the one or more processor cause the one or more processor to receive image data of a geographic region around and including a well site; receive well site location data of a location of the well site; analyze well site data to determine well pad location data of a location of a well pad including an area of observation extending beyond and around a well site; determine pixel data of the well pad within the image data for a particular time from the well pad location data; and analyze the pixel data of the well pad for a particular time to determine a volume of flared gas based on the pixel data.

Abstract: A device includes an image data receiving component, a vegetation index generation component, a crop data receiving component, a masking component and a multivariate regression component. The image data receiving component receives image data of a geographic region. The vegetation index generation component generates an array of vegetation indices based on the received image data, and includes a plurality of vegetation index generating components, each operable to generate a respective individual vegetation index based on the received image data. The crop data receiving component receives crop data associated with the geographic region. The masking component generates a masked vegetation index based on the array of vegetation indices and the received crop data. The multivariate regression component generates a crop parameter based on the masked vegetation index.

Abstract: Computer-implemented methods and systems for image analysis of multiband images of geographic regions are described, including a method by one or more computer executing executable instructions stored in one or more non-transitory, tangible, computer readable media, the method comprising: receiving one or more multiband image of a geographic region, the one or more multiband image having pixels; generating a grey level co-occurrence matrix for the pixels in the one or more multiband image; generating a surface index for the one or more multiband image containing information indicative of a surface type represented by one or more of the pixels in the one or more multiband image; and classifying the pixels of the one or more multiband image into one of a group of predefined land cover classes, based on the surface index in combination with the grey level co-occurrence matrix.

Abstract: A device includes an image data receiving component, a vegetation index generation component, a crop data receiving component, a masking component and a multivariate regression component. The image data receiving component receives image data of a geographic region. The vegetation index generation component generates an array of vegetation indices based on the received image data, and includes a plurality of vegetation index generating components, each operable to generate a respective individual vegetation index based on the received image data. The crop data receiving component receives crop data associated with the geographic region. The masking component generates a masked vegetation index based on the array of vegetation indices and the received crop data. The multivariate regression component generates a crop parameter based on the masked vegetation index.

Abstract: Methods and systems for predicting well site production are disclosed, including a computer system comprising one or more processor and a non-transitory computer memory storing processor readable instructions that when executed by the one or more processor cause the one or more processor to receive image data of a geographic region around and including a well site; receive well site location data of a location of the well site; analyze well site data to determine well pad location data of a location of a well pad including an area of observation extending beyond and around a well site; determine pixel data of the well pad within the image data for a particular time from the well pad location data; and analyze the pixel data of the well pad for a particular time to determine a volume of flared gas based on the pixel data.

Abstract: A device includes an image data receiving processor, a well site data receiving processor, a zonal statistics processor and a vent flare calculator. The image data receiving processor receives image data of a geographic region around and including a well site. The well site data receiving processor receives well site location data of a location of the well site and generates well pad location data of a location of a well pad including the well site. The zonal statistics processor generates pixel data from the well pad location. The vent flare calculator calculates a volume of flared gas and based on the pixel data.

Abstract: Computer-implemented methods and systems for image analysis of multiband images of geographic regions are described, including a method by one or more computer executing executable instructions stored in one or more non-transitory, tangible, computer readable media, the method comprising: receiving one or more multiband image of a geographic region, the one or more multiband image having pixels; generating a grey level co-occurrence matrix for the pixels in the one or more multiband image; generating a surface index for the one or more multiband image containing information indicative of a surface type represented by one or more of the pixels in the one or more multiband image; and classifying the pixels of the one or more multiband image into one of a group of predefined land cover classes, based on the surface index in combination with the grey level co-occurrence matrix.